Economics of Travel Demand Management: Comparative Cost Effectiveness and Public Investment

Transcription

1 Economcs of Travel Demand Management: Comparatve Cost Effectveness and Publc Investment BD Fnal Report March 2007

2 Economcs of Travel Demand Management: Comparatve Cost Effectveness and Publc Investment Fnal Report March 2007 Prepared for Florda Department of Transportaton BD Prepared by Natonal Center for Transt Research Center for Urban Transportaton Research Unversty of South Florda 4202 E. Fowler Avenue, CUT 100 Tampa, FL (813)

3 The opnons, fndngs, and conclusons expressed n ths publcaton are those of the authors and not necessarly those of the State of Florda Department of Transportaton or the US Department of Transportaton

4 1. Report No. NCTR , FDOT BD Government Accesson No. 3. Recpent's Catalog No. 4. Ttle and Subttle Economcs of Travel Demand Management: Comparatve Cost Effectveness and Publc Investment 7. Author(s) Concas, Ssnno, Wnters, Phlp L. 5. Report Date March Performng Organzaton Code 8. Performng Organzaton Report No. 9. Performng Organzaton Name and Address Center for Urban Transportaton Research 4202 E. Fowler Avenue, CUT 100 Tampa, FL Sponsorng Agency Name and Address 10. Work Unt No. (TRAIS) 11. Contract or Grant No. DTRS98-G Type of Report and Perod Covered Offce of Research and Specal Programs Florda DOT U.S. Department of Transportaton 605 Suwannee Washngton, DC Tallahassee, FL Sponsorng Agency Code 15. Supplementary Notes Supported by a grant from the USDOT Research and Specal Programs Admnstraton, and the Florda Department of Transportaton. 16. Abstract The 2006 Congeston Mtgaton and Ar Qualty Improvement (CMAQ) Program Interm Gudance provdes explct gudelnes to program effectveness assessment and benchmarkng by callng for a quantfcaton of benefts, as well as dsbenefts, resultng from emsson reducton strateges for project selecton and evaluaton. The objectve of ths study s to develop a methodology that combnes academc and practtoner experences wthn a theoretcal framework that truly captures consumers prce responsveness to dverse transportaton optons by embracng the most relevant trade-offs faced under ncome, modal prce and avalablty constrants. The development of the theoretcal model leads to the desgn and mplementaton of TRIMMS (Trp Reducton Impacts for Moblty Management Strateges), a practtoner orented sketch plannng tool. TRIMMS permts program managers and fundng agences lke FDOT to make nformed decsons on where to spend fnte transportaton dollars based on a full range of benefts and costs. The approach s consstent wth other beneft to cost analyses. Its accuracy and the perceved farness are crtcal when sgnfcant funds are at stake. The model allows some regons to use local data or opt to use defaults from natonal research fndngs, select the benefts and costs of nterest, and calculate the costs and benefts of a gven program. A step by step ntroducton to the program, ts capabltes, and a set of workng examples to gude the user through the process of evaluaton s ncluded n the report. A key strength of ths model s ts wde range of benefts and costs that can be selected for the analyss. The model s flexblty and robustness allows t to be adopted by agences throughout the country. Future research could seek to enhance the model to nclude more of the nternal benefts to employers (e.g., changes n worker productvty, reducton n overhead, changes n employee retenton, etc.). A byproduct of ths research effort that goes beyond the ntal project objectves s the development of a structured approach to evaluate the mpact of soft programs. Compared to the currently avalable soft program evaluatons methods, the approach developed ths report provdes a less heurstc method of estmaton resultng n statstcally robust mode share mpact predctons. Another future area of analyss would be the refnement of such model to provde a standardzed approach to soft program mpact assessment. 17. Key Word 18. Dstrbuton Statement Transportaton Demand Management, TDM, Trp Reducton, Value of a Trp Removed, TDM Impacts, TDM Evaluaton, TDM Benefts, TDM Comprehensve Evaluaton, TRIMMS, Soft Programs 19. Securty Classf. (of ths report) Unclassfed 20. Securty Classf. (of ths page) Unclassfed 21. No. of Pages Prce

5 Florda Department of Transportaton Project Manager: Mchael Wrght, Commuter Assstance Program Manager Prncpal Investgators: Ssnno Concas, Senor Research Assocate Phlp L. Wnters, TDM Program Drector Project Staff: Anurag Komandur, Graduate Research Assstant Vshaka Shva Raman, Graduate Research Assstant Lren Huago, Graduate Research Assstant v

6 Executve Summary The 2006 Congeston Mtgaton and Ar Qualty Improvement (CMAQ) Program Interm Gudance provdes explct gudelnes to program effectveness assessment and benchmarkng by callng for a quantfcaton of benefts, as well as dsbenefts resultng from emsson reducton strateges for project selecton and evaluaton[1]. More publc agences are attemptng to measure the value of Transportaton Demand Management (TDM) strateges relatve to ther potental benefts and costs n comparson to other transportaton solutons commonly employed to address capacty needs. Varous tools, such as the Workste Trp Reducton Model (WTRM) developed by the Natonal Center for Transt Research, the Envronmental Protecton Agency (EPA) COMMUTER model, and mpact calculaton methods developed by the Calforna Ar Resources Board (CARB), are currently avalable for estmatng some of the benefts of several TDM and other emsson reducton strateges. However, no standardzed gudance exsts to quantfy the costs and benefts of TDM strateges that consders the full range of benefts and costs accrued. The avalablty of an effectve tool that takes nto account a broader range of costs and benefts could greatly enhance agences abltes to evaluate alternatves and estmate post-mplementaton benefts of TDM strateges. At the same tme, poor estmates could steer traffc mtgaton and emsson reducton polces towards neffcent transportaton nvestments at the local and regonal level. The objectve of ths project s to develop a standardzed methodology for calculatng the costs and benefts of TDM for comparatve assessment and publc decson makng. To acheve ths goal, ths report conceptualzes a new approach that bulds on exstng technques and tools to produce a model that would save agences tme and money, provdng a hgh level of relablty n mpact estmates, whle generatng results that could be compared among regons and across projects. A methodology that combnes academc and practtoner experences wthn a theoretcal framework that truly captures what s at the core of TDM evaluaton s heren detaled. That s, an approach that models consumers prce responsveness to dverse transportaton optons by embracng the most relevant trade-offs faced under ncome, mode cost and avalablty constrants. The development of the theoretcal model leads to the desgn and mplementaton of TRIMMS (Trp Reducton Impacts for Moblty Management Strateges), a practtoner orented sketch plannng tool. TRIMMS permts program managers and fundng agences lke FDOT to make nformed decsons on where to spend fnte transportaton dollars based on a full range of benefts and costs. The approach s consstent wth other beneft to cost analyses. Its accuracy and the perceved farness are crtcal when sgnfcant funds are at stake. The model allows some regons to use local data or opt to v

7 use defaults from natonal research fndngs, select the benefts and costs of nterest, and calculate the costs and benefts of a gven program. A key strength of ths model s ts wde range of benefts and costs that can be selected for the analyss. The model s flexblty and robustness allows t to be adopted by agences throughout the country. A step by step ntroducton to the program, ts capabltes, and a set of workng examples to gude the user through the process of evaluaton s ncluded n the report. Future research could seek to enhance the model to nclude more of the nternal benefts to employers (e.g., changes n worker productvty, reducton n overhead costs, changes n employee retenton, etc.). The challenge of ths future enhancement s fndng data relatng to gven TDM strateges to such busness outcomes. Another area of future research would be to develop a framework to nclude regonal or local values for some of the cost externaltes and mode prce elastctes for regon-specfc analyss. Fnally, a byproduct of ths research effort that goes beyond the ntal research objectves s the development of a structured approach to evaluate the mpact of soft programs (.e., programs other than changes n tme or costs such as guaranteed rde home programs). Compared to the currently avalable soft program evaluaton methods, the approach developed n ths report provdes a less heurstc method of estmaton, resultng n statstcally robust mode share mpact predctons. Another future area of analyss would be the refnement of such a model to provde a standardzed approach to soft program mpact assessment. v

8 Table of Contents Executve Summary... v Introducton... 1 Current Systematc Evaluaton Methods... 4 COMMUTER Model V Advantages and Constrants... 6 Internatonal Evaluaton Procedures... 8 New Zealand Transfund Theoretcal Framework and Evaluaton Procedure Advantages and Constrants Other Exstng General Gudelnes to Evaluatng Strateges Case Studes Unversty of Washngton U-Pass Program Program Strateges Program Evaluaton Way-To-Go, Seattle! Program Strateges Program Evaluaton Hayward Heavy Up Promoton Evaluaton- San Francsco Bay Area Rapd Transt (BART) Program Strategy Program Evaluaton AT&T Telework Program TDM Strateges Program Evaluaton Evaluatng Behavor Change n Transport: Beneft Cost Analyss of Indvdualzed Marketng for the Cty of South Perth TDM Strateges Program Evaluaton Trp Reducton Performance Program, Washngton State Proposed Predcton Model Modelng Technque Constant Elastcty Demand for Trps Advantages and Constrants Soft Program Trp Change Adjustments Evaluaton Crtera Evaluaton Method: Per Passenger-Trp Average Annualzed Benefts Appled Example: Transt Travel Tme Improvement and Parkng Cost Increase Model Implementaton: TRIMMS Defnng the Base Case: Input Requrements v

9 Soft Program Impacts Model Output Customzng the Model Analyss Examples Hard Program Impacts: Transt Fare Subsdy Soft and Hard Program Impacts Conclusons References Lst of Tables Table 1 New Zealand Transfund TDM Benefts and Costs Table 2 U-Pass Program Evaluaton Table 3 Polluton Costs Table 4 ROI of BART Promotonal Campagn Table 5 SOV Cost Externaltes Table 6 Analyss Example Base Case Scenaro Assumptons Lst of Fgures Fgure 1 EPA COMMUTER V 2.0 Estmatng Procedure... 6 Fgure 2 Model Flowchart Fgure 3 Demand for SOV trps Fgure 4 TRIMMS Inner Layout Fgure 5 TRIMMS Base Case Scenaro Worksheet Fgure 6 TRIMMS - Fnancal Incentve Worksheet Fgure 7 TRIMMS Travel Tme Improvements Worksheet Fgure 8 TRIMMS Step by Step Soft Program Evaluaton Fgure 9 TRIMMS Model Output Fgure 10 TRIMMS Model Parameters Modfcaton Fgure 11 TRIMMS Prce and Travel Tme Elastcty Parameters Modfcaton Fgure 12 TRIMMS - User Suppled Fnal Mode Shares Fgure 13 TRIMMS Transt Fare Subsdy Fgure 14 TRIMMS - Transt Fare Subsdy Impact Fgure 15 TRIMMS Transt Subsdy and Parkng Surcharge Fgure 16 TRIMMS Transt Subsdy and Parkng Surcharge Impacts Fgure 17 TRIMMS Transt Subsdy and Parkng Surcharge Fnal Mode Share Impacts Fgure 18 TRIMMS Soft Program Module: Step One Fgure 19 TRIMMS Soft Program Module: Step Two Fgure 20 TRIMMS Soft Program Module: Step Three Fgure 21 TRIMMS Soft Program Module: Step Four Fgure 22 TRIMMS Soft Program Module: Step Fve Fgure 23 TRIMMS Soft Program Module: Step Sx Fgure 24 TRIMMS Combned Hard Program/Soft Program Impacts v

10 Introducton Transportaton Demand Management (TDM) refers to the varous strateges adopted to change travel behavor to ncrease the transportaton system effcency and also to acheve reducton n congeston, energy and fuel conservaton, savngs n parkng and road costs, whle focusng on the safety and moblty of the road users. The 2006 Congeston Mtgaton and Ar Qualty Improvement (CMAQ) Improvement Program Interm Gudance provdes explct gudelnes to program effectveness assessment and benchmarkng by callng for a quantfcaton of benefts, as well as dsbenefts resultng from emsson reducton strateges for project selecton and evaluaton[1]. More publc agences are attemptng to measure the value of TDM strateges relatve to ther potental benefts and costs n comparson to other transportaton solutons commonly employed to address capacty needs. They seek to assess f the strateges have met performance-based plannng standards or goals establshed for the strateges and whether or not t was a cost-effectve expendture of funds. For example, the Washngton State Commute Trp Reducton program revealed that the program s cost to the state was 54 per reduced trp (or $136 for the year)[2]. These fndngs were used n some urban areas to argue for ncreased publc fundng to support employer TDM programs and provde ncentves for the use of alternatve modes. To date, no standardzed gudance exsts to quantfy the costs and benefts of TDM strateges that takes nto account the range of benefts and costs that accrue from TDM programs. The objectve of ths project s to develop a standardzed methodology for calculatng the costs and benefts of TDM for comparatve assessment and publc decson makng. To acheve ths goal, ths report conceptualzes a new approach that bulds on exstng technques and tools to produce a model that would save agences tme and money, would provde a hgh level of relablty n mpacts results, whle generatng results that could be compared among regons and across projects. A methodology that combnes academc and practtoner experences wthn a theoretcal framework that truly captures what s at the core of TDM evaluaton s heren detaled. That s, an approach that models consumers prce responsveness to dverse transportaton optons by embracng the most relevant trade-offs faced under ncome, modal prce and avalablty constrants. Ths report s dvded nto four man sectons. Secton I deals wth systematc TDM evaluaton methods. The analyss focuses on evaluaton approaches that have a formal theoretcal and emprcal structure that result n tools for program benefts estmaton. Each of the methods advantages and constrants are dscussed to hghlght key elements for evaluaton and ncluson n the model development phase. 1

11 The nvestgaton nvolved a comprehensve search of transportaton databases and Internet sources to ensure comprehensve coverage of reports and papers descrbng relevant aspects of TDM assessment. In addton, CUTR reached out to nearly 1,000 subscrbers n ts TRANSP-TDM lstserv to dentfy evaluaton and return on nvestment analyses. The revew uncovered a paucty of predctve evaluaton approaches to TDM program evaluaton and cost effectveness. Most of the evaluaton experence n the U.S. s based on the assessment of ndvdual plot projects and programs that focus on sngle TDM measures (such as vanpoolng or user subsdes) or on employer stes. Broader evaluatons are conducted on a cross-sectonal bass over a range of mult-objectve programs[3]. The most relevant predctve evaluaton methods and models are represented by the Envronmental Protecton Agency (EPA) COMMUTER model and by the New Zealand and Australan experences[4-6]. The remanng models are n the form of busness benefts calculators, whch are manly desgned to ad employers and practtoners n settng up specfc TDM programs. In addton, the revew of nternatonal experences dealt wth a detaled analyss of manuals and gudelnes to TDM program evaluaton and effectveness. These studes provde detals and general drecton towards a more comprehensve approach to TDM assessment n a fashon smlar to that currently employed n the evaluaton of transportaton nfrastructure nvestments. The bulk of ths work has been compled by the research conducted by the Vctora Transport Polcy Insttute, based n Canada[7-10]. Secton II of the report revews a set of case studes spannng dverse TDM strateges. The objectve s to assess how programs are evaluated, what measures of mpacts and assessment are employed, and how these measures vary accordng to the TDM strategy beng assessed. The lterature search uncovered a host of case studes. Ths secton focuses on those that are most relevant to ths study s objectves. Ths secton also ncludes a revew of the Commute Trp Reducton Performance Grant Program of Washngton State Department of Transportaton. Although not related to a specfc TDM program or mplementaton, ths case study revew was deemed as relevant because t offers an nnovatve approach to assessng the value of TDM by ntroducng the marketbased concept where buyers and sellers compete to determne the prce of a removed sngle occupancy vehcle (SOV) trp. Secton III provdes the ratonale for seekng an alternatve method to evaluate TDM strateges on a more comprehensve bass. The analyss carred out n Secton I and the methods currently n use and descrbed n Secton II provde the bass for lookng to develop a standard approach to TDM evaluaton that overcomes the constrants outlned n ths report. Ths secton detals a methodology that combnes academc and practtoner experences to produce a theoretcal framework that truly captures what s at the bass of TDM travel behavor: an approach that models consumers prce responsveness to dverse transportaton optons by embracng the most relevant tradeoffs faced under ncome, modal prce and avalablty constrants. The development of the theoretcal model leads to the desgn and mplementaton of a sketch plannng tool, TRIMMS (Trp Reducton Impacts for Moblty Management Strateges) and s detaled n Secton IV. The secton provdes a step by step ntroducton 2

12 to the program, ts capabltes, and a set of workng examples to gude the user through the process of evaluaton. The work concludes wth recommendatons on how to mprove and expand the model and provdes drecton for further research. 3

13 Current Systematc Evaluaton Methods Ths secton s concerned wth models that evaluate TDM cost effectveness for publc fundng purposes. They provde formal ways to model the mpacts of TDM alternatves n a predctve fashon. The ensung lterature revew focuses on methods ncorporatng (1) costs and benefts n economc terms accompaned by (2) a calculator or estmator or model for projectng TDM effects of one or more TDM strateges beng consdered for mplementaton. The lterature search uncovered few exstng approaches to the evaluaton of TDM mpacts on a predctve bass. To date, most of the evaluaton deals wth the assessment of ndvdual plot projects and programs that focus on sngle TDM measures (such as vanpoolng or user subsdes) or on employer stes[3]. The vast majorty of these methods take the form of calculators for the set up and benefts assessment of employerbased programs. Usually, such tools are not predctve n nature, or f so, they tend to be based on smple rule-of-thumb approaches. The revew showed that the most common evaluaton method s cost beneft analyss, as t provdes both a means of recommendng and rankng dfferent alternatves. The constrants assocated wth these approaches are related to the necessary estmaton of each of the dentfed benefts and costs, and the dffculty to provde a comprehensve evaluaton of concurrent TDM strateges (.e., synergstc effects). These approaches are characterzed by a structured approach to the quantfcaton of benefts, such as travel tme savngs, congeston reducton, health and ftness. The methods provde ways to estmate the change n benefts brought about by dfferent TDM strateges, as well as monetary values. The latter are usually provded n ranges and are the byproduct of current and past studes at an aggregate level. COMMUTER Model V2.0 The COMMUTER model, developed by the Envronmental Protecton Agency, s ntended to be used to project emsson mpacts of dfferent TDM strateges of commuter choce ncentve programs. The model s capable of estmatng, at a sketch plannng level, mpacts of TDM strateges drected at affectng accessblty, transt tme, walkng tme, parkng prcng, modal and other subsdes[7, 8]. The mpacts of alternatve TDM strateges are estmated dfferently accordng to the program beng consdered, as shown n Fgure 1. For example, mpacts of soft programs, such as alternatve work schedules and employer support programs are projected by means of look-up tables. These look-up tables provde modal ncremental changes that are assocated wth the programs beng consdered, reflectng dfferent applcaton assumptons and levels of ntensty. A normalzaton procedure assures that total mode share sums to 100 percent. 4

14 TDM strateges that mpact travel costs and travel tmes are estmated usng pvot pont logt model approach. Ths conssts of a smplfed verson of the tradtonal four-step travel demand forecastng procedure to estmate changes n vehcle mles traveled (VMT) and the related number of trps spannng from generalzed cost and travel tme changes. At the core of the model s the followng basc pvot pont logt equaton: Where ( m) P = share of mode m; e = exponental functon; U = utlty equaton for mode m; and, m U 1... = utlty of other alternatve modes P U e + e m ( m) = U U U3 U e 1 + e e It s then suffcent to use the above equaton to enter the ntal or base mode share, mode use ad-hoc or default parameters enterng each mode s utlty functon to obtan the projected change n modal share due, for example, to a change n generalzed cost. The modal share s produced by TDM programs or projects that change the cost or tme costs across modes. The model estmates and reports the followng: Baselne and fnal mode share by mode, ncludng percent of trps elmnated; Percent of trps shfted by peak perod; Change n VMT (based on trps removed multpled by percentage of workforce affected and average trp length); and, as a result of the change n VMT, Total daly emsson reducton for each pollutant. 5

15 Fgure 1 EPA COMMUTER V 2.0 Estmatng Procedure Source: COMMUTER V 2.0 Procedure Manual Advantages and Constrants The major advantages of the COMMUTER model are ts smplcty and the requred level of aggregaton. For example, the model dfferentates between three basc categores of metropoltan areas from 750,000 to over two mllon people; has two scopes of analyss (regonal and on-ste), and accounts for three urban area types (central Busness Dstrct, hgh densty actvty center, and suburban low densty areas). The 6

16 aggregaton of results s justfed by assumng that TDM programs generate modest modal changes provdng an acceptable trade-off between accuracy and ease of use. The pvot logt equaton approach smplfes the estmaton process and drastcally reduces data requrements, makng the model avalable to a broader, less techncally orented, audence of planners and employers. Coeffcents derved from regonal or area specfc travel demand models are used as nputs and appled to the pvot logt equaton to estmate changes n baselne mode shares spurred from specfc TDM strateges. The coeffcents are assumed to be derved usng sound statstcal methods to guarantee statstcal robustness. Among the constrants of such an approach are: Trps and VMT estmates are strongly dependent on pre-specfed parameters; No guarantee that the pvot logt equaton wll predct actual mode shft (predcted mode shft wll le on the logt curve); The logt equaton s based on dscrete, mutually exclusve choces (auto vs. transt, wthout admttng concurrent choces of transt and, say, walkng); Coeffcents are affected by factors such as the varables ncluded n the model (and the nteractons between the varables), calbraton procedures, and the qualty of the underlyng data; and, There s no dstncton between short run vs. long run effects. The default parameters are obtaned from tradtonal four-step travel demand forecast models. These models are usually estmated and calbrated for specfc regons and uses, wth lttle potental for a generalzed use, transferablty across dfferent regonal areas, and predctve power. Ths s more evdent when tryng to estmate the mpact of TDM strateges n areas where regonal transport demand models are not avalable. 1 The tradeoff of usng pvot-pont modelng versus more ntensve computatonal methods, lke four-step travel demand forecastng model s justfed by assumng that for modest change n mode shares, such as those generated by TDM strateges, the ncremental extrapolaton s farly accurate. The COMMUTER procedure manual suggests that there exst other ways of applyng the ncremental or pvot-pont modelng approach, for example by applyng elastcty parameters from emprcal work to extrapolate changes n base values. The use of elastctes was not consdered as t was argued that they are lmted n beng able to take nto account the nteractve effects that occur when multple actons are appled or multple modes are evaluated.[8] Ths asserton, though, seems to contradct the preferred choce of the pvot-pont logt approach. Indeed, the logt equaton s based on a multnomal dscrete choce model, whch by ts own defnton estmates the lkelhood that dfferent, mutually exclusve choces are smultaneously taken by an ndvdual. The 1 The user manual that accompanes the Commuter model reports that travel and emsson mpact estmates are hghly senstve to the values of these coeffcents, especally cost coeffcents. The user s warned aganst creatng hybrd equatons or alterng the default parameters n the absence of detaled local data from travel forecastng models. 7

17 use of elastctes n a properly talored framework could take nto account drect and ndrect relatonshps between dfferent modes. In addton, the use of cross elastctes assures takng nto account substtuton and complementary effects among transportaton alternatves. Fnally, the use of the pvot-pont logt equaton precludes the dstncton between short run and long run effects. The parameters that nfluence modal shares are the byproduct of cross-sectonal analyses (unless specfed otherwse) whch do not take nto account the long-run adjustments those users nevtably face. The use of a model based on transport elastctes could provde a method that dfferentates between a program s short and long run mpacts. Internatonal Evaluaton Procedures The lterature revew extended to cover models and approaches followed nternatonally, wth a focus on predctve evaluaton methods. European efforts are concentrated on montorng and evaluaton, as dstnct from projecton and estmaton, wth the bggest effort represented by the Moblty Management Strateges for the Next Decades (MOST). Ths project, sponsored by the European Commsson untl 2002, was ntended to provde an nsght on polcy frameworks and mplementaton strateges, as well as an nvestgaton of settng up standardzed montorng and evaluaton tools[9]. The lterature revew dd not encounter examples of predctve evaluatons n Europe. Gven the MOST project objectves and focus on montorng and mplementaton, a full revew of ts structure and conclusons was omtted from ths lterature revew. 2 In addton, CUTR recently publshed a research effort summarzng European experences n the feld of TDM[10]. The bulk of nternatonal, non-european experence s reflected n the Australan and New Zealand efforts to develop predctve TDM evaluaton procedures[5, 6]. In Australa and New Zealand most of the TDM measures fall under the defnton of Travel Behavor Change (TBhC) strateges. TBhC embraces a subset of TDM measures mostly centered on marketng approaches desgned to buld awareness n SOV users about alternatve modes of transports or to promote voluntary mode change. TBhC measures nclude: Workplace based ntatves (carpoolng, vanpoolng) Telecommutng School travel ntatves Household ntatves Communty-based ntatves 2 Note: the Transfund lterature revew reported the unavalablty of examples of predctve evaluatons n UK and Europe or any establshed TDM evaluaton procedures. 8

18 In New Zealand, evaluaton of TDM strateges falls under the Transfund Fundng Framework and Evaluaton Procedures. A major requrement n the assessment s that TDM projectons must be conducted usng methods comparable to those used to assess tradtonal transportaton nfrastructure projects. The economc evaluaton approach must be based on changes n the perceved cost/benefts, wth addton of resource cost correcton and externalty effects[5]. In addton, TDM projects are expected to produce benefts smlar to those of road nfrastructure projects and should be estmated usng the same beneft and cost unt values, as provded by the Project Evaluaton Manual (PEM). TDM projects should also be assessed wth methods consstent wth those developed for publc transport and freght projects that contrbute to reduced nfrastructure and mantenance costs. The procedure takes nto account the benefts added to exstng users, the net benefts accrung to those swtchng modes as a result of the projects, and ndrect benefts to the remanng users and envronmental benefts. Under these gudelnes, New Zealand Transfund commssoned a 2004 study to develop project assessment procedures sutable to TDM projects[6]. The study provdes a comprehensve approach based on a cost/beneft analyss that ncludes the followng three major beneft categores: 3 Beneft to traveler swtchng mode(s); Resource cost correctons; and, Externalty benefts. The premse to the approach s that the mode share of one mode wth respect to another s a functon of the dfference n generalzed cost between the two modes. Ths relatonshp s then used to determne the change n generalzed cost to brng about the observed change n mode share. Conceptually, the approach follows that of EPA COMMUTER Model v2.0, as t reles on travel demand forecast models to obtan evaluaton parameters. Contrary to the EPA model, whch uses a relatve mode share change, ths approach uses an absolute percentage pont change as reference parameters. The use of ths approach does not requre any pror knowledge of ntal mode share wthn a company, school or communty. Ths measure of beneft comprses the followng categores of benefts: Travel tme for new users; Decongeston; Induced traffc; Vehcle operatng costs; and, 3 Ultmately, the estmated beneft value for TDM users s $1.00 for each four percentage pont change n mode share from SOV to publc transport or cycle and walk. 9

19 Safety. Table 1 reports the benefts consdered, as well as ranges used as standard predctve evaluaton measures. The study also recommends a range of dverson rates obtaned from dverse projects located n Australa, New Zealand and worldwde. These rates are to be used as default values provdng the expected changes n mode share from SOV to alternatve modes, expressed as absolute percentage ponts. Accordng to the report, these values can be used wthout knowledge of exstng mode shares, whch smplfes the approach, although t probably weakens the assessment. The dverson rates are estmated for dfferent travel plans (school, work) n an aggregate fashon, wthout sub-groupng by locaton and soco-economc characterstcs, due to unavalablty of statstcally sgnfcant coeffcents. 10

20 Measure Travel Tme Savngs Vehcle Operatng Costs Health Benefts of Cyclng and Walkng Car Parkng Descrpton Fully nternalzed and estmated by means of perceved beneft approach. These benefts comprse travel tme dfference between modes, watng tme, and trp tme relablty Resource cost wth cost correctons. Part of the costs s drectly perceved by users, such as fuel costs. Addtonal costs, such as vehcle operatng, and other costs usually consdered as fxed are ncluded as a result of a TDM strategy that bulds aw Resource cost wth the followng correcton: half are nternal half are ncluded n net benefts to TDM users walkng benefts are 2.5 tmes of cyclng Resource cost wth cost correctons that ncludes: car parkng cost land use cost parkng faclty captal costs securty costs Resource cost correcton assumpton: car users perceve 75% of total resource cost Publc Transport Fares Congeston Reducton Cycle Operatng Costs Walkng Costs Accdent Costs Car Publc Transport Operatng Cost Resource cost wth cost correctons. Fares are a fnancal transfer from users to operators, but perceved as a cost by users. Consdered as an externalty. Resource cost wth cost correctons. The correctons are: vehcle operatng cost savngs equal to 7% of total travel tme decongeston benefts Dscount the effect of nduced travel demand of TDM strategy usng a 50% factor Note: road system benefts are neglgble and do not enter nto cost correcton ad addtonal beneft Resource cost wth cost correctons. The correctons s set to zero when accountng for addtonal accdent rsks by assumng ncreasng traffc calmng effects Same as cyclng Resource cost wth cost correctons, comprsed of three parts: 1 - Internal perceved costs (to TDM user); 2 - Internal costs not perceved wth cost correctons 3 - Externalty cost born by socety (hosptal, loss productvty) Note: Internal perceved cost savngs are equal to 50-66% of accdent resource costs Only ncluded as a cost f the TDM strategy results n an ncrease n demand hgh enough to warrant addtonal nfrastructure or operatng costs Estmated as the sum of all effects ncludng local ar, nose, and water Envronmental Externaltes polluton, and greenhouse gas emssons. These benefts enter only n short-run evaluatons Table 1 New Zealand Transfund TDM Benefts and Costs New Zealand Transfund Theoretcal Framework and Evaluaton Procedure The overall ratonale for developng the Transfund evaluaton approach to TDM s to justfy fundng sustanablty whle provdng an evaluaton framework consstent wth what was used to evaluate hghway and transt projects. The evaluaton approach s based on a cost beneft analyss framework to allow a comparson wth other types of 11

21 transport mprovement nterventons and to mantan credblty of TDM strateges and fundng sustanablty. The cost beneft analyss s based on a method that assesses changes n perceved costs whch ncludes resource cost correctons. The general assumpton s that travelers perceve only the drect costs related to a gven transportaton choce. These costs usually nclude out of pocket costs such as fuel, parkng charges, and publc transt fares. Fully perceved costs nclude the value of tme (transt and watng) and other externaltes. The Transfund approach argues that n many cases the out-of-pocket costs do not fully account for the resource costs, hence resource cost correctons are needed. The resource cost correctons ncluded n the assessment expand the range of out of pocket costs to nclude those ntally unperceved costs uncovered to the user as a results of a TDM strategy. The framework takes nto account the followng benefts: A. Resource benefts to people already usng the mode whch s mproved (generalzed cost change for that mode); ths s especally mportant when studyng the effect of transt mprovements; B. Perceved benefts to mode swtchers (people changng behavor); C. Benefts from avodance of unperceved costs assocated wth prevous behavor of swtchers, comprsng: 1. Resource cost adjustments for swtchers themselves; ncludng monetary (e.g., non-fuel varable vehcle operatng costs) and non-monetary (e.g., accdent trauma); and, 2. Other resource cost mpacts (externaltes) on other transport system users or of the transport system (e.g., decongeston, envronmental, and accdent externaltes). D. Unperceved costs assocated wth new behavor of swtchers, comprsng:. Resource cost adjustments for swtchers themselves; ncludng monetary (e.g., publc transport fare payments) and non-monetary (e.g., health benefts of cyclng and walkng); and,. Other resource cost mpacts (externaltes) on other transport system users or on the transport system, e.g., envronmental, accdent, and health externaltes (to the extent that costs of dmnshng health were beng ncurred by socety as a whole rather than the behavor changer ndvdually). Benefts of Type A are determned by changes n generalzed costs (ncludng tme and comfort) to the exstng users. Benefts of Type B are the most relevant n evaluatng the mpact of TDM strateges that nfluence the exstng cost dfferentals among avalable modes. These strateges nclude 12

22 changes n vanpoolng schedules or transt fare subsdes, and any other type of nterventon that changes the total cost of transport of a gven mode. Followng consumer surplus theory, these benefts are calculated usng the rule of one half of the benefts of Type A for exstng users. For the evaluaton of user benefts spannng from changes n perceved costs, the Transfund model reles on projected mode share changes as estmated by regonal fourstage travel demand models. In ths context, t s necessary to nput the current modal share, as well as the expected modal share to estmate the requred generalzed cost changes to acheve a gven goal. The report provdes dverson rate tables that were then used as default values for predctve evaluaton wthn a Mcrosoft Excel spreadsheet tool. 4 The model evaluaton results n a beneft to cost rato that s then used as the value for money of TDM projects, whch comprses: Net perceved and ndrect benefts (and dsbenefts) to all TDM users, other transport users affected by the project and all externaltes. These elements consttute the numerator; and, Net costs to the government of the TDM strategy beng evaluated, whch consttutes the denomnator. Advantages and Constrants One of the major advantages of ths approach s that t seeks to establsh a methodology to provde a comprehensve assessment of the full range of benefts and costs brought about by TDM ntatves whle mantanng a framework wthn the gudelnes of the more tradtonal nfrastructure nvestment apprasal. By followng a perceved cost approach, TDM strateges are fully accounted for ther mpacts on nternalzng costs that would be otherwse left out of the decson makng process of TDM swtchers. At the same tme, the approach retans the theoretcal construct of the more tradtonal beneft cost analyss. Two major constrants were dentfed n the Transfund approach to evaluate TDM strateges. The frst deals wth the way benefts are measured, due to the notons of resource costs and cost correctons. The approach s based on perceved costs whereas t s assumed that ndvduals face the full cost of the alternatve chosen. For example, parkng costs are assumed to comprse not only the average cost of parkng, but the full opportunty cost of usng land for parkng, the captal cost of the parkng nfrastructure, and the cost of added securty (f any) to the parkng faclty. Summed all together, these components represent the full resource cost of parkng. A resource cost correcton s then accounted for, by assumng that the ndvdual nternalzes only a percentage of the total 4 The evaluaton procedure was formalzed nto a Mcrosoft Excel spreadsheet model now beng used by the Vctora Travel Smart Program. Essentally, t s the same spreadsheet, but wth values talored to the Australan network. 13

23 resource costs. For example, n the case of parkng resource costs, the model assumes that ndvdual perceves 75 percent of the resource costs, wth a requred cost correcton of 25 percent. A gven TDM strategy mght nfluence the way a user perceves ths cost by ether ncreasng or lowerng the perceved component. By lettng the researcher establsh what should be ncluded n perceved costs, and by assumng what ndvduals are able to nternalze n terms of costs, the approach s lkely to overestmate TDM benefts. 5 Second, the model does not rely on a pvot pont formula, but on a set of pre-estmated modal shares talored for New Zealand. These shares are obtaned from regonal transport demand models and used as fxed parameters n the spreadsheet, wthout callng out a pvot logt or any equaton. As n the case of the EPA COMMUTER model, the relablty of the modal share shfts reles upon regonal estmates comng from tradtonal four-step models. As a result, the default parameters depend on the calbraton processes employed n these models, whch cannot be easly generalzed n a broader context. 5 For example, the model assumes a full resource cost of parkng of $10.00 for the Auckland area for peak perod commutng trps to the Central Busness Dstrct (CBD). Then, t assumes that ndvduals only perceve 75 percent of such cost for a total of $7.50. On the other hand, the average parkng fee s only $2.50 (page 29). Another example s provded by how walkng and cyclng accdent costs. When computng the total health benefts of walkng and cyclng, the model assumes that these are resource costs that do not need to be dscounted by the rsk of ncurrng n accdents (e.g., ndvduals do not nternalze the added rsk of swtchng to walkng or cyclng). 14

24 Other Exstng General Gudelnes to Evaluatng Strateges The lterature revew revealed a substantal effort to uncover benefts brought about by TDM ntatves. There exst numerous practtoner orented gudelnes to TDM mpact assessment based on formalzed approaches to comprehensve evaluaton[11-16]. Several studes have culled fndngs of program evaluatons to compare the emprcal evdence of a range of TDM alternatves[16, 17]. Some of the gudelnes lst relevant mpact measures to evaluate TDM projects[11, 12, 18], and outlne the major constrants to a comprehensve TDM evaluaton. These research efforts all recognze that, generally, TDM projects result n relatvely small mpacts over a large number of ndvduals. They are more dffcult to evaluate for the followng reasons: 1. Impacts are dfferent across users, whereas n project nfrastructure evaluatons users are assumed homogeneous (.e., they receve the same benefts); and, 2. Dfferent TDM strateges are smultaneously mplemented callng for a comprehensve evaluaton. Ths leads to a trade-off between evaluaton procedures that estmate all of the ndvdual responses to TDM strateges and procedures that provde a more aggregate apprasal usng a greater level of approxmaton. The approxmaton s an nevtable trade-off of the requrement of a standardzed approach. These ssues have been consdered n the lterature. TDM measures are socal plans and ther benefts encompass a vast sphere of socal lfe. For example, a congeston reducton program mght beneft not only from reductons n VMT, but mght also gan from ar qualty mprovements, decreased fossl fuel consumpton, and reduced parkng demand. Prce changes can have a varety of mpacts on travel, affectng the number of trps people take, ther destnaton, route, mode, travel tme, type of vehcle (ncludng sze, fuel effcency and fuel type), parkng locaton and duraton, and whch type of transport servces they choose. All these are essental ndcators n evaluatng a TDM project. Approaches that are currently avalable to evaluate the cost effectveness of TDM programs and strateges deal wth assessng the mpacts on a comparatve bass[3]. Ths s usually carred out by assessng TDM mpacts n terms of measures lnked to emsson reducton, such as vehcle trp or VMT reducton. To date, the bulk of work on measurng the effectveness of TDM programs on a comparatve bass n terms of emsson reducton s represented by the Transportaton Research Board Specal Report 264[19]. Ths research effort summarzed semnal work conducted to date wth a focus on the cost effectveness of programs funded under the objectve of polluton emsson reducton. 15

25 Case Studes In ths secton, a selected number of cases are presented, comprsng studes that evaluate dfferent popular TDM strateges. The objectve s to provde nsght on how TDM mpacts are beng quantfed by practtoners, n partcular: Evaluaton Crtera Whle general gudelnes as provded by TDM expert publcatons provde a full range of benefts, practtoner experence provdes addtonal nsghtful nformaton as to what s actually measurable, gven data and budgetary constrants; and, Evaluaton Methods Practtoner work can shed some lght on the most commonly used evaluaton approaches, such as beneft cost, lfe cycle or least cost plannng analyses. As part of ths secton of the lterature revew, many reports were carefully perused. Each study that has been ncluded n ths report provdes a dfferent evaluaton methodology and set of evaluaton measures. Among the evaluaton methods are return on nvestment analyss, break-even pont analyss, and quanttatve analyss focusng on advantages n a sngle sphere (e.g., travel tmes, ar qualty etc.), mathematcal model evaluaton and research orented studes from Washngton and Australa. Unversty of Washngton U-Pass Program The U-Pass program was started by the Unversty of Washngton to offer flexble transportaton to ts students at a low prce. Research for a new Campus Master Plan conducted by the Unversty n 1989 projected an ncrease n the number of students, faculty and staff wth a subsequent reducton n the number of parkng spaces. The Unversty thus assembled a task force of students, faculty and staff from two local transt agences, namely the Kng County Metro and the Communty Transt, and developed a new Transportaton Master Plan (TMP). The key element of the plan was to sgnfcantly ncrease the Unversty parkng rates, to dscourage drvng alone and also to rase funds for the mplementaton of the U-Pass Program. Wth the above vews, the program was launched n September 1991[20]. Program Strateges The key element of the U-Pass program s managng the demand of SOV through product prcng. It s an award wnnng program used as a model for other transportaton programs, both locally and natonally. As the man dea of the U-Pass program s to encourage the students and staff to adopt alternatve modes to drvng alone, the partcpants are provded wth many ncentves ncludng: 16

26 Increased and subsdzed transt servce; Rde matchng servces; Vanpool subsdes; Free carpool and vanpool parkng; Bcycle ncentves; Rembursed rdes home for emergences; Occasonal parkng permts for those who do not drve every day; Nght-tme neghborhood shuttle servce; and, Merchant dscounts. In addton there are ncentves offered on bcycle and pedestran safety equpment, an emergency rde home program for employees, dscounts on Flexcar, etc. All these measures have helped n reducng the number of people travelng by SOV and n makng use of alternatve modes of travel whenever avalable. The man TDM deas of the program are: Manage transportaton demand by ncreasng the prce of parkng faster than the prce of alternatves; Expand parkng prcng ncentves to gve faculty and staff reasons to consder alternatves; Purchase more transt servce from provders; Contnue to mplement a marketng approach that targets geographc areas; and, Integrate pedestran and bcycle facltes program nto the fabrc of campus and neghborhood communtes. Program Evaluaton The effectveness of the program s measured by sales, changes n vehcle trps and shfts n transportaton modes. The montorng system tracks ths by the use of a bennal U- PASS survey, (last conducted n 2004), parkng utlzaton reports, annual vehcle trp surveys, and the monthly montorng of each U-PASS element[21]. The effectveness of the program s benchmarked by comparng survey data aganst targets as they were ntally set up by the TMP n Table 2 reports the mpact measures and data collecton method employed by the study. The targets establshed by the Unversty of Washngton n the 1991 TMP have been met. The annual traffc count fgures show that the peak hour traffc has been able to reman lower than that n 1990, n spte of the populaton growth and subsequent trps to the campus. The U-Pass program has helped n reducng fuel consumpton, thereby mprovng the ar qualty n the regon, and has also helped to reduce traffc congeston. Facts gven n the 2001 Fact Sheet regardng achevements over the past 10 years nclude: More than 75 percent of the populaton uses other means to travel to campus; 17

27 Carpool trps have trpled and vanpool trps have ncreased by 75 percent snce the program started n 1991; and, The Unversty has saved more than $100 mllon by avodng the constructon of 3,600 parkng spaces[22]. Before mplementng the U-PASS program, the domnant commute mode was drvng alone and transt. The U-PASS program has been reported to have successfully met ts 10 year target n transportaton management by provdng a package of flexble, low-cost transportaton choces for faculty, staff, and students and beneftng them by reducng traffc congeston, mprovng ar qualty, and realzng sgnfcant fnancal savngs to regular transt users. The man challenges faced by such transt programs were marketng the program and educatng people about usng transt. Program Element TDM Strategy Program Evaluaton Data Collected Publc Transt and Tran Walkng Bcycle Free, unlmted rdes over 60 routes n Kng County Metro, Communty Transt About 9% of Metro trps and 7% of and Sound Transt buses. A full-fare Communty transt trps were made U- coverage of up to $8.00 for a round trp n PASS holders trans Launched Walkng campagns n 2003 and n the 3rd campagn, awarded 432 partcpants and conducts noontme actvtes 720 bcycle racks wth a capacty of 5,200 bkes and 562 bke locker rentals, dscounts on bcycle parts. Launched n 2004, the Rde n the Ran Bke Challenge encourages students and staff to partcpate and gves awards to them. 6% of faculty, 4% of staff and 31% of students walk to campus 12% of faculty, 5% of staff and 5% of students cycle to campus. In 2005, 596 partcpated n the Bke Challenge n 72 teams Transportaton Survey and the Kng County Metro. The UW Travel Study conducted a survey as part of Pedestran Improvement Plan (PIP) and U-PASS survey U-PASS survey Rdeshare Vanpoolng Carpoolng Emergency Rde Home Flexcar Merchant Dscounts RdeshareOnlne a regonal rdematch system Partcpants travelng from 10 mles or more receve up to $40 per month towards ther vanpool fare. Nomnal fee for car parkng whch was free pror to Staff and students n emergency can get rembursement up to 90% and 50 mles per quarter for a taxcab rde. A prvate membershp-based car sharng program to reduce SOV commuters by usng one of the 11 flexcars on or near campus. U-PASS holders receve a fee waver. The RdeshareOnlne matches rders and drvers n Kng and Perce Countes. In 2005, 33 vanpools operated wth 220 partcpants. Carpoolng decreased by 24% n 2004 snce the ncepton n In 2005, an average of 90 people used the U-Pass In 2005, 1,200 U-PASS holders were actve members Merchants receve free publcty n U- PASS marketng lke advertsements and In 2005, 60 local and natonal merchants lstng n the U-PASS webste, n return to partcpated n the program provdng dscounts to U-PASS holders U-PASS survey 2005 U-PASS survey 2004 U-PASS survey 2005 U-PASS survey 2005 U-PASS survey 2005 U-PASS survey Nght Rde Flexble Workng Arrangements An evenng van servce from 8 pm to am, that pcks up rders at fve locatons nsde the campus and drops them off at destnatons n neghborhood Includes Teleworkng and Studyng from home and Compressed work week schedules as a means of elmnatng commute trps In 2005, ths servce was provded to an average of 128 rders per day 23% of faculty, 8% of staff work from home and 18% of students study from home Table 2 U-Pass Program Evaluaton 2005 U-PASS survey 2004 U-PASS survey Way-To-Go, Seattle! Ths communty-based marketng program s amed at neghborhood trp reducton, one of the key objectves of TDM. The program ams to fulfll the goals of the Cty s 20 year 18

28 comprehensve plan of solvng automoble traffc problems, whle provdng a symbotc multmodal transportaton system. Accordng to the program, reducton n automoble use helps not only to ease traffc congeston and reduce addtonal costs due to parkng and polluton, but also decreases household expendtures. Way-to-Go, Seattle falls under an umbrella of many projects, each of whch was ntated for non-commute trp reducton[23]. These nclude the Commuter Cash program (whch pays people for dfferent optons lke walkng or referrng a frend), the One Less Car Challenge (whch provdes ncentves to reduce the number of cars n the household), and the Roosevelt Hgh School transportaton demand management project. Program Strateges The man strategy s to rely on marketng to determne consumer needs and preferences, create and test the new procedures, hghlght the benefts of partcular projects and provde the program wth addtonal nformaton and help on the projects. Program Evaluaton Ths project s evaluated by tradtonal economc methods whch nvolve quantfyng ncremental or margnal economc mpacts and ncludes them n a cost beneft analyss to determne the extent of program mpacts. Data are collected prmarly from exstng documents whch evaluated smlar projects and explaned ther effectveness. These nclude: Project applcatons; Project evaluaton reports; Press clppngs ncludng those from the Internet; and, Project products. Addtonal data are collected drectly from project managers and partcpants. The beneft cost analyss dentfes benefts and costs and compares ther magntude, but s not lmted to mpacts that are easly monetzed. Some evaluaton crtera, such as stakeholder and publc responses, are not benefts or costs, but are factors to consder when evaluatng programs and dentfyng ways to mprove them. There are two knds of analyses carred out n the program, a quanttatve cost-beneft analyss and a qualtatve analyss. These studed the mpact of varous programs on performance ndcators such as partcpant moblty mpacts, communty objectves, economc development, equty mpacts, stakeholder response and publc response. 19

29 Quanttatve Evaluaton (a) Project Costs All the avalable project costs lke partcpant ncentves, contractors, employer and partcpant costs, ncludng estmated costs such as vehcle congeston, roadway costs, parkng costs, safety, securty and health based on natonal research, have been ncluded n the study. The drect project expenses and other ones whch had a drect mpact on government agences can be manly dvded nto: 1. Admnstratve costs (e.g., project staff and other overhead expenses); 2. Grants and fnancal ncentves (e.g., funds dstrbuted under the program); and, 3. Costs to other agences (e.g., matchng funds by other agences). (b) Roadway Costs Reduced roadway traffc and travel shfts to dfferent modes help n savng roadways costs largely due to reduced road mantenance and traffc servces ncludng emergency servces and street lghtng for motor vehcles. Accordng to the Puget South Regonal Councl, expendtures on traffc servces were estmated to be $98 per capta on average for that regon[24]. Also savngs on roadway costs and traffc servces were estmated to average 2 per automoble-mle and 6 per bus-mle reduced. (c) Parkng Costs The parkng costs can be mtgated by reducng the vehcle ownershp and ther use n households. The report states that these beneft the companes and government by reducng the on-street parkng demand of other motorsts by reducng congeston and benefts the partcpants as they do not have to pay for parkng. Studes have shown that reductons n vehcle use are estmated to provde a parkng cost allevaton averagng 10 per vehcle-mle reduced. (d) Transportaton Impacts The drect mpacts such as reducton n automoble trps and mleage, shfts to alternatve modes, and ndrect mpacts ncludng congeston reducton, faclty cost savngs, safety and emsson reductons are measured. For example, the One-Less-Car program reportedly has reduced 15,700 vehcle-mles traveled, and ndrectly 340,000 partcpants have also reduced ther drvng. Smlarly swtchng to alternatve modes of travel could lead to mproved facltes and servces whch encourage further vehcle reductons. (e) Partcpant Fnancal Costs and Benefts These nclude fnancal rewards or ncentves and provde transport expenses. Partcpants are those who already use alternate modes and receve fnancal rewards, and others who change ther travel behavor are provded wth fnancal rewards. The net beneft s calculated followng the rule of half of consumer surplus analyss. 6 (f) Partcpant Moblty Impacts These are mpacts resultng from changes n travel pattern, ncludng mproved transportaton optons, reduced need for drvers to chauffer non-drvers, health benefts from actve transportaton and ncreased tme spent n travel. 6 The rule of half derves from the theory of consumer surplus (CS). When CS theory s used to evaluate the benefts of transportaton mprovements, benefts (or costs) to new users are valued at ther md-pont. 20

30 The reducton n drvng and walkng nstead provdes partcpants reported benefts ncludng fnancal rewards, better walkng facltes, and provdes benefts of exercse. (g) Congeston Reducton These benefts derve from reduced urban-peak vehcle travel. Ths cost reflects the delay that each addtonal vehcle mposes on other vehcle users, the avoded costs of ncreasng roadway capacty, or the drawbacks to other consumers who forego urban-peak trps because they are dscouraged by congeston. The One-Less-Car program reportedly reduces the average mx of personal travel whch saves an average of 7.5 per vehcle-mle traveled, and the Vanpoolng-To-Senor-Softball- Games project saves 3 per vehcle-mle traveled. Also the Roosevelt Hgh School project reduces the urban-peak bus travel, whch provdes 40 per vehcle-mle n congeston reducton benefts. (h) Safety, Securty and Health Shfts from drvng to transt help reduce the total traffc rsk per passenger mle whle shftng to walkng and cyclng mproves publc health and provdes ftness. Health mpacts are sgnfcant, but dffcult to quantfy[25]. About 10 tmes as many people de from cardovascular-related llnesses as from vehcle collsons, so f shfts from drvng to non-motorzed travel provde even modest reductons n such dseases, ther health benefts are comparable to large reductons n crashes. Ths analyss assgns a 5 -per-mle of reduced drvng to those trps that shft to an alternatve mode that nvolves actve transportaton, ncludng transt trps that nvolve a cyclng or walkng lnk. The report however consders only the advantages of walkng and cyclng and does not analyze the rsks nvolved wth the same. Reduced automoble travel reduces the total person-mles of travel whch helps n reducng the crash rate. The average crash cost ranges from about 5 to 15 per vehcle-mle, whch can be saved due to the reduced automoble travel. () Energy and Emssons Motor vehcle traffc causes ar, nose and water polluton and also economc external costs due to ncreased fuel consumpton. The VTPI Transportaton Costs and Beneft Analyss[12] gves a table whch shows the mddle range estmates of ar polluton costs per urban vehcle-mle. 21

31 Polluton cost per mle Auto cost( cents) Desel bus cost (cents) Ar Polluton 5 10 Nose Polluton 2 10 Water Polluton 1 1 Petroleum Externaltes 2 4 Total Table 3 Polluton Costs Vctora Transport Polcy Insttute[12] Qualtatve Evaluaton Each program was checked to determne f t meets certan crtera, and the benefts and costs were also calculated. (a) Economc Development The economc goals to be acheved are measured n terms of employment, ncome, busness actvty, etc. Shft of expendtures from fuel to more locally produced goods, reduced vehcle travel, whch n turn helps n reduced congeston delay and parkng cost savngs, and effcent land use, all contrbute towards economc productvty. (b) Equty Impacts The two types of equty mpacts consdered n the study are Horzontal Equty (whch consders whether people are treated equally) and Vertcal Equty (whch allows allocaton of costs between dfferent ncome classes and adopts polces to assst economcally, socally or physcally dsabled people). (c) Stakeholders and Publc Response The responses gven by program partcpants, staff, the general publc, meda, etc., as to whether they consdered the program effectve and benefcal are consdered n the study. Hayward Heavy Up Promoton Evaluaton- San Francsco Bay Area Rapd Transt (BART) The Hayward Heavy up Promoton s a transt orented marketng program developed by BART, Calforna, to ncrease transt rdershp. The marketng effort nvolved coordnatng an advertsng and promotonal campagn usng televson, newspaper and drect mal. A study was commssoned to assess the effcacy of ths program. The key objectve was to assess the Return of Investment (ROI) assocated wth a drect mal element[26]. 22

32 Program Strategy The key element of the campagn was the drect mal element that ncluded a flyer and a free BART tcket. The drect mal element, whch was also the most expensve, accounted for 47 percent of the promotonal campagn budget. Program Evaluaton The evaluaton was conducted usng ROI analyss to compare the cost of promoton wth the revenue generated. A telephone survey was used to collect the data for evaluaton n the month followng the expraton of the free tckets. A sample sze of 1,526 was randomly drawn from the 60,000 mals whch yelded 544 successful ntervews. The analyss produced a value of 18 percent, defned as low by the evaluaton report, due to the followng reasons[26]: 1. Not enough tckets were used; and, 2. Many of the tckets were used as a substtute for a BART trp whch would have been taken even wthout the tcket. Table 4 shows the breakup of the nvestment cost and the revenue generated. The general recommendatons gven based on the results are that an easly understood tcket and a longer valdty perod before expraton would have ncreased the number of tckets used. The costs and benefts were evaluated usng a ROI rato. 7 Ths study evaluates the drect costs and revenues and not the other potental benefts that a TDM project typcally encompasses. 7 ROI s a measure of potental cash generated by an nvestment, or the cash lost due to the nvestment. Also termed rate of return, ROI s the rato of money ganed or lost on an nvestment (proft/loss, nterest) to the amount of money nvested (captal, asset, prncpal). 23

33 AT&T Telework Program Investment Cost Amount n Dollars Meda Buys 37,023 Drect Mal 33,152 Free Tcket Substtute 20,376 Total 90,551 Revenue Generated 2,079 Tcket user Return Trps 2,079 Accompanyng Passenger 7,536 Total 9,617 Total revenue generated/ Total 11% Investment Cost Revenue Generated/(Costs-Meda) 18% Table 4 ROI of BART Promotonal Campagn Source: BART Promoton Evaluaton Report AT&T has supported ts telework program snce 1992 to encourage ts managers to work from home. The goals of the ntatve are to: Support busness objectves by puttng n place a more effectve, effcent, flexble and reslent structure for the frm; Assst employees n achevng a work/lfe balance; and, Provde an attractve ncentve to potental employees. TDM Strateges The program was establshed as part of the response to the 1990 Clean Ar Act Amendments (CAAA). AT&T establshed a company-wde team to develop complance strateges for state mplementaton of Ttle I, whch contaned a two paragraph provson that requred companes wth 100 or more employees at a sngle locaton n severe (or extreme) ozone non-attanment to develop programs to ncrease average passenger occupancy, as a surrogate measure of emssons reductons. Begnnng wth modest forecast predctons of about 10 percent n 1992; by early 2000, the program had grown to an extent where nearly 56 percent of ts managers telecommuted at least once a month whle 27 percent telecommuted at least once a week. The quantfable advantages that the company reports nclude envronmental mpacts and reduced commute tmes. The AT&T calculaton of the envronmental mpact from telecommutng has been lmted to the net transportaton effects assocated wth the commute and errand mles. 24

34 Program Evaluaton The AT&T Telework Program evaluaton s conducted on an emsson reducton bass. Other quantfable advantages that the company reports nclude envronmental mpacts and reduced commute tmes. Calculaton of the envronmental mpact from telecommutng has been lmted to the net transportaton effects assocated wth the commute and errand mles. The AT&T survey studes the average commute lengths for the employees who telework along wth the average length of commute. Emsson factors used are obtaned from the Natonal Envronmental Polcy Insttute (NEPI) and are based on a mass per mle bass, assumng average gasolne mleage. These are multpled by the estmated savngs n commute travel (n mles) to estmate the total savngs. These savngs were calculated based on the average dstrbuton of days worked at home, the average roundtrp commute dstance and net errand mles, and then aggregated to the 67,900 employees reported by AT&T to have teleworked at the tme of the October 2000 survey. The total number of mles avoded was 110,000, wth 5.1 mllon gallons of gasolne saved. It must be acknowledged that the mpacts rely on the assumpton that all telecommutng behavor s assumed to be attrbutable to the program. It s not clear f any attempt was made to estmate telecommute trends n the regon or at other companes over the same perod wthout a smlar program. The fact-sheet of the AT&T annual survey of ts employees on telework ndcates that n 2000, AT&T's employee telework program resulted n: Avodance of 110 mllon mles of drvng to the offce; 5.1 mllon gallons of gas saved; Reducton of 50,000 tons of carbon doxde emssons; 56 percent of partcpants teleworkng at least one day per month; and, 27 percent of partcpants workng from home once or more per week. A key element of the reported programs success has been AT&T s web portal to promote and educate employees about the Telework Intatve. The web portal smplfes the requrements to set-up a teleworkng locaton by ncludng gudance on how to acqure a computer; how to obtan proper telephone lne nstallaton; securty ssues and formal polces and agreements requred. Evaluatng Behavor Change n Transport: Beneft Cost Analyss of Indvdualzed Marketng for the Cty of South Perth Vewed as a plot project, ths study was carred out n Perth, Australa to encourage a study group to swtch to transt, walkng and cyclng. A beneft cost analyss was developed as part of the assessment process to attract captal works fundng for a no- 25

35 buld soluton to ncrease use of exstng publc transport, cyclng and walkng assets and to defer the demand for future road assets. The fundng submsson process was successful wth $1.2 mllon dollars beng allocated to the project. TDM Strateges The study was motvated by the premse that travel behavoral change can be brought about by educatng ndvduals separately about the costs and benefts assocated wth each mode. Ths strategy, termed ndvdualzed marketng, comprses motvatonal methods to alter travel behavor that reduces one of the major presumed constrants assocated wth smlar promotonal efforts: the effectveness of learnng declnes over tme unless the message s contnually renforced. Program Evaluaton Benefts, costs and transfers are all quantfed n three dfferent contexts- soco-economc, publc sector fnance and prvate user. Based on the applcablty of monetary values, especally for socal and envronmental mpacts, and the dervaton and applcaton of mplct or explct weghtng schemes for varous components, the costs and benefts can be ncorporated nto a sngle evaluaton framework. There are two costs assocated wth ths program: settng up the ndvdualzed marketng and ts contnued support, and the cost of mprovng transt facltes. The benefts are quantfed and classfed nto the followng categores: Travel Tme and Transportaton Related Benefts to the User These nclude benefts from swtchng to publc transt, cyclng costs, walkng costs, publc transt fares, and the effect of reduced/ncreased travel tmes. Travel tme costs are estmated based on certan standardzed procedures, but the value that s attrbuted to travel tme mght vary from person to person and depend on the knd of employment. Dfferent values attrbuted to travel tme make the overall beneft cost rato dfferent. A value of zero s taken as the base case and then dfferent values are attrbuted to the travel tme and the benefts n each case are quantfed. User Exposure to Ar Pollutants There may be an averson to cyclng and walkng n heavy traffc owng to vehcle emssons. Research establshed that car-occupants absorb much hgher levels of exhaust polluton than cyclsts, walkers or bus passengers (ETA, 1997) [27]. In ths exercse, t s stated that ths nformaton s lkely to have renforced the substtuton for more dstant destnatons for some trps. Changes n user exposure to ar polluton have not been quantfed or valued n ths evaluaton, but t s mportant to acknowledge that such changes represent a negatve mpact for those who now choose to walk, cycle or catch publc transport (Most reports gve numercal values to the ar 26

36 emsson levels makng them quantfable also. Hence, benefts are n terms of reduced emsson levels and lower pollutant levels). Road Trauma The report states that the road trauma mpacts of changes n travel behavor have two prncpal components:. A reducton n road trauma nvolvng motor vehcles; and,. An ncrease n road trauma nvolvng cyclsts and walkers. Health and Ftness Substtutng more actve modes of transport (such as cyclng and walkng) for car drvng mproves the health and ftness of people who make that change. Ths has been well documented and estmates can be made of the magntude of some of the mpacts, but not generally wthn a framework sutable for adopton n soco-economc evaluaton. There has, however, been useful quantfcaton of ncreased lfe expectancy due to cyclng actvty. Hllman (1997) has estmated that, n the Unted Kngdom, for every lfe year lost as a result of ncreased cyclng (bearng n mnd that cyclng has a hgher accdent rate than motorzed modes), 20 lfe years are ganed through mproved health and ftness. Assumng that the same relatvty s approprate n Australa, the 20:1 rato can be appled to the fatalty component (4%) of the road trauma resultng from ncreased cycle use. Congeston Costs Ths s an mportant part of the evaluaton procedure. There are dfferent condtons assocated wth congeston:. Margnal cost always exceeds average cost; the cost mposed by one more car exceeds the cost experenced by each car already on the road;. Margnal cost ncreases wth traffc volume - each extra car mposes successvely hgher costs; and,. Most congeston costs (66% n Melbourne), across the whole road network mposed by the margnal vehcle are mposed on other road users. Evaluatons are carred out for soco-economc, fnancal evaluaton for publc agences and are carred over horzons of 10 and 30 years. Even on the most conservatve assumpton n the central evaluaton, an nvestment of $1.3 mllon n ndvdualzed marketng n South Perth would produce benefts of $16.8 mllon (present value) over 10 years, wth a beneft-cost rato of nearly 13:1. ; ncludng the antcpated benefts through mortalty reducton ncreases the BCR (Beneft Cost Rato) to 15:1. The report concludes that ndvdualzed marketng has been demonstrated to be an effectve technque, n South Perth, for changng travel behavor and can delver benefts that substantally exceed the drect and ndrect costs. Usng a methodology and values consstent wth the evaluaton of road projects, the socoeconomc benefts of ndvdualzed marketng for South Perth exceeded the costs by a factor of between 11:1 and 13:1, over 10 years, and 12.5:1 to 15:1 over 30 years. These beneft-cost ratos are much hgher than those of nvestments n metropoltan road nfrastructure. However, for small ncrements of travel tme, the maxmum possble value consstent wth the results 27

37 of the plot project, the estmate of overall soco-economc return becomes negatve n the worst case scenaro. Trp Reducton Performance Program, Washngton State Although not related to a specfc TDM program or strategy, ths case study was deemed as relevant to ths research effort. In partcular, because t offers an nnovatve approach to assess the value of TDM by ntroducng the market based concept where buyers and sellers compete to determne the prce of a removed SOV trp. The Commute Trp Reducton (CTR) Performance Grant Program s a poneer effort n testng whether the Washngton State Department of Transportaton (WSDOT) can free transportaton capacty by removng SOV trps from the exstng network nfrastructure by means of creatng a sngle buyer market for avoded trps. Establshed n 2003, the program awards grants on a compettve bass to prvate employers, publc agences, nonproft organzatons, developers, and property managers who offer fnancal ncentves to ther employees and tenants that reduce the number of SOV commute trps taken by ther employees and tenants. In 2003, the Washngton State Legslature created a framework for the Performance Grant program and engaged the CTR Task Force n obtanng the detals n admnstratve rules. Through the program, WSDOT s tryng to create a market for purchasng SOV trps from wllng sellers, such as prvate sector entrepreneurs, non-proft seekng and publc sector enttes. The program s objectves are to: Purchase avoded SOV trps from wllng sellers; Attract entrepreneurs to trp reducton by offerng proft opportuntes; and, Encourage development of nnovatve trp reducton strateges. Based on the recommendatons of the 1991 CTR Act, whch called for the creaton of a trp reducton market, the legslature enacted a task force to ntroduce a performancebased grant program to fund projects that offer fnancal ncentves to commuters to swtch from SOV travel. The CTR work force assumed that ths would create opportunty for entrepreneurs to nvest n trp reducton and create prvate sector nterest n removng trps where addtonal roadway nfrastructure s prohbtvely expensve. The 2001 CTR Legslatve Report recommended the State Legslature create a trp reducton program to allow WSDOT to purchase removed trps from prvate partes and attract entrepreneurs to trp reducton by offerng proft opportuntes. The performance grant program conssts of a dual structure; t combnes the characterstcs of a typcal grant program, whch awards grants to organzatons that submt proposals; and a market program, whch buys performance and pays the partcpants for the number of trp reduced. The legslature and the admnstratve rules both emphasze that the program s a grant program and the performance requrement 28

38 ponts to t as a market program, whle the award of start-up costs ndcates that WSDOT funds projects as well as buys trps. A study was conducted to determne the feasblty of a trp reducton market[28]. Among the fndngs, two possble markets were dentfed: 1. A sngle-buyer market, where the buyer decdes the number or trps to be purchased and the prce wth the presence of multple sellers; and, 2. A prvate tradng market, wth multple buyers and sellers where the market prces are determned by the law of supply and demand. The study reported the sngle-buyer market as the optmal structure, gven WSDOT objectves and ts publc entty status. In ths context WSDOT values reduced trps as a good that provdes addtonal roadway capacty and where sellers are enttes provdng SOV trp reducton strateges measurable n terms of reduced SOV trps. WSDOT would act as a sngle-buyer on the market. On the other hand, a prvate tradng market s deemed unfeasble due to poltcal and legal hurdles n settng a cap on commute trps, the uncertanty n determnng whether the prvate tradng would provde the desred congeston relef, and the ambguty whether the emsson tradng markets are a postve strategy n managng ar polluton. In ths framework, the value of an avoded trp s related to many factors lke avalable fundng and underlyng prce caps. Some of the trp prcng models suggested were: Settng a trp value based on the toll amount drvers would pay to drve under reduced congeston, where prce would be nfluenced by factors such as tme of day, commute dstance, and geographc locaton; Settng a trp value based on the addtonal nfrastructure nvestment requred to add network capacty, whch depends on the number of peak users n the corrdor; and, Establshng a trp value accordng to avalable fundng and mnmum requred number of avoded trps. Ultmately, WSDOT settled for a sngle-buyer market structure characterzed by prce caps, wth a sngle statewde cap set at a maxmum of $460 per avoded trp. The cap s based on the optmal tollng for the new hghway system n the Puget Sound regon. In ths sngle-buyer market prvate employers, publc agences, nonproft organzatons and other enttes are nvted to compete n sellng reduced SOV trps by proposng trp reducton strateges or programs. Each strategy must provde an accurate assessment of ts trp reducton effcacy by measurng projected SOV trp reducton aganst a baselne. Ths baselne must be measured by means of surveys that report vehcle trps and VMT made by program or project partcpants. In addton, project performance surveys must be conducted to measure projected vs. actual trp reducton. The requrement of accuracy s defned as reasonable estmate of employee partcpaton, trp reducton, and VMT reducton, wth no specfc gudelnes or 29

39 provsons on estmaton methods[29]. Under ths framework, n 2006 WSDOT approved 17 projects for the bennum worth $1.3 mllon to purchase 3,831 SOV daly commute trps from the state hghway system. 30

40 Proposed Predcton Model In ths secton, we propose an alternatve approach to estmatng the mpact of TDM strateges. The evaluaton framework follows a basc structure for consstent assessment and comparson as found whle revewng relevant gudelnes and procedure manuals[11, 12, 18, 19]. The approach embraces the best elements of currently avalable predctve evaluaton methods, whle overcomng ther constrants dentfed n the prevous secton, namely: It uses best derved measures of prce senstvty; It follows a consumer surplus framework; It captures mportant transportaton users trade-offs; It can assess short and long run mpacts; and, It goes beyond emsson control mpact evaluaton. Fgure 2 outlnes the analytcal process, whch conssts of the followng steps: 1- Modelng Technque Ths step dentfes the theoretcal framework to predct how a polcy change or program mplementaton wll affect travel behavor. The modelng technque overcomes the constrants lnked to the use of coeffcents derved from generalzed travel demand forecastng models, as descrbed n the prevous secton. 2- Impact Measures Ths step lnks the change n travel behavor to a set of mpact measures to be used for evaluaton. Impacts are determned n terms of objectves. The objectve of ths study s to evaluate the mpact of TDM n terms of costs and benefts as vewed by a publc transportaton agency. Therefore, n lne wth the lterature revew fndngs, the mpact measures comprse the set of costs and benefts as perceved from a socetal vewpont. 3- Evaluaton Metrc In ths fnal step, the mpact measures are used wthn an evaluaton approach to determne program effectveness. The evaluaton follows establshed gudelnes that fall wthn a beneft/cost analyss framework that ultmately prces out the value of a sngle vehcle trp dverted from the network. 31

41 Baselne trps and mode shares Program Informaton Modellng Technque Change n trps for generalzed cost and travel tme polces Adjust change n trps for soft programs Constant elastcty demand model Relatonal factors adjustment Compute fnal change n Trps, VMT, Mode Shares Evaluaton Metrc Impact Measures Compute mpacts Reduced Trp Value Fgure 2 Model Flowchart 32

42 Modelng Technque In ths step, a theoretcal model to predct how a polcy change or program affects travel behavor n terms of trp change behavor s frst dentfed. The objectve s to develop a framework of analyss that can predct the effects on travel decson of dverse and often concurrent TDM strateges. The model predcts changes n the number of mode trps brought about by specfc programs or polces. The approach follows the prncples governng the law of demand for market goods and s based on prce elastctes. Economsts have long used the concept of elastcty to descrbe how ndvduals react to prce changes. The law of demand shows that, n the aggregate, as the prce of a good ncreases ts demand declnes. Ths also apples to the demand for transportaton goods and servces, where prces can take many forms, monetary, such as the cost of usng a gven mode, and non monetary, such as the perceved cost of tme. For example, changes n the cost of travel can affect the number of trps undertaken, the choce of travel tme and the choce of mode. The elastcty of demand measures how changes n the prce of a good wll lead to changes n the quantty purchased and consumpton of that good. The elastcty records how the quantty demanded changes n response to a percentage change n ts prce (and also n the prce of competng or complementary goods)[27]. As detaled n ths secton, the proposed framework allows capturng a broader range of trade-offs that users constantly face and s capable of quantfyng mpacts on travel patterns by usng prces as the drect drvers of travel demand. Furthermore, the approach s able to take nto account how ndvduals re-adjust over tme n ther trade-offs. Constant Elastcty Demand for Trps The followng example s desgned to provde a better understandng of the relatonshp between prce and travel tme elastctes and how these relate to travel behavor. Two basc assumptons, whch wll be relaxed once the model s fully developed and appled n the next secton of the report, are made, namely: 8 There are two modes, auto and transt; and, The major cost drvers are represented by fuel cost and travel tmes. Let us assume the followng travel demand functon: Where: d P ε T ε ε j T, j = AP T T (1) 8 Durng the spreadsheet desgn phase, descrbed n the next secton of the report, the model s expanded to nclude more than two modes, addtonal modal cost drvers, such as transt fare, watng tme, parkng costs, and other varable vehcle operatng costs. 33

43 d = demand for auto travel (say vehcle trps per day) j = transt mode A = scale parameter P = car travel fuel prce T = car travel tme T j = transt travel tme P ε T ε T ε, j = car fuel demand elastcty = car travel tme demand elastcty = car travel tme cross-elastcty wth respect to transt travel tme Ths specfc form of the demand functon, a constant-elastcty demand functon, s chosen because of ts wde emprcal applcaton n the estmaton of travel demand elastctes and for ts ease of analytcal tractablty. 9 The fuel prce elastcty of a car measures the percent reducton n car vehcle trps due to a one percent ncrease n ts prce. The travel tme elastcty of demand measures the percent reducton n car vehcle trps due to a one percent ncrease n travel tme. Fnally, the car travel tme cross elastcty wth respect to transt travel tme measures the percent reducton n vehcle trps due to a one percent decrease n transt travel tme. Ths assumes that car and transt are substtutes. 10 Now, for ntal values of fuel prce, tme and trps, denoted by subscrpt zeros, the equaton wll be: d 0 P ε 0 T ε 0 T, j ε j0 = AP T T (2) 9 The demand curves usually employed and depcted n graphs are lnear demand curves, whch have the property that prce elastcty declnes as we move down the demand curve. Not all demand curves have ths property, however; on the contrary, there are demand curves for whch prce elastcty can reman constant or even rse wth movements down the demand curve. The constant elastcty demand curve s the name gven to a demand curve for whch elastcty does not vary wth prce and quantty. Whereas the lnear demand curve has the general form: P = a bq, the constant elastcty demand curve s nstead wrtten as: k P = 1 η Q Where k and η are postve numbers that determned the shape of the curve. 10 Two goods are consdered substtutes f the ncrease n the prce of one determnes an ncrease n the demand for the other. Two goods are consdered complements f the ncrease n the prce of one good causes a decrease n the demand for both goods (e.g., coffee and cream). The relatonshp s further refned by consderng perfect versus less-than-perfect substtuton and complement. 34

44 Solvng for A n (2) and substtutng the results back nto (1), we can elmnate the scale parameter and ensure that the demand functon passes through the pont (d 0,P 0, T 0 ). The resultng equaton s: T j T P j j T T T T P P d d, ε ε ε = (3) Then, f a polcy or program changes the transportaton costs and travel tmes, the new number of vehcle trps s obtaned by substtutng the new costs and travel tmes nto equaton (3), gvng: T j T P j j T T T T P P d d, ε ε ε = (4) Fnally, what we are nterested n s the change n the number of vehcle trps, whch s gven by: = = Δ 1, T j T P j j T T T T P P d d d d ε ε ε (5) Ths last formula consttutes the approach to model the change n demand brought about by program or polces affectng the perceved cost of travel, both monetary and non monetary. Equaton (5) can be smplfed or expanded to nclude addtonal cost factors and to comprse cross relatonshps wth one or more modes as shown n the next secton of the report. Advantages and Constrants The prevous secton of ths report observed that there exst dfferent ways of provdng a smple, yet powerful and robust approach to estmatng the mpacts of alternatve strateges at a sketch plannng level. For example, the EPA COMMUTER model employs a pvot pont approach whch reles on the theoretcal underpnnngs of dscrete choce governng travel demand estmaton. The EPA choce reles on an ndvdual decson makng process among mutually exclusve alternatves, namely dfferent and opposng transportaton modes. Ths s what s usually assumed by all predctve evaluaton methods currently avalable for TDM assessment. The approach proposed heren s capable of estmatng mode share changes. It can predct mode share changes not only from SOV to other alternatves, but among these alternatves themselves. It 35

45 acknowledges substtuton and complements effects that mght exst between varous modes. The constant elastcty of demand approach proposed requres basc nformaton on the cost and tme components of modal trps, on the ntal mode share. By enterng the mpact on the generalzed cost of travel of a gven polcy or program, the model estmates the mpact on the fnal mode shares. These data requrements are descrbed n greater detal n the next secton of ths report. The model estmates mpacts on travel behavor n a synergstc fashon. That s, the model allows the smultaneous mpact assessment of several TDM polces or strateges, where the fnal total mpacts are greater than the sum of the mpact of each ndvdual strategy. In addton, the constant elastcty of demand equaton (5) assures that mpacts are assessed n a multplcatve, rather than an addtve, fashon avodng mpacts overestmaton. For example, f one strategy (e.g., a transt subsdy) reduces SOV use by 5 percent and another strategy, say parkng prcng, reduces SOV use by an addtonal 7 percent, the total combned effect s a 11.5 percent reducton( calculated as 100% - [95% x 93%]), rather than a 12 percent reducton (lnearly calculated as 7% + 5%). Another advantage of the model s that t allows program evaluaton based on ncremental mpacts. For example, under the constant elastcty demand framework the congeston reducton benefts of a shft from SOV to transt s the dfference n congeston mpacts between SOV and transt travel. Usng a base case approach (a scenaro where a polcy or program s not mplemented), the model estmates the net benefts of shftng from SOV to alternatve modes. Also, the model permts dstngushng between peak and off-peak mpact estmaton at an urban area level. One of the constrants related to the use of elastctes relates to tmeframes employed when emprcally estmatng ther values. Appled work generally employs short and medum terms (3-5 years), thus tendng to underestmate the full, long term effects of prce and servce changes. In other terms, ncreasng (reducng) a transt fare has more negatve (postve) effects than what generally predcted by most models. Soft Program Trp Change Adjustments The precedng model estmates the mpact on trp behavor of polces affectng the generalzed cost of drvng, thus allowng the mpact of the followng TDM strateges to be captured. The constant elastcty of demand model s best suted for strateges that drectly affect the generalzed cost of drvng, and a set of TDM strateges, such as: Parkng prcng; Modal subsdes; Pay as you go schemes; 36

46 Transt servce mprovements; and, Other nterventons affectng the cost of drvng or modal access and travel tme. These strateges often ntegrate both ncentves and dsncentves. The latter are usually defned as stcks and comprse actons geared at drectly nfluencng the cost of drvng, such as ncreased auto user charges, parkng prcng, and traffc calmng. All other strateges that are desgned to enhance voluntary behavor changes are defned as carrots and usually consst of measures geared ether at ncreasng the knowledge of alternatve modes and programs or at nternalzng some of the costs assocated to drvng that would otherwse be borne by others. Examples of soft program ntatves nclude: Travel Plannng; Personalzed Marketng; Flexble Work Hours; Telecommutng; Guaranteed Rde Home Programs; and, Dscount for Walkng and/or Cyclng Gear. Although these programs do not drectly affect the cost of usng a mode, they tend to mpact travel behavor when part of a program conssts of hard measures. Generally, t s not possble to drectly estmate a pror change n travel behavor of these TDM strateges. The lterature revew uncovered that the general trend to evaluaton s one that reles on cullng nformaton from a varety of reports and evaluaton analyses to produce a table of dverson rates to then be used to estmate trp change behavor. Ths approach s followed by the New Zealand Travel Behavor Change Gudance and by the U.K. Department of Transportaton Smarter Choce Program. In ths report, the approach to evaluate the mpact of soft programs on travel behavor reles on an econometrc analyss of the relatonshp between hard and soft programs. Startng wth the assumpton that voluntary travel behavor ntatves lead to change only n the presence of hard programs, the mpact of the followng carrot ntatves s consdered: Program Promoton; Flexble Work Hours; Telecommutng; Guaranteed Rde Home Programs; and, Presence of Amentes (restaurants, ATMs, chldcare). The mpact analyss s conducted by buldng a regresson equaton where each of these programs enters nto an emprcal equaton estmatng the change n rdershp as an 37

47 explanatory varable n a context of nteracton wth hard programs. 11 equaton takes the form: The regresson y = β 0 + β1x1 + β 2x β k xk + ε (7) Where: y = s dependent varable, n ths case vehcle trp rate at workste x 1, x2,..., x k = explanatory varables (soft and hard program polces, frm characterstcs, other controls) ε = stochastc or error term Equaton (7) can nclude hgher order term to acknowledge nonlnear relatonshps, and nteracton terms between the response varables. Gven that the objectve s to buld a model that can predct the effect on vehcle trp rate reducton of one or more soft program ntatves, workste trp reducton data between consecutve years are needed. In the analyss, the Washngton Sate Department of Transportaton Trp Reducton Program dataset was obtaned for the perod 1995 to The data reports nformaton on workste characterstcs, such as frm sze and ndustry type, employee mode share, and nformaton of TDM programs. The data were analyzed and factor analyss was employed to reduce the number of explanatory varables to mprove model predcton power. 12 Durng the model buldng phase, several varatons of Equaton (7) were consdered. At the end, a predctve model that allows for nteracton between qualtatve varables was chosen as the one wth the hgher predctve power. 13 A table of dverson rates was developed based on ths predctve model to be used wthn the sketch plannng tool descrbed n the next secton of ths report The model heren proposed to buld upon prevous work conducted by CUTR n estmatng workste trp reducton tables [30]. 12 Factor analyss s a statstcal technque that reduces several varables that are correlated nto a smaller set of new, uncorrelated and meanngful varables. 13 In a regresson model, qualtatve varables take the form of dummy varables. These are explanatory varables that take the value of 1 f present or take the value 0 f absent. For example, dummy varables can be used to estmate man effects due to the presence or the absence of a gven program promoton ntatve, a gven subsdy, and the offerng or not of a guaranteed rde home program. Furthermore, very often these ntatves are lnked to each other n an nteractve fashon. An nteracton model has to be bult to analyze a man effect model. 14 The dverson rates accompany the model CD. 38

48 Evaluaton Crtera It has been demonstrated how the modelng technque provdes a consstent approach to predct travel behavor change brought about by both hard and soft TDM programs. The next step s to lnk behavoral change to mpacts wthn an evaluaton framework that provdes cost effectveness benchmarkng and allows TDM to be compared to tradtonal nfrastructure nvestments. The estmated number of trps reduced must be lnked to a set of benefts or mpacts. It s therefore relevant to determne what should consttute the set of approprate benefts to be used for fnal evaluaton. The lterature revew uncovered two man factors that lead to a proper evaluaton of TDM strateges: TDM evaluaton must be comprehensve, embracng benefts that drectly relate to the users and ndrectly to all other ndvduals, and t should Lead to a framework of consumer demand conducve to a beneft cost analyss approach for comparatve assessment. The lterature on TDM benefts shows how these are drectly related to cost generated by SOV use. Generally, costs that are borne drectly by the users are defned as nternal costs and those costs that are not drectly borne by the users are defned as external costs. The latter socetal costs belong to what economsts descrbe as negatve externaltes. Negatve externaltes arse whenever costs assocated wth SOV use, such as added congeston delay, ar polluton, and ncreased accdent rsk, are not drectly sustaned by auto users but are rather mposed on the socety as a whole. Although a comprehensve approach should capture all mpacts whether nternal or external, the proper set of mpacts should be defned based on the nature of the decsonmaker. If the evaluaton has an employer focus, then the set of mpacts mght nclude benefts manly representng actual savngs to employers. If the evaluaton s carred out by a publc decson makng agent, such as a transt agency or a government body, then the set of mpacts should be more nclusve of negatve externaltes. If the evaluaton has an employer focus, then the set of mpacts mght nclude benefts manly representng actual savngs to employers. Table 5 shows the range of transportaton costs categores or TDM benefts that comprse the set of evaluaton crtera to be used wthn the proposed modelng framework. It conssts of a subset of all possble mpacts that mght be generated by TDM polces, focusng on those that can be readly monetzed n a consstent and robust fashon. The lst of mpacts s also consstent wth what s currently employed n evaluatng tradtonal nfrastructure nvestments Although, n most transportaton nfrastructure nvestment decsons a subset of mpacts s usually consdered, such as travel tme, vehcle operatng, accdent, and polluton costs. 39

49 Costs Descrpton Type Vehcle Ownershp Vehcle purchase, nsurance and other charges Internal-Fxed Vehcle Operaton Mantenance and repar costs Internal-Varable Travel Tme Internal Crash External Crash Value of travel tme based on prevalng wage rate Drect user property damage, personal njury, death Property damage, personal njury, death mposed on others Internal-Varable Internal-Varable External Internal Parkng Average car parkng cost Internal-Fxed External Parkng Land use, captal costs External Congeston Ar Polluton Other Polluton Land Use Other Externaltes Incremental travel tme delay and ncreased fuel consumpton Cost of major pollutants: Hydro Carbons (HC), Carbon Monoxde (CO) and Ntrous Oxdes (NOx). Includes nose, water and waste (vehcle parts dsposal) opportunty cost land devoted to roads Includes costs related to barrer effects, equty, dversty, and other resource externaltes Table 5 SOV Cost Externaltes External External External External External As t wll be seen n the next secton dealng wth the model applcaton, ths set of externaltes can be expanded or contracted wthn the sketch plannng tool. Ths grants flexblty to the users by allowng the ncluson or excluson of gven externaltes, dependng on the program beng evaluated or the objectves to be reached. Evaluaton Method: Per Passenger-Trp Average Annualzed Benefts In ths fnal step, the mpact measures are used wthn an evaluaton approach to determne program effectveness. The evaluaton follows establshed gudelnes that fall wthn a beneft/cost analyss framework that ultmately prces out the value of a snglevehcle trp dverted from the network. Gven that the objectve of most (f not all) TDM 40

50 strateges s to reduce the need for addtonal SOV trps, the choce of passenger-trp as a unt of measurement allows the most accurate benchmarkng measure. The value of a trp removed s measured n annualzed dollars per addtonal passengertrp. The value of a trp removed s obtaned usng the followng formula: Value of trp removed = Sum (per passenger-trp annualzed benefts mnus per passenger-trp annualzed costs) The unt of measure s expressed n current dollars, and the followng procedure shows how to estmate the value of a trp removed and measure t n annualzed dollars on a per passenger-trp bass. Equaton (5) estmates the number of passenger-trps reduced per day. By assumng that ths reducton wll last for the duraton of the program, the followng dentty can be establshed: Trps Reduced/Day Average Trps Reduced = per Day/Year = Average Annual Daly Trps (AADT) Reduced The dentty sgnfes that the number of daly passenger-trps reduced stays constant throughout the duraton of the program (no addtonal new daly passenger-trp reducton wll be ganed durng each remanng day of the year). Therefore, the number of daly passenger-trps reduced s equvalent to the average annual daly trps reduced. Next, the daly benefts of the program are computed. Ths s done by multplyng the number of reduced passenger-trps by the per trp beneft: Trps Reduced/Day X Beneft($)/ Trp = Beneft ($)/Day Next, daly benefts must be annualzed. Assumng there are 235 workng days n a year, 16 then the total annual benefts are computed as: Beneft ($)/Day X = Work Days/Year Beneft ($)/ Year Now, recall that the number of daly passenger-trps removed s the same as the average annual daly trps removed, on an annualzed bass, the annualzed benefts per passengertrp removed are computed as: 16 Ths assumes 10 days of holdays, 10 days of vacaton, and 5 days of sck leave. 41

51 Beneft ($)/ Year Average Annual Daly / Trps (AADT) = Reduced Annualzed Benefts per AADT Reduced Next, the formula to convert program costs nto an annualzed bass s: ( 1+ ) n ( 1+ ) n A = P (6) 1 Where: A = Annualzed value, measured n dollars P = present value, measured n dollars = annual nterest rate n = length of the program, measured n years Another benchmark measure that the model provdes s a per passenger-trp beneft to cost rato, defned as the rato of annualzed per passenger-trp benefts to per passengertrp costs: Annualzed Benefts/ AADT Reduced Annualzed Costs/ / AADT Reduced = Beneft/Cost Rato As seen n the followng example, ths last measure provdes a metrc sutable for ntracomparson across dfferent competng TDM alternatves and for nter-comparson,.e., TDM strategy versus capacty expanson. Appled Example: Transt Travel Tme Improvement and Parkng Cost Increase A smple example provdes some nsght on how the constant elastcty of the demand model can be used to estmate mpacts on travel behavor produced by changes n the generalzed costs of two modes. We start by defnng a base case scenaro (absence of program strategy) by assumng a set of ntal cost and travel tme values for both SOV and transt: 17 d = 3,000 vehcle round trps per day P 0 = $6.00 current daly SOV parkng cost 17 Elastcty estmates are obtaned from Ltman [28]. The study provdes a summary of varous elastcty estmates culled from several publcatons. 42

52 T 0 = 15 mnutes two way auto travel tme T 1 = 15 mnutes two way auto travel tme T j0 = 30 mnutes two way transt travel tme P ε =-0.08 parkng prce elastcty T ε = auto travel tme elastcty T ε, j = auto travel cross tme elastcty wth respect to transt = Auto j = Transt Next we ntroduce a trp reducton strategy that reduces transt travel tme by 10 mnutes and ncreases SOV parkng cost from $6.00 to $9.00 per day. The program detals and costs are as follows: P 1 = $9.00 new daly SOV parkng cost T j1 = 20 mnutes new two way transt travel tme $50,000 program mplementaton cost n = 2 program length (years) = 6.00% current nterest rate[30] Wth these ntal base case scenaro values, the demand for SOV trps s equal to 3,000 round trps per day. Next, we use Equaton (5) to estmate the change n vehcle trps brought about by a transt mprovement that reduces the overall travel tme by 10 mnutes, and an ncrease n car parkng costs from $6.00 to $9.00 daly. Followng ths approach, t suffces to plug n the above values n Equaton (5) to obtan the change n vehcle trps per day as a result of the combned effect of transt mprovement and car parkng polcy. The estmaton produces a decrease of 138 vehcle trps, or 5 percent, based on the ntal elastcty assumptons: 18 Δd 9.00 = 3, = 138 It s relevant to note that the total number of trps reduced s the result of a multplcatve effect of the two polces affectng parkng prcng and transt travel tme. Each of these polces has a drect and ndrect mpact on travel demand, as detaled n Fgure 3, whch dsplays the demand for SOV trps. 19 Let Tj be the travel tme of the alternatve mode, n 18 Note that trps do not add up for each day that goes by, as to say that the frst day we reduce 138 trps and the next day we reduce another 138 new trps. These reduced trps are recurrng reduced daly trps and are to be consdered as annual daly vehcle trps or ADDT, f we wsh to use the acronym normally employed n transportaton demand modelng. 19 For ease of dsplay, the demand curve s represented as a lnear functon, whle the constant elastcty s curvlnear n nature. The graph s not to scale. 43

53 ths example transt travel tme. In the fgure, D 0,j0 represents the demand for car trps at the ntal value of transt travel tme and car parkng cost, whle D 1,j1 represent the fnal demand for vehcle trps at the new parkng cost and transt travel tme. Let Q symbolze the number of vehcle trps and P the cost or prce per vehcle trp. Note that the cost per vehcle trp could comprse several components ncludng parkng, operatng and mantenance costs. The two polces exert two effects on the demand for SOV trps. The frst s determned by the reducton n transt travel tme. Assumng that SOV and transt are substtutes (ndvduals consder them as two competng travel modes), a decrease n transt travel tme causes a modal change from SOV to transt. Ths s represented by the move from pont A to pont B and depcted by a shft to the left of the demand for SOV trps, a reducton n 44 vehcle trps. The second effect s determned by the parkng charge ncrease and s represented by the movement along the new demand curve from pont B to pont C; a reducton of 94 vehcle trps. The latter mpact s greater, ndcatng the relevance of parkng prcng polces on the demand for SOV trps. 20 P D 0,j0 D 1,j1 P 1 C P 0 B A Q 2,862 2,956 3,000 Fgure 3 Demand for SOV trps The reader mght wonder what the effect of a SOV parkng charge ncrease would be on the demand for transt trps. Ths requres adjustng Equaton (5) to nclude a parameter 20 As confrmed by emprcal analyses on drect and cross parkng prce elastctes. 44

54 to represent the cross-prce elastcty of transt trps wth respect to auto parkng prce. Ths s done n the full extenson of Equaton (5) of the sketch plannng applcaton. Indeed, ths approach can be extended to evaluate all TDM programs or strateges affectng the generalzed costs of transport and modal travel tmes. The estmated change n SOV trps can subsequently be used wthn a socal welfare framework of analyss. For example, the number of SOV dverted trps can be evaluated n a beneft cost analyss fashon, where each reduced trp s valued for the socetal benefts t contrbutes to, and dscounted by the cost ncurred to dvert t to other modes. The next step of the evaluaton s to assess the net annualzed benefts that these 138 reduced vehcle trps provde. Let us assume that the sum of per passenger-trp external costs assocated wth SOV s equal to $2.00 per round trp. Therefore, the average daly benefts brought about by the 138 reduced trps are: (138 trps/day) X ($2.00/trp) = $276/day Assumng an average of 235 workng days per year, the annual benefts are equal to: ($276/day) X (235 days/year) = $64,782/year Snce the number of daly passenger-trps reduced s equvalent to the average annual daly trps (AADT) reduced, the annualzed per passenger-trp beneft s equal to: ($64,782) / (138 AADT reduced) = $470 per AADT reduced Now, we turn to compute the annualzed cost of the program, by pluggng the example numbers nto Equaton (6): A = ( ) ( ) ,000 2 Whch on a per AADT reduced bass s equvalent to: 2 1 = $27,272 ($27,272)/(138)= $ 198 per AADT reduced Fnally, the value of a trp removed s equal to the sum of benefts and costs: Value of trp removed (per AADT reduced) = $470 - $198 = $272 Another sgnfcant measure of the program effectveness s gven by the beneft to cost rato, whch s equvalent to: $470 / $198 =

55 The latter means that for every one dollar nvested n the TDM polcy there s a gan of $2.40 n overall benefts. Both the value of the trp removed and the beneft to cost rato are measures of effectveness wdely used for program benchmarkng and evaluaton. 46

56 Model Implementaton: TRIMMS To translate the theoretcal framework of the predcton model developed n the prevous secton, we developed a sketch-plannng model n the form of a spreadsheet module. Sketch-plannng models represent a class of rather straghtforward models that focus on the ntal or screenng phases of analyss. These models are used for stuatons where performng a more sophstcated analyss s not possble, or requres a costly effort n terms of data gatherng. Spreadsheet modules or applcatons represent an deal tool for the frst phases of plannng and estmaton. They are desgned n a way whch allows someone other than the developer to perform useful work wthout extensve tranng. Spreadsheets enable the end user to perform a dverse set of analyses usng effcent methods and algorthms to produce accurate results, utlzng an nterface that s clear and consstent. Modules can be desgned n a fashon so that they can be modfed wth mnmum effort and maxmum flexblty; they are portable and run on any system that has commonly used software. The spreadsheet model takes the acronym of TRIMMS, Trp Reducton Impacts of Moblty Management Strateges. The model takes ts name from ts man characterstc, namely the estmaton of the value of a passenger trp removed as a result of a TDM polcy. Fgure 4 depcts the nternal structure of TRIMMS, whch follows from the theoretcal framework developed n the prevous secton. Startng from a base case scenaro representatve of the program or strategy beng evaluated, the constant elastcty model estmates fnal mode share changes, resultng n hard program mpacts. If the evaluaton extends to soft programs, such as program promoton or any other voluntary behavoral change measure, a separate module s desgned to estmate the mpacts. The evaluaton s carred out n an nteractve fashon where the user answers a set of questons, whose results are used to call a pror estmated dverson rates. The fnal mpact shares are then used to conduct the socal welfare analyss that leads to the producton of the evaluaton metrc explaned n the prevous secton, namely the value of a trp removed. 47

57 Baselne Case Scenaro Baselne Inputs - Trp Splt - Mode Share - Travel Tmes Hard Program Impacts - Fnancal Incentves - Fnancal Ds-ncentves Trp Demand Estmaton -Constant Elastcty of Demand Model Soft Program Impacts - Program Promoton - Guaranteed Rde Home - Flexble Work Hours - Telecommutng - Amentes Hedonc Regresson Analyss Model Output Change n baselne trps - New - Dverted - Change n fnal mode shares - Change n fnal VMT Socal Welfare Analyss - Added & reduced externaltes Beneft Measures - Health and Safety - Congeston - Emsson Polluton - Land Use Impacts - Other Value of Trp Removed - Net per passenger trp annualzed benefts - Net per passenger trp annualzed program cost - Peak and off-peak values - Beneft to cost rato Fgure 4 TRIMMS Inner Layout 48

58 Defnng the Base Case: Input Requrements To functon correctly, the model needs a set of nput data that altogether defne the base case scenaro. The base case defnes the status of a program n ts current shape and form, wthout the mplementaton of the proposed polcy or strategy. Program Informaton - Ths conssts of nformaton on the base case scenaro, where program characterstcs are descrbed. Indvdual Informaton Ths conssts of nformaton on the number of users the polcy wll affect. Usually ths comprses the pool of employees partcpatng as beng part of a TDM program. Trp Data Ths ncludes nformaton on mode shares, average trp length and travel tme by mode, and average vehcle occupancy. Ths nformaton s entered nto a worksheet tab enttled Base Case Scenaro, whch s dsplayed n Fgure 5. Fgure 5 TRIMMS Base Case Scenaro Worksheet When enterng the program nformaton, the user can select the year the analyss s beng conducted and all costs and benefts are mmedately adjusted to current dollar values. Next, the user s drected to estmate the mpact of several program strateges or polces. Followng the lterature on TDM strateges, mpact evaluaton s splt nto hard program 49

59 and soft program evaluaton. Hard program evaluaton s splt nto two separate worksheets, each allowng the assessment of a wde range of polces or strateges havng a drect mpact on the generalzed cost of travel and the value of tme. At the clck of a button, the model can be fully customzed by modfyng all of the default cost and trp demand functon parameters, as explaned n further detals n ths secton. Fnancal Incentves and Dsncentves In ths worksheet, dfferent TDM strateges affectng the cost of travel can be assessed. These nclude programs or polces geared at penalzng the cost of SOV use (the so called stcks ), such as; SOV parkng prce changes; Pay-as-you-go schemes; and, Other polces affectng the cost of SOV use. Ths worksheet also allows estmaton of the mpact of TDM ncentves ( carrots ) drectly affectng the cost of drvng alternatve modes ether by drectly lowerng the cost of usng a mode or ndrectly n the form of a subsdy. Fgure 6 provdes a snapshot of the Fnancal Incentves worksheet. Fgure 6 TRIMMS - Fnancal Incentve Worksheet 50

60 Travel Tme Improvements In ths worksheet the user can evaluate the mpact of strateges affectng modal travel tme. Fgure 7 shows that the model dfferentates between access and travel tme, thus allowng the user to assess the mpact of strateges that affect the two most relevant components of travel tme. The model allows the evaluaton of a sngle polcy or the smultaneous assessment of a portfolo of strateges representng a mx of stcks and carrots to understand how polces are nterlnked. Senstvty analyss of the sketch-plannng model showed that the fnal mpact of the value of a trp removed s dependent upon the followng assumptons: Program sze and characterstcs (employee ntal modal splt); Polcy beng evaluated (sngle polcy vs. a package of ncentves and dsncentves); and, Mx of fnancal ncentves and travel tme mprovements. In partcular, the value of a trp removed s relatvely senstve to a polcy affectng the cost of parkng. The mpact s relatvely greater f addtonal polces are consdered, such as applyng a subsdy and a travel tme mprovement on transt servces. Fgure 7 TRIMMS Travel Tme Improvements Worksheet Soft Program Impacts In ths worksheet, the user can evaluate the followng ntatves: 51

61 Program Promoton; Flexble Work Hours; Telecommutng; Guaranteed Rde Home Programs; and, Presence of Amentes (restaurants, ATMs, chldcare). As dscussed n the prevous secton, these measures fall nto the defnton of carrots to ndcate those polces that are ntended to voluntarly promote change n travel behavor. The lterature revew and case study analyss revealed that there exsts an abundance of such polces, whose mpact on travel behavor s dffcult to estmate. As prevously descrbed, whle these strateges do not have a drect mpact on the cost of drvng or the value of travel tme, they exert an ndrect effect on the choce of alternatve modes. Furthermore, ther mpact on fnal modal share s the result of the absence or presence of hard program measures. In ths worksheet, the user s guded through several steps where he/she s asked to answer several questons as dsplayed n Fgure 8. Based on the answers, fnal modal shares are provded to evaluate soft program mpacts. In the presence of hard program measures, these sets of questons serve to balance the fnal modal share to provde a combned evaluaton of soft and hard program measures. The user s asked to fll nformaton on the followng steps: 1. Industry Classfcaton; 2. Workste Characterstcs; 3. Program Marketng; 4. Program Subsdes; 5. Guaranteed Rde Home and Rde Match; and, 6. Telecommutng and Flexble Work Hours. 52

62 Fgure 8 TRIMMS Step by Step Soft Program Evaluaton The user s guded through a set of questons comprsng the sx screens. Based on the answers provded, the model automatcally apples a set of dverson rates, whch were derved usng the soft program estmaton procedures outlned n the prevous secton. Just lke n the case of hard program evaluaton, the user has the opton to overrde the model and manually supply the fnal mode shares. Model Output Fgure 9 shows the layout of the Model Output worksheet. All polces or strateges beng evaluated are summarzed and ther mpact s presented and summarzed by employng the evaluaton metrc of choce dscussed n the prevous secton. The layout s smlar to that of the EPA Commuter 2.0, to provde contnuty to those practtoners already accustomed to polluton emsson evaluaton. The user can create custom charts by clckng on command buttons located on the worksheet, as well as go back to the Base Case Scenaro. To better understand how to read and nterpret the results, the next secton of the report provdes applcaton examples. 53

63 Fgure 9 TRIMMS Model Output 54

64 Customzng the Model TRIMMS has been desgned to be fully flexble and customzable by the end user. To allow modfcaton of assumpton and results, the model permts full customzaton of the followng: Modal Cost Externaltes; Travel Demand Functon Elastctes; and, User Suppled Fnal Modal Shares. In every step of the analyss, the user can modfy these three man factors and s encouraged to customze the model to better ft t to the analyss context. Below, each of these factors s dscussed n terms of effects and mplcaton on the model results. Modal Cost Externaltes In the Base Case Scenaro worksheet, the user can clck on the Modfy Model Parameters button. Ths opens a wndow that shows a seres of tabs, each allowng modfcaton of the externaltes cost parameters as dsplayed n Fgure 10. The cost parameters are measured n actual dollars per passenger-trp unts and are splt n peak and off-peak values. These can be accessed by clckng on the apposte tabs. Note that by settng the values to zero, the user can overrde the model for ncludng a gven externalty n the evaluaton process. For example, f the user s nterested n just evaluatng the health and safety mpacts of a gven program or strategy, he or she can set the remanng externalty cost values equal to zero. The model wll then run and evaluate results only consderng health and safety mpacts to estmate the value of a passenger trp removed. Throughout ths step by step process, the user s allowed to cancel the operaton at any tme leavng the model unchanged. A fnal confrmaton s also requred to modfy the model. Once the model s changed, t can always be reverted to ts defaults by clckng on the Model Reset button. 55

65 Fgure 10 TRIMMS Model Parameters Modfcaton Travel Demand Functons Elastcty Parameters The user can also modfy the modal trp demand functon elastcty parameters. Ths allows adaptng the trp demand functons to ad-hoc stuatons where the user possesses better nformaton on how ndvduals react to prce changes or polces affectng access and transt travel tme. To modfy the elastcty parameter the user must clck the Modfy Model Parameters button and then clck on the Elastctes tab. Ths provdes access to the wndow dsplayed n Fgure 11. The user can experment wth the default values by slghtly modfyng them to see how the model results are senstve to parameter modfcaton. As n the case of the per passenger-trp cost externaltes, the user can close the wndow and leave the model unchanged. Once the model s modfed, t can always be reset by clckng the Model Reset button. 56

66 Fgure 11 TRIMMS Prce and Travel Tme Elastcty Parameters Modfcaton User Suppled Fnal Mode Shares The model s strength s ts capacty to estmate the mpact on fnal mode shares of a gven polcy or strategy. Ths s accomplshed by means of the constant elastcty of the demand model as descrbed earler n the report. Whenever the user possesses specfc nformaton or a guess estmate about the potental mpact a gven polcy mght have on fnal mode share, he or she can overrde the model by manually enterng the values. Ths opton s accessble from the Fnancal Incentves, Travel Tme Improvements, and Soft Program Evaluaton worksheets by clckng on the Supply Fnal Mode Shares button. Ths opens a wndow as dsplayed n Fgure 12. The user enters the new mode shares (n percentage ponts) and then clcks the Ok button. A fnal warnng dsplays to confrm the decson to over rde the model. The model can always be reset by clckng on the Model Reset button. If the user suppled shares sum s not equal to 100 percent, a warnng message nforms the user of ths mbalance. Nonetheless, the model automatcally rebalances the fnal mode share to total 100 percent. Note that although the Model Output worksheet dsplays the user suppled fnal mode shares, the balanced shares are used to compute mpacts. 57

67 Fgure 12 TRIMMS - User Suppled Fnal Mode Shares 58

68 Analyss Examples In ths secton, we gude the user through a step by step estmaton of the mpacts related to two examples. The frst example s related to mplementng a program fallng nto polces geared at affectng the generalzed cost of usng a mode and changng travel tmes. The second example evaluates a set of soft program measures that are mplemented to support the hard program measures analyzed n the frst example. Table 6 summarzes assumptons on the base case scenaro that wll be used for all examples descrbed below. Program Detals Total Cost $ 45,000 Program Duraton (Years) 2 Dscount Rate 6.0% Employment Informaton Full Tme Employees 4,000 Part-tme Employees 1,000 Current mode share (%) Auto-Drve Alone 78.3% Auto-Rdeshare 12.1% Vanpool 0.5% Publc Transport 4.9% Cyclng 0.4% Walkng 3.0% Other 0.8% Trp Length (mles) Auto-Drve Alone Auto-Rdeshare Vanpool Publc Transport Cyclng 2.90 Walkng 0.90 Other Trp Travel Tme (mnutes) Auto-Drve Alone Auto-Rdeshare Vanpool Publc Transport Cyclng 5.00 Walkng 5.00 Other Vehcle Occupancy (number) Peak Off-Peak Average Rdeshare Average Vanpool Bus Peak Perod Data Percent of Work Trps n Peak perods (%) 75% Table 6 Analyss Example Base Case Scenaro Assumptons Hard Program Impacts: Transt Fare Subsdy In ths example, we analyze the mpact of reducng the daly transt passenger-trp cost from $4.00 to $3.50, a 14 percent reducton. Ths mght be the result of a subsdy mplementaton or a transt fare reducton of.50. To conduct the analyss, the user must clck on the Fnancal Incentves button located on the Base Case Scenaro worksheet. In the worksheet, the user must enter these values as depcted n Fgure

69 Fgure 13 TRIMMS Transt Fare Subsdy Fnally, to vew the results, t s suffcent to clck the Vew Results button. Fgure 14 dsplays the outcome. The lower fare results n a total reducton of 109 daly vehcle trps, wth a net value of a trp removed equal to $645.00, and a beneft cost rato of 2.8. Fgure 14 TRIMMS - Transt Fare Subsdy Impact 60

70 Next, n conjuncton wth the polcy just mplemented, we consder mplementng a $1.00 daly parkng surcharge on SOV users that ncreases average daly parkng costs from $6.00 to $7.00. To estmate the fnal mpact, t s suffcent to clck on the Fnancal Incentves worksheet and enter the parkng cost values as dsplayed n Fgure 15. Fgure 15 TRIMMS Transt Subsdy and Parkng Surcharge By clckng the Results button the new mpacts are summarzed. Fgure 16 shows the result ndcatng that the combned effect of the two polces leads to a reducton of 178 vehcle trps, a net trp removed value of $ and a beneft to cost rato of 5.5. The user can also chart the fnal mode share mpacts by clckng the approprate button on the Results worksheet, as dsplayed n Fgure 17. The chart provdes some nsght about the mpact of the transt subsdy and parkng surcharge on mode shares. Whle the transt subsdy has the effect of dvertng SOV vehcle trps, the parkng surcharge both dverts vehcle trps to transt and all other modes, n a partcular rdeshare (an ncrease of 0.2%). 61

71 Fgure 16 TRIMMS Transt Subsdy and Parkng Surcharge Impacts Mode Share Impacts 90.0% 80.0% 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% -10.0% Auto-Drve Alone Auto-Rdeshare Vanpool Publc Transport Cyclng Walkng Other Baselne 78.3% 12.1% 0.5% 4.9% 0.4% 3.0% 0.8% Fnal 77.6% 12.3% 0.5% 5.3% 0.4% 3.1% 0.8% % Change -0.7% +0.2% +0.0% +0.4% +0.0% +0.1% +0.0% Fgure 17 TRIMMS Transt Subsdy and Parkng Surcharge Fnal Mode Share Impacts 62

72 Soft and Hard Program Impacts Next, the addtonal mpacts of a set of ntatves geared at promotng voluntary change n travel behavor are consdered. The prevous example are expaned to assess the mpacts related to program promoton through a set of marketng ntatves and the mplementaton of telecommutng and flexble workng schedules. To conduct the analyss, the user must press the Soft Program Evaluaton button located n the Base Case Scenaro worksheet. Ths opens a separate wndow consstng of a step-by-step set of tabs askng questons related to soft programs. Based on the answers, specfc dverson rates are used to estmate fnal mode share changes. The user can always overrde the model by clckng the Supply Mode Fnal Mode Shares button. Frst, the user must select the approprate ndustry sector that the organzaton beng evaluated belongs to. In ths example, t s assumed that the organzaton s major functons fall under fnance, nsurance and real estate. Fgure 18 TRIMMS Soft Program Module: Step One 63

73 Next, the user s asked a set of questons related to the presence or absence of accessblty enhancements (bus stops, bke lanes, and sdewalks), workste amentes and parkng facltes/arrangements. In ths example, t s assumed that the workste provdes bus stops, bke lanes and sdewalks wthn ¼ mle radus. In addton, ATM, and restaurant facltes are present, as well as the provson of rdeshare parkng. Fgure 19 TRIMMS Soft Program Module: Step Two In step three, the user s asked a queston related to program marketng promoton, both nsde and outsde the organzaton. Marketng campagns are essentally dvded nto two categores: those desgned to specfcally target ndvduals wthn the organzaton and those conceved to ncrease awareness and potental partcpaton at a regonal area level. 64

74 Fgure 20 TRIMMS Soft Program Module: Step Three Next, the user s asked to enter nformaton on the presence of any ongong subsdy program. 65

75 Fgure 21 TRIMMS Soft Program Module: Step Four In step fve, there s nformaton on Guaranteed Rde Home (GRH) programs that provde an occasonal subsdzed rde to commuters who use alternatve modes. For example, f a vanpool user must return home n an emergency, or a carpooler must stay at work later than expected, the employer guarantees the rde back home. 66

76 Fgure 22 TRIMMS Soft Program Module: Step Fve Fnally, n step sx, the user answers questons related to the mplementaton of telecommutng and/or flexble workng schedules. In step sx the user s asked f the organzaton offers specal arrangements that allow ndvduals usually workng a fxed schedule to alter ther daly workng hours. In ths report, the followng defntons are employed: Alternatve Work Schedules (also called Varable Work Hours) nclude: o Flextme. In ths arrangement employees are allowed some flexblty n ther daly fxed work schedules that permts them to get to work earler or later dependng on ther stuaton. o Compressed Workweek: where employees work fewer but longer days, such as four 10-hour days each week (4/40), or 9-hour days wth one day off every two weeks (9/80). 67

77 o Staggered Shfts: where work shfts are staggered to reduce the number of employees arrvng and leavng a workste at one tme. For example, some shfts may be set to start from 8:00 a.m. to 4:30 p.m., others from 8:30 a.m. to 5:00 p.m., and others from 9:00 a.m. to 5:30 p.m. Telecommutng: refers to salared employees who are allowed to work from home or another locaton (such as a telework center) to reduce commute travel. Fgure 23 TRIMMS Soft Program Module: Step Sx By clckng the Fnsh button, the module closes and the model automatcally swtches to the Results worksheet. The fnal mode shares prevously estmated and dsplayed n Fgure 16 are adjusted to compensate for the mpacts produced by the soft program evaluaton and are dsplayed n Fgure 24. The combned effect of a soft and hard program produced a reducton of 241 vehcle trps, a net beneft of $ at urban peak values, and a beneft to cost rato of

78 Fgure 24 TRIMMS Combned Hard Program/Soft Program Impacts 69