A MODELING FRAMEWORK FOR LONG DISTANCE PLEASURE TRAVEL SUPPLY ANALYSIS

Transcription

1 A MODELING FRAMEWORK FOR LONG DISTANCE PLEASURE TRAVEL SUPPLY ANALYSIS Sa Xao Graduate Student, Graduate Research Assstant Department of Cvl and Envronmental Engneerng, Unversty of Washngton Box 00, Seattle, WA -00 Tel: (0) -, Emal: Runze Yu Ph.D. Canddate, Graduate Research Assstant Department of Cvl and Envronmental Engneerng, Unversty of Washngton Box 00, Seattle, WA -00 Tel: (0) -, Emal: and *Ynha Wang, Ph.D. Professor Department of Cvl and Envronmental Engneerng, Unversty of Washngton Box 00, Seattle, WA -00 Tel: (0) -, Fax: (0) -, Emal: Submtted for Presentaton at the nd Transportaton Research Board Annual Meetng and Publcaton n the Transportaton Research Record Washngton, D.C., January, 0 Date Submtted: July, 0 Word Count:,0 words + ( fgures * 0 words) =,0 words *Correspondng author TRB 0 Annual Meetng Paper revsed from orgnal submttal.

2 Xao, Yu, Wang 0 0 ABSTRACT The massve vehcle-mles and person-mles traveled on long dstance trps have generated broad mpacts on multple aspects of the socety. However, modelng long dstance travel presents a large-scale problem wth great complexty, and knowledge about long dstance travel s an acknowledged ncomplete pece compared to the ntra-urban travel, whch has been studed n adequate depth and multple dmensons. One mperatve ssue s the scarcty of the supply-sde nformaton for long dstance travel, whch embraces the servce qualty of the transportaton nfrastructure and costs for competng travelng optons. Focusng on the long dstance pleasure travel over the natonal hghways, ths study proposes an nnovatve and comprehensve modelng framework to fll the data gap, as well as to gan knowledge and nsghts of dstrbutve patterns of long dstance pleasure travel at nterregonal level, usng avalable data sources. Meanwhle, a novel mpedance model s presented to ncorporate both tangble (travel data) and ntangble attrbutes (contextual data) n pleasure travel nto the modelng framework. The case study further demonstrates the feasblty of the modelng framework and ts capablty of capturng long dstance travelers behavor. The modelng framework also provdes quanttatve system-wde ndcators and performance measures to facltate decson makng n transportaton polces, nvestments, and operatons. Keywords: Long Dstance Travel; Network Loadng; Travel Impedance; Supply Analyss TRB 0 Annual Meetng Paper revsed from orgnal submttal.

3 Xao, Yu, Wang INTRODUCTION Long dstance passenger travel fulflls many unque needs beyond the scope of ntra-urban travel. It connects far flung famles and frends, attracts people to natural sceneres and cultural attractons, supports natonal and regonal economy and boosts local busness through toursm. In, Amercan households took about mllon long dstance domestc trps (00+ mles, one way), whch totaled bllon person trps (). Personal use vehcles domnated long dstance passenger travel, accountng for about % of household trps and resultng n over 0 bllon vehcle mles of travel on the naton s hghways. The massve travel generates extensve mpacts on broad aspects ncludng nfrastructure operaton, travel relablty, greenhouse gas emssons, and energy use. However, our knowledge about long dstance passenger travel s an acknowledged ncomplete pece compared to the ntra-urban travel, whch has been studed n adequate depth and multple dmensons. One mperatve ssue s the scarcty of the supply-sde nformaton for long dstance travel, whch embraces the servce qualty of the transportaton nfrastructure and costs for competng travelng optons. Whle MPOs perodcally and extensvely collect both supply and demand data to support regonal model development, we lack detaled measure of hghway performance and ts costs for long dstance travel, whch s crtcal to supportng decsons about transportaton polces, nvestments, and operatons. Addtonally, there s no comprehensve procedure to dstrbute long dstance trps to the natonal hghway network to yeld supply-sde nformaton. Long dstance travel s not a smple extenson of travel dstance to the well-studed ntra-urban travel. It s stll unclear whether the sequental modelng framework for ntra-urban travel can be readly transferred to long dstance travel studes. Because n an ntra-urban context traffc assgnment s an aggregated outcome of ndvdual route choce behavor (usually summarzed as lnk flows), whereas n a long dstance travel context the prmary concern s the network loadng condtons and dstrbutve patterns of the gven O-D demand, where detaled lnk-level nformaton s abstracted nto corrdor-level statstcs at an nterregonal resoluton. Very lttle prevous research provded quanttatve system-wde ndcators and performance measures to facltate polcy evaluaton of long dstance travel. Quantfyng travel mpedance brngs another challenge to studyng the network loadng ssues of long dstance travel. Exclusvely tme-based travel mpedance model has been wdely deployed n the ntra-urban traffc assgnment research, however, t may not be capable of capturng long dstance travelers behavor, or ncorporatng contextual factors that are nfluental to long dstance route choce nearby land use, actvty denstes, and avalablty of facltes that support or attract long dstance trps. Addressng the aforementoned challenges s especally urgent n long dstance pleasure travel, because t takes a substantal share of all trp purposes n the long dstance passenger travel doman. Accordng to the ATS (),.% of long dstance trps are for pleasure (lesure and vstng frends and relatves) across all the modes. Partcularly, lesure travel ncreased by % between and, as a major drver for the total growth of longdstance travel (). And t s generally beleved that pleasure travel wll contnue to grow, despte the current economc downturn. A survey conducted by the Prcelne.com has shown that % of the travelers were stll plannng for vacaton trps even wth ncreasng travel cost (). Travelng for exploraton seems to be an ntegral part of Amercan lfe and people are spendng substantally TRB 0 Annual Meetng Paper revsed from orgnal submttal.

4 Xao, Yu, Wang on t (). The U.S. Bureau of Labor Statstcs () reported that n 00, a U.S. household spent an average of $, on vacaton and pleasure trps. Notably, the retrng baby-boomer generaton wll serve as a drvng force to the growng demand for pleasure travel n the comng decade ( and ). Pleasure travel possesses several unque characterstcs. Frst, hgher utlzaton of surface transportaton modes: two-thrds of all long-dstance person trps by personal use vehcle n were for pleasure (% to vst frends or relatves and % for lesure travel). Especally for lesure travel, personal use vehcles are the domnatng mode wth an % mode share. Second, pleasure travel s usually assocated wth bgger travel groups. The average sze of the travel party on lesure trps n was. persons, hghest among all the four trp purposes. Thrd, people on lesure trps take longer tme and dstance on the road. On average. nghts away from home were spent on lesure travel accordng to the ATS. Fourth, pleasure travel supports local economy through toursm due to ts hghly consumpton-orented nature. Capturng those ntrnsc characterstcs of pleasure travel adds another dmenson to the challenges of modelng long dstance travel. The objectve of ths paper s to gan knowledge and nsghts of dstrbutve patterns of long dstance passenger travel at nterregonal level gven exstng resources, addressng the aforementoned challenges ncludng supply-sde data ssues, modelng framework, and polcy evaluaton. Partcularly, ths research focuses on pleasure travel across the natonal hghway system, snce ths market presents consderable dversty n tself and dssmlarty from ntraurban travel n terms of pull and push factors n selectng travel routes. Ths paper s organzed as follows: t frst gves an overvew of ssues and challenges of modelng long dstance travel as well as the objectve of ths study, followed by an elaboraton on the modelng framework. It then presents a case study wth exploratory results of long dstance network loadng and dscusson of dfferent flow patterns resulted from varyng model specfcatons. In the end t summarzes the whole research and brngs nsghts nto future research and mplementaton. MODELING FRAMEWORK Long dstance passenger travel embraces farly dosyncratc traveler behavor, dependng on trp purposes and travelers soco-demographc characterstcs. Perceptons to pull and push factors regardng alternatve routes are qute contrastve across dfferent traveler groups. Addtonally, t should be recognzed that nteractons between dfferent traveler groups are neglgble. For example, loadng lesure trps to the network wll not substantally nfluence the route choce of busness travelers. It s not only because long dstance trps merely account for about one percent of total trps, but also because the seasonalty characterstcs vary by trp purpose. Therefore t s reasonable to study each traveler group ndvdually and assume that travelers wthn a certan group select routes n a smlar way. Based on ths assumpton a modelng framework for resolvng the problem s proposed as follows: Identfy Attrbutes of Pleasure Travelers Pleasure travelers present dverse demographcs. For example, after retrevng the lesure travel subset from the ATS sample data, Nostrand et al. () found that the elderly ( or older) and lower-ncome households made fewer lesure trps. Also lesure travel presented a varety- TRB 0 Annual Meetng Paper revsed from orgnal submttal.

5 Xao, Yu, Wang seekng property, meanng that people tend to vst multple destnatons per year rather than the same destnaton for multple tmes. Obvously lower ncome households would be more senstve to addtonal travel dstances than hgher ncome travelers; the mddle age group nclnes to travel shorter dstance due to professonal or famly oblgatons than younger (< years) and older (> years) age groups. The dverse soco-demographc characterstcs of pleasure travelers result n dstnct travel behavor from busness travelers. In general, pleasure travelers are less senstve to the monetary travel cost but rather value recreatonal components along a route. A survey conducted by Tyrrell and Devtt () showed that respondents were wllng to pay approxmately $0. per trp ( Dollar) to use a roadway that s desgnated as scenc. Addtonally, people on lesure trps take longer tme and dstance on the road. Unlke busness trps usually made wth constraned tme wndows (e.g. travelers meetng clents at a specfc tme, attendng conferences, etc.), on average. nghts away from home were spent on lesure travel accordng to the ATS. Therefore analyzng the route choce of pleasure travelers can be conducted n two dmensons: tangble characterstcs of alternatve routes and ntangble attrbutes of the travelers. For example, travel tme and travel dstance are two major tangble route characterstcs. Personal characterstcs, however, are determned by the needs, motvatons, or personal values carred wthn pleasure travel populaton and reflected from people s percepton towards a partcular route. Develop Impedance Model for Pleasure Travel Travel mpedance measures the resstance along a certan route (0) and can be depcted as a generalzed cost functon. For pleasure travel both tangble and ntangble attrbutes should be summarzed n the mpedance functon. In ths study, a generalzed cost functon translates tangble attrbutes ncludng fxed cost, travel dstance, and travel tme nto monetary values to formulate a unfed cost measure as travel mpedance. Compared to the tangble attrbutes, ntangble attrbutes such are of secondary mportance when travelers select routes (), whch however are hard to be quantfed but can be ndrectly captured by people s reactons to contextual factors. Therefore t s reasonable to assume that the long dstance travel mpedance should reflect the compoundng effects of the generalzed travel cost and contextual factors, and the mpacts of the latter are generally sgnfcant n pleasure travel. Snce t s not realstc to enumerate all the contextual factors and quantfy ther mpacts, ths study consders two man categores of contextual factors: route attracton and route proxmty effects. Route attracton represents the attractveness of the route tself, whle the proxmty of the route to nearby attractons also hugely nfluences route choce, ncludng closeness to tourst attractons (natonal/state parks, sk resorts, vewponts, etc.) as well as closeness to the supportng facltes (hotels, etc.). Ths route proxmty can be roughly captured by the number of attractons wthn certan dstance of the roadway secton. For example, a route wth more accommodaton facltes s more attractve to pleasure travelers, consderng the fact that many pleasure trps nvolves mult-day travel along the route. The mpedance functon for pleasure s then proposed by ntroducng two new parameters to dscount the generalzed cost functon, as shown n Equaton. TRB 0 Annual Meetng Paper revsed from orgnal submttal.

6 Xao, Yu, Wang 0 0 an x c s e k L t C where: c Dscounted generalzed cost on lnk ; s Factor for route attracton of lnk, s 0, ; n Number of roadsde attractons wthn mles; a Factor for route proxmty of lnk ; k Fxed cost on lnk ; Constant such as the operatng cost per unt of length; L Length of lnk ; Constant representng the value of tme; t Free flow travel tme on lnk ;, BPR Constants; x Flow on lnk ; C Capacty of lnk ; Equaton shows a composte mpedance model combnng both tangble attrbutes and contextual factors. Tangble attrbutes are accounted by a generalzed cost functon n the braces of Equaton. It summarzes a fxed cost component, a dstance-based operatng cost and a monetary cost for travel tme (determned by BPR functon) as a unfed travel cost model n the unt of dollars. Values of parameters are determned by emprcal justfcaton and prevous research. Based on the Your Drvng Cost publshed by Amercan Automoble Assocaton (AAA) and natonal passenger vehcle composton data retreved from the Bureau of Transportaton Statstcs (BTS), the estmated operatonal cost s. cents per mle for urban travel and cents per mle for rural travel n 00. The value of tme n 00 are $./hr for urban and $./hr for rural, usng U.S.DOT recommended value of tme factors and the medan annual household ncome reported by the Census Bureau. Addtonally, ths study apples values of and ( and ), together wth speed lmts () by roadway functonal class for the BPR functons. As showed n Equaton, ntangble attrbutes are ndrectly consdered by mpedance functon by ntroducng s factor and a factor. The s factor and a factor present a framework to consder two popular types of contextual factors as aforementoned. Addtonally, they are desgned to possess several benefcal propertes from a behavoral modelng pont of vew: valuaton of s represents the level of attractveness of the route: for non-attractve route, s ; for attractve routes s (0,), whch ndcates that the generalzed travel cost s dscounted to make the route tself more attractve to pleasure travelers; both parameters are wthn the nterval (0,], whch bounds possble scenaros to plausble ranges; both parameters mantan the postvty of the adjusted travel mpedance and are able to dscount the () TRB 0 Annual Meetng Paper revsed from orgnal submttal.

7 Xao, Yu, Wang 0 measured mpedance effectvely to reveal attractveness; the multpler decreases monotoncally wth an ncreasng number of roadsde attractons; for the attracton factor a, an when n 0, the multpler e goes to and there s no dscount effect, whch s consstent an wth realty; the multpler e s desgned wth the capablty to ental dfferent travelng behavor. As shown n Fgure, when a 0., the dscountng effect has a quas-lnear decrease wth an ncreasng n, meanng people have a steadly changng atttude towards roadsde attractons; when 0., the dscountng effect has an exponental decrease wth a an ncreasng n, reflectng the behavor that people have a strong reacton to a wth or wthout roadsde attractons scenaro, yet a less senstve reacton to when there are many attractons along the route (e.g. when a 0., an ncrease of attractons from to wll cause an extra dscount n the travel mpedance of %, whle an ncrease of attractons from to wll only cause an extra dscount of.%). In the next Secton, dstrbutve patterns under dfferent magntudes of s factor and a factor wll be presented. an e 0 Fgure Factor for Route Proxmty Reflects Dfferent Behavor. Incorporate the Generalzed Cost Model nto Traffc Assgnment Algorthms A dversty of traffc assgnment algorthms have been proposed, developed, and practced snce the 0s. Prevalng traffc assgnment approaches nclude Determnstc User Equlbrum (DUE) (), Stochastc User Equlbrum (SUE) (), and System Optmum (SO) (), each on the bass of a certan behavoral assumpton. A workng soluton n a long dstance travel network loadng context should acheve a balance between accuracy and feasblty, gven the network sze, temporal resoluton, and computatonal cost of the problem. TRB 0 Annual Meetng Paper revsed from orgnal submttal.

8 Xao, Yu, Wang SUE s selected as the algorthm for ths study for the followng reasons: Frst, t better smulates real-world scenaros by ntroducng uncertanty (errors) n the decson-makng process of route choce; second, ths study focuses on annual travel patterns and does not requre a fner temporal modelng resoluton; Thrd, SUE models are wdely appled and successfully mplemented n smlar large-scale studes. One example s the Freght Analyss Framework (FAF ) completed by the Oak Rdge Natonal Laboratory (ORNL). The assgnment for freght traffc was accomplshed by SUE traffc assgnment procedure n TransCAD.0 wth user defned volume-delay functon (VDF) (). Comparson of Network Loadng Scenaros Conductng large scale travel survey for model calbraton s beyond the scope of ths research; therefore mplementaton of the proposed modelng framework s manly for a hypothess testng purpose. As an expermental effort to explore the long dstance travel s dstrbutve pattern under dfferent assumptons, a seres of scenaros descrbng dfferent model specfcatons wll be mplemented and compared. Through the mplementaton several crtcal questons can be answered, ncludng the valdty of proposed mpedance functon, the sgnfcance and senstvty of newly proposed parameters, the range and magntude of those parameters, the change n the dstrbutve patterns caused by dfferent assgnment algorthms (DUE, SUE, and SO), and the system-wse performance measures (total VHT and VMT, total delay, trp length dstrbuton, etc.) IMPLEMENTATION AND RESULTS: A CASE STUDY The aforementoned modelng framework s mplemented onto a real-world large-scale network as a case study. The case study llustrates the network loadng process of the long dstance passenger travel wthn west-coast states of Washngton, Oregon, and Calforna at county level, followng the modelng framework. In followng sectons, data acquston s brefly ntroduced, followed by a specfcaton of testng scenaros, each correspondng to the ntroducton or the varaton of a model parameter; the mplementaton results are then presented before summarzng mplementaton ndcatons and further thoughts of the case study. Data Acquston O-D Demand Data Wlbur Smth Assocates (WSA) estmated the 00 long-dstance auto trp O-D table () at county level based on the ATS. They projected that the U.S. resdents took,, long-dstance person trps n 00, of whch,,0 were for pleasure/other purposes, across all the travel modes. Consderng the mplementaton scope of the case study, only trps between countes n states of Washngton, Oregon, and Calforna are selected. In total there are,0, pleasure trps. Addtonally, average occupancy s estmated from the ATS sample dataset:.0 persons per vehcle for busness travel, and. persons per vehcle for pleasure/other travel, to convert person trps to vehcle trps. Network Data TRB 0 Annual Meetng Paper revsed from orgnal submttal.

9 Xao, Yu, Wang The Freght Analyss Framework (FAF ) network s selected as the base network of natonal hghways n ths study. Satsfactorly the network dataset ncludes detaled and updated roadway features as length, functonal class, AADT, lnk capacty, and lnk speed lmt, whch are salent for resolvng the network loadng ssues of long dstance passenger travel. Partcularly the AADT0, one of attrbutes n FAF network, s ntroduced as the preloaded volume to the network. In addton to the completeness of the dataset, another reason for choosng FAF les n ts excellent network connectvty and topologcal ntegrty, as recommended by the Federal Hghway Admnstraton (FHWA) expert team. After resolvng the topologcal dscrepancy and mprovng network connectvty, the base network for the case study contans a total of,0 lnks representng prncpal and mnor arterals wthn states of Washngton, Oregon, Calforna, Idaho, and Nevada. Hghways n Idaho and Nevada are ncluded to consder the possblty that some trps may traverse ther jursdctons. Countes are treated as Traffc Analyss Zones (TAZs) for the network loadng. Travel mpedance on centrod connectors s determned by Annual Congeston Cost per Auto Commuter calculated by TTI () n order to be consstent wth the monetary cost developed n ths study. Other Datasets Ths study uses scenc hghways and parks/hotels to llustrate the applcaton of s factor and a factor respectvely. Scenc hghway dataset from Natonal Scenc Byways Onlne (NSBO) s shown as green lnks n Fgure. Geospatal analyss s performed n ArcGIS to dentfy scenc lnks n FAF network by overlappng two datasets. Addtonally, ths study acqures Natonal and State Parks data from multple state agences and U.S. Hotels, Motels, and Accommodatons Database obtaned from onlne vendors to count number of roadsde attractons wthn mles of roadways. The ATS sample data s retreved for trp length dstrbuton comparson. After excludng non-hghway modes, there are,0 busness person trps and,0 lesure/other person trps by auto wthn Washngton, Oregon, and Calforna. Addtonally the Oak Rdge Natonal Laboratory (ORNL) provded a rough estmate of the trp dstances for all trps (). TRB 0 Annual Meetng Paper revsed from orgnal submttal.

10 Xao, Yu, Wang 0 Fgure Scenc Hghways n Fve States & an Illustraton Showng Roadsde Attractons. Scenaro Confguratons Besdes testng the mplementaton feasblty of the proposed modelng framework, the followng scenaros descrbng dfferent confguratons are analyzed:. Dstrbutve patterns when dfferent assgnment algorthms are appled;. The effects of varyng dstrbutons and magntude of the error term n SUE;. The effects and senstvty of newly ntroduced scenc factor and attracton factor. Confguraton ncludes travel tme and travel dstance as well as operatonal cost, n the form x of c L t C Based on Confguraton, Confguraton. wth normal dstrbuton and. wth Gumbel dstrbuton are set wth varyng magntudes of error term to test the applcaton of SUE algorthm. Confguraton. and. further extend mpedance functon for pleasure travel wth varyng values of s and a factor as follows: x Confguraton.: c s k L t where s 0,0.,0.,,0.,.0 C TRB 0 Annual Meetng Paper revsed from orgnal submttal.

11 Xao, Yu, Wang x Confguraton.: an c e k L t C Results where a ;0.;0.;0.0;0.0 TrasnCAD.0 s deployed as the mplementaton platform. Ths secton summarzes mplementaton results. For each correspondng scenaro total VMT, VHT, and delay are estmated as system-wde performance measures. Centered on the SUE algorthm, the dstrbutons and magntudes of the error term are frst nvestgated and ts mpact on dstrbutve patterns s studed (Confguraton. and.). In addton, the mpacts of newly ntroduced parameters (scenc factor and attracton factor) are studed, n terms of system-wde performance measures and dstrbutve patterns. Fnally the trp length dstrbutons from ths mplementaton are compared to the ATS data. Error Term of SUE The magntude of the random error n SUE roughly reflects how dfferently people perceve ther travel tme from the actual travel tme. A larger error term ndcates a sgnfcant dfference exsts between a traveler s percepton and the actual travel mpedance; as a result, route utlzaton s very dverse across the travelng populaton, ncludng some that may be assocated wth sgnfcantly hgher mpedance than the true shortest path. When the error becomes nfnty, the share of flow on all routes wll be equal, regardless of route travel mpedance, meanng people are ndfferent about travel mpedance and just unformly and randomly choosng routes. When the error becomes zero the travel mpedance on all routes wll be equal, meanng people have perfect judgment on the travel mpedance and the entre scenaro becomes a DUE one. Total VHT for Pleasure Total VMT for Pleasure Lesure Normal Lesure Gumbel Lesure Normal Lesure Gumbel Mllons Error Term,,,,,,,, 0 00 Error Term Fgure Total VMT and VHT Change wth Varyng Magntudes of Error Terms. Mllons TRB 0 Annual Meetng Paper revsed from orgnal submttal.

12 Xao, Yu, Wang 0 Fgure summarzes changes n total VMT and total VHT wth varyng magntudes of error terms. Frst of all, regardless of dstrbuton of the error term, changes show a smlar trend: wth an ncreasng magntude of the error term, total VMT and total VHT grow as well; because a larger error term wll result n a more dverse route choce. Second of all, when the error term s less than (meanng people s perceved travel mpedance s wthn the range of % of the actual mpedance), changes n total VMT and total VHT are nsgnfcant (ncrease of total VHT s less than %; ncrease of total VMT s less than %). However, when the error term s larger than, the total VMT and total VHT show an almost lnear and dramatc ncrease. As the error term grows from to 00, ncrease of total VHT s around % and ncrease of total VMT s around %. Ths ndcates that system-wde performance measures present a range of tolerance n terms of long dstance travelers percepton errors, and ths range s not nfluenced by the trp purpose or the assumed dstrbuton of the error term. Total Delay by Error Term: Pleasure Gumbel Normal SO Mllons Error Term Fgure Total Delays by Error Term. Total delays are defned as the dfference between travel tme on the used route and the free-flow travel tme. Total delays by error term are llustrated n Fgure for pleasure travel. As a comparson, total delays n an SO scenaro are also presented n the fgure, where the mnmum total VHT s acheved. Agan Gumbel dstrbuted error terms show a smlar trend as the normally dstrbuted ones. It s a very nterestng observaton that when error terms range from roughly % to %, the SUE-based total delays are lower than SO-based total delays as much as %. The reason les n that under the behavoral assumpton of SUE, many travelers wll not fnd the theoretcally best routes, n whch case certan ndvduals non-optmal route choces ease the congeston on heavly traveled routes and enable others to travel much more effcently, whch creates a lower total delay than the SO scenaro. In a long dstance travel context, gven the long duraton and dstance spent on travelng, t can be assumed that the relatve error n people s percepton s lower than ntra-urban travel. TRB 0 Annual Meetng Paper revsed from orgnal submttal.

13 Xao, Yu, Wang 0 For example, a 0 mnutes perceved error nduces a % error n a 0-mnute commute, yet only a.% error n a -hour travel. Addtonally gven the fndngs from ths case study, the system-wde performance measures are not varyng sgnfcantly under the threshold of %. Therefore n the followng dscusson, a % error term s adopted. However, ths nvestgaton also ndcates a more n-depth study on mpact factors on long dstance travelers percepton error. For example, people tend to seek new routes when travelng for pleasure. s and a Factors n Pleasure Travel In ths case study, the s factor and a factor are represented by the attractveness of scenc hghways and roadsde attractons respectvely. In Fgure, the top horzontal axs s scale of the a factor, and the bottom one for s factors. Total VHT, VMT, and delay for pleasure travel are llustrated wth varyng magntudes of those factors. Total VHT by s or a Factors Mllons a Factors s_due s_normal s_gumbel a_normal a_gumbel a_due s Factors TRB 0 Annual Meetng Paper revsed from orgnal submttal.

14 Xao, Yu, Wang Total VMT by s or a Factors Mllons,00,000, a Factors s_due,000 s_normal,00 s_gumbel,000 a_normal,00 a_gumbel,000 a_due,00, s Factors Total Delay by s or a Factors Mllons a Factors s_due s_normal s_gumbel a_normal a_gumbel a_due s Factors Fgure Impacts of s and a Factors. Both factors functon as how they are desgned. When s and a factors are appled, people are becomng less senstve to the monetary travel cost. A hgher s factor or a lower a factor reflects a lower valuaton from travelers towards scenc hghways and roadsde attractons TRB 0 Annual Meetng Paper revsed from orgnal submttal.

15 Xao, Yu, Wang 0 0 respectvely; therefore people are less lkely to select a beautfully expensve route, whch s reflected by lower system-wde performance measures. Addtonally, s factor presents a very consstent and stable characterstc across dfferent assgnment algorthms (DUE, SUE_Gumbel, and SUE_Normal). The a factor, however, can result n very dfferent performance measures when assgnment algorthms vary. For example, when a =, compared to usng the SUE_Gumbel, usng DUE wll ncrease the total VHT by %, the total VMT by %, and total delays by %. Dstrbutve Patterns Varyng magntudes of s and a factors generate sgnfcant dfferences n the estmated dstrbutve patterns on a large-scale real-world network and potentally affect plannng and polcy decsons. Pleasure trps from Seattle to Los Angeles are chosen to demonstrate the mpact, as shown n Fgure and. When s = 0., pleasure travelers only slghtly value the attractveness of scenc hghways, therefore most of travelers stll choose to travel Interstate, as they perceve the route mnmzes ther travel mpedance. When s = 0., most of travelers are usng the U.S. Route and the U.S. Route 0, both scenc routes. When s = 0., another extreme representng that travelers show a hgh preference n scenc hghways, the U.S. Route 0 s most traveled for the Oregon and Calforna sectons, whle n the state of Washngton, a number of travelers follow the Interstate-, a beautful drve along the Columba Rver. Fgure Dstrbutve Patterns when s = 0., 0., 0. (left to rght); Trps from Seattle to LA. TRB 0 Annual Meetng Paper revsed from orgnal submttal.

16 Xao, Yu, Wang 0 0 Fgure Dstrbutve Patterns when a =, 0.0, 0.0(left to rght); Trps from Seattle to LA. Smlar patterns are observed usng the a factor. When a =, the U.S. Route 0 s most loaded route; whle a = 0.0, most travelers selected Interstate-; n between when a = 0.0, some travelers select U.S. Route 0 along the coast, whle others stll travel along the Interstate. Wthout further data collecton and travel survey, t s unknown for now how much the s factor (or the a factor) exactly s, however, through ths case study, t s shown both factors are effectve n terms of reflectng dfferent dstrbutve patterns wthn a plausble range. Trp Length Dstrbuton The ATS sample data wth trp length nformaton s acqured to be compared wth results from the case study. In general the ATS trp length estmaton process nvolves an AON assgnment method (allocate all the trps to the shortest path) and a travel tme-based mpedance wth adjustments by hghway functonal class. A detaled descrpton of the process can be found n Hwang and Rollow (). Contrastvely ths study apples UE assgnment mechansms wth an enrched composte travel mpedance functon. And trp length dstrbutons for pleasure travel are shown n Fgure. TRB 0 Annual Meetng Paper revsed from orgnal submttal.

17 Xao, Yu, Wang (00, 00] (00, 00] (00, 00] (00, 00] (00, 000] >000 Fgure Trp Length Dstrbutons Pleasure: Comparson wth the ATS. In general the case study yelds fewer trps n shorter than 00 mles categores, and more trps n longer than 00 mles categores. There are three potental reasons for the dscrepancy: Frst, the ATS sample data s on a MSA O-D demand bass, wth a bas towards long dstance trps between urban areas and therefore gnores long dstance trps between a rural O-D par. The O-D matrx for ths study, although derved the ATS data, has been averaged out at a county level. Some longer trps between remotely dstrbuted countes are artfcally generated through ths averagng process, whch add more trps to longer than 00 mles categores. Second, the ATS trp dstance estmaton appled a shortest path algorthm and based over hgher class roadways, whch underestmated the lengths of many trps travelng the lower class roadways, and thus overestmated the number n shorter than 00 mles categores. Thrd, the ATS trp dstance estmaton dd not dfferentate pleasure travel from busness travel, nor consder the dscount effect wthn the pleasure travelng populaton n the network loadng process, therefore many lengthy pleasure trps were underestmated as shorter trps. Ths dscrepancy reveals mportant polcy makng ndcatons, regardng the recently rsng natonal nterest n hgh-speed ral nvestment. Consderng prevalng long dstance travelng modes, two compettors of hgh-speed ral are autos and arplanes; 00 to 00-mle s the crtcal market for the hgh-speed ral. Correctly estmated travel volume n ths market (especally for pleasure travel) s a salent quanttatve reference for justfcaton of massve nvestment. CONCLUSIONS ATS Confguraton s = 0 s = 0. s = 0. s = 0. s = 0. s = 0. s = 0. s = 0. s = 0. s = 0. s = a = a = 0. a = 0. a = 0.0 a = 0.0 Ths research answers several key questons n the supply analyss of long dstance travel. The modelng framework proposed s a feasble soluton to the long dstance travel network loadng. Varatons n model parameters, ncludng the error term, the s factor, and the a factor, generate TRB 0 Annual Meetng Paper revsed from orgnal submttal.

18 Xao, Yu, Wang sgnfcant mpacts on the dstrbutve patterns. Partcularly, both newly ntroduced factors functon as how they are desgned, able to well generalze pleasure travelers behavor and reflect t onto the dstrbutve patterns. Dfferent assgnment algorthms based on varyng behavoral assumptons are also nfluental. The case study not only brngs nsght to the plannng practce, but also to the polcy makng process. For example, results show that the ATS trp length dstrbuton underestmated the number of trps n longer than 00 mles categores, where the 00 to 00-mle s the crtcal market for the hgh-speed ral. Some contrbutons from ths study nclude: frst, utlzng avalable data resources, ths research flls the gap on the supply-sde sde of long dstance travel. On the one hand, results from the modelng framework developed (at least as shown n the case study) portray varous dstrbutve patterns of passenger flows over the hghway network. It explctly hghlghts the varatons of corrdors selected by long dstance travelers under dfferent behavoral assumptons. System-wde performance measures, total VMT, VHT, and delays are estmated smultaneously as well. On the other hand, costs for dfferent travel markets, coverng a dversty of cost components, are explctly estmated, whch provdes a crtcal prcng reference for justfyng a competng travel mode (e.g. hgh-speed ral); Second, ths research presents a complete procedure for long dstance network loadng. Specfcally, t develops the travel mpedance models n a way that contextual data are ncorporated nto the framework, nfluencng and smulatng pleasure travelers behavor, a market wth over 0% share of total number of long dstance trps; thrd, Accountng for roughly % of the natonal total VMT, long dstance travel generates mmense mpacts on the hghway nfrastructure n a broad spectrum of aspects: toursm economy, travel patterns of an agng populaton, hgh-speed ntercty ral, energy effcency, and greenhouse gas emssons. By provdng quanttatve system-wde ndcators and performance measures, the modelng framework facltates related polcy evaluaton. Future work nvolves ground-truth data collecton for model calbraton and valdaton. The ground-truth data can ether be gathered by survey or retreved from GPS-enabled cell phone applcatons. Addtonally, t s worth endeavorng to mplement the proposed network loadng model of the long dstance passenger travel at Metropoltan Statstcal Area level, and further compare the results wth those from the ATS, snce the ATS sample data s on a MSA O-D demand bass. ACKNOWLEDGEMENT Authors wsh to acknowledge the FHWA for fundng support on ths research. Authors also apprecate Mr. Patrck Zhang from the FHWA and Mr. Roger Mngo from the R.D. Mngo and Assocates for ther valuable comments and crucal help wth the research. REFERENCES. U.S. Department of Transportaton, Bureau of Transportaton Statstcs. Amerca on the Go: Fndngs from the Natonal Household Travel Survey-U.S. Busness Travel, October Accessed July, 0. TRB 0 Annual Meetng Paper revsed from orgnal submttal.

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20 Xao, Yu, Wang 0. Wardrop, J. Some Theoretcal Aspects of Road Traffc Research. Proceedngs of the Insttuton of Cvl Engneers, Vol. II, No.,, pp... Daganzo, C. F., and Y. Sheff. On Stochastc Models of Traffc Assgnment. Transportaton Scence, Vol., No.,, pp... Battelle. FAF Freght Traffc Analyss, March 0. Accessed July, 0.. Krshnan, V., and D. Vary. Development of a Natonwde Long Dstance Auto Trp Table. th Transportaton Research Board Conference on Innovatons n Travel Modelng, Tampa, Fla., May 0.. Schrank, D., T. Lomax, and B. Esele. TTI s 00 urban Moblty Report Powered by INRIX Traffc Data, September 0. Accessed July, 0. TRB 0 Annual Meetng Paper revsed from orgnal submttal.