Regional Transportation Authority

Transcription

1 Regional Transportation Authority REGIONAL TRANSIT SIGNAL PRIORITY LOCATION STUDY CATEGORIZATION OF THE UNIVERSE OF PHASE I FINAL REPORT Prepared by: : Parsons transportation group, inc. EJM ENGINEERING, P.C.

2 CONTENTS EXECUTIVE SUMMARY...iv INTRODUCTION AND SCOPE...xiv 1.0 UNIVERSE OF PROPOSED TRANSIT SIGNAL PRIORITY CORRIDORS Introduction Methodology Corridor Characteristics PAC Recommendations Next Steps CATEGORIZATION OF THE UNIVERSE OF TRANSIT SIGNAL PRIORITY CORRIDORS Introduction Base Characteristics for Categorization Potential Refinement Summary DATA ELEMENTS FOR COLLECTION Introduction Data Elements for Collection Sources for Data Elements Summary DATA COLLECTION RESULTS AND INTERSECTION TAXONOMY Introduction and Data Collection Results Development of Intersection Taxonomy Intersection Analysis Scenarios Summary of Intersection Taxonomy and Analysis Scenarios RECOMMENDED LOCATIONS FOR FURTHER ANALYSIS Introduction Selection Methodology Potential Locations for Further Analysis Next Steps MODEL SIMULATION ASSESSMENT Introduction State-of-the-Practice Parsons Transportation Group i

3 CONTENTS (CONTINUED) 6.3 Measures of Effectiveness Model Assessment Summary and Recommendation APPENDIX A Glossary of Terms APPENDIX B Data Collection Worksheets APPENDIX C MOE Survey Results Parsons Transportation Group ii

4 FIGURES Figure Identified Universe of Transit Signal Priority Routes (Region) Figure Identified Universe of Transit Signal Priority Routes (Cook County Area) Figure Categorization of TSP Segments Figure Overall Strategy of TSP Location Study, Phase I Site Selection Figure Segment Categorization Summary Figure Segment Categorization Summary Figure Recommended Locations for Further Analysis Figure 6.1 Example of CORSIM Animation Figure 6.2 Example of VISSIM Animation Figure 6.3 Example of WATSIM Animation TABLES Table Recommended Transit Signal Priority Corridors (Summary) Table Recommended Transit Signal Priority Corridors Table Prospective List of Route Data Collection Items Table Base Characteristics Table Other Characteristics Table Data Elements to Calculate The Base Distinguishing Characteristics Table Summary of Data Elements To Be Obtained and The Anticipated Sources Table 4.1 Data Collection Results Table 4.2 Cell #8 Contents Table 4.3 Cell #9 Contents Table Intersection Taxonomy Table 5.1 Recommended Segments for Further Analysis Table 5.2 Comparison of Segment Characteristics Table Commonly Used Simulation Models Table Comparison of Simulation Model Capabilities Table Maximum Network Size Limitations by Model Parsons Transportation Group iii

5 EXECUTIVE SUMMARY Transit Signal Priority (TSP) is a tool that can improve bus service and operating efficiency while complementing the region s ongoing efforts to relieve traffic congestion. In order to ensure regional coordination for this promising technology, the Regional Transportation Authority (RTA) is leading a comprehensive study known as the Regional Transit Signal Priority Integration Plan. The goal of the plan, which is being undertaken in conjunction with Service Board (Chicago Transit Authority and Pace Suburban Bus) demonstrations, is to provide a framework for the implementation of a regionally integrated TSP system. Plan objectives include development of regional standards and guidelines for design, implementation, operation and maintenance of a multi-jurisdictional TSP system. The Location Study is a crucial element of the overall integration plan. The purpose of the TSP Location Study is to identify and effectively coordinate the location of suitable sites for deployment of an integrated TSP system throughout the region. The study is being conducted in two phases: a Phase I to identify a candidate universe of corridors and select representative sample corridors, and a Phase II to conduct detailed corridor evaluations on the sample corridors. Two of the key objectives of Phase I of the TSP Location Study are to identify corridor characteristics that indicate the likelihood of TSP success, and to identify and classify candidate TSP corridors. The subsequent Phase II will involve simulation modeling of representative corridors to confirm the types of corridors in which TSP will be successful. This will help finalize a structured approach for selecting corridors for implementation of TSP in the region. To facilitate project coordination and communication, the RTA convened a Project Advisory Committee (PAC) to provide input and recommendations towards the selection and prioritization of candidate routes and to reach a consensus on a common methodology to measure the effectiveness of a regionally coordinated TSP system. The PAC consists of key stakeholders from transit and highway agencies. This includes Chicago Transit Authority (CTA), Pace Suburban Bus (Pace), Metra, Illinois Department of Transportation (IDOT), Illinois State Toll Highway Authority (ISTHA), Federal Transit Administration (FTA), Federal Highway Administration (FHWA), Chicago Department of Transportation (CDOT), Chicago Bureau of Electricity, Chicago Area Transportation Study (CATS), county officials, and local municipalities. Parsons Transportation Group iv

6 UNIVERSE OF PROPOSED TSP CORRIDORS The first task in this process was to identify the universe of potential locations for TSP implementation. The first step to this task is to define the corridor characteristics of potential TSP locations. The consultant team developed the proposed characteristics based on review of previous studies. A considerable body of literature in the field of TSP systems for bus and light rail operation has developed. For the purposes of this study, major reliance has been placed on the following reports: Pace Bus Signal Priority Study, by Pace in association with Barton-Aschman Associates and JRH Transportation Engineering; Barriers to Implementation of Signal Priority Systems for Transit Operations: Lessons Learned from Advanced Traffic Management Systems, by David A. Noyce, P.E. at Texas A & M University; Improved Traffic Signal Priority for Transit, Transit Cooperative Research Program Project A-16 (Interim Report), prepared by Gardner Systems; The Cermak Road Bus Preemption Study, by IDOT in association with Civiltech Engineering, Inc. and JRH Transportation Engineering, Inc.; Based on the literature review, extended discussions with RTA staff and preliminary input from the operating agencies, a proposed set of six corridor characteristics for TSP locations was presented for consideration by the PAC. The PAC reviewed these proposed corridor characteristics and a consensus list of characteristics was developed. These characteristics were proposed to aid the agencies in defining their nominated locations and corridors. The characteristics reflecting the consensus views of the PAC are listed below: Existing or proposed fixed route service, primarily on a designated SRA or SRT arterial. Multi-lane, or two lane roadways with throat widening or intersection channelization, with average signal spacing of at least ¼ mile interval. A CTA or Pace core route or serves major destinations and transfer points Peak hour volumes of at least 4 buses or minimum of 100 passengers per peak hour (in one direction). Non-CBD and non-congested routes having a preponderance of intersections with peak hour v/c ratios less than.90. Parsons Transportation Group v

7 Less than 400 conflicting pedestrians per hour at most intersections. Members of the PAC were requested to submit candidate corridors for TSP without screening out corridors by the consensus characteristics. The overall idea is to build a universe of typical transit routes, roadway corridors, and intersections in the region for future model simulation study and reference. Recommendations for locations to be included in the universe were received from Pace, CTA, CATS, CDOT, and ISTHA. The project team (consisting of RTA, PTG, and EJM) added additional possibilities to the nominated locations and the proposed universe was mapped (see Figure 1.1 in the Final Report) and presented to the PAC. Related studies reviewed and integrated into the Location Study include, but not limited to, disparate databases such as: RTA s Strategic Regional Transit (SRT) routes CATS/IDOT Strategic Regional Arterials (SRA) CTA and Pace designated core routes Pace Comprehensive Operating Plan corridors The universe was identified from existing and proposed transit routes, roadway corridors and segments, and regional arterials and included those that would be possible candidates for implementation of a regional TSP system. Included in the universe are the CTA and Pace TSP demonstrations either planned or under way in the region, and corridors in the vicinity of major expressways. The PAC identified 65 transit routes and roadway corridors comprising 598 miles as the universe on which to consider TSP operations. The nearly 600 miles of the identified universe represents a diverse mix of roadway and facility types. Included are collector/distributors, and minor and major arterials. Roadway widths vary from two to six through lanes, and the corridors lie in dense urban and suburban areas as well as less populated areas. This broad mix reflects the desires of PAC members to consider TSP operations on many different types of facilities across the region in an effort to maximize the benefit to the transit-riding public. Parsons Transportation Group vi

8 CATEGORIZATION OF UNIVERSE OF TSP CORRIDORS Given the size of the universe, there was a need to categorize the transit routes and roadway corridors into groups that will help distinguish which types are candidates for TSP. It is important that group members be fairly uniform in basic character so that simulation results can be extrapolated to all corridors within the group. In this way, the distinguishing characteristics will help define rules for evaluating proposed TSP corridors. The categorization methodology is expected to evolve into a fundamental tool for guiding TSP implementation region-wide. The base characteristics for categorization are those most likely to indicate TSP performance. The base characteristics include peak hour roadway volume-to-capacity ratio, peak hour buses per direction, and average signal spacing (details in Table 2.2 of the Final Report). Other characteristics (as shown in Table 2.3 of the Final Report) that may further refine the categorization include number of lanes, daily bus ridership, segment orientation, geographic location, Strategic Regional Arterial/Strategic Regional Transit system (SRA/SRT) status, overlapping route corridor, frequency of crossing another TSP corridor, type of service (i.e., express or local), and intersection transit features. The cube (as shown in Figure 2.1 of the Final Report) illustrates the categorization concept along with the initially proposed thresholds of the base characteristics. The universe of corridors was categorized into 12 major groups, or cells (2 x 3 x 2 levels). The number of levels reflects both a balance between a reasonable member count in each cell and characteristic thresholds relative to TSP performance. It should be noted that the threshold values presented in this figure were based on roadway and transit system information obtained prior to major data collection. It should be also be noted that any one of the proposed corridors in the universe is likely to vary across its length with respect to each of the characteristics (e.g., a corridor segment with a V/C ratio primarily less than 0.90, next to a segment primarily in excess of 0.90). This means that a given corridor is likely to divide into several segments. DATA ELEMENTS FOR COLLECTION In order to divide the corridors into segments and categorize the segments into homogenous cells, data describing the base and other distinguishing characteristics were collected and/or calculated. The base Parsons Transportation Group vii

9 characteristics were calculated from existing data. The data used to define the base distinguishing characteristics of a segment were peak hour headways per direction, average daily traffic (ADT), number of lanes and geometric features that might affect capacity (e.g., intersection widening, parking on-street, etc.), and signal locations. The data used to define the other characteristics include ridership information, segment orientation and geographic location of the segment, SRA/SRT system information, CTA and Pace routes along the corridors, crossing TSP segments, and type of service. Transit intersection features collected include percentage of far-side bus stop locations, bus turn-out lanes, and queue by-pass lanes. Many of the data elements were collected from the members of the PAC. Other items such as volume to capacity ratio were calculated, while other items such as geographic location and overlapping route segments were inferred from the map of the universe of corridors. DATA COLLECTION RESULTS Based on the categorization methodology and data collection results, the universe was divided, and the resulting segments were placed in classif ication cells. The complete results of categorization (as shown in Table 4.1 of the Final Report) include the characteristics of each segment. A graphic summary of the final assignments is provided in Figure 4.1 of the Final Report, showing the resulting number of segments per cell. Overall, it can be observed that the characteristics of each cell are different, but that segments within a cell are similar to one another. For instance, Cell 8 segments are primarily heavily traveled arterials serving the City of Chicago with relatively close signal spacing and mid-level bus activity, while the segments in Cell 9 are lower volume arterials located in less dense areas with wider signal spacing and having high bus activity. INTERSECTION TAXONOMY AND TYPICAL INTERSECTION SCENARIOS The selection of representative segments for further analysis assures that a good representation of all segment types is achieved, with a view towards identifying segment and corridor characteristics that affect TSP performance. It is important that the chosen segments take into account intersection features and characteristics, since these may also impact TSP performance. The aim is to develop a taxonomy, or classification system, of various intersection types in the universe based primarily on data previously gathered in the study. From these intersection types, scenarios will be selected that represent typical cases Parsons Transportation Group viii

10 of implementation of a TSP system including proposed intersection treatments. These treatments will include design or operational controls likely to maximize TSP performance. The roadway features used to develop the intersection scenarios are related to geometric, demand or volume, and traffic control characteristics. The intersection scenarios recommended for consideration are presented in Table 4.4 of the Final Report. Data was collected for each corridor relevant to bus stop locations, type of bus service, traffic volumes, and the peak hour volume to capacity ratio. Based on the literature review, the best chance for success exists where TSP operation and control can be flexible in design and implementation, and the identified features are the ones expected to reflect varying levels of flexibility. RECOMMENDED LOCATIONS FOR FURTHUR ANALYSIS The basis for selecting the recommended locations was the cells that were defined by the base characteristics. Since members of any given cell were assumed to be homogenous, at least one segment from each cell should be analyzed in Phase II to distinguish segments where TSP implementation is most beneficial. Another reason to choose at least one segment per cell is to evaluate the broad mix of facilities proposed by the PAC. The intent is to extrapolate results of a simulated segment to all segments with similar characteristic s. Therefore, in choosing the recommended segments, different segment characteristics as well as different intersection features were reviewed. Segments that are included in upcoming TSP demonstration projects were also included. A total of 17 segments are recommended for further analysis (see Table 5.1 in the Final Report). The recommended segments represent each cell, and yet were also chosen to represent a diverse set of other characteristics for further analysis. The recommended segments are well dispersed geographically and while most segments cross another recommended corridor (13 segments), others do not (4 corridors). The segment length varies widely, from less than 1 mile to 12 miles. Four of the segments carry CTA only, 3 carry Pace only, and 10 segments carry both CTA and Pace. Eight segments represent average daily ridership of less than 10,000, while 9 segments represent ridership of greater than 10,000. Two diagonal segments were chosen since diagonal streets tend to have 5 or more legged intersections for analysis of complex intersections. Parsons Transportation Group ix

11 MEASURES OF EFFECTIVENESS (MOEs) A primary objective of the Phase I Location Study was to identify candidate sites for TSP implementation. A secondary objective was to gain agreement from the PAC on a common methodology to measure the effectiveness of TSP operations. Before developing specific MOEs, it is important to consider the various interests, or players, affected by TSP implementation and operation. Broadly speaking, there are four players in TSP operations: transit operators; transit passengers; signal system/street system agencies; and other road users including pedestrians, bicyclists, trucks, emergency vehicles and persons in autos. These players will be affected in different ways and the chosen MOEs address each of their interests. In general, transit operators wish to provide the maximum level of transit service at the least possible cost. Thus any action that reduces equipment or labor costs while enhancing patron service is considered favorable. Transit passengers seek: reliable, on-time service that gets them to their destination as quickly as possible. Signal system/street system agencies wish to provide efficient and safe roads that support a broad range of users, both in vehicles and on foot. Other road users include those who share the roads with transit (i.e, bikes, trucks, pedestrians). Pedestrian volumes in particular are critical for determining minimum green times to allow pedestrians to safely cross streets. MOEs will be used to calibrate the simulation model to field conditions, compare simulation results between different scenarios, and quantify the long-term benefits of TSP after it is implemented in the field. The proposed MOEs include bus travel time, bus schedule reliability, segment bus delay, segment automobile delay, segment person delay, cross-street delay, green time distribution, vehicle emissions, fuel consumption, benefit-to-cost ratio, ridership, and transit passenger wait time. For more details or definitions of the proposed MOEs see Chapter 5. Members of the PAC were surveyed to rank the proposed MOEs and to define their expectations on outputs and results from the modeling process. Responses were provided by CTA, Pace, CDOT, IDOT, RTA and the University of Illinois at Chicago. Schedule Reliability ranked the highest or most important MOE, while Vehicle Emissions ranked the lowest or least important. The most controversial MOE appears to be Green Time Distribution. Pace, RTA, and UIC ranked Green Time Distribution the least Parsons Transportation Group x

12 important; while CTA, CDOT and IDOT ranked it one of the most important MOEs. Several agencies mentioned safety as an important MOE to be included in the evaluation. CDOT and Pace noted several of their expectations of the results of Phase II Simulation. Pace would like a breakdown of the Phase II Simulation results over the day. In this way, the simulation results would include an evaluation showing if TSP could be effective and useful at different times of the day. CDOT s expecta tions were that Phase II verify that improved transit performance does not come at the expense of significant cross-street traffic delay and that pedestrian walk time (a controlling factor for green time at many Chicago intersections) is not sacrificed. CDOT also mentioned that the benefit-cost ratio should include the costs to relocate the bus stops to the far side of the intersection, if that is part of the TSP recommendation. SIMULATION MODEL ASSESSMENT The selection of a simulation model for Phase II required the assessment of project objectives, data availability, level of detail required, and MOE requirements. In this case, the objective of the project is to identify appropriate corridors for TSP implementation using several traffic related and environmental MOEs. This reduces the field of potential simulation models to just four commonly used models. Specifically, CORSIM, TransSim II, WATSIM, and VISSIM can model complex traffic control and bus interactions well enough to be considered for this TSP analysis. Of these models, TransSim II models automobiles macroscopically while the others are microscopic simulation models. A comparison of the features of each of the four simulation models under consideration revealed the strengths and weaknesses of each model in relation to the detailed modeling techniques required to simulate realistic transit and traffic conditions. Although TransSim II models bus operations and traffic signal operations with a good amount of detail, it does not model automobile operations to the same level of detail as the other models, nor does it provide the necessary environmental MOEs. Therefore, TransSim II was eliminated from further consideration. Among the remaining simulation models, a comparison of their features showed that each simulates detailed automobile and bus operations, which is a result of their microscopic nature. In addition, WATSIM and CORSIM have nearly identical features, except that WATSIM has some additional transit- Parsons Transportation Group xi

13 related features (train operations and TSP strategies, most notably). However, VISSIM exhibits several more features than CORSIM or WATSIM. Specifically, VISSIM can simulate more types of traffic control (and TSP strategies), more detailed motorist characteristics, and more priority vehicle operations. In addition, VISSIM can be used to create a more complex and more realistic transportation network than either WATSIM or CORSIM due to its less rigid coding structure, which also provides much more flexibility in analyzing user-specified traffic conditions on the network. VISSIM is also the only model that is coded in an entirely graphical environment, which simplifies the process of creating the model and entering the necessary data. The biggest advantage that VISSIM has over the other two models is that it provides a completely userprogrammable traffic signal controller emulator. In combination with its fully programmable vehicle detectors, this feature allows VISSIM users to program any type of traffic control into the VISSIM model instead of depending on built-in pretimed or actuated traffic signal algorithms in the other models. This flexibility allows the user to test very specific TSP algorithms in the segment, as well as to possibly develop new ones. Although WATSIM s traffic signal controller logic can be modified to simulate various traffic control strategies, this would require hiring the software maker to make the necessary software adjustments, which would be inconvenient and expensive. In conclusion, VISSIM was recommended as the simulation model to use for this TSP analysis for the following reasons: VISSIM provides a coding structure that allows the most realistic simulation of the transportation network. VISSIM allows the overlay of an aerial image or CADD drawing of the study area to aid in coding the network and in presenting animated results of the simulation. VISSIM successfully simulates the complex interaction of automobiles, buses, and traffic control due to its microscopic nature. VISSIM provides the user with the flexibilit y to analyze all types of traffic signal control and TSP strategies due to its completely user-programmable traffic signal controller emulator. Parsons Transportation Group xii

14 VISSIM provides the most flexibility in calculating MOEs according to user specifications. VISSIM can be purchased from the vendor without obligation for purchasing consulting services and has very responsive user-support resources. NEXT STEPS The ultimate Location Study goal is to develop a reasonable basis to assess the impacts of TSP across the metropolitan area. The methodology can then serve as a screening tool to consider specific requests for TSP, and help guide implementation. Phase II simulations of representative samples will be varied across levels of both the base and the other characteristics. Depending on performance impacts, the base characteristics may be changed, expanded, or revised with respect to thresholds between characteristic ranges. It is possible that the simulations may show consistent performance relating to one or more of the other characteristics, and not just the base characteristics. Greater differences in performance may be seen with different groupings of segments, as defined by changes in either the base characteristics or their thresholds. Although the review of past studies and literature implies that the proposed cells are homogenous and will have similar results, the characteristics as well as the thresholds need to be tested and refined for the region in Phase II. Success of TSP should be determined through an iterative simulation analysis and PAC agreement on performance, or measures of effectiveness. Phase II should also explore and analyze the details of TSP operations (e.g., control options such as conditional or unconditional priority, frequency of TSP operation at a given intersection) and intersection operations (e.g., far side bus stops). Once the characteristics are validated in Phase II, a final categorization methodology can be completed to guide region-wide TSP implementation. Parsons Transportation Group xiii

15 INTRODUCTION AND SCOPE The Regional Transportation Authority (RTA) is leading a comprehensive study known as the Regional Transit Signal Priority (TSP) Integration Plan. The goal of the plan, which is being undertaken in conjunction with Service Boards (Chicago Transit Authority and Pace Suburban Bus) demonstrations, is to provide a framework for the implementation of a regionally coordinated and integrated TSP system. The Location Study is a crucial element of the overall integration plan. The purpose of the TSP Location Study is to identify and effectively coordinate the location of suitable sites for deployment of an integrated TSP system throughout the region. The study is being conducted in two phases: a Phase I to identify a candidate universe of corridors and select representative sample corridors, and a Phase II to conduct detailed corridor evaluations on the sample corridors. In December 1999, RTA retained the consultant team of Parsons Transportation Group, Inc. (PTG) and EJM Engineering, P.C. (EJM) to conduct Phase I of the TSP Location Study. The scope of this Regional TSP Location Study, Phase I is structured to achieve the following objectives: Identification of suitable locations for TSP and representative samples for model simulation (Phase II) of integrated TSP systems through a systematic approach. Agreement by stakeholders on a common methodology to measure effectiveness of signal priority systems (e.g., reduce delay or increase schedule reliability). Assessment of various micro and macro simulation models to replicate field conditions and encourage future model simulation exercises, and recommendation of specific model(s). The subsequent Phase II will involve simulation modeling of representative corridors to confirm the types of corridors in which TSP will be successful. This will help finalize a structured approach for selecting corridors for implementation of TSP in the region. The project work scope calls for the production of six technical papers. These documents were combined to create this final report. The papers were converted to chapters in the order of the work scope. Minor portions of each introduction have been taken out for less repetitiveness. Parsons Transportation Group xiv

16 1.0 UNIVERSE OF PROPOSED TRANSIT SIGNAL PRIORITY CORRIDORS 1.1 INTRODUCTION The first task in Phase I is to define the locations potentially suitable for TSP in the region (the identified locations are termed the universe for this study). The purpose of this Chapter is to present this first task. 1.2 METHODOLOGY The approach to the first task is to define the universe based on the corridor characteristics of potential TSP locations. To facilitate project coordination and communication throughout the project, a Project Advisory Committee (PAC) was formed. The PAC consists of members recommended by RTA and includes Chicago Transportation Authority (CTA), Pace Suburban Bus (Pace), Metra, Illinois Department of Transportation (IDOT), Illinois State Toll Highway Authority (ISTHA), Federal Transit Authority (FTA), Federal Highway Administration (FHWA), Chicago Department of Transportation (CDOT), Chicago Bureau of Electricity, Chicago Area Transportation Study (CATS), county officials, and local municipalities. The first step to this task is to define the corridor characteristics of potential TSP locations. The consultant team developed the proposed characteristics based on a review of previous studies. A considerable body of literature in the field of TSP systems for bus and light rail operation has developed. Major reliance has been placed on the following studies: Pace Bus Signal Priority Study, by Pace in association with Barton-Aschman Associates and JRH Transportation Engineering; Barriers to Implementation of Signal Priority Systems for Transit Operations: Lessons Learned from Advanced Traffic Management Systems, by David A. Noyce, P.E. at Texas A & M University; Improved Traffic Signal Priority for Transit, Transit Cooperative Research Program Project A-16 (Interim Report), prepared by Gardner Systems; The Cermak Road Bus Preemption Study, by IDOT in association with Civiltech Engineering, Inc. and JRH Transportation Engineering, Inc.; Parsons Transportation Group 1-1

17 The PAC then reviewed these proposed corridor characteristics and a consensus list of characteristics was developed. The PAC was asked to nominate locations and corridors for consideration. The project team (consisting of RTA, PTG, and EJM) added additional possibilities to the nominated locations and the proposed universe was mapped for presentation to the PAC. Previous studies reviewed and integrated into the universe include, but not limited to, disparate databases such as: RTA s Strategic Regional Transit (SRT) routes CATS/IDOT Strategic Regional Arterials (SRA) CTA and Pace designated core routes Pace Comprehensive Operating Plan corridors The universe was identified from existing and proposed transit routes, roadway corridors and segments, and regional arterials and included those that would be possible candidates for implementation of a regional TSP system. Included in the universe are the CTA and Pace TSP demonstrations either planned or under way in the region, and corridors in the vicinity of major expressways. 1.3 CORRIDOR CHARACTERISTICS Based upon the review of the literature, extended discussions with RTA staff and preliminary input from the operating agencies, a proposed set of six corridor characteristics for TSP locations was presented for consideration by the PAC. The PAC reviewed these proposed corridor characteristics and a consensus list of characteristics was developed. These characteristics were proposed to aid the agencies in defining their nominated locations and corridors PROPOSED The proposed characteristics were: Existing or proposed fixed route service, primarily on a designated SRA or SRT arterial Multi-lane roadway with average signal spacing of at least ¼ mile interval A CTA or Pace core route or serves major destinations and transfer points Peak hour volumes of at least 4 buses or minimum of 100 passengers per peak hour (in one direction) Parsons Transportation Group 1-2

18 Non-CBD and non congested routes having a preponderance of intersections with peak hour v/c ratios less than.90 Low to moderate pedestrian traffic at most intersections Parallel with the development of these defining characteristics, the team also identified a series of proposed Measures of Effectiveness (MOEs) to be used in future data gathering and model simulation. The MOEs are the evaluation criteria used to judge the performance of a TSP corridor. The proposed MOEs as presented to the PAC are: On-time performance and schedule reliability Bus travel time Transit passenger waiting time Corridor delay person, transit vehicle, auto Impact on cross-street traffic, pedestrian movement and other traffic conflicts Ridership Fuel consumption and emissions Benefit-cost ratio These will be refined as the project proceeds and are presented in more detail in Chapter PAC CONSENSUS At a meeting of the PAC on January 21, 2000, the proposed corridor characteristics and MOEs were presented for discussion and the PAC was asked to submit nominations of bus routes and corridors for inclusion in the universe to be analyzed. While there were many questions and extended discussion relative to the proposed characteristics and MOEs, two characteristics required revision: the low to moderate pedestrian traffic was changed to less than 400 conflicting pedestrians at most intersections, and the multi-lane characteristic was changed to include two-lane roads with throat widening or intersection channelization. The resulting consensus characteristics will be applied to the universe of existing and proposed transit routes, roadway corridors and segments, and regional arterials for categorization and ranking in later tasks. The revised characteristics reflecting the consensus views of the PAC are listed below: Existing or proposed fixed route service, primarily on a designated SRA or SRT arterial. Parsons Transportation Group 1-3

19 Multi-lane, or two lane roadways with throat widening or intersection channelization, with average signal spacing of at least ¼ mile interval. A CTA or Pace core route or serves major destinations and transfer points Peak hour volumes of at least 4 buses or minimum of 100 passengers per peak hour (in one direction). Non-CBD and non-congested routes having a preponderance of intersections with peak hour v/c ratios less than.90. Less than 400 conflicting pedestrians per hour at most intersections. 1.4 PAC RECOMMENDATIONS Members of the PAC were requested to submit candidate corridors for TSP subsequent to the meeting, and not to screen out corridors by the consensus characteristics. The overall idea is to build a universe of typical transit routes, roadway corridors, and intersections in the region for future model simulation study and reference. Following the PAC meeting, recommendations of locations to be included in the universe were received from Pace, CTA, CATS, CDOT, and ISTHA. As summarized in Table 1.1, a total of 96 potential bus routes and roadway corridors were recommended. Because of overlapping recommendations between agencies, the net number of recommendations was 65 corridors comprising approximately 598 miles of corridor bus transit service. Table 1.1: Recommended Transit Signal Priority Corridors (Summary) No. Corridors Total Miles Av. Miles/Corridor Pace CTA 42* CATS 21* CDOT 3* ISTHA 3* Rail-Bus Transfer 8 5** 1.7 Centers Total Net Total *Includes overlapping routes/corridors. **Net additional miles. Table 1.2 lists all the corridors and routes recommended for inclusion in the universe. Figures 1.1 and 1.2 are maps showing the location of each corridor recommended by the PAC for consideration. The maps Parsons Transportation Group 1-4

20 are color coded to identify the agency recommendation and to show the extent of overlap between agencies. Figure 1.1 is a regional view and Figure 1.2 provides a close-up view of the corridors in the Cook County area. Parsons Transportation Group 1-5

21 Table 1.2: Recommended Transit Signal Priority Corridors RECOMMENDED CORRIDOR BUS ROUTES FROM TO MILES BY 127th St Cicero Indiana 6 CATS 159th St Oak Park Torrence 12 CATS/PACE 35th St 35 Cottage California 4.8 CTA 47th St 47 King Cicero 7 CTA 63rd St 63 Stoney Cicero 8.5 CTA 71st St 71 Yates State 3 CTA 79th St / Brandon 88 th St PACE/CTA CTA-79 87th St 87 Buffalo Cicero 10.6 CTA/CATS 95th St / CTA-95E-95W LaGrange Colfax 15.5 CATS/CTA/PACE Archer Ave 62-62H Clark 1st Ave 9.8 CTA/CATS Ashland Ave 9 Irving Park 95 th St CTA Belmont Ave 77 Lake Shore Cumberland 11 CTA Blue Island- 60 Western Kenton 3.8 CTA 26th Broadway 36 Devon Diversey 5.2 CTA Central Ave 85 Edmunds Harrison 7 CTA Cermak Rd Harlem Yorktown Mall 10.6 PACE Cermak Rd 21 King 54 th Ave. 7.7 CTA Chicago Ave 66 Halsted Austin 8 CTA Cicero Ave / CTA-54-54B Pensacola 159 th St PACE/CTA/CATS/ CDOT Clark St Rogers North 8 CTA Cottage Grove 4 35 th St. 95 th St. 7.5 CTA Cumberland Rd / CTA-69-81W Higgins Ogden 12 CATS Dempster St 250 Oak Miner River 10.1 PACE Devon Ave 155 Sheridan Kedzie 2.5 CTA Fullerton Ave 74 Halsted Nordica 8.5 CTA Garfield Ave 55 Hyde Pk. Cicero 8.9 CTA/CATS Parsons Transportation Group 1-6

22 Table 1.2: Recommended Transit Signal Priority Corridors (cont.) CORRIDOR BUS ROUTES FROM TO MILES Golf Rd Parsons Transportation Group 1-7 RECOMMENDED BY Crawford Barrington 21.6 PACE/CATS Grand Ave, Waukegan 565 Gurnee Mill U.P. Northline 5.6 ISTHA Halsted St 8 Waveland 79 th St CTA Halsted St th St. Sibley 6.8 PACE Harlem Ave Oakton 127 th St PACE/CTA/CATS / CTA Irving Park Rd 80 Lake Shore Cumberland 10.6 CTA/CATS Jeffery Ave 6 67 th St. VanVlissingen 4.2 CTA Kedzie Ave 52-52A 36 th St. 115 th St. 8.9 CTA Kimball-Homan 82 Lincoln Grand 7.5 CTA King Drive 3-4 Cermak 95 th St. 8.1 CTA/CDOT LaGrange/ Touhy Joliet 16.4 CATS/PACE Mannheim Rd Lake St Austin Wolf 6.8 PACE Lake Cook Road 626 Waukegan Buffalo Grove 6.5 ISTHA Lawrence Ave 81 Marine Milwaukee 6.4 CTA Madison Ave / CTA- 20 Halsted 25 th St PACE/CTA Michigan Ave th St. 127 th St. 4 CTA Milwaukee Ave 572 Buckley Townline 4.5 CATS/ISTHA Milwaukee Ave Lake Jefferson Park Station 9.7 PACE North Ave / Wolf Clark 14 PACE/CTA/CATS CTA-72 Oak Park Ave 311 North 46 th St. 7 PACE Ogden Ave Cicero LaGrange 7.3 PACE/CATS Pershing Rd 39 Cottage St. Louis 6 CTA Peterson Ave 84 Ridge Cicero 4.2 CTA Pulaski Ave / CTA A Peterson 115 th St CTA/CATS Roosevelt Rd / CTA-12 Wolf Columbus 15.6 PACE/CTA

23 Table 1.2: Recommended Transit Signal Priority Corridors (cont.) CORRIDOR BUS ROUTES FROM TO MILES RECOMMENDED BY State St 29 Roosevelt 95 th St CTA Stoney Island th St. 103 rd St. 5.9 CTA/CATS Touhy Ave Ridge Elmhurst 12 PACE/CATS U.S. 30/Lincoln Cicero Cottage 6.8 CATS Hwy Waukegan Rd Willow Oakton 5 CATS Western Ave 349 / CTA-49-49A-49B Birchwood Dixie-Sibley 29.8 PACE/CTA/CATS/ CDOT METRA TRANSFER CENTERS Main Street Lisle Main Street Glenn Ellyn Washington St Naperville Hobson Ogden 2 METRA/PTG Geneva Windsor 1 METRA/PTG Ogden Bauer 2 METRA/PTG CTA TRANSFER CENTERS Dan Ryan/95th Street Midway Forest Park Red Line Orange Line Blue Line METRA/CTA TRANSFER CENTERS Jefferson Park Davis Street UP/Blue Line UP/Purple Line Parsons Transportation Group 1-8

24 Figure 1.1 Parsons Transportation Group 1-9

25 Figure 1.2 Parsons Transportation Group 1-10

26 As mentioned above, recommendations of locations to be included in the universe were received from Pace, CTA, CATS, CDOT, and ISTHA. Many of the Pace recommended routes represent the Pace Comprehensive Operating Plan routes included in the SRT System. CTA s recommendations are an almost comprehensive grid pattern of major roadways in the City of Chicago. CATS identified their recommended corridors through a query of the Illinois Roadway Information System (IRIS) with the selection criteria of 3 lanes or more and those located on both the SRA and SRT Systems. CDOT recommended corridors based on planned TSP demonstration sites. The recommendation from ISTHA was for general areas in Lake County related to the IL Route 53 extension, from which three specific corridors were identified as meeting the criteria of serving major destinations or transfer points. At the recommendation of the project team, eight major transfer points were also included in the universe. These transfer points represent 1) three Metra stations with a combination of high levels of feeder bus service and high passenger load stations; 2) three major CTA rail-bus transfer points; and 3) two shared CTA/Metra transfer facilities. A noteworthy point of the universe is that nine corridors represent the intermodal connectors (i.e., highway links that connect major passenger and freight intermodal facilities to the National Highway System) as presented in the CATS 2020 Regional Transportation Plan: 1. Main Street in DuPage County (Lisle and Glen Ellyn) th Street in Chicago 2. Milwaukee Avenue in Cook County th Street in Chicago 4. Belmont Avenue in Chicago 5. Chicago Avenue in Chicago 6. Fullerton Avenue in Chicago 7. Pulaski Road in Chicago 8. Broadway in Chicago No recommendations were made for study of possible future transit corridors not presently having service, except for the general areas in Lake County submitted by ISTHA. The nearly 600 miles of the universe represents a diverse mix of roadway and facility types. Included are collector/distributors, minor arterials and major arterials. Roadway width varies from two to six through lanes, and the corridors lie in dense urban and suburban areas as well as less populated areas. This broad Parsons Transportation Group 1-11

27 mix reflects the desires of PAC members to consider TSP operations on many different types of facilities across the region in an effort to maximize the benefit to the transit-riding public. 1.5 NEXT STEPS Due to the large number and high mileage of potential corridors identified by the PAC, the next step is to develop a method to categorize the universe. It is important that the corridors be split into segments that are fairly uniform with respect to likely TSP performance, since an overall goal of the Regional TSP Integration Plan is to predict whether any given corridor is likely to be a good TSP candidate. The challenge will be to identify major distinguishing characteristics that can be used to categorize corridors. Once the distinguishing characteristics are developed, and associated data collection items are defined, data collection on the universe of corridors will take place. At the same time, key intersection treatments to maximize TSP effectiveness will be proposed and evaluated. A related step will be to select representative samples of the categorization groups as simulation study corridors for Phase II of the location study. All of the steps are interrelated, and therefore must be planned and completed in parallel. Parsons Transportation Group 1-12

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29 2.0 CATEGORIZATION OF THE UNIVERSE OF TRANSIT SIGNAL PRIORITY CORRIDORS 2.1 INTRODUCTION The focus of this Chapter is the categorization methodology for use throughout the project. As presented in Chapter 1 (Universe of Proposed Transit Signal Priority Corridors), the Project Advisory Committee (PAC) identified 65 transit routes and roadway corridors comprising 598 miles as the universe on which to consider TSP operations. The nearly 600 miles of the identified universe of corridors represents a diverse mix of roadway and facility types. Included are collector/distributors, and minor and major arterials. Roadway width varies from two to six through lanes, and the corridors lie in dense urban and suburban areas as well as less populated areas. This broad mix reflects the desires of PAC members to consider TSP operations on many different types of facilities across the region in an effort to maximize the benefit to the transit-riding public. Given the size of this universe, there is a need to categorize the component corridors and corridor segments into groups that will help distinguish which types or groups are candidates for TSP. An overall consideration is the Phase II work in which simulations on selected group samples will be performed. It is important that group members be fairly uniform in basic character so that simulation results can be extrapolated to all corridors within the group. In this way, the distinguishing characteristics will help define rules for evaluating current and future proposed TSP corridors. The categorization methodology thus will be the fundamental tool for guiding TSP implementation region-wide. 2.2 BASE CHARACTERISTICS FOR CATEGORIZATION The base characteristics should be those most likely to predict TSP performance, as evaluated by Measures of Effectiveness (MOEs) that will be finalized in a later task. Likely MOEs are TSP impacts on general traffic flow and delays, person travel time, bus on-time performance, and related measures. It is important to select characteristics that will be the most accurate predictors of MOE performance. Given reliable base characteristics, it will then be possible to categorize TSP corridor segments into similar groups. The underlying assumption is that all segments in a group will perform in a like manner with respect to TSP MOEs, as discussed below. Parsons Transportation Group 2-1

30 To select base characteristics, the project team first reviewed the prospective list of data collection items of the project work scope, listed in Table 2.1, in light of research and recommendations in the literature. Several key ideas came out of the review. First, several documents highlight the fact that as traffic congestion increases, TSP tends to degrade general traffic operations to an unacceptable degree (1,2,3,4). This suggests using some type of volume-to-capacity (v/c) measure as a base characteristic. Table 2.1: Prospective List of Route Data Collection Items (1) Transit Elements Average Daily Ridership by route Passengers per Revenue Hour by route Peak-Period Bus Frequency by route Time Points Route Length Trip Time by route and period Interconnect Systems Overlapping Routes Crossing Routes Bus Stop Locations (1) Per project work scope. Roadway Elements Corridor Length Number and Location of Signals by corridor Signal Density by corridor or major segment Signal Interconnect Systems ADT Number of Lanes (prevailing by section) Volume-to-Capacity Ratio (calculated by ADT/{lane capacity*number of lanes}) Travel Speed by Corridor or Segments Counties in the Corridor Intersection Approach Lanes and ADT at Major Crossing Routes Another idea in the literature is that the performance of TSP will vary with the number of bus priority instances (3,4). If the number of TSP occurrences is too low, the overall benefit may not be great enough in terms of either person delay or improved bus operating efficiencies (i.e., reduction in number of buses). On the other hand, if the number of TSP occurrences is too high, the disruption to general traffic flow may be unacceptably high. An important related point is the possible use of conditional TSP control in which priority is granted only for transit vehicles that are running behind schedule, and would thus be less disruptive of general traffic flow (3,5). This aspect cannot be addressed in detail, however, until the Phase II simulation work, when alternate control strategies could be tested. At this stage of defining initial base characteristics, the recommendation is to start with a base characteristic of number of peak hour buses per direction. Parsons Transportation Group 2-2

31 The literature also suggests that TSP should use total person delay in the control algorithm of the simulation model, performance evaluation or both (4,5,6). The idea is that as more transit passengers experience the benefits of TSP, the greater the likelihood that overall person travel time and delay will decrease. Thus the ridership parameter is suggested as a base characteristic. Although other characteristics from Table 2.1 could be considered, they are generally not as easily quantified, or are directly related to the proposed characteristics (e.g., ADT and Number of Lanes are the direct inputs to determine v/c ratio). Thus, the parameters just discussed were selected as base characteristics, expressed in the following form: prevailing peak hour roadway volume/capacity ratio, peak hour buses per direction, and daily bus ridership. These three were presented to RTA staff for review. RTA staff checked available data and found that the number of peak hour buses was highly correlated with ridership. In other words, the greater the number of peak hour buses, the higher the daily ridership. This correlation is contrary to the strong preference for independent factors when trying to predict performance. In addition, RTA staff felt that including another roadway element as a base characteristic was desirable. Also, the average signal spacing in a corridor may effect the average travel speed and ability to coordinate the signals within the corridor. Thus, the potential benefit of TSP may differ in corridors with shorter and longer signal spacing. Based on these three considerations, it was decided to replace daily bus ridership with average signal spacing. Table 2.2 summarizes the base distinguishing characteristics, including the rationale for selection and the initial number of levels, or parameter ranges, of each. Figure 2.1 illustrates the categorization concept along with the initially proposed thresholds of the base characteristics. As a result, it is proposed that the universe of corridors be initially categorized into 12 major groups, or cells (2 x 3 x 2 levels). The number of levels reflects both a balance between a manageable number of cells with a reasonable member count in each cell, and expected break points in TSP performance relative to the MOEs. It should be noted that any one of the listed 65 corridors in Chapter 1 is likely to vary across its length with respect to each of the characteristics (e.g., a corridor segment with a V/C ratio primarily less than 0.90, next to a Parsons Transportation Group 2-3