Pace Transit Signal Priority (TSP) Initiative Evaluation Report for the Harvey Area TSP Demonstration Project Prepared for Prepared by March, 2012 1
Table of Contents EVALUATION HIGHLIGHTS.....ii SUMMARY... ii What is the purpose of this document?... iii TSP 101: What is TSP and how does it work?... iii What is the Pace Transit Signal Priority (TSP) Initiative?... viii What are the Goals and Objectives of the Harvey Area TSP Demonstration Project?... ix How do the Pace TSP Initiative and the Harvey Area TSP Demonstration Project align with efforts to improve transit service throughout the Chicago metropolitan area?... xi What do I need to know about the Harvey Area TSP Demonstration Project?... xii What have we learned from the Harvey Area TSP Demonstration Project, and what are the key findings?... xv 1.0 INTRODUCTION... - 1-1.1 Report Organization... - 1-1.2 Background... - 1-1.3 Task 2 Demonstration Project Area... - 3-1.4 Harvey Area TSP Demonstration Project Traffic Signal Timing Improvements - 5-1.5 Goals and Objectives... - 5-2.0 QUANTITATIVE EVALUATION METHODOLOGY... - 9-2.1 Measures of Effectiveness... - 9-2.2 Data Collection... - 10-2.3 Analysis Methods... - 15-3.0 QUANTITATIVE EVALUATION RESULTS... - 16-3.1 Comparison of Before (Existing) and After (TSP On) Conditions... - 16-3.1.1 Transit Mobility... - 16-3.1.2 Transit Reliability... - 16-3.2 Signal Optimization Results... - 19-3.2.1 Transit Mobility... - 19-3.2.2 Transit Reliability... - 20-3.2.3 General Traffic Mobility... - 21-3.3 TSP Implementation Results... - 22-3.3.1 Transit Mobility... - 22-4.0 QUALITATIVE EVALUATION MEASURES... - 40-4.1 Experiences and Lessons Learned in TSP System Deployment... - 40-4.1.1 TSP System Planning and Design... - 40-4.1.2 TSP System Deployment... - 42-4.2 Institutional Considerations... - 42-4.3 Other Factors that Impact TSP Benefits... - 44-5.0 KEY FINDINGS and NEXT STEPS... - 47-5.1 Key Findings... - 47-5.2 Next Steps... - 47 - i
Harvey Area TSP Demonstration Project Evaluation Highlights The Harvey Area TSP Demonstration Project (Phase 1) was successfully implemented and tested in 2010 along Pace bus routes 350, 352 and 364, operating on Sibley Boulevard, Halsted Street, and 159 th Street, respectively, realized significant benefits as detailed below. Not only did Pace reduce its costs by reducing delays, but Pace riders saw a reduction in travel time and were more often on time. Pace equipped 20 intersections and 55 buses with TSP equipment, and a TSP Central Management System was established at Pace headquarters. The following are some key benefits found during the Harvey TSP Demonstration Project Deployment: Bus Travel times were reduced up to 15% (by a range of 25 seconds to 3.3 minutes). Cumulative Daily Delay for buses was reduced by 27 minutes at TSP- equipped intersections during AM and PM Peak Periods. Average travel time for all traffic was reduced by as much as 6 minutes during peak hours. The number of stops made by buses at signalized intersections with TSP at a corridor level was reduced by a range of 3 to a maximum of 13 on a directional basis by route. In conclusion, Harvey TSP Demonstration Project was successful both in terms of benefits to Pace riders and technology implementation. Pace plans to start Phase 2 deployment of the project by mid-year 2012 and begin subsequent region wide TSP deployment along major Arterial Rapid Transit (ART) corridors. ii
SUMMARY What is the purpose of this document? This document presents an evaluation of the Harvey Area Transit Signal Priority (TSP) Demonstration Project, a component of the Pace TSP Initiative. The evaluation report includes both qualitative and quantitative findings and emphasizes both the invaluable experience gained by Pace during the process of planning, procuring, constructing, testing, and operating the TSP system that has been deployed as part of the demonstration project as well as the measurable benefits of improved schedule adherence and travel time savings. TSP 101: What is TSP and how does it work? TSP gives transit vehicles a little extra green time or a little less red time at signalized intersections to reduce the time they are slowed down by traffic signals. TSP is an operational strategy that facilitates the movement of in-service transit vehicles, either buses or streetcars, through traffic signal controlled intersections. [S]ignal priority modifies the normal signal operation process to better accommodate transit vehicles. [O]bjectives of TSP include improved schedule adherence, improved transit efficiency, contribution to enhanced transit information, and increased road network efficiency. 1 By reducing the time that transit vehicles spend delayed at intersection queues, TSP can reduce transit delay and travel time and improve transit service reliability, thereby increasing transit quality of service. It also has the potential for reducing overall delay at the intersection on a perperson basis. At the same time, TSP attempts to provide these benefits with a minimum of impact on other facility users, including cross-traffic and pedestrians. 2 Objectives of TSP The objectives of TSP include 3 : Improved schedule adherence Reduced delay Improved transit efficiency Contribution to enhanced transit information Increased road network efficiency Improving schedule adherence can reduce waiting time and passenger anxiety by lessening the extent to which riders need to add additional time as a contingency (e.g., catching an earlier bus, leaving for bus stop early) in order to arrive on time at their destination. Reduced delay but not iii
elimination of delay -- to transit vehicles can enhance transit efficiency as well as potentially improve schedule adherence. TSP may also facilitate the provision of enhanced rider information by enabling real-time detection information to be used for other purposes. Any resulting increases in ridership and the higher occupancies on transit vehicles can also contribute to the significance of reductions in transit vehicle delay. Since transit service is typically much more frequent than rail or emergency vehicle service, use of priority rather than preemption allows the system to maintain a higher level of performance. Key Components of a TSP System 4 The basic components of a TSP system are described in the following section. See Figure ES-1 for a simplified representation of how TSP works. Vehicle detection system The vehicle detection system provides vehicle data (location, arrival time, approach, etc.) to a Priority Request Generator (PRG). For the Pace Harvey Area TSP Demonstration Project, satellite (GPS)-based vehicle detection is utilized; a GPS antenna on board the bus provides location data to the PRG. Priority Request Generator (PRG) Generates the request for TSP. The PRG is located in the transit vehicle and communicates with the Priority Request Server (PRS) at the local TSP-equipped intersections. Once a vehicle has been detected within a specified vicinity of a TSP-equipped intersection, the PRG initiates requests for TSP based on predefined criteria; in the case of the Pace TSP System, transit vehicles will only request TSP when running behind schedule by more than 1 minute. Priority Request Server (PRS) Receives request(s) for TSP from the PRG. Prioritizes and processes the request(s) for TSP at the intersection based on predefined TSP criteria. The PRS is located inside the traffic signal controller cabinet. Communications System The communication system links the PRG, PRS, and other components with one another. In the case of the Pace Harvey Area TSP Demonstration Project, the PRGs on the buses and the PRSs at the TSP intersections communicate with one another via a hardened (i.e. outdoor) Wi-Fi network, which was installed as part of the project. TSP Traffic Signal Controller Strategies A traffic signal controller software enhancement that allows for a little extra green time or a little less red time while still operating within requirements of the agency that has jurisdiction of the intersection. TSP Management System (optional) Can configure settings, log events, and provide reporting capabilities on the TSP system either locally or remotely via the communications system. iv
Figure ES-1: TSP at Traffic Signals A Simplified Representation 5 PRG PRS The general steps involved in providing TSP are as follows: 1. The bus approaching the intersection is detected ( check-in ) at some point Pd upstream of the intersection (various detection methods exist). 2. The Priority Request Generator (PRG) on board the bus notifies the Priority Request Server (PRS) installed in traffic signal controller cabinet that the approaching bus would like to receive TSP. 3. The PRS processes the request and decides whether to grant TSP based on defined conditions. 4. If those conditions are met, the PRS will communicate with the traffic signal controller, C, to then initiate action to provide TSP based on defined TSP control strategies. Typically, if the intersection signals are already displaying a green light for the approach being used by the bus, the controller will extend the length of the green phase (i.e. green extension ) to enable the bus to pass through the intersection on that phase. If the intersection signals are displaying a red light on the bus approach, the controller will shorten the green phase on the cross street (i.e. truncate the red phase or red truncation ) to provide an earlier green phase for the bus approach. 5. When the bus passes through the intersection, clearance is detected ( check-out ) by the vehicle detection system at Pc and a communication is sent to the controller C that the bus has cleared the intersection. 6. On being notified that the bus has cleared the intersection, the controller, C, restores the normal traffic signal timing through a predetermined logic. Transit Signal Priority Examples 6 : The following examples provide a general explanation of what happens at an intersection when TSP is triggered. These examples are consistent with the TSP control strategies that are implemented as part of the Pace Harvey Area TSP Demonstration project, known as red truncation and green extension. Typically, if the intersection signals are displaying a red light on the bus approach, the controller will shorten the green phase on the cross street to provide an earlier green phase (i.e. truncate the v
red phase or red truncation ) for the bus approach. If the intersection signals are already displaying a green light for the approach being used by the bus, the controller will extend the length of the green phase (i.e. green extension ) to enable the bus to pass through the intersection on that phase. The following figure, Figure ES-2, shows how red truncation and green extension work. Figure ES-2: Transit Signal Priority Examples TSP Bus TSP Bus TSP Bus TSP Bus TSP Bus TSP Bus vi
Traffic Signal Timing Operation for TSP 7 Figure ES-3: Normal Traffic Signal Timing Operation Red Truncation: The intersection signals are displaying a red light on the bus approach; the controller will shorten the green phase on the cross street to provide an earlier green phase (i.e. truncate the red phase or red truncation ) for the bus approach. Figure ES-4: Traffic Signal Timing Operation with Red Truncation (i.e. Early Green) Main Street maintains coordination with adjacent traffic signals in a coordinated signal system. Green Extension: The intersection signals are displaying a green light on the bus approach; the green light on the bus approach is lengthened up to a maximum permitted time. This proves helpful when the transit vehicle is detected near the end of the green and no near side bus stop is present. By extending the green a few seconds, the transit vehicle avoids stopping at the signal. vii
Figure ES-5: Traffic Signal Timing Operation with Green Extension Example: Green Extension Bus traveling on Main Street arrives late during Main Street green and wants phase extension. What is the Pace Transit Signal Priority (TSP) Initiative? Identified in the Vision 2020 plan, Pace s blueprint for the future of suburban transit, as one of several key service improvements intended to help enhance bus speed and thus improve travel times and on-time performance, TSP is envisioned as an integral part of Pace s Intelligent Bus System (IBS) and a key component of future Arterial Rapid Transit (ART) service as Pace reshapes it system by using new methods and technologies. It is anticipated that implementing TSP throughout the Pace service area at strategically-selected signalized intersections along Pace bus routes will improve bus mobility and reliability, and therefore, as a result, will help Pace provide enhanced transit services to better meet current and future demands, attract additional ridership, and increase the satisfaction of transit users. In order to investigate how to best implement a region-wide TSP program, determine where TSP should be deployed, and assess how TSP would benefit Pace transit operations, Pace began work on the planning, design, demonstration, testing, and evaluation of a TSP system through the Pace TSP Initiative. The Pace TSP Initiative included the development of a comprehensive Regional TSP Deployment Plan and the execution of a TSP demonstration project. Regional TSP Deployment Plan This plan is being used by Pace to help guide the future deployment of TSP throughout Pace s service area. The Regional TSP Deployment Plan, viii
completed in June 2008, identified and prioritized corridors in Pace s service area that could benefit from the deployment of TSP in short-, medium-, and long-term timeframes. Harvey Area TSP Demonstration Project The purpose of the Harvey Area TSP Demonstration Project is to help educate and inform Pace on the following: o how to best implement a TSP program o the benefits that can be realized from the deployment of TSP in coordination with other transit technologies o to provide a roadmap for future TSP deployments What are the Goals and Objectives of the Harvey Area TSP Demonstration Project? Quantitative Goals and Objectives: The quantitative goals and objectives were identified to assess the potential improvements in mobility and reliability for buses and general traffic after TSP implementation. Goal 1: Improve Transit Mobility TSP implementation will improve mobility for Pace buses. Objective 1-1: To reduce bus travel time Objective 1-2: To reduce bus delay at TSP intersections Objective 1-3: To reduce bus delay at the corridor level (i.e. to reduce bus delay for each bus within the segment of the bus route where TSP is deployed) Goal 2: Improve Transit Reliability TSP implementation will improve schedule adherence for Pace buses. Objective 2-1: To reduce bus travel time variance Objective 2-2: To reduce the amount of time that arrival/departure times deviate from the schedule Goal 3: Improve General Traffic Mobility Signal optimization and TSP implementation will improve mobility for general traffic. Objective 3-1: To reduce general traffic travel time (i.e. all other traffic besides Pace buses) Please refer to Section 2, which describes the methodology used for the quantitative evaluation including descriptions of measures of effectiveness (MOE), data collection, and analysis methods. Section 3 presents the quantitative evaluation analysis results. ix
Qualitative Goals and Objectives: While not Pace s first foray into TSP, the Harvey Area TSP Demonstration Project represents a considerable advancement in project scope, the capabilities of the available TSP technology and related equipment, and the project s goals and objectives when compared to the Cermak Road Bus Preemption Study and demonstration project completed in 1998. As indicated in the previous section, the Harvey Area TSP Demonstration Project aims to help Pace learn how to best implement and reap the benefits from TSP, which will provide invaluable experience for upcoming TSP deployments. The qualitative goals and objectives were developed to assess the areas of the project that cannot be measured in hard numbers. Goal 1: Address Institutional Concerns Address institutional concerns related to deploying TSP in the demonstration project area and throughout the Pace service area Objective 1-1: Coordinate with local jurisdictions, such as Illinois DOT, City of Harvey, and Village of Riverdale. Goal 2: Address Needs for Deploying TSP on Buses Objective 2-1: Integrate TSP system with Pace s IBS, the existing Automated Vehicle Location (AVL) system Objective 2-2: Implement conditional priority where the buses only request TSP when behind schedule Objective 2-3: Cancel TSP calls when entrance/exit doors are open and when the next stop pull cords are activated Objective 2-4: Distinguish the locations of near-side and far-side bus stops at TSP intersections Goal 3: Address Needs for Deploying TSP at Intersections Objective 3-1: Implement green extension and red truncation TSP strategies Objective 3-2: Implement TSP on the various locally-approved traffic signal controllers, mainly the Econolite ASC/2 and ASC/3 controllers and Siemens EAGLE EPAC300 M40 and M50 controllers. Objective 3-3: Maintain coordination for traffic signals that are part of interconnected signal systems Objective 3-4: Maintain pedestrian clearance intervals Objective 3-5:Maintain functionality of existing Emergency Vehicle Preemption (EVP) systems Goal 4: Address Requirements for Deploying TSP Central Management System x
Objective 3-6: Remotely monitor, collect data from, and configure the TSP system from Pace Headquarters in Arlington Heights. Please refer to Section 4, which presents qualitative evaluation measures and results, including project experiences that will benefit Pace in future deployments of TSP systems in the region. How do the Pace TSP Initiative and the Harvey Area TSP Demonstration Project align with efforts to improve transit service throughout the Chicago metropolitan area? The following section describes how the TSP Initiative and the Harvey Area TSP Demonstration Project align with, and help to achieve, the goals and objectives of other efforts to improve transit service and regional mobility by Pace and its sister agencies. Chicago Metropolitan Agency for Planning (CMAP) CMAP is the federally designated Metropolitan Planning Organization (MPO) for the northeastern Illinois counties of Cook, DuPage, Kane, Kendall, Lake, McHenry, and Will. CMAP developed and now guides the implementation of GO TO 2040, metropolitan Chicago's first comprehensive regional plan in more than 100 years. To address anticipated population growth of more than 2 million new residents, GO TO 2040 establishes coordinated strategies that help the region's 284 communities address transportation, housing, economic development, open space, the environment, and other quality-of-life issues. GO TO 2040 includes specific recommendations on improvements related to public transit, Intelligent Transportation Systems (ITS), and TSP. The following two paragraphs are direct quotes from the GO TO 2040 plan. GO TO 2040 recommends that the region prioritize investments toward strategic enhancements and modernization of the transportation system. If carefully targeted, these types of projects will improve access, mobility, and the overall experience for all users. 8 Improvements related to Intelligent Transportation Systems (ITS) are also considered strategic enhancements and modernization. These include the use of real-time traveler information for both highway and transit, signal improvements such as interconnects or Transit Signal Priority (TSP) systems, traffic management centers, and many others. ( ) GO TO 2040 supports continuing to advance ITS projects of all types, and recommends a continued role for CMAP in coordinating these efforts regionally. 9 xi
Pace s Vision 2020 Plan Unveiled in 2002, Pace continues to use its Vision 2020 plan as a guide into the future. The Pace TSP Initiative and the Harvey Area TSP Demonstration Project will help Pace realize many of the expected benefits of implementing the Vision 2020 plan, which are as follows 10. (A check mark indicates an identified benefit of implementing the Vision 2020 plan that TSP can have a positive influence on.) The key reasons to implement Vision 2020 are: Customers Higher level of suburban mobility Faster service More flexible service o Pedestrian and bicycle access o Improved passenger facilities o Greater public safety Improved connections o Better access to jobs and community facilities Reduced reliance on the automobile Region o Positive effect on new development Less congestion Infrastructure improvements o Strong economic development Strong regional public transportation system Environment Improved Air Quality Better connected communities Serves Everyone Transit dependent Work commuters Riders with strollers People with disabilities Seniors Full Suburban Access Convenient o Affordable o Easy to use Faster o Direct Pace s 2012 Budget, Appendix E: Planning Initiatives Pace is meeting the goals of Vision 2020 in a variety of ways, including through several continued efforts aimed at increasing network speed as noted in the 2012 Pace Budget 11. Those network speed enhancements include the following strategies: implementing TSP on designated corridors as part of the 5-year Traffic Corridor Optimization and Traffic Signal Priority Program improving on-time performance of Pace fixed routes converting routes from flag stop service to posted stop service xii
The Harvey Area TSP Demonstration project included two (2) bus routes that were converted from flag stop service to posted stop service during the course of the project, and Pace Service Planning is currently using data from the Harvey Area TSP Demonstration project system to help improve on-time performance as part of its ongoing program to make transit work better for existing riders and to encourage non-users to try public transit. What do I need to know about the Harvey Area TSP Demonstration Project? The Harvey Area TSP Demonstration project included the following activities: Pace equipped 20 signalized intersections in the area surrounding the Harvey Transportation Center (HTC) with TSP equipment (PRS units) Three diverse and strategically-selected Pace bus routes that serve the HTC, Route 350 (Sibley), Route 352 (Halsted), and Route 364 (159th Street), travel through the TSP-equipped intersections. Pace outfitted 55 buses that operate out of the South Division Garage with TSP equipment (PRG units). Pace installed a TSP Central Management System at the Arlington Heights headquarters so that Pace could monitor, evaluate, and configure the TSP system remotely. Pace installed a robust communications system that connects the various elements of the TSP system, from the wayside (on-street) equipment to the bus-mounted equipment to the Central Management System at Pace Headquarters. The TSP system provides Pace buses with the technology to either extend green lights (green extension) or shorten red lights (red truncation) in the direction that the bus is traveling at the 20 TSP-equipped intersections when the buses are running behind schedule by more than one (1) minute. The TSP system can be managed from anywhere with access to the internet by anyone that has the required security clearance for the Central Management System s servers that reside at Pace Headquarters. A key objective of the Pace TSP system is to improve the schedule adherence of Pace fixedroute service. This is aided by integrating the TSP System with the bus Automated Vehicle Location (AVL) system, Pace s on-board Intelligent Bus System (IBS). When the Pace IBS determines that a bus is more than one minute behind schedule, the bus will request TSP until the deviation from the route s schedule has been corrected. Improving the schedule adherence will indirectly lead to operational cost savings through a decrease in fuel consumption, emissions, and wear-and-tear on the buses as a result of fewer stops and starts at red lights afforded by TSP. Customer satisfaction with Pace transit can also be improved as passengers notice an increase in on-time performance and a decrease in transit travel times, which could potentially increase ridership along TSP Corridors. xii
Table ES-1 provides a table listing of the 20 signalized intersections that were equipped with TSP equipment. Table ES-1: Pace Harvey Area TSP Demonstration Project TSP Intersections 147th St Corridor (7 Signals) 147th St @ LaSalle St 147th St @ Indiana Ave/State St 147th St @ Chicago Rd/South Park Ave 147th St @ Cottage Grove Ave 147th St @ Greenwood Rd 147th St @ Woodlawn Ave 147th St @ Lincoln Ave/Michigan City Rd 159th St Corridor (7 Signals) 159th St @ Vincennes Rd 159th St @ Indiana Ave/State St 159th St @ Wausau Ave 159th St @ Chicago Rd/South Park Ave 159th St @ Cottage Grove Ave 159th St @ Ellis Ave 159th St @ Woodlawn Ave Halsted St Corridor (3 Signals) Halsted St @ 138th St Halsted St @ 144th St Halsted St @ 147th St Park Ave Corridor (3 Signals) Park Ave @ 154th St Park Ave @ 155th St Park Ave @ 157th St Figure ES-2 on the following page provides a graphic of the project area featuring the three Pace bus routes and the 20 TSP-equipped intersections in the project area. xiii
Figure ES-6: Pace Harvey Area TSP Demonstration Project Area Riverdale to 95 th /Dan Ryan Dalton to Hammond TC South Holland Harvey to Hammond TC to Chicago Hts xiv
What have we learned from the Harvey Area TSP Demonstration Project, and what are the key findings? The evaluation results are presented in this document in both quantitative and qualitative terms. Quantitative results are presented at a high level in Tables ES-2 through ES-5 and Figures ES-7 through ES-9 found in the following pages. Transit and traffic data have been collected from three major sources, including the Pace Intelligent Bus System (IBS data) as well as more detailed data collected by URS staff traveling through the TSP project area on Pace buses (Bus Ride Along Data) and in passenger vehicles (Floating Car Data). Transit and traffic data collection was conducted for AM and PM peak periods over the course of the demonstration project to study the conditions at specific stages of the project. Before (Existing) Conditions Data collected during this stage of the project represents Pace operations before any work was done on the project. Optimized (TSP Off) Data collected during this stage of the project represents Pace operations after traffic signal timings were optimized to best accommodate current traffic patterns and conditions but before TSP was deployed. After (TSP On) Data collected during this stage of the project, the final configuration of the demonstration project, represents Pace operations after the traffic signal timings were optimized and the TSP System was deployed. The evaluation focused on transit mobility and reliability and was performed by comparing the Measures of Effectiveness (MOEs) for travel time, delay, time deviated from schedule, and number of delayed buses before and after TSP implementation. Direct value change and percentage change were both used to quantify the improvements for these MOEs. The tables and figures summarize the major MOEs (travel time and travel time variation) discussed in this document for Pace Routes 350, 352, and 364 respectively. The improvements to Pace transit operations for the AM and PM peak periods are displayed by comparing the Existing state (Before) vs. the TSP state (After). Improvements are all highlighted in blue in the tables. Overall, the travel time was reduced by a range from 2% (25 sec) to 15% (3.3 min). The travel time variation was reduced by a range of 14% (12 sec) to 66% (4 min). Route 364 WB received the most improvements during the PM peak period. There were some instances where the TSP system did not improve transit operations as expected. Some reasons for this include various changes made to transit operations between the rounds of data collection. These are discussed in more detail within this document. In addition, different traffic levels during the before and after phases when the evaluation data was collected may also xv
impact the evaluation results. If more travel runs were collected during the peak hour out of the three-hour peak periods, the higher likelihood is to obtain higher travel time and delay which may cause the results to vary. While TSP can improve schedule adherence and transit travel times, TSP alone can only reduce the delays to transit vehicles caused by traffic signals, specifically the delay from red lights. For the TSP Demonstration evaluation, signal delay was objectively defined as the time between when a transit vehicle stops at the end of a queue at a red light while waiting for a green light and when that light first turns green. Delay can occur at that same intersection for other reasons as well. Slow-moving traffic can prevent the transit vehicle from clearing the intersection, thus causing it to be delayed through an additional red signal cycle. Delay can also be caused by other factors on the roadway, such as train crossings, which may be creating lengthy vehicle queues beyond the intersection which the transit vehicle is waiting to clear. Thus, the green extension or red truncation of TSP cannot be guaranteed to eliminate all of the delay that can potentially occur at a signalized intersection. TSP can only reduce the amount of time that a transit vehicle is stopped at a red light. xvi
Table ES-2: Comparison of Total Daily Travel Time (hh:mm:ss) for Each Route and All Routes Combined During AM and PM Peak Periods Route 350 352 364 Route Direction From To EB HTC 147 th St (Sibley Blvd) @ I-94 WB 147 th St (Sibley Blvd) @ I-94 Halsted St NB HTC @ Blue Island- Riverdale Rd. Halsted St SB @ Blue Island- Riverdale Rd. EB HTC 159th St(US 6) @ I-94 WB 159th St(US 6) @ I-94 Before (Existing) After (TSP On) Change % Change 5:52:32 5:32:36-0:19:56-5.7% HTC 5:29:27 5:49:24 0:19:56 6.1% 5:17:06 5:03:03-0:14:03-4.4% HTC 4:55:32 4:09:00-0:46:32-15.7% 4:03:25 4:20:36 0:17:10 7.1% HTC 4:19:10 3:53:00-0:26:10-10.1% All All - - 29:57:13 28:47:39-1:09:34-3.9% Routes Note: AM Peak Period: 6:00 am 9:00 am; PM Peak Period: 3:30 pm 6:30 pm Figure ES-7: Percentage Change in Daily Travel Time Between Before and After Conditions Percentage Change in Daily Travel Time Between Before and After Conditions 10.0% 6.1% 7.1% 5.0% Percentage Change (%) 0.0% -5.0% -10.0% 350 EB 350 WB 352 NB 352 SB 364 EB 364 WB -5.7% -4.4% -10.1% % Diff -15.0% -15.7% -20.0% Bus Route xvii
Table ES-3: Comparison of Daily Travel Time Variation (mm:ss) for Each Route and All Routes Combined During AM and PM Peak Periods Route 350 352 364 Route Direction From To EB HTC 147 th St (Sibley Blvd) @ I-94 WB 147 th St (Sibley Blvd) @ I-94 Halsted St NB HTC @ Blue Island- Riverdale Rd. Halsted St SB @ Blue Island- Riverdale Rd. EB HTC 159th St(US 6) @ I-94 WB 159th St(US 6) @ I-94 Before (Existing) After (TSP On) Change % Change 03:43 01:59-01:43-46% HTC 01:31 01:26-00:05-6% 01:40 02:06 00:26 26% HTC 01:40 00:59-00:40-41% 04:10 01:26-02:43-65% HTC 05:21 02:25-02:55-55% All All Average Travel Time Variations 03:01 01:44-01:17-43% Routes Note: AM Peak Period: 6:00 am 9:00 am; PM Peak Period: 3:30 pm 6:30 pm Figure ES-8: Percentage of Daily Travel Time Variation Between Before and After Conditions 40% Percentage Change in Travel Time Variation Between Before and After 26% 20% Percentage Chagne (%) 0% -20% -40% -60% -80% 350 EB 350 WB -6% 352 NB 352 SB 364 EB 364 WB -46% -41% -55% -65% Bus Route % Diff xviii
Table ES-4: Comparison of Daily TSP Intersection Delay (mm:ss) for each TSP Intersection and All TSP Intersections Combined During AM and PM Peak Periods TSP Intersection Optimized (TSP Off) After (TSP On) Change 147th St @ Halsted St 26:26 16:42-09:44 147th St @ LaSalle St 00:08 00:23 00:15 147th St @ Indiana Ave/State St 04:05 00:37-03:28 147th St @ Chicago Rd/South Park Ave 05:00 03:41-01:19 147th St @ Cottage Grove Ave 00:48 00:18-00:30 147th St @ Greenwood Rd 01:50 03:29 01:39 147th St @ Woodlawn Ave 01:53 01:47-00:06 147th St @ Lincoln Ave/Michigan City Rd 02:42 03:57 01:15 Halsted St @ 144th St 02:35 01:22-01:13 Halsted St @ 138th St 03:24 02:04-01:20 Park Ave @ 154th St 01:44 01:41-00:03 Park Ave @ 155th St 08:22 08:21-00:01 Park Ave @ 157th St 06:24 03:32-02:52 159th St @ Vincennes Rd 12:55 06:24-06:31 159th St @ Indiana Ave/State St 22:21 19:58-02:23 159th St @ Wausau Ave 01:07 02:14 01:07 159th St @ Chicago Rd/South Park Ave 03:34 03:01-00:33 159th St @ Cottage Grove Ave 01:38 01:32-00:06 159th St @ Ellis Ave 03:07 02:08-00:59 159th St @ Woodlawn Ave 02:01 01:19-00:42 All Intersections 1:52:04 1:24:30-27:34 Note: AM Peak Period: 6:00 am 9:00 am; PM Peak Period: 3:30 pm 6:30 pm xix
Table ES-5: Comparison of Daily TSP Intersection Delay (mm:ss) for Each Route and for All Routes Combined Route Number Of TSP Intersections Optimized (TSP Off) After (TSP On) Change % Change 350EB 8 16:23 10:29-05:54-36% 350WB 8 11:06 10:22-00:44-7% 352NB 3 11:30 09:02-02:28-21% 352SB 3 09:52 04:27-05:25-55% 364EB 10 34:13 28:55-05:18-15% 364WB 10 29:00 21:15-07:45-27% All Total Delay for All Routes Intersections* 1:52:04 1:24:30-27:34-25% * Note: The total number of intersections is 20. Routes 350 and 352 both travel through the TSP intersection at 147th St at Halsted St. Figure ES-12: Percentage Change in Intersection Delay Between TSP Off and TSP On Conditions Percentage Change in Intersection Delay Between TSP OFF and TSP ON 0% 350 EB 350 WB 352 NB 352 SB 364 EB 364 WB -10% -7% Percentage Change (%) -20% -30% -40% -50% -36% -21% -15% -27% % Diff. -60% -55% Bus Route xx
1.0 INTRODUCTION 1.1 Report Organization Section 2 describes the methodology used for the quantitative evaluation including descriptions of measures of effectiveness (MOE), data collection, and analysis methods. Section 3 presents the quantitative evaluation analysis results. Section 4 presents qualitative evaluation measures, including project experiences that will benefit Pace in future deployments of TSP systems in the region. Section 5 summarizes key finds learned from the deployment of the TSP system and the evaluation analysis and lists the items that the project teams need to be aware of for future TSP deployment. 1.2 Background Pace, the suburban bus division of the Regional Transportation Authority (RTA), provides suburban fixed bus route, ADA Paratransit, vanpools, and Dial-a-Ride public transportation services to six-counties (Cook, DuPage, Will, Kane, McHenry, and Lake) in northeastern Illinois. It is the intent of Pace to implement methods that can improve and maximize the usage of all transit services in the six-county service area. As Pace s service area continues to expand and develop from population growth and employment opportunities, the demand for a faster, more efficient and effective transit system becomes an increased concern. Pace has been a leader in the application of technology to improve transit operations, enhance the travel experience of its customers, and meet the stated goals of its Vision 2020 long-range plan. TSP technology is widely used to improve transit operational efficiency by reducing bus delay at signalized intersections, maintaining bus speed, and enhancing bus schedule adherence. It is anticipated that implementing a TSP system throughout the region at signalized intersections along Pace bus routes will improve Pace bus mobility and reliability, and as a result, help Pace provide better transit services to meet current and future demands, attract additional ridership, and increase the satisfaction of transit users. In order to investigate how to best implement a TSP system, determine where TSP should be deployed, and assess how the TSP system would benefit Pace transit operations, Pace began work on the planning, design, demonstration, testing, and evaluation of a TSP system through the Pace TSP Initiative. The Pace TSP Initiative included the development of a comprehensive Regional TSP Deployment Plan and the execution of a TSP Demonstration project. The Pace TSP Initiative includes a total of five tasks that cover both the Regional TSP Deployment Plan and the TSP Demonstration project. The tasks and associated milestones for each task of the project are listed below: - 1 -
Task 1: Coordinate with Public Agencies (for both the Regional TSP Deployment Plan and TSP Demonstration) - Kickoff Meeting - Outreach Plan - Project Management TSP Demonstration Project Task 2: Harvey Area TSP Demonstration Project - Subtask 1: Perform Needs Assessment - Subtask 2: Develop High-Level System Requirements - Subtask 3: Complete Signal Timing Optimization, Field Operations Test Plan and Specifications - Subtask 4: Complete Pre-Deployment Impact Analysis - Subtask 5: Perform TSP Deployment, Demonstration, and Evaluation Regional TSP Deployment Plan Task 3: Collection of Transit and Traffic Characteristics Data for TSP Implementation - Establish Study Corridors - Develop Data Gathering Plan and Costs - Assemble Data Task 4: Prioritization of Pace Routes/Corridors for TSP Implementation Based on Cost- Benefit Analysis and Return on Investments - Develop/Apply Locational Delay Rating Algorithm - Develop Menu of Route Improvement Techniques - Evaluate Corridors for Applying TSP Techniques Task 5: Design and Evaluation Strategy - System Architecture and Hardware / Software - TSP Implementation / Deployment Plan - TSP Deployment Costs This document presents the results of an evaluation of the Harvey Area TSP Demonstration Project in Task 2. The results consists of both qualitative and quantitative sections to emphasize both the measurable benefits of travel time savings as well as the invaluable experience gained by Pace personnel in the process of planning, deploying, and operating the TSP System around the HTC. - 2 -
Tasks 3, 4, and 5 listed above were completed in June 2008 and resulted in the development of a Regional TSP Deployment Plan that identified several Pace corridors that could benefit from the deployment of TSP technologies in short, medium, and long term timeframes. 1.3 Task 2 Demonstration Project Area Three Pace bus routes serving the Harvey Transportation Center were chosen to be part of the Demonstration. These are routes 350 (Sibley / 147 th Ave.), 352 (Halsted St.), and 364 (159 th St.). Together, these three bus routes travel through a total of 20 signalized intersections that have been equipped with TSP equipment that receives requests from Pace buses for transit signal priority. Table 1-1 provides a table listing of the 20 signalized intersections with TSP equipment. Figure 1-2 on the following page provides a graphic of the project area, the three Pace bus routes, and the 20 TSP-equipped intersections in the project area. Table 1-1: Traffic Signal Intersection in Pace TSP Demonstration 147th St Corridor (7 Signals) 147th St @ LaSalle St 147th St @ Indiana Ave/State St 147th St @ Chicago Rd/South Park Ave 147th St @ Cottage Grove Ave 147th St @ Greenwood Rd 147th St @ Woodlawn Ave 147th St @ Lincoln Ave/Michigan City Rd 159th St Corridor (7 Signals) 159th St @ Vincennes Rd 159th St @ Indiana Ave/State St 159th St @ Wausau Ave 159th St @ Chicago Rd/South Park Ave 159th St @ Cottage Grove Ave 159th St @ Ellis Ave 159th St @ Woodlawn Ave Halsted St Corridor (3 Signals) Halsted St @ 138th St Halsted St @ 144th St Halsted St @ 147th St Park Ave Corridor (3 Signals) Park Ave @ 154th St Park Ave @ 155th St Park Ave @ 157th St - 3 -
Figure 1-2: Harvey Area TSP Demonstration Project Area Riverdale to 95 th /Dan Ryan Dalton to Hammond TC South Holland Harvey to Hammond TC to Chicago Hts - 4 -
1.4 Harvey Area TSP Demonstration Project Traffic Signal Timing Improvements Prior to the deployment of TSP equipment at the traffic signals identified in Figure 1-1, Pace conducted an effort as part of Task 2 of this project to improve the overall traffic signal timing operations in the project area. This evaluation report presents data measured before these signal timing improvements, after the improvements (but before TSP equipment was installed), and after TSP equipment was installed and operational at all intersections. A separate evaluation report was prepared detailing travel time savings to general traffic as a result of the traffic signal timing improvements made in Phase 2. 1.5 Goals and Objectives Quantitative Goals and Objectives: The quantitative goals and objectives were identified to assess the potential improvements in mobility and reliability for buses and general traffic after TSP implementation. Goal 1: Improve Transit Mobility TSP implementation will improve mobility for Pace buses. Objective 1-1: To reduce bus travel time Objective 1-2: To reduce bus delay at TSP intersections Objective 1-3: To reduce bus delay at the corridor level (i.e. to reduce bus delay for each bus within the segment of the bus route where TSP is deployed) Goal 2: Improve Transit Reliability TSP implementation will improve schedule adherence for Pace buses. Objective 2-1: To reduce bus travel time variance Objective 2-2: To reduce the amount of time that arrival/departure times deviate from the schedule Goal 3: Improve General Traffic Mobility Signal optimization and TSP implementation will improve mobility for general traffic. Objective 3-1: To reduce general traffic travel time (i.e. all other traffic besides Pace buses) Please refer to Section 2, which describes the methodology used for the quantitative evaluation including descriptions of measures of effectiveness (MOE), data collection, and analysis methods. Section 3 presents the quantitative evaluation analysis results. - 5 -
Qualitative Goals and Objectives: While not Pace s first foray into TSP, the Harvey Area TSP Demonstration Project represents a considerable advancement in project scope, the capabilities of the available TSP technology and related equipment, and the project s goals and objectives when compared to the Cermak Road Bus Preemption Study and demonstration project completed in 1998. As indicated in the previous section, the Harvey Area TSP Demonstration Project aims to help Pace learn how to best implement and reap the benefits from TSP, which will provide invaluable experience for upcoming TSP deployments. The qualitative goals and objectives were developed to assess the areas of the project that cannot be measured in hard numbers. Goal 1: Address Institutional Concerns Address institutional concerns related to deploying TSP in the demonstration project area and throughout the Pace service area Objective 1-1: Coordinate with local jurisdictions, such as Illinois DOT, City of Harvey, and Village of Riverdale. Goal 2: Address Requirements for Deploying TSP on Buses Objective 2-1: Integrate TSP system with Pace s IBS, the existing Automated Vehicle Location (AVL) system Objective 2-2: Implement conditional priority where the buses only request TSP when behind schedule Objective 2-3: Cancel TSP calls when entrance/exit doors are open and when the next stop pull cords are activated Objective 2-4: Distinguish the locations of near-side and far-side bus stops at TSP intersections Goal 3: Address Requirements for Deploying TSP at Intersections Objective 3-1: Implement green extension and red truncation TSP strategies Objective 3-2: Implement TSP on the various locally-approved traffic signal controllers, mainly the Econolite ASC/2 and ASC/3 controllers and Siemens EAGLE EPAC300 M40 and M50 controllers. Objective 3-3: Maintain coordination for traffic signals that are part of interconnected signal systems Objective 3-4: Maintain pedestrian clearance intervals Objective 3-5:Maintain functionality of existing Emergency Vehicle Preemption (EVP) systems - 6 -
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Goal 4: Address Requirements for Deploying TSP Central Management System Objective 3-6: Remotely monitor, collect data from, and configure the TSP system from Pace Headquarters in Arlington Heights. Please refer to Section 4, which presents qualitative evaluation measures and results, including project experiences that will benefit Pace in future deployments of TSP systems in the region. - 8 -
2.0 QUANTITATIVE EVALUATION METHODOLOGY This section presents the quantitative evaluation methodology of the Harvey Area TSP Demonstration, including the specific measures of effectiveness (MOEs), data, and analyses that will be employed. 2.1 Measures of Effectiveness MOEs are identified to quantify the effect of traffic signal optimization and TSP implementation on transit and general traffic. The MOE s are defined as follows to help evaluate the goals and objectives listed in the following sub-sections. 2.1.1 Transit Mobility Average Bus Travel Time: Bus travel time is defined as the total time that a bus commutes between passing a starting data collection point (an intersection or a bus stop) and passing an ending data collection point (an intersection or a bus stop) along the studied segment. The travel time includes running time, stop time, and dwell time for a bus. Average bus travel time was calculated by averaging the observed travel time for multiple bus runs. Bus travel time data were collected by field bus travel time runs and data from IBS bus database. Bus Intersection Delay: Bus delay is defined as the bus stop time that a bus experiences at each intersection. Bus intersection delay for each bus run was derived by subtracting the point in time when buses began moving at a stopped position from the point in time when buses stopped at an intersection under a red light. Total bus delay was calculated by adding the derived bus intersection delays for multiple bus runs based on field bus travel time run data. Bus Corridor Delay: Bus corridor delay is defined as the sum of the bus intersection delay experienced by each bus route along a corridor. Bus corridor delay for each bus run was derived by adding the intersection bus delays for each bus run. Average bus corridor delay was calculated by averaging the derived bus corridor delays for multiple bus runs based on field bus travel time run data. Number of Stops: Number of stops is defined as the total number of buses that stopped at each intersection. Number of bus stops was derived by counting all buses that stopped at each intersection for each bus route during the peak period based on field bus travel time run data. 2.1.2 Transit Reliability Bus Travel Time Variance: Bus travel time variance is defined as one standard deviation for observed Pace bus travel time based on field bus data. Pace bus travel time is defined as the total time that a bus commutes between passing an identified starting Pace bus time-point and passing - 9 -
an ending Pace bus time-point for selected routes along the studied segments. The bus travel time variance is calculated by determining one standard deviation for the observed Pace bus travel time during A.M. and P.M. peak periods based on field bus run data and IBS bus database. Average Bus Schedule Deviation Time: Bus schedule deviation time is defined as the offset between the scheduled bus arrival time and actual field bus arrival time at a selected bus stop. The average bus schedule deviation time was calculated by averaging the absolute value of the time deviated (including both early arrival and late arrival) from the schedule for multiple buses during the peak periods. The bus schedule deviation times will be collected by Pace IBS bus database. 2.1.3 General Traffic Mobility Average Car Travel Time: Car travel time is defined as the travel time that a probe vehicle commutes among the traffic flow between passing a starting data collection point (intersection) and passing an ending data collection point (intersection) along the studied segment. Average car travel time was calculated by averaging the observed car travel time for all probe vehicle runs. Car travel time data were collected by the field probe vehicle travel time runs. 2.2 Data Collection Evaluation data were collected during three phases in time: Before (Existing): Before traffic signal timing optimization Optimized (TSP Off): After traffic signal timing optimization, but before TSP System implementation After (TSP On): After TSP System implementation Traffic signal timing optimization throughout the project area was a task required prior to TSP System deployment to ensure that signal timings were optimized to accommodate the current traffic volumes and travel patterns. Data on transit and traffic characteristics were also obtained from three key data sources: 1) Pace Intelligent Bus System (IBS), which provides transit vehicle data from the Automated Vehicle Locator technology on buses, 2) Bus ride-along travel time runs, which provides additional details on transit vehicle delays along TSP bus routes and at individual TSP intersections., and 3) floating car travel time runs, which provides data on general traffic conditions along TSP bus routes and at individual TSP intersections. - 10 -
Transit and traffic data collection was performed before traffic signal optimization by gathering IBS data on the TSP bus routes, Routes 350, 352, and 364. Bus ride-along and floating car travel time data collection was also performed prior to traffic signal optimization. While traffic signal timings were optimized in May 2007, transit and traffic data were not collected for Phase 2 until after the TSP System was deployed and operational. Transit and traffic data for Phases 2 and 3 were collected in consecutive weeks, which more accurately revealed how the TSP System affects both transit and traffic operations while minimizing the potential for road construction, changes in traffic volumes and travel patterns, or other factors to influence transit and traffic operations between these two intervals. The TSP System was de-activated to allow for Phase 2 data collection to occur during the weeks of August 8 th and August 15 th, 2011. Phase 3 data collection was completed during the weeks of July 25 th and August 1st. Table 2-1 below displays the timeline of data collection activities. Table 2-1: Types of Data Collection during Harvey Area TSP Demonstration Data Type Route Before (Existing) Optimized (TSP Off) After (TSP) Pace IBS 350, 352, 364 February 2006 August 2011 Jul/Aug 2011 Bus Ride Along Data 350, 352, 364 May 2006 August 2011 Jul/Aug 2011 Floating Car Travel Time 159 th St (US 6), Runs 147 th St (IL 83) November 2006 August 2011 Jul/Aug 2011 2.2.1 Pace IBS Bus Data Pace uses Automatic Vehicle Location (AVL) systems installed on selected bus routes to collect real time bus data. The Pace bus data includes trip information, timestamps (both arrival and departure times), bus headways, schedule deviations, bus identification numbers, and bus position coordinates at each time point along the bus route. Bus travel time and schedule deviation were derived from the Pace bus data to assess bus operational performance and schedule adherence improvement after the signal timing optimization and TSP implementation. - 11 -