美国交通信号配时实践与技术综述

摘要/Abstract

摘要： 交通信号控制是城市交通管理的重要组成部分。交通信号配时优化作为一项投入规模较小、效果较为明显的交通治理措施，近年来受到了广泛关注。美国是世界上较早应用交通信号控制的国家，对其交通信号配时实践与技术进行分析具有重要借鉴意义。本文从实践角度出发，综述了美国交通信号配时的技术特点、工作流程、主要配时工具以及近期研究动向。首先，将美国交通信号配时的技术特点归纳为3点，即配时参数定义自成体系，强调感应控制条件下的信号协调和采用“环栅相位结构”表示配时方案。其次，依据“结果导向”式的信号配时步骤归纳了美国信号配时工作主要流程，同时分析了 Synchro，TRANSYT-7F，TranSync，Tru-Traffic 等信号配时软件工具。另外，围绕“信号配时效果评价”“智能网联条件下的交通信号控制”两项主题介绍了近期美国交通信号控制的研究动向。最后讨论了未来交通信号配时技术的发展并提出4点展望和关注，分别是配时软件工具开发与应用将发挥日益重要的作用，新数据资源的应用将能够极大程度上改进现有交通信号配时实践并带来显著工程效益，面向传统交通信号控制向智能网联环境过渡阶段的配时研究需要加强，以及交通信号控制相关的基础性交通研究仍需进一步深入和巩固。

关键词: 交通工程, 信号配时, 研究综述, 感应协调控制, 配时软件应用

Abstract: Traffic signal control is a critical part of urban transportation management. As a cost-effective approach to traffic operational improvements, facilitating the development of signal timing has been of a great interest to traffic engineers and researchers in recent years. The United States (US) is one of the most advanced countries where traffic signals were first implemented, and its best practices and lessons learned could be beneficial to many other countries. This paper provides a comprehensive review of traffic signal timing practice and techniques in the US, focusing on signal control characteristics, timing development process and software tools, as well as emerging technologies and techniques. The signal control practice in the US (also Canada) possesses some unique characteristics comparing to other countries. First, some signal timing terminologies may only exist in the US or have different meanings, such as a “signal phase”. Those who are interested in understanding the US practice must go through the details of the term definitions documented in the US manuals and standards. Secondly, a special ring-barrier structure is widely adopted to describe signal phasing and timing. Through a combination of rings and barriers that imply the duration, sequence and compatibility of signal phases, this structure allows for safe and efficient implementation of signal timing, especially at typical intersections with actuated traffic signals. Thirdly, the US signal control facilities and signal timing techniques are mostly on traffic actuated control. In the context of an actuated control mode, timing development for isolated signals can be simplified, as signal operations are largely in response to detector actuations; hence, the major effort goes to developing signal coordination.An outcome-based procedure has been highly encouraged in the US signal timing development process. The procedure is comprised of several steps, such as data collection, data analysis, timing development, and timing maintenance, in which the effectiveness and efficiency of signal timing development must rely on advanced software tools. In this paper, five signal timing software tools are analyzed regarding features of data management, timing optimization, timing diagnosis, and performance evaluation. While all of these software tools have basic functions of signal timing optimization and data management, some major differences exist in terms of timing diagnosis and performance evaluation. Timing diagnosis is important for identifying erroneous and abnormal signal operations, which ensures consistency between the designed timing plans and actual field operations. The mobile version of TranSync features active time- space diagrams and visualization of ring- barrier- strucature- based signal operations, allowing for convenient timing diagnosis in the field. Performance measurement is needed for monitoring the quality of signal timing and validating the effectiveness of signal re- timing. Earlier software packages, such as TRANSYT- 7F, PASSER and Synchro, only provide performance evaluation functions based on deterministic algrithoms and simulation, while emerging tools such as Tru- Traffic and TranSync allow users to collect actual travel- run trajectories and produce performance evaluations accordingly. The signal timing practice and techniques in the US are transforming along with the emerging technologies. Numerous studies have been conducted in recent years, and two topics are highlighted in this review, i.e., traffic signal performance meansures based on new data sources and new signal control methodologies considering a connected-andautonomous- vehicles (CAV) environment. In recent years, a variety of data sources have been used to assess traffic control performance. Automated Traffic Signal Performance Measures (ATSPMs) is an influential research effort that incorporates high-resolution controller and detector event data to gauge traffic control efficieny such as the quality of platoon progression. Travel-run trajectory data are also used in some studies to evaluate signal coordination according to travel time and the number of stops. A vast number of studies are conducted on the second topic, investigating the impacts of future CAV applications and formulating many possibilities of next- generation traffic signal control. In addition to the two topics, a few studies are devoted to improving the classic signal timing optimization algorithms. The improvements are aimed at signal coordination for multimodal traffic and special cases. Lastly, this paper provides an outlook for future signal timing practice and techniques. Signal timing tools will continue to play an important role in satisfying complex traffic management strategies and goals. The innovative use of multi-source data will enhance the traffic timing process in terms of performance monitoring. The application of CAV technologies may lead to a revolution of signal control; however, a dramatic change of the current signal control infrastructure is unlikely in the near future due to the immaturity of the current research and the mixed driving environment during a transition stage. As a result, it advocates studies for improving traffic signal timing during the transition stage towards a complete CAV circumstance. Research efforts are also required for developing necessary updates for the classic signal timing theories that were established decades ago.

Key words: traffic engineering, signal timing, research review, coordinated actuated control, signal timing software

中图分类号:

U491.5

田宗忠, 王奥博. 美国交通信号配时实践与技术综述[J]. 交通运输系统工程与信息, 2021, 21(5): 66-76.

TIAN Zong, WANG Ao-bo. A Comprehensive Review of Traffic Signal Timing Practice and Techniques in the United States[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(5): 66-76.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: http://www.tseit.org.cn/CN/abstract/abstract30309.shtml

http://www.tseit.org.cn/CN/Y2021/V21/I5/66

参考文献

[1] TANG K, BOLTZE M, NAKAMURA H, et al. Global practices on road traffic signal control: Fixed-time control at isolated intersections [M]. Amsterdam, Netherlands: Cambridge, MA, United States: Elsevier, 2019.

[2] DAY C M, BULLOCK D M, LI H, et al. Performance measures for traffic signal systems: An outcome-oriented approach (No. TPF-5 (258)) [R]. West Lafayette, Indiana: Purdue University, 2014.

[3] DAY C M, LANGDON S, STEVANOVIC A, et al. Traffic signal systems research: Past, present, and future trends [C]. Standing Committee on Traffic Signal Systems (AHB25), Centennial Papers, Washington, DC: Transportation Research Board, 2019.

[4] ATC 5301 V02 (Cabinet). Advanced transportation controller cabinet standard (ATCC) [S]. Washington, DC: AASHTO, ITE, and NEMA, 2018.

[5] ATC 5201 v06 (Controller). Advanced transportation controller cabinet standard (ATCC) [S]. Washington, DC: AASHTO, ITE, and NEMA, 2020.

[6] National transportation communications for ITS protocol object definitions for actuated signal controllers (ASC) interface NTCIP 1202 v03[S]. Washington, DC: AASHTO, ITE, and NEMA, 2019.

[7] KOONCE P, RODEGERDTS L, LEE K, et al. Traffic signal timing manual, report FHWA- HOP- 08- 024[R]. Washington, DC: Federal Highway Administration, 2008.

[8] URBANIK T, TANAKA A, LOZNER B, et al. Signal timing manual(second edition)NCHRP report 812[R]. Washington, DC: Transportation Research Board, 2015.

[9] National Committee on Uniform Traffic Control Devices Federal Highway Administration. The manual on uniform traffic control devices for streets and highways, revision, final rule (No. FHWA-2010-0159) [R]. Washington, DC: Federal Highway Administration, 2012.

[10] Cubic Trafficware Technical Team. Controller manual: scout V85.x-Cubic/Trafficware Commander and 2070- 1C ATC [M]. Sugar Land, Texas: Cubic ITS, Inc, 2014

[11] Econolite Technical Team. Cobalt programming manual P/N 140-0903-001 Rev. 00[M]. Anaheim, California: Econolite, LLC, 2013.

[12] WEBSTER F V. Traffic signal settings[R]. Road Research Technical Paper No. 39. H.M. Stationary Office, London, 1958.

[13] MANAR A, BAASS K G. Traffic platoon dispersion modeling on arterial streets[J]. Transportation Research Record, 1996, 1566(1): 49-53.

[14] PARK B B, CHEN Y. Quantifying the benefits of coordinated actuated traffic signal systems: A case study (No. VTRC 11- CR2) [R]. Charlottesville, VA: Virginia Transportation Research Council, 2010.

[15] HENRY R D, SABRA W. Signal timing on a shoestring (No. FHWA- HOP- 07- 006) [R]. United States. Federal Highway Administration, 2005.

[16] Traffic Operations Division. MnDOT signal timing and coordination manual[M]. Saint Paul, Minnesota: the Minnesota Department of Transportation, 2014.

[17] SHELBY S G, BULLOCK D M, GETTMAN D. Transition methods in traffic signal control[J]. Transportation Research Record, 2006, 1978(1): 130-140.

[18] BUCKHOLZ J. The 10 major pitfalls of coordinated signal timing[J]. ITE Journal, 1993, 63(8): 26-29.

[19] CHRISTOPHERSON P, RIDDLE R. Ideal street spacing tables for balanced progression(No. FHWA- RD- 79- 28) [R]. Washington, DC: Federal Highway Administration, 1979.

[20] SHELBY S G, BULLOCK D M, GETTMAN D. Resonant cycles in traffic signal control[J]. Transportation Research Record, 2005, 1925(1): 215-226.

[21] SUNKARI S R, ENGELBRECHT R J, BALKE K N.Evaluation of advance coordination features in traffic signal controllers (No. FHWA/TX- 05/0- 4657- 1) [R]. Texas Transportation Institute, Texas A & M University System, 2004.

[22] BONNESON J, SUNKARI S R, PRATT M, et al. Traffic signal operations handbook (No. FHWA/TX- 11/0- 6402- P1) [R]. Texas. Dept. of Transportation Research and Technology Implementation Office, 2011.

[23] Institute of Transportation Engineers. 2012 national traffic signal report card-technical report[R]. Washington, DC: National Transportation Operations Coalition, 2012.

[24] DENNEY R. Improving traffic signal management and operations: A basic service model[R]. Washington, DC: Federal Highway Administration, 2009.

[25] CHAUDHARY N A, CHU C L. Guidelines for timing and coordinating diamond interchanges with adjacent traffic signals (No. TX- 00/4913- 2) [R]. College Station, Texas: Texas Transportation Institute, Texas A & M University System, 2000.

[26] TIAN Z, URBANIK T, GIBBY R. Application of diamond interchange control strategies at closely spaced intersections[J]. Transportation Research Record, 2007, 2035(1): 32-39.

[27] TIAN Z, XU H, DE CAMP G, et al. Readily implementable signal phasing schemes for diverging diamond interchanges (No. 15- 0723) [C]. Transportation Research Board 94th Annual Meeting. Washington, DC: Transportation Research Board, 2015.

[28] GORDON R L. Traffic signal retiming practices in the United States (NCHRP Synthesis Report 419) [R]. Washington, DC: Transportation Research Board, 2010.

[29] Traffic Operation Division. Benefit cost evaluation of signal timing [R]. Columbus, Ohio: the Ohio Department of Transportation, 2021.

[30] WANG A, TIAN Z. A cost-effective approach to signal retiming through leveraging controller operational data (No. TRBAM- 21- 04004) [C]. Transportation Research Board 100th Annual Meeting. Washington, DC: Transportation Research Board, 2021

[31] DAY C M, BULLOCK D M, LI H, et al. Integrating traffic signal performance measures into agency business processes[R]. West Lafayette, Indiana: Purdue University, 2016.

[32] DAY C M, O'BRIEN P, STEVANOVIC A, et al. A methodology and case study: Evaluating the benefits and costs of implementing automated traffic signal performance (No. FHWA-HOP-20-003) [R]. Washington, DC: Federal Highway Administration, 2020.

[33] DAY C M, HASEMAN R, PREMACHANDRA H, et al. Evaluation of arterial signal coordination: Methodologies for visualizing high-resolution event data and measuring travel time [J]. Transportation Research Record, 2010, 2192(1): 37-49.

[34] DAY C M, BULLOCK D M. Optimization of traffic signal offsets with high-resolution event data[J]. Journal of Transportation Engineering, Part A: Systems, 2020, 146 (3): 04019076.

[35] FREIJE R S, HAINEN A M, STEVENS A L, et al. Graphical performance measures for practitioners to triage split failure trouble calls[J]. Transportation Research Record, 2014, 2439(1): 27-40.

[36] SCHUMAN R. INRIX U S. Signals scorecard[R]. Kirkland, Washington: INRIX Signal Analytics, 2021.

[37] TIAN Z, WANG A, XU H. Developing a quality of signal timing performance measure methodology for arterial operations-NDOT research report (607-17-803) [R]. Carson City, Nevada: The Nevada Department of Transportation, 2020.

[38] JIANG H, HU J, AN S, et al. Eco approaching at an isolated signalized intersection under partially connected and automated vehicles environment[J]. Transportation Research Part C: Emerging Technologies, 2017, 79: 290- 307.

[39] LI W, BAN X. Connected vehicles- based traffic signal timing optimization[J]. IEEE Transactions on Intelligent Transportation Systems, 2018, 20(12): 4354-4366.

[40] HU J, PARK B B, PARKANY A E. Transit signal priority with connected vehicle technology[J]. Transportation Research Record, 2014, 2418(1): 20-29.

[41] LIANG X J, GULER S I, GAYAH V V. An equitable traffic signal control scheme at isolated signalized intersections using connected vehicle technology[J]. Transportation Research Part C: Emerging Technologies, 2020, 110: 81-97.

[42] CESME B, FURTH P G. Self- organizing traffic signals using secondary extension and dynamic coordination[J]. Transportation Research Part C: Emerging Technologies, 2014, 48: 1-15.

[43] LITTLE J, KELSON M D, GARTNER N H. MAXBAND: A program for setting signals on arteries and triangular networks[J]. Transportation Research Record 795: TRB, National Research Council, Washington, 1981, 795(1): 40-46.

[44] STAMATIADIS C, GARTNER N H. MULTIBAND-96: A program for variable-bandwidth progression optimization of multiarterial traffic networks[J]. Transportation Research Record, 1996, 1554(1): 9-17.

[45] ZHANG C, XIE Y, GARTNER N H, et al. AM-band: An asymmetrical multi-band model for arterial traffic signal coordination[J]. Transportation Research Part C: Emerging Technologies, 2015, 58: 515-531.

[46] ARSAVA T, XIE Y, GARTNER N. OD-NETBAND: An approach for origin-destination based networkprogression band optimization[J]. Transportation Research Record, 2018, 2672(18): 58-70.

[47] MOLAN A M, HUMMER J E, KSAIBATI K. Introducing the super DDI as a promising alternative service interchange[J]. Transportation Research Record, 2019, 2673(3): 586-597.

[48] GETTMAN D, ABBAS M, LIU H, et al. Operation of traffic signal systems in oversaturated conditions[R]. Volume 2 Final Report. Washington, DC: The National Academies Press, 2014.