Field Testing the Effectiveness of Adaptive Traffic Control for Arterial Signal Management

The report describes the methodology and findings of the evaluation of adaptive signal control in a real-life corridor. The study section was a five mile section of the Pacific Coast Highway in Los Angeles with nine signalized intersections operating under adaptive control using the Los Angeles DOT ATCS (adaptive traffic control system). Optimal fixed time time-of-day plans were developed and implemented at the test site. The performance of the ATCS system and the fixed-time plans was evaluated using extensive field data on travel times and queue lengths collected through probe vehicles, Bluetooth sensors and video cameras. The findings indicate that ATCS performed better than the fixed-time plans during the time of peak direction in the arterial through traffic. All strategies had similar performance in the midday time period. A number of limitations were identified for ATCS under oversaturated conditions, including under-allocating green time to the critical approach at the bottleneck intersection, allocating more green time than necessary at intersections upstream of the bottleneck, and inappropriate setting offsets at intersections downstream of the bottleneck resulting in additional delays for traffic departing the bottleneck and creating the potential for queue spillbacks to the bottleneck itself. Possible remedial actions for these issues are discussed.

[1]  Larry E. Owen,et al.  Evaluating adaptive signal control using CORSIM , 1998, 1998 Winter Simulation Conference. Proceedings (Cat. No.98CH36274).

[2]  Pitu B. Mirchandani,et al.  AN APPROACH TOWARDS THE INTEGRATION OF BUS PRIORITY AND TRAFFIC ADAPTIVE SIGNAL CONTROL , 2001 .

[3]  G N Holmes,et al.  A STUDY TO IDENTIFY THE FREQUENCY AND IMPORTANCE OF INCIDENTS IN CAUSING CONGESTION , 1992 .

[4]  Hani S. Mahmassani,et al.  Dynamic origin-destination demand estimation using automatic vehicle identification data , 2006, IEEE Transactions on Intelligent Transportation Systems.

[5]  S Skehan.  ADAPTIVE TRAFFIC CONTROL SYSTEM , 1996 .

[6]  M. Papageorgiou,et al.  OPTIMAL SIGNAL CONTROL OF URBAN TRAFFIC NETWORKS , 1992 .

[7]  Paolo Dell'Olmo,et al.  REALBAND : an approach for real-time coordination of traffic flows on networks , 1995 .

[8]  C. Peck,et al.  The application of SCOOT in developing countries , 1990 .

[9]  G. Davis,et al.  Recursive estimation of origin-destination matrices from input/output counts , 1987 .

[10]  Pravin Varaiya,et al.  Real-Time Estimation of Origin-Destination Matrices with Partial Trajectories from Electronic Toll Collection Tag Data , 2005 .

[11]  E. Cascetta.  Estimation of trip matrices from traffic counts and survey data: A generalized least squares estimator , 1984 .

[12]  H. Spiess.  A MAXIMUM LIKELIHOOD MODEL FOR ESTIMATING ORIGIN-DESTINATION MATRICES , 1987 .

[13]  R. D. Bretherton,et al.  AGEING OF FIXED-TIME TRAFFIC SIGNAL PLANS , 1986 .

[14]  Hai Yang.  Heuristic algorithms for the bilevel origin-destination matrix estimation problem , 1995 .

[15]  D I Robertson,et al.  TRANSYT: A TRAFFIC NETWORK STUDY TOOL , 1969 .

[16]  R J Powell.  SCOOT IN SOUTHAMPTON , 1985 .

[17]  Pitu B. Mirchandani,et al.  HIERARCHICAL FRAMEWORK FOR REAL-TIME TRAFFIC CONTROL , 1992 .

[18]  R. D. Bretherton,et al.  Intelligent bus priority in London: Evaluation and exploitation in INCOME , 1999 .

[19]  M. Bell.  THE ESTIMATION OF ORIGIN-DESTINATION MATRICES BY CONSTRAINED GENERALISED LEAST SQUARES , 1991 .

[20]  Suvrajeet Sen,et al.  Controlled Optimization of Phases at an Intersection , 1997, Transp. Sci..

[21]  Alexander Skabardonis,et al.  Determining Capacity Benefits of Real-Time Signal Control at an Intersection , 1999 .

[22]  Bart De Moor,et al.  Dynamic identification of origin–destination matrices in the presence of incomplete observations , 2002 .

[23]  William C Taylor,et al.  Incident management under SCAT adaptive control system : FAST-TRAC phase III deliverable. #11, Final report on incident management under SCATS adaptive control system , 1998 .

[24]  R. Sivanandan,et al.  A linear programming approach for synthesizing origin-destination trip tables from link traffic volumes , 1994 .

[25]  Darcy M. Bullock,et al.  Overview and Performance Evaluation of ACS Lite: Low-Cost Adaptive Signal Control System , 2008 .

[26]  M. Maher.  INFERENCES ON TRIP MATRICES FROM OBSERVATIONS ON LINK VOLUMES: A BAYESIAN STATISTICAL APPROACH , 1983 .

[27]  J Y Luk,et al.  TRANSYT: traffic network study tool , 1990 .

[28]  M. Baucus.  Transportation Research Board , 1982 .

[29]  G T Bowen.  BUS PRIORITY IN SCOOT , 1997 .

[30]  A Skabardonis.  EVALUATION OF THE FUEL-EFFICIENT TRAFFIC SIGNAL MANAGEMENT (FETSIM) PROGRAM: 1983-1993. FINAL REPORT , 1994 .

[31]  Jifeng Wu,et al.  A real-time origin-destination matrix updating algorithm for on-line applications , 1997 .

[32]  Kenneth L Head,et al.  EVENT-BASED SHORT-TERM TRAFFIC FLOW PREDICTION MODEL , 1995 .

[33]  V F Hurdle,et al.  DYNAMIC IDENTIFICATION OF FLOWS FROM TRAFFIC COUNTS AT COMPLEX INTERSECTIONS , 1983 .

[34]  R. D. Bretherton,et al.  Latest developments in SCOOT - version 3.1 , 1996 .

[35]  Louahdi Khoudour,et al.  TRAFFIC MANAGEMENT. RTS ENGLISH ISSUE NUMBER 6. PRODYN: THREE YEARS OF TRIALS IN THE ZELT EXPERIMENTAL ZONE , 1991 .

[36]  Henk J van Zuylen,et al.  The most likely trip matrix estimated from traffic counts , 1980 .

[37]  P B Hunt,et al.  THE EFFECT OF AN INCIDENT IN A SCOOT SYSTEM - IN SIMULATION AND ON-STREET , 1985 .

[38]  Sam R. Thangiah,et al.  Computer-aided Scheduling of Public Transport , 2003, J. Sched..

[39]  Dave Bretherton.  Current Developments in SCOOT: Version 3 , 1996 .

[40]  L Willumsen,et al.  SCOOT IN SANTIAGO , 1995 .

[41]  Henk Taale,et al.  The second assessment of the SCOOT system in Nijmegen , 1998 .

[42]  William H. K. Lam,et al.  Estimation of an origin-destination matrix with random link choice proportions : a statistical approach , 1996 .

[43]  W. Taylor,et al.  Incident Management, FAST-TRAC Phase IIB Deliverables , 1999 .

[44]  Aleksandar Stevanovic,et al.  Adaptive Traffic Control Systems: Domestic and Foreign State of Practice , 2010 .

[45]  Laurence R. Rilett,et al.  Population Origin-Destination Estimation Using Automatic Vehicle Identification and Volume Data , 2005 .

[46]  Martin Fellendorf.  PUBLIC TRANSPORT PRIORITY WITHIN SCATS - A SIMULATION CASE STUDY IN DUBLIN , 1997 .

[47]  Henry X. Liu,et al.  Development of the Capability-Enhanced PARAMICS Simulation Environment , 2002 .

[48]  Alexander Skabardonis,et al.  Detecting Errors and Imputing Missing Data for Single-Loop Surveillance Systems , 2003 .

[49]  D I Robertson,et al.  RESEARCH ON THE TRANSYT AND SCOOT METHODS OF SIGNAL COORDINATION , 1986 .

[50]  R D Bretherton,et al.  SCOOT-a Traffic Responsive Method of Coordinating Signals , 1981 .

[51]  K. Larry Head,et al.  THE RHODES PROTOTYPE : A DESCRIPTION AND SOME RESULTS , 1998 .

[52]  D J Cook,et al.  TRAFFIC CONTROL STUDIES IN LONDON: SCOOT AND BUS DETECTION , 1985 .

[53]  R D Bretherton,et al.  THE SCOOT ON-LINE TRAFFIC SIGNAL OPTIMISATION TECHNIQUE , 1982 .

[54]  Paolo Dell'Olmo,et al.  A Model for Real-Time Traffic Coordination Using Simulation Based Optimization , 1996 .

[55]  Peter T. Martin,et al.  SCOOT Real-Time Adaptive Control in a CORSIM Simulation Environment , 2000 .

[56]  Pitu B. Mirchandani,et al.  An Approach Towards the Integration of Bus Priority, Traffic Adaptive Signal Control, and Bus Information/Scheduling Systems , 2001 .

[57]  Bart De Moor,et al.  RECURSIVE ESTIMATION BASED ON THE EQUALITY-CONSTRAINED OPTIMIZATION FOR INTERSECTION ORIGIN-DESTINATION MATRICES , 1999 .

[58]  Nathan H. Gartner,et al.  OPAC: A DEMAND-RESPONSIVE STRATEGY FOR TRAFFIC SIGNAL CONTROL , 1983 .

[59]  Peter T. Martin,et al.  SCOOT--AN UPDATE , 1995 .

[60]  R. D. Bretherton,et al.  Recent enhancements to SCOOT-SCOOT Version 2.4 , 1990 .