Adaptive Quasi-Dynamic Traffic Light Control

We consider the traffic light control problem for a single intersection modeled as a stochastic hybrid system. We study a quasi-dynamic policy based on partial state information defined by detecting whether vehicle backlogs are above or below certain thresholds. The policy is parameterized by green and red cycle lengths as well as the road content thresholds. Using infinitesimal perturbation analysis, we derive online gradient estimators of a cost metric with respect to the controllable light cycles and threshold parameters and use these estimators to iteratively adjust all the controllable parameters through an online gradient-based algorithm so as to improve the overall system performance under various traffic conditions. The results obtained by applying this methodology to a simulated urban setting are also included.

[1]  Wilfred W. Recker,et al.  Stochastic adaptive control model for traffic signal systems , 2006 .

[2]  Nicholas V. Findler,et al.  On-line decisions about permitted/protected left-hand turns in distributed traffic signal control , 1997 .

[3]  Satish V. Ukkusuri,et al.  A robust transportation signal control problem accounting for traffic dynamics , 2010, Comput. Oper. Res..

[4]  Yafeng Yin,et al.  Robust optimal traffic signal timing , 2008 .

[5]  Nicholas V. Findler,et al.  Distributed Approach to Optimized Control of Street Traffic Signals , 1992 .

[6]  Christos G. Cassandras,et al.  Multi-intersection Traffic Light Control with blocking , 2015, Discret. Event Dyn. Syst..

[7]  Ana L. C. Bazzan,et al.  Opportunities for multiagent systems and multiagent reinforcement learning in traffic control , 2009, Autonomous Agents and Multi-Agent Systems.

[8]  P R Lowrie,et al.  The Sydney coordinated adaptive traffic system - principles, methodology, algorithms , 1982 .

[9]  Christos G. Cassandras,et al.  Infinitesimal Perturbation Analysis for Quasi-Dynamic Traffic Light Controllers , 2014, WODES.

[10]  Shalabh Bhatnagar,et al.  Reinforcement Learning With Function Approximation for Traffic Signal Control , 2011, IEEE Transactions on Intelligent Transportation Systems.

[11]  John D. C. Little,et al.  MAXBAND: A PROGRAM FOR SETTING SIGNALS ON ARTERIES AND TRIANGULAR NETWORKS , 1981 .

[12]  Michael C. Fu,et al.  ONLINE TRAFFIC LIGHT CONTROL THROUGH GRADIENT ESTIMATION USING STOCHASTIC FLUID MODELS , 2005 .

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

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

[15]  István Varga,et al.  Robust Control for Urban Road Traffic Networks , 2014, IEEE Transactions on Intelligent Transportation Systems.

[16]  Christos G. Cassandras,et al.  Multi-intersection traffic light control using infinitesimal perturbation analysis , 2012, WODES.

[17]  Yorai Wardi,et al.  A Unified Approach to Infinitesimal Perturbation Analysis in Stochastic Flow Models: The Single-Stage Case , 2010, IEEE Transactions on Automatic Control.

[18]  Jean-Loup Farges,et al.  Neuro-fuzzy techniques for traffic control , 1997 .

[19]  W WEN,et al.  A dynamic and automatic traffic light control expert system for solving the road congestion problem , 2008, Expert Syst. Appl..

[20]  D I Robertson,et al.  "TRANSYT" METHOD FOR AREA TRAFFIC CONTROL , 1969 .

[21]  Ozan K. Tonguz,et al.  Implementing virtual traffic lights with partial penetration: a game-theoretic approach , 2014, IEEE Communications Magazine.

[22]  Arne Koopman,et al.  Intelligent Traffic Light Control , 2004 .

[23]  Zhiyong Liu,et al.  Urban Traffic Signal Timing Optimization Based on Multi-layer Chaos Neural Networks Involving Feedback , 2005, ICNC.

[24]  James C. Spall,et al.  TRAFFIC-RESPONSIVE SIGNAL TIMING FOR SYSTEM-WIDE TRAFFIC CONTROL , 1997 .

[25]  Christos G. Cassandras,et al.  Traffic light control using Infinitesimal Perturbation Analysis , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

[26]  C. P. Pappis,et al.  A Fuzzy Logic Controller for a Trafc Junction , 1977, IEEE Transactions on Systems, Man, and Cybernetics.

[27]  E. Mamdani,et al.  FUZZY LOGIC CONTROLLER FOR A TRAFFIC JUNCTION , 1977 .

[28]  Wann-Ming Wey,et al.  Model formulation and solution algorithm of traffic signal control in an urban network , 2000 .

[29]  Christos G. Cassandras,et al.  Perturbation analysis of stochastic hybrid systems and applications to resource contention games , 2011 .

[30]  Christos G. Cassandras,et al.  Introduction to Discrete Event Systems , 1999, The Kluwer International Series on Discrete Event Dynamic Systems.

[31]  Wu Tie.  Reduced-order rolling horizon optimization of traffic control based on ant algorithm , 2005 .

[32]  Zhiyong Liu,et al.  A Survey of Intelligence Methods in Urban Traffic Signal Control , 2007 .

[33]  Daniel Vanderpooten,et al.  Multiobjective and multimodal adaptive traffic light control on single junctions , 2011, 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[34]  Stéphane Lafortune,et al.  A decentralized scheme for real-time optimization of traffic signals , 1996, Proceeding of the 1996 IEEE International Conference on Control Applications IEEE International Conference on Control Applications held together with IEEE International Symposium on Intelligent Contro.

[35]  Jun-min Liu.  Chaos particle swarm optimization algorithm: Chaos particle swarm optimization algorithm , 2008 .

[36]  Christos G. Cassandras,et al.  Perturbation Analysis and Optimization of Stochastic Hybrid Systems , 2010, Eur. J. Control.

[37]  Christos G. Cassandras,et al.  Quasi-dynamic traffic light control for a single intersection , 2013, 52nd IEEE Conference on Decision and Control.

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

[39]  Nicholas J. Garber,et al.  Traffic and Highway Engineering , 1988 .

[40]  Yangzhou Chen,et al.  Traffic light control method for a single intersection based on hybrid systems , 2003, Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems.

[41]  Baher Abdulhai,et al.  Reinforcement learning for true adaptive traffic signal control , 2003 .

[42]  Michael C. Fu,et al.  Application of perturbation analysis to traffic light signal timing , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[43]  Hannes Hartenstein,et al.  Inter-vehicle communication: Quo vadis , 2014, IEEE Communications Magazine.

[44]  Sung-Joo Lee,et al.  A Traffic Light Controlling FLC Considering the Traffic Congestion , 2002, AFSS.

[45]  Christos G. Cassandras,et al.  Event-Driven Control and Optimization in Hybrid Systems , 2018 .

[46]  William Casey Howell,et al.  Simulation optimization of traffic light signal timings via perturbation analysis , 2006 .

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

[48]  B. De Schutter.  Optimal traffic light control for a single intersection , 1999 .

[49]  I Alvarez,et al.  Game theory applied to urban traffic control problem , 2010, ICCAS 2010.

[50]  Christos G. Cassandras,et al.  Perturbation analysis for online control and optimization of stochastic fluid models , 2002, IEEE Trans. Autom. Control..