A Simulation-Based Framework for the Cooperation of VMS Travel Guidance and Traffic Signal Control

Nowadays, both travel guidance systems and traffic signal control systems are quite common for urban traffic management. In order to achieve collaborative effect, different models had been proposed in the last two decades. In recent years, with the development of variable message sign (VMS) technology, more and more VMS panels are installed on major arterials to provide highly visible and concise graphs or text messages to drivers, especially in developing countries. To discover drivers’ responses to VMS, we establish a drivers’ en route diversion model according to a stated-preference survey. Basically, we proposed a cooperative mechanism and systematic framework of VMS travel guidance and major arterials signal operations. And then a two-stage nested optimization problem is formulated. To solve this optimization problem, a simulation-based optimization method is adopted to optimize the cooperative strategies with TRANSIMS. The proposed method is applied to the real network of Tianjin City comprising of 30 nodes and 46 links. Simulations show that this new method could well improve the network condition by 26.3%. And analysis reveals that GA with nested dynamic programming is an effective technique to solve the optimization problem.

[1]  Jaeyoung Kwak,et al.  Calibration and validation of TRANSIMS microsimulator for an urban arterial network , 2011 .

[2]  Mariëtte Kraan,et al.  EVALUATING NETWORK WIDE EFFECTS OF VMS’S IN THE NETHERLANDS , 2005 .

[3]  Aric Hagberg,et al.  Exploring Network Structure, Dynamics, and Function using NetworkX , 2008, Proceedings of the Python in Science Conference.

[4]  Pitu B. Mirchandani,et al.  A REAL-TIME TRAFFIC SIGNAL CONTROL SYSTEM: ARCHITECTURE, ALGORITHMS, AND ANALYSIS , 2001 .

[5]  Hani S. Mahmassani,et al.  System Optimal Time-Dependent Path Assignment and Signal Timing in Traffic Network , 1998 .

[6]  Liu Xue-lian.  Traffic control and VMS collaborative technique in sudden disaster , 2012 .

[7]  M. E. Williams,et al.  TRANSIMS: TRANSPORTATION ANALYSIS AND SIMULATION SYSTEM , 1995 .

[8]  Nick Hounsell,et al.  Review of urban traffic management and the impacts of new vehicle technologies , 2009 .

[9]  Angelica Duran,et al.  An introduction , 1967, Rome Is Burning.

[10]  Mike Smith,et al.  A model for the dynamic system optimum traffic assignment problem , 1995 .

[11]  Jorge Ramos,et al.  Content of Variable Message Signs and On-Line Driver Behavior , 2000 .

[12]  P. E. Firmin,et al.  Perception of VMS effectiveness: a British and Canadian perspective , 2004 .

[13]  Nathan H. Gartner,et al.  Integration of Dynamic Traffic Assignment with Real-Time Traffic Adaptive Control System , 1998 .

[14]  Melanie Mitchell,et al.  An introduction to genetic algorithms , 1996 .

[15]  Mike Smith,et al.  The existence, uniqueness and stability of traffic equilibria , 1979 .

[16]  Mike J. Smith.  The existence and calculation of traffic equilibria , 1983 .

[17]  A. Caroline Sutandi.  Evaluation of The Impacts of VMS on Traffic Performance Measures in An Urban Area in Indonesia , 2008 .

[18]  R E Allsop.  SOME POSSIBILITIES FOR USING TRAFFIC CONTROL TO INFLUENCE TRIP DISTRIBUTION AND ROUTE CHOICE , 1974 .

[19]  Wang,et al.  Review of road traffic control strategies , 2003, Proceedings of the IEEE.

[20]  Nathan H. Gartner,et al.  Dynamic Programming Approach for Arterial Signal Optimization , 2013 .

[21]  Sharif H. Melouk,et al.  A simulation optimization-based decision support tool for mitigating traffic congestion , 2011, J. Oper. Res. Soc..

[22]  Michel Bierlaire,et al.  Mitigating network congestion: analytical models, optimization methods and their applications , 2011 .

[23]  Christian S. Perone,et al.  Pyevolve: a Python open-source framework for genetic algorithms , 2009, SEVO.

[24]  Bas Tutert,et al.  Evaluating Networkwide Effects of Variable Message Signs in the Netherlands , 1999 .

[25]  Carolina Osorio,et al.  Mitigating Network Congestion: Analytical Models, Optimization Methods and their Applications , 2010 .