Influence of inter-vehicle communication on peak hour traffic flow

Mixed traffic flow consisting of vehicles equipped with wireless inter-vehicle communication devices and non-equipped vehicles is analyzed using bidirectionally coupled network traffic and road traffic simulators in a peak hour scenario. For equipped vehicles a strategy to stabilize traffic flow and to reduce travel time is proposed. The strategy comprises rules to determine both how and when to change driving behavior. Vehicles that detect perturbations downstream try to keep a larger gap to their predecessor by which they aim to compensate traffic inhomogeneities. Improvement of traffic flow was observed even for a ratio of equipped vehicles as low as five percent.

[1]  S.P. Fekete,et al.  Shawn: The fast, highly customizable sensor network simulator , 2007, 2007 Fourth International Conference on Networked Sensing Systems.

[2]  B. Kerner THE PHYSICS OF TRAFFIC , 1999 .

[3]  D. Clawin,et al.  Wireless LAN performance under varied stress conditions in vehicular traffic scenarios , 2002, Proceedings IEEE 56th Vehicular Technology Conference.

[4]  S.L. Klenov,et al.  Testbed for wireless vehicle communication: a simulation approach based on three-phase traffic theory , 2008, 2008 IEEE Intelligent Vehicles Symposium.

[5]  Robbert van Renesse,et al.  JiST: an efficient approach to simulation using virtual machines , 2005, Softw. Pract. Exp..

[6]  Dirk Helbing,et al.  Jam-Avoiding Adaptive Cruise Control (ACC) and its Impact on Traffic Dynamics , 2005 .

[7]  W. Knospe,et al.  A realistic two-lane traffic model for highway traffic , 2002, cond-mat/0203346.

[8]  A. Schadschneider,et al.  Empirical test for cellular automaton models of traffic flow. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[9]  Ziyou Gao,et al.  Properties of Cellular Automaton Model for On-ramp System , 2010, ACRI.

[10]  Michael Schreckenberg,et al.  A cellular automaton model for freeway traffic , 1992 .

[11]  Robbert van Renesse,et al.  Scalable Wireless Ad Hoc Network Simulation , 2005, Handbook on Theoretical and Algorithmic Aspects of Sensor, Ad Hoc Wireless, and Peer-to-Peer Networks.

[12]  Tao Zhou,et al.  Advanced information feedback in intelligent traffic systems. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[13]  Zygmunt J. Haas,et al.  An Efficient, Unifying Approach to Simulation Using Virtual Machines , 2004 .

[14]  M.C. Weigle,et al.  ASH: Application-aware SWANS with highway mobility , 2008, IEEE INFOCOM Workshops 2008.

[15]  Ahmed Al-Kaisy,et al.  Freeway Quality of Service: What Really Matters to Drivers and Passengers? , 2001 .

[16]  Arne Kesting,et al.  Microscopic Modeling of Human and Automated Driving: Towards Traffic-Adaptive Cruise Control , 2008 .

[17]  Marco Fiore Vehicular Mobility Models , 2009 .