LICP: A look-ahead intersection control policy with intelligent vehicles

We consider a practical application of intelligent vehicles for intersection traffic control. Specially, we study the intersection traffic control problem using Reservation-based Intersection Traffic Control System, which utilizes the information exchange between intelligent vehicles and management agents around the intersections to direct traffic, instead of traffic lights. We focus on how to design an effective passing permission (PP) allocation strategy for this system. In this work, with an observation that will cause this system to be inefficient, we propose a novel look-ahead passing permission allocation strategy (LICP) for intersection traffic control. The large-scale testing results show that LICP can make nearly 25% performance improvement on average intersection delay than the previous First Come, First Serve method (FCFS).

[1]  N. Nishizuka,et al.  Fuzzy Logic Phase Controller for Traffic Junctions in the One-way Arterial Road , 1984 .

[2]  Peter Stone,et al.  Multiagent traffic management: an improved intersection control mechanism , 2005, AAMAS '05.

[3]  Dean A. Pomerleau,et al.  Neural Network Perception for Mobile Robot Guidance , 1993 .

[4]  Lily Elefteriadou,et al.  Capability-Enhanced Microscopic Simulation With Real-Time Traffic Signal Control , 2007, IEEE Transactions on Intelligent Transportation Systems.

[5]  Xu Li,et al.  Performance Evaluation of Vehicle-Based Mobile Sensor Networks for Traffic Monitoring , 2009, IEEE Transactions on Vehicular Technology.

[6]  Minglu Li,et al.  A practical map-matching algorithm for GPS-based vehicular networks in Shanghai urban area , 2007 .

[7]  Jussi Suomela,et al.  Positioning an autonomous off-road vehicle by using fused DGPS and inertial navigation , 1996, Int. J. Syst. Sci..

[8]  Jingyan Song,et al.  Control Mechanism Analysis of Small-Agent Networks Using a Distinguished Node Model for Urban Traffic Controls , 2008, IEEE Transactions on Automation Science and Engineering.

[9]  Peter Stone,et al.  Multiagent traffic management: a reservation-based intersection control mechanism , 2004, Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 2004. AAMAS 2004..

[10]  Patrick Brézillon,et al.  Lecture Notes in Artificial Intelligence , 1999 .

[11]  Peter Stone,et al.  Multiagent Traffic Management: Opportunities for Multiagent Learning , 2005, LAMAS.

[12]  Peter Stone,et al.  A Multiagent Approach to Autonomous Intersection Management , 2008, J. Artif. Intell. Res..

[13]  Xu Li,et al.  Traffic Data Processing in Vehicular Sensor Networks , 2008, 2008 Proceedings of 17th International Conference on Computer Communications and Networks.

[14]  Pat Langley,et al.  An adaptive interactive agent for route advice , 1999, AGENTS '99.

[15]  Li Shui-you Artificial neural networks self-tuning predictive control for traffic signals , 2003 .