Proactive Vehicle Re-routing Strategies for Congestion Avoidance

Susan Juan Pan (1) , Mohammad A. Khan (1) , Iulian Sandu Popa (2, 3) , Karine Zeitouni (3) , Cristian Borcea (1)

1 NJIT - New Jersey Institute of Technology [Newark]
2 SMIS - Secured and Mobile Information Systems
3 PRISM - Parallélisme, Réseaux, Systèmes, Modélisation

Traffic congestion causes driver frustration and costs billions of dollars annually in lost time and fuel consumption. This paper presents three traffic re-routing strategies designed to be incorporated in a cost-effective and easily deployable vehicular traffic guidance system that reduces the effect of traffic congestions. This system collects real-time traffic data from vehicles and road-side sensors and computes proactive, individually-tailored re-routing guidance which is pushed to vehicles when signs of congestion are observed on their route. Extensive simulation results over two urban road networks show that all three strategies, namely multipath load balancing considering future vehicle positions (EBkSP), random multipath load balancing (RkSP), and dynamic shortest path (DSP), significantly decrease the average travel time. EBkSP is the best, with as much as 104% improvement compared to the "no re-routing" baseline. Additionally, it lowers with 34% the re-routing frequency compared to the other strategies. Finally, all strategies offer good improvements even when many drivers ignore the guidance or when the system adoption rate is relatively low.

Domaines: Base de données [cs.DB]

Susan Juan Pan, Mohammad A. Khan, Iulian Sandu Popa, Karine Zeitouni, Cristian Borcea. Proactive Vehicle Re-routing Strategies for Congestion Avoidance. Proceedings of the 8th IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS '12), May 2012, Hangzhou, China. pp.265-272, ⟨10.1109/DCOSS.2012.29⟩. ⟨hal-00768334⟩