TY - GEN
T1 - Proactive vehicle re-routing strategies for congestion avoidance
AU - Pan, Juan
AU - Khan, Mohammad A.
AU - Popa, Iulian Sandu
AU - Zeitouni, Karine
AU - Borcea, Cristian
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84864234926&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84864234926&partnerID=8YFLogxK
U2 - 10.1109/DCOSS.2012.29
DO - 10.1109/DCOSS.2012.29
M3 - Conference contribution
AN - SCOPUS:84864234926
SN - 9780769547077
T3 - Proceedings - IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2012
SP - 265
EP - 272
BT - Proceedings - IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2012
T2 - 8th IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2012
Y2 - 16 May 2012 through 18 May 2012
ER -