TY - GEN
T1 - VAN
T2 - 2010 IEEE 7th International Conference on Mobile Adhoc and Sensor Systems, MASS 2010
AU - Chen, Wenping
AU - Zhu, Sencun
AU - Li, Deying
PY - 2010
Y1 - 2010
N2 - Traffic congestion is a very serious problem in large cities. With the number of vehicles increasing rapidly, especially in cities whose economy is booming, the situation is getting even worse. In this paper, by leveraging the techniques of Vehicular Ad hoc Networks (VANETs) we present a dynamic navigation protocol called VAN for individual vehicles to find the shortest-time paths toward their given destinations. Specifically, a vehicle initiates a number of queries, which are routed by VANETs along different paths toward its destination. During query forwarding, the real-time road traffic information in each road segment is aggregated from multiple participating vehicles and returned to the source after the query reaches the destination. This information enables the source to calculate the shortest-time path. We also propose two forwarding optimization methods to reduce communication costs and an error handling mechanism to deal with abnormal circumstances. To evaluate its performance, we use the real traffic data of Beijing, including 2,308 road segments at two different times. Our simulation results demonstrate that our protocol, on average, could save around 30% driving time, compared to traveling along the shortest distance paths.
AB - Traffic congestion is a very serious problem in large cities. With the number of vehicles increasing rapidly, especially in cities whose economy is booming, the situation is getting even worse. In this paper, by leveraging the techniques of Vehicular Ad hoc Networks (VANETs) we present a dynamic navigation protocol called VAN for individual vehicles to find the shortest-time paths toward their given destinations. Specifically, a vehicle initiates a number of queries, which are routed by VANETs along different paths toward its destination. During query forwarding, the real-time road traffic information in each road segment is aggregated from multiple participating vehicles and returned to the source after the query reaches the destination. This information enables the source to calculate the shortest-time path. We also propose two forwarding optimization methods to reduce communication costs and an error handling mechanism to deal with abnormal circumstances. To evaluate its performance, we use the real traffic data of Beijing, including 2,308 road segments at two different times. Our simulation results demonstrate that our protocol, on average, could save around 30% driving time, compared to traveling along the shortest distance paths.
UR - http://www.scopus.com/inward/record.url?scp=78650979795&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78650979795&partnerID=8YFLogxK
U2 - 10.1109/MASS.2010.5663936
DO - 10.1109/MASS.2010.5663936
M3 - Conference contribution
AN - SCOPUS:78650979795
SN - 9781424474882
T3 - 2010 IEEE 7th International Conference on Mobile Adhoc and Sensor Systems, MASS 2010
SP - 442
EP - 451
BT - 2010 IEEE 7th International Conference on Mobile Adhoc and Sensor Systems, MASS 2010
Y2 - 8 November 2010 through 12 November 2010
ER -