TY - GEN
T1 - Data-driven traffic flow analysis for vehicular communications
AU - Wang, Yang
AU - Huang, Liusheng
AU - Gu, Tianbo
AU - Wei, Hao
AU - Xing, Kai
AU - Zhang, Junshan
PY - 2014
Y1 - 2014
N2 - Due to high mobility and frequent disconnections in a vehicular network, reliable and efficient vehicular communication is very challenging. Previous studies focus on predicting the trajectories of single vehicles. Due to many random factors, however, there is little regularity in the movements of a single vehicle in an urban area, and this motivates us to take a holistic network perspective. With this insight, we model the time varying regularities of road traffic flows in road segments and intersections by mining statistic trajectories of all vehicles in the network. Based on these regularities and local real-time traffic information, we propose a new method to calculate the expected transfer delay from a current position to a given destination. We also propose a method to collect updated destination information. By combining the above two methods, we design a routing algorithm for vehicle-to-vehicle data transmission in vehicular networks, and then prove that it is a linear-time algorithm. Finally, we evaluate our algorithm by using information of real taxi vehicles. The results show that the performance of our algorithm is significantly better than other solutions in terms of packet delay.
AB - Due to high mobility and frequent disconnections in a vehicular network, reliable and efficient vehicular communication is very challenging. Previous studies focus on predicting the trajectories of single vehicles. Due to many random factors, however, there is little regularity in the movements of a single vehicle in an urban area, and this motivates us to take a holistic network perspective. With this insight, we model the time varying regularities of road traffic flows in road segments and intersections by mining statistic trajectories of all vehicles in the network. Based on these regularities and local real-time traffic information, we propose a new method to calculate the expected transfer delay from a current position to a given destination. We also propose a method to collect updated destination information. By combining the above two methods, we design a routing algorithm for vehicle-to-vehicle data transmission in vehicular networks, and then prove that it is a linear-time algorithm. Finally, we evaluate our algorithm by using information of real taxi vehicles. The results show that the performance of our algorithm is significantly better than other solutions in terms of packet delay.
UR - http://www.scopus.com/inward/record.url?scp=84904427731&partnerID=8YFLogxK
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U2 - 10.1109/INFOCOM.2014.6848138
DO - 10.1109/INFOCOM.2014.6848138
M3 - Conference contribution
AN - SCOPUS:84904427731
SN - 9781479933600
T3 - Proceedings - IEEE INFOCOM
SP - 1977
EP - 1985
BT - IEEE INFOCOM 2014 - IEEE Conference on Computer Communications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 33rd IEEE Conference on Computer Communications, IEEE INFOCOM 2014
Y2 - 27 April 2014 through 2 May 2014
ER -