TY - GEN
T1 - A Novel Dynamic En-Route Decision Real-Time Route Guidance Scheme in Intelligent Transportation Systems
AU - Lin, Jie
AU - Yu, Wei
AU - Yang, Xinyu
AU - Yang, Qingyu
AU - Fu, Xinwen
AU - Zhao, Wei
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/7/22
Y1 - 2015/7/22
N2 - In an intelligence transportation system (ITS), to increase traffic efficiency, a number of dynamic route guidance schemes have been designed to assist drivers in determining the optimal route for their travels. In order to determine optimal routes, it is critical to effectively predict the traffic condition of roads along the guided routes based on real-time traffic information to mitigate traffic congestion and improve traffic efficiency. In this paper, we propose a Dynamic En-route Decision real-time Route guidance (DEDR) scheme to effectively mitigate road congestion caused by the sudden increase of vehicles and reduce travel time. Particularly, DEDR considers real-time traffic information generation and transmission. Based on the shared traffic information, DEDR introduces Trust Probability to predict traffic conditions and dynamically en-route determine alternative optimal routes. In addition, DEDR considers multiple metrics to comprehensively assess traffic conditions and drivers can determine optimal route with individual preference of these metrics during travel. DEDR also considers effects of external factors (e.g., Bad weather, incidents, etc.) on traffic conditions. Through a combination of extensive theoretical analysis and simulation experiments, our data shows that DEDR can greatly increase the efficiency of an ITS in terms of great time efficiency and balancing efficiency in comparison with existing schemes.
AB - In an intelligence transportation system (ITS), to increase traffic efficiency, a number of dynamic route guidance schemes have been designed to assist drivers in determining the optimal route for their travels. In order to determine optimal routes, it is critical to effectively predict the traffic condition of roads along the guided routes based on real-time traffic information to mitigate traffic congestion and improve traffic efficiency. In this paper, we propose a Dynamic En-route Decision real-time Route guidance (DEDR) scheme to effectively mitigate road congestion caused by the sudden increase of vehicles and reduce travel time. Particularly, DEDR considers real-time traffic information generation and transmission. Based on the shared traffic information, DEDR introduces Trust Probability to predict traffic conditions and dynamically en-route determine alternative optimal routes. In addition, DEDR considers multiple metrics to comprehensively assess traffic conditions and drivers can determine optimal route with individual preference of these metrics during travel. DEDR also considers effects of external factors (e.g., Bad weather, incidents, etc.) on traffic conditions. Through a combination of extensive theoretical analysis and simulation experiments, our data shows that DEDR can greatly increase the efficiency of an ITS in terms of great time efficiency and balancing efficiency in comparison with existing schemes.
KW - Dynamic route Guidance Systems
KW - En-route guided route decision
KW - Intelligence transportation systems
KW - Real-time traffic information
UR - https://www.scopus.com/pages/publications/84944318781
U2 - 10.1109/ICDCS.2015.15
DO - 10.1109/ICDCS.2015.15
M3 - 会议稿件
AN - SCOPUS:84944318781
T3 - Proceedings - International Conference on Distributed Computing Systems
SP - 61
EP - 72
BT - Proceedings - 2015 IEEE 35th International Conference on Distributed Computing Systems, ICDCS 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 35th IEEE International Conference on Distributed Computing Systems, ICDCS 2015
Y2 - 29 June 2015 through 2 July 2015
ER -
