Development of eco-routing guidance for connected electric vehicles in urban traffic systems

被引:2
|
作者
Chen, Jie [1 ,2 ]
Hu, Maobin [3 ]
Shi, Congling [4 ]
机构
[1] Anhui Normal Univ, Sch Comp & Informat, Wuhu 241003, Peoples R China
[2] Southeast Univ, Sch Math, Nanjing 210096, Peoples R China
[3] Univ Sci & Technol China, Sch Engn Sci, Hefei 230026, Peoples R China
[4] China Acad Safety Sci & Technol, Beijing Key Lab MFPTS, Beijing 100012, Peoples R China
基金
中国国家自然科学基金;
关键词
Energy consumption; Travel time; Connected electric vehicles; Route guidance; Eco-driving; CELLULAR-AUTOMATON MODEL; FUEL CONSUMPTION; OPTIMIZATION; CONGESTION; REDUCTION; EMISSION; HYBRID; COST;
D O I
10.1016/j.physa.2023.128718
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Despite extensive work on energy consumption of vehicles, the economic performance of vehicles in urban road networks urgently requires a route guidance strategy, which can optimize travel cost along the path. In this work, a set of cost minimization path was newly developed based on the operation information of connected electric vehicles including both energy consumption and travel time. At first, the energy consumption for vehicles was estimated using Comprehensive Power-based Energy consumption Model (CPEM). Then the real-time energy consumption and travel time of vehicles on each road were collected and sent to other vehicles to calculate the travel path. The traffic flow in city networks was investigated using cellular automaton simulation. Compared to previous static shortest path and dynamic quickest path, both electricity consumption and travel time can be reduced by adopting new path. The maximum energy and travel cost saving can achieve approximate to 4% in a wide range of traffic density and various networks. Combined with tolling scheme, the cost minimization paths can further improve traffic efficiency. With the rapid development of intelligent transportation system (ITS) technology, the cost minimization paths can be used to provide eco-driving route-choice suggestion for drivers.(c) 2023 Elsevier B.V. All rights reserved.
引用
收藏
页数:18
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