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基于路由节点的最优油耗路径规划模型
引用本文:刘琳,李春媛,陈彦虎,冯辉宗,华新泽.基于路由节点的最优油耗路径规划模型[J].重庆大学学报(自然科学版),2018,41(7):73-81.
作者姓名:刘琳  李春媛  陈彦虎  冯辉宗  华新泽
作者单位:重庆邮电大学 自动化学院,重庆,400065
基金项目:重庆市科委基础科学与前沿技术资助项目(CSTC2017JCYJAX0402),重庆市教委科学技术研究资助项目(KJ1600416),重庆邮电大学自然科学基金资助项目(A2013-27)
摘    要:交通路况瞬息万变,为能更准确地获取最优油耗路径规划,需实时获知道路车流量。基于车流量存在随机性和突发性的特点,提出基于路由节点的最优油耗路径规划模型。针对每个节点建立路阻路由表并依托车联网平台进行实时更新,车辆只需查找所在位置节点的路由表即可通过路阻值获取当前最优油耗路径。通过改变路阻值模拟车流量大小和变更目的点模拟不同的任务,分别仿真不同交通状况下完成同一任务和同一交通状况下完成不同任务2种情况,验证本算法的节能效果。结果显示拥堵情况越严重或者中转节点数量越多,本算法的节油效果越明显,可以实现经济环保出行。

关 键 词:智能交通  节能驾驶  路径规划  路由选择
收稿时间:2018/1/2 0:00:00

Research on path planning model of optimal fuel consumption based on routing nodes
LIU lin,LI Chunyuan,CHEN Yanhu,FENG Huizong and HUA Xinze.Research on path planning model of optimal fuel consumption based on routing nodes[J].Journal of Chongqing University(Natural Science Edition),2018,41(7):73-81.
Authors:LIU lin  LI Chunyuan  CHEN Yanhu  FENG Huizong and HUA Xinze
Institution:College of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, P. R. China,College of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, P. R. China,College of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, P. R. China,College of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, P. R. China and College of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, P. R. China
Abstract:Real-time response is essential for accurately getting path planning of optimal fuel consumption in rapidly changing traffic conditions. Based on the randomness and abruptness characteristics of traffic flow, this paper proposes an optimal fuel consumption path planning model in relation to routing nodes. Road impedance parameters routing tables of each node in transportation network are built and timely updated by sharing the traffic information from Internet of vehicle(IOV). Therefore, the path of optimal fuel consumption can be timely obtained by searching corresponding node''s road impedance parameters routing table. In order to testify the fuel-saving effect of this proposed model, simulations are carried out in different traffic conditions to complete the same task and in the same traffic condition to complete different tasks respectively by altering traffic flow and destinations. The results show that the more congestion or the more transfer nodes, the better fuel-saving efficiency, so that economical and environment friendly travel can be realized.
Keywords:intelligent transportation  eco-driving  path planning  routing
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