[1]陈浩,庄伟超,殷国栋,等.网联电动汽车信号灯控路口经济性驾驶策略[J].东南大学学报(自然科学版),2021,(1):178-186.[doi:10.3969/j.issn.1001-0505.2021.01.024]
　Chen Hao,Zhuang Weichao,Yin Guodong,et al.Eco-driving control strategy of connected electric vehicle at signalized intersection[J].Journal of Southeast University (Natural Science Edition),2021,(1):178-186.[doi:10.3969/j.issn.1001-0505.2021.01.024]
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网联电动汽车信号灯控路口经济性驾驶策略()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
期数:
2021年第1期
页码:
178-186
栏目:
交通运输工程
出版日期:
2021-01-20

文章信息/Info

Title:
Eco-driving control strategy of connected electric vehicle at signalized intersection
作者:
陈浩; 庄伟超; 殷国栋; 董昊轩
东南大学机械工程学院, 南京 210096
Author(s):
Chen Hao;  Zhuang Weichao;  Yin Guodong;  Dong Haoxuan
School of Mechanical Engineering, Southeast University, Nanjing 210096, China
关键词:
经济性驾驶;  智能网联汽车;  信号灯控路口;  滚动优化;  庞特里亚金极小值原理
Keywords:
eco-driving;  connected and autonomous vehicle(CAV);  signalized intersection;  receding optimization;  Pontryagin’s minimum principle
分类号:
U461
DOI:
10.3969/j.issn.1001-0505.2021.01.024
摘要:
针对智能网联电动汽车在信号灯控路口的经济性驾驶问题,提出一种基于最优控制的经济性驾驶车速优化策略.首先,构建包含信号灯、车速限制等约束,以能量消耗最小化为目标的信号灯控路口车辆速度优化问题;然后,利用庞特里亚金极小值原理解析求解最优控制率;考虑到动态交通场景中车辆对未来交通信息的预测能力有限、信号灯约束条件多变等特点,提出了一种双层滚动距离域车速优化策略,将信号灯控路口经济性驾驶问题转化为分段最优控制问题,得到分段最优速度轨迹.仿真结果表明:在有限预测能力和无限预测能力2种情况下,所提出的经济性驾驶车速优化策略较加速—匀速—制动策略分别有9.2%和10.3%的能量节省;随着预测距离和信号灯控路口通行速度的增大,在提高通行效率的同时,能量节省效率进一步提高.
Abstract:
Aiming at the eco-driving problem of connected and autonomous electric vehicle(EV)at signalized intersection, an eco-driving speed optimization method based on optimal control was proposed. First, a vehicle speed optimization problem at signalized intersection was constructed, including traffic lights and speed limitation and other constraints, with the goal of minimizing the energy consumption. Then, the optimal control rate was solved by using Pontryagin’s minimum principle. Finally, considering the characteristics of vehicles in the dynamic traffic scenes, such as the limited ability to predict the future traffic information and the variable traffic lights constraints, a double-layer receding distance horizon velocity optimization control strategy was proposed by transforming the eco-driving problem at the signalized intersection into the segmented optimal control problem, thus obtaining the segmented optimal speed trajectory. Simulation results show that under the two conditions of finite and infinite predictive ability, the eco-driving optimization strategy has 9.2% and 10.3% energy savings compared with the accelerate-constant-brake(ACB)strategy, respectively. With the increase of the predicted distance and the speed at the signalized intersection, while improving the traffic efficiency, the energy saving efficiency is further improved.

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备注/Memo

备注/Memo:
收稿日期: 2020-07-27.
作者简介: 陈浩(1995—),男,硕士生;殷国栋(联系人),男,博士,教授,博士生导师,ygd@seu.edu.cn.
基金项目: 国家重点研发计划资助项目(2016YFD0700905)、江苏省重点研发计划资助项目(BE2019004).
引用本文: 陈浩,庄伟超,殷国栋,等.网联电动汽车信号灯控路口经济性驾驶策略[J].东南大学学报(自然科学版),2021,51(1):178-186. DOI:10.3969/j.issn.1001-0505.2021.01.024.
更新日期/Last Update: 2021-01-20