Connected Eco-driving for Urban Corridors

被引:1
|
作者
Wang, Xinpeng [1 ]
Zheng, Han [1 ]
Ahn, Kukhyun [2 ]
Zhang, Xiaowu [2 ]
Deshpande, Shreshta Rajakumar [2 ]
Soto, Ciro [2 ]
Peng, Huei [1 ]
机构
[1] Univ Michigan, Dept Mech Engn, Ann Arbor, MI 48109 USA
[2] Ford Motor Co, Dearborn, MI 48126 USA
来源
IFAC PAPERSONLINE | 2023年 / 56卷 / 03期
关键词
Eco-driving; Model Predictive Control; Connected Automated Vehicles; VEHICLE;
D O I
10.1016/j.ifacol.2023.12.036
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this work, we develop an eco-driving algorithm for Connected and Automated Vehicles (CAVs) to reduce their energy consumption for urban corridor scenarios. The proposed algorithm considers the uncertainty from both the adaptive traffic signals and the surrounding traffic, thereby increasing its suitability for real-world deployment. In this hierarchical approach, the higher level makes global passing decisions and computes speed targets for further intersections, while the lower level generates smooth and safe speed trajectories. The performance of the algorithm is then demonstrated for an electric vehicle model through extensive (traffic) simulations. Across these experiments, 8-12% energy savings is observed compared to the baseline algorithm. Copyright (c) 2023 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)
引用
收藏
页码:271 / 276
页数:6
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