Flexible Eco-cruising Strategy for Connected and Automated Vehicles with Efficient Driving Lane Planning and Speed Optimization
Jun 1, 2023·,,,,,,·
0 min read
Haoxuan Dong
Qun Wang
Weichao Zhuang
Guodong Yin
Kun Gao
Zhaojian Li
Ziyou Song
Abstract
We present a flexible eco-cruising strategy for connected and automated vehicles that jointly optimizes lane planning and speed trajectory. The hierarchical framework decouples discrete lane decisions from continuous speed optimization and leverages V2X information for anticipatory control, delivering significant energy savings on multi-lane highways under realistic traffic conditions.
Type
Publication
IEEE Transactions on Transportation Electrification
Authors
Postdoctoral Fellow
Qun Wang is a Postdoctoral Fellow at the AIMS Lab, Hong Kong Polytechnic
University, working with Assistant Professor Hailong Huang. His research
focuses on energy-saving optimization and safety-guaranteed control of
autonomous electrified vehicles, with emphasis on reinforcement
learning for eco-driving, human driving behavior modeling, and
multi-agent car-following control. He has published over 10 papers in
leading journals including IEEE Transactions on ITS, TTE, TCST and Energy.