Journal Article

Study on Speed Planning of Signalized Intersections with Autonomous Vehicles Considering Regenerative Braking

Li, Ning, Liu, Yang, Yang, Jiarao, Jiang, Junping, Hong, Feng, Ning, Xiaobin

2022

Overview

In order to reduce the energy consumption caused by the frequent braking of vehicles at signalized intersections, an optimized speed trajectory control method is proposed, based on braking energy recovery efficiency (BERE) in connection with an automated system for vehicle real-time interaction with roadside facilities and regional central control. Our objectives were as follows; firstly, to establish the simulation model of the hybrid energy regenerative braking system (HERBS) and to verify it by bench test. Secondly, to build up the genetic algorithm (GA) optimization model for the deceleration stopping of the HERBS. Then, to obtain signal light status and timing information to be the constraints; the BERE is to be the optimized objective, resulting in optimization for the speed trajectory under the deceleration stopping condition of a single signalized intersection. Finally, vehicle simulations in ADVISOR software are utilized to validate the optimization results. The results show that the BERE during deceleration stopping at a single signalized intersection after the speed trajectory optimization is 36.21% higher than that of inexperienced drivers, and 7.82% higher than that of experienced drivers.

• Publisher: MDPI AG
• Subject: Autonomous vehicles / Control algorithms / Control methods / Control theory / Deceleration / Energy consumption / Energy efficiency / Energy management / Energy recovery / Fuel cells / Genetic algorithms / Herbs / Hybrid systems / Internet / Intersections / Mathematical models / Optimization / Optimization models / Planning / Regenerative braking / Roadsides / Simulation / Simulation models / Trajectory control / Trajectory optimization