Alleviating Bunching by Platoon-Based Eco-Driving with Berth Allocation in Bus Corridors

2022-01-7090

12/22/2022

Features
Event
SAE 2022 Intelligent and Connected Vehicles Symposium
Authors Abstract
Content
Bus bunching usually occurs in high-frequency bus corridors with negative effects for the passengers and the service providers. In order to solve the problem of bus bunching, this work proposed a berth allocation scheme and a platoon-based eco-driving speed optimization model of intelligent connected bus platoon considering the deviation of the buses following the advisory curve and the fuel consumption. The model is based on the distance of interval between two adjacent stations in bus corridor, using IDM car-following model to control the safety distance between follower and leader in same bus platoon, and utilizing particle swarm algorithm to optimize the solution to obtain the optimal speed curve of leader, for the purpose of guiding platoons to smoothly move in the bus corridor to alleviate bunching. Three cases based on the scenario in Xiamen City, including two cases simulated in VISSIM and the last case simulated in MATLAB, are constructed for comparative simulation test to verify the effectiveness of the proposed model. The simulation results show that compared with existing bus operation case, the proposed optimization model in this paper can not only reduce the number of bus bunching by 90.00% and the fuel consumption by 64.74%, but also improve other performance indicators. Therefore, the model can effectively alleviate the problem of cost of passengers and energy waste caused by bunching in bus corridor.
Meta TagsDetails
DOI
https://doi.org/10.4271/2022-01-7090
Pages
10
Citation
Lu, Y., Qiao, Y., Zhang, Q., Yu, S. et al., "Alleviating Bunching by Platoon-Based Eco-Driving with Berth Allocation in Bus Corridors," SAE Technical Paper 2022-01-7090, 2022, https://doi.org/10.4271/2022-01-7090.
Additional Details
Publisher
Published
Dec 22, 2022
Product Code
2022-01-7090
Content Type
Technical Paper
Language
English