Cooperative Game Approach to Optimal Merging Sequence and On-Ramp Merging Control of Connected and Automated Vehicles
Abstract
Vehicle merging is one of the main causes of reduced traffic efficiency, increased risk of collision, and fuel consumption. Connected and automated vehicles (CAVs) can improve traffic efficiency, increase safety, and reduce the negative environmental impacts through effective communication and control. Therefore, to improve the traffic efficiency and reduce the fuel consumption in on-ramp scenarios, this paper addresses the global and optimal coordination of the CAVs in a merging zone. In this work, a cooperative multi-player game-based optimization framework and an algorithm are presented to coordinate vehicles and achieve minimum values for the global pay-off conditions. Fuel consumption, passenger comfort, and travel time within the merging control zone were used as the pay-off conditions. After analyzing the characteristics of the merging control zone and selecting the appropriate control decision duration, multi-player games were decomposed into multiple two-player games. An optimal merging strategy was, thereby, derived from a pay-off matrix, and minimum payoffs were predicted for a number of different potential strategies. The optimal trajectory corresponding to the predicted minimum payoffs was then utilized as the control law to coordinate the vehicles merging. The proposed control scheme derives an optimal merging sequence and an optimal trajectory for each vehicle. The effectivenessmore »
- Authors:
-
- Chang'an Univ., Xi'an (China)
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Chang'an Univ., Xi'an (China); Univ. of Tennessee, Knoxville, TN (United States)
- Publication Date:
- Research Org.:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1550734
- Grant/Contract Number:
- AC05-00OR22725
- Resource Type:
- Journal Article: Accepted Manuscript
- Journal Name:
- IEEE Transactions on Intelligent Transportation Systems
- Additional Journal Information:
- Journal Volume: 20; Journal Issue: 11; Journal ID: ISSN 1524-9050
- Publisher:
- IEEE
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; Connected and automated vehicle; cooperative game; optimal merging sequence; merging control; on-ramp
Citation Formats
Jing, Shoucai, Hui, Fei, Zhao, Xiangmo, Rios Torres, Jackeline, and Khattak, Asad J. Cooperative Game Approach to Optimal Merging Sequence and On-Ramp Merging Control of Connected and Automated Vehicles. United States: N. p., 2019.
Web. doi:10.1109/TITS.2019.2925871.
Jing, Shoucai, Hui, Fei, Zhao, Xiangmo, Rios Torres, Jackeline, & Khattak, Asad J. Cooperative Game Approach to Optimal Merging Sequence and On-Ramp Merging Control of Connected and Automated Vehicles. United States. https://doi.org/10.1109/TITS.2019.2925871
Jing, Shoucai, Hui, Fei, Zhao, Xiangmo, Rios Torres, Jackeline, and Khattak, Asad J. 2019.
"Cooperative Game Approach to Optimal Merging Sequence and On-Ramp Merging Control of Connected and Automated Vehicles". United States. https://doi.org/10.1109/TITS.2019.2925871. https://www.osti.gov/servlets/purl/1550734.
@article{osti_1550734,
title = {Cooperative Game Approach to Optimal Merging Sequence and On-Ramp Merging Control of Connected and Automated Vehicles},
author = {Jing, Shoucai and Hui, Fei and Zhao, Xiangmo and Rios Torres, Jackeline and Khattak, Asad J.},
abstractNote = {Vehicle merging is one of the main causes of reduced traffic efficiency, increased risk of collision, and fuel consumption. Connected and automated vehicles (CAVs) can improve traffic efficiency, increase safety, and reduce the negative environmental impacts through effective communication and control. Therefore, to improve the traffic efficiency and reduce the fuel consumption in on-ramp scenarios, this paper addresses the global and optimal coordination of the CAVs in a merging zone. In this work, a cooperative multi-player game-based optimization framework and an algorithm are presented to coordinate vehicles and achieve minimum values for the global pay-off conditions. Fuel consumption, passenger comfort, and travel time within the merging control zone were used as the pay-off conditions. After analyzing the characteristics of the merging control zone and selecting the appropriate control decision duration, multi-player games were decomposed into multiple two-player games. An optimal merging strategy was, thereby, derived from a pay-off matrix, and minimum payoffs were predicted for a number of different potential strategies. The optimal trajectory corresponding to the predicted minimum payoffs was then utilized as the control law to coordinate the vehicles merging. The proposed control scheme derives an optimal merging sequence and an optimal trajectory for each vehicle. The effectiveness of the proposed model is validated through simulation. Finally, the proposed controller is compared with two alternative methods to demonstrate its potential to reduce fuel consumption and travel time and to improve passenger comfort and traffic efficiency.},
doi = {10.1109/TITS.2019.2925871},
url = {https://www.osti.gov/biblio/1550734},
journal = {IEEE Transactions on Intelligent Transportation Systems},
issn = {1524-9050},
number = 11,
volume = 20,
place = {United States},
year = {Mon Jun 17 00:00:00 EDT 2019},
month = {Mon Jun 17 00:00:00 EDT 2019}
}
Web of Science
Works referencing / citing this record:
Trajectory Planning Method for Mixed Vehicles Considering Traffic Stability and Fuel Consumption at the Signalized Intersection
journal, January 2020
- Fang, Shan; Yang, Lan; Wang, Tianqi
- Journal of Advanced Transportation, Vol. 2020