Chen, Pin-Chun, Liu, Xiangguo, Lin, Chung-Wei, Huang, Chao 
ORCID: 0000-0002-9300-1787 and Zhu, Qi
(2023)
Mixed-Traffic Intersection Management Utilizing Connected and Autonomous Vehicles as Traffic Regulators.
In: ASPDAC '23: 28th Asia and South Pacific Design Automation Conference.
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Abstract
Connected and autonomous vehicles (CAVs) can realize many revolutionary applications, but it is expected to have mixed-traffic including CAVs and human-driving vehicles (HVs) together for decades. In this paper, we target the problem of mixed-traffic intersection management and schedule CAVs to control the subsequent HVs. We develop a dynamic programming approach and a mixed integer linear programming (MILP) formulation to optimally solve the problems with the corresponding intersection models. We then propose an MILP-based approach which is more efficient and real-time-applicable than solving the optimal MILP formulation, while keeping good solution quality as well as outperforming the first-come-first-served (FCFS) approach. Experimental results and SUMO simulation indicate that controlling CAVs by our approaches is effective to regulate mixed-traffic even if the CAV penetration rate is low, which brings incentive to early adoption of CAVs.
| Item Type: | Conference or Workshop Item (Unspecified) |
|---|---|
| Uncontrolled Keywords: | Connected and autonomous vehicles, intersection management, mixed-traffic |
| Divisions: | Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 22 Jun 2023 07:41 |
| Last Modified: | 22 Jun 2023 07:41 |
| DOI: | 10.1145/3566097.3567849 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3171195 |
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