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Intersection Control and Delay Optimization for Autonomous Vehicles Flows Only as Well as Mixed Flows with Ordinary Vehicles

Department of Civil Engineering, The University of Akron, Akron, OH 44325, USA
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Received: 28 July 2020 / Revised: 22 August 2020 / Accepted: 24 August 2020 / Published: 26 August 2020
(This article belongs to the Special Issue Autonomous Vehicle Control)
The rapidly improving autonomous vehicle (AV) technology will have a significant impact on traffic safety and efficiency. This study introduces a game-theory-based priority control algorithm for autonomous vehicles to improve intersection safety and efficiency with mixed traffic. By using vehicle-to-infrastructure (V2I) communications, this model allows an AV to exchange information with the roadside units (RSU) to support the decision making of whether an ordinary vehicle (OV) or an AV should pass the intersection first. The safety of vehicles is taken in different stages of decisions to assure collision-free intersection operations. Two different mathematical models have been developed, where model one is for an AV/AV situation and model two is when an AV meets an OV. A simulation model was developed to implement the algorithm and compare the performance of each model with the conventional traffic control at a four-legged signalized intersection and at a roundabout. Three levels of traffic volume and speed combinations were tested in the simulation. The results show significant reductions in delay for both cases; for case (I), AV/AV model, a 65% reduction compared to a roundabout and 84% compared to a four-legged signalized intersection, and for case (II), AV/OV model, the reduction is 30% and 89%, respectively. View Full-Text
Keywords: autonomous vehicles; intersection management; delay reduction; vehicle-to-infrastructure; ordinary vehicles; game theory; signalized intersection; roundabout autonomous vehicles; intersection management; delay reduction; vehicle-to-infrastructure; ordinary vehicles; game theory; signalized intersection; roundabout
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MDPI and ACS Style

Baz, A.; Yi, P.; Qurashi, A. Intersection Control and Delay Optimization for Autonomous Vehicles Flows Only as Well as Mixed Flows with Ordinary Vehicles. Vehicles 2020, 2, 523-541. https://0-doi-org.brum.beds.ac.uk/10.3390/vehicles2030029

AMA Style

Baz A, Yi P, Qurashi A. Intersection Control and Delay Optimization for Autonomous Vehicles Flows Only as Well as Mixed Flows with Ordinary Vehicles. Vehicles. 2020; 2(3):523-541. https://0-doi-org.brum.beds.ac.uk/10.3390/vehicles2030029

Chicago/Turabian Style

Baz, Abdullah; Yi, Ping; Qurashi, Ahmad. 2020. "Intersection Control and Delay Optimization for Autonomous Vehicles Flows Only as Well as Mixed Flows with Ordinary Vehicles" Vehicles 2, no. 3: 523-541. https://0-doi-org.brum.beds.ac.uk/10.3390/vehicles2030029

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