Negotiation Protocol Design for Cooperative Maneuvering of Connected Automated Vehicles Using Conflict Charts

In this study, we propose a novel negotiation-based cooperative maneuvering strategy to assist connected automated vehicles (CAVs) in resolving conflicts under different traffic scenarios. We introduce conflict charts to determine when negotiation is necessary, along with a request and response protocol to facilitate traffic conflict resolution. Additionally, we propose an easy-to-implement controller that allows CAVs to resolve conflicts based on the agreement reached through negotiation. Simulation results using real vehicle data are used to demonstrate that the proposed negotiation protocol helps to ensure safety while improving time efficiency compared to cooperations that rely on other communication strategies.

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Publication Details

Published
2025-06-22
DOI
https://doi.org/10.1109/iv64158.2025.11097500
Primary Topic
Robotic Path Planning Algorithms
Type
article
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article

Negotiation Protocol Design for Cooperative Maneuvering of Connected Automated Vehicles Using Conflict Charts

Hao M. Wang, Gábor Orosz, Onur Altintas, Sergei S. Avedisov et al.
Robotic Path Planning Algorithms
article

Negotiation Protocol Design for Cooperative Maneuvering of Connected Automated Vehicles Using Conflict Charts

Hao M. Wang, Gábor Orosz, Onur Altintas, Sergei S. Avedisov, Kai Deng
article en

Abstract

In this study, we propose a novel negotiation-based cooperative maneuvering strategy to assist connected automated vehicles (CAVs) in resolving conflicts under different traffic scenarios. We introduce conflict charts to determine when negotiation is necessary, along with a request and response protocol to facilitate traffic conflict resolution. Additionally, we propose an easy-to-implement controller that allows CAVs to resolve conflicts based on the agreement reached through negotiation. Simulation results using real vehicle data are used to demonstrate that the proposed negotiation protocol helps to ensure safety while improving time efficiency compared to cooperations that rely on other communication strategies.

University of Michigan (US), Toyota Motor North America (United States) (US)
Openalex Percentile: Top 82%
Robotic Path Planning Algorithms
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