[2M6-GS-10] AI application

[2M6-GS-10-01] A Study on the Implementation of Cooperative CAVs by Sharing the Observation Information Using Large-Scale Simulations

〇Ken Matsuda¹, Ei-Ichi Osawa² (1. Graduate School of Systems Information Science, Future University Hakodate, 2. Department of Complex and Intelligent Systems, School of Systems Information Science, Future Univerisity Hakodate)

Keywords:Cooperative CAVs, Autonomous Vehicles, Connected Vehicles, Traffic Simulation, Multi-agent Reinforcement Learning

The focus of this research is on the cooperative connected autonomous vehicles (cooperative CAVs). The aim of this research is to propose a simulator and a environment to enable the learning and implementation of cooperative CAVs. Since there are many challenges to implement cooperative CAVs, large-scale demonstration have not yet been conducted. Therefore, it is valuable to conduct experiments of cooperative CAVs by large-scale simulations. In this research, we propose a simulator and a environment to learn cooperative CAVs driving policy using RL. A communication feature is incorporated to the simulator by sharing the observation information determined based on distance in a chain. Experiments are conducted to determine if cooperative CAVs can be implemented by sharing the observation information. We compared the rewards obtained by learning with and without sharing the observation information. Results show that cooperative CAVs cannot be implemented solely by sharing the observation information, as the reward obtained is higher when the observation information is not shared. Through discussions, we identified issues that need be addressed to implement cooperative CAVs.