Search-Based Autonomous Vehicle Motion Planning Using Game Theory

--In this paper, we propose a search-based interactive motion planning scheme for autonomous vehicles (A Vs), using a game-theoretic approach. In contrast to traditional search-based approaches, the newly developed approach considers other road users (e.g. This leads to the generation of a more realistic path for the A V . Due to the low computational time, the proposed motion planning scheme is implementable in real-time applications. The performance of the developed motion planning scheme is compared with existing motion planning techniques and validated through experiments using W A T onoBus, an electrical all-weather autonomous shuttle bus. NTELLIGENT vehicles have increased their capabilities for highly automated driving under controlled environments i.e., driving scenarios that are designed to be predictable, stable, and safe for autonomous vehicles (A Vs) to operate in [1], [2]. Scene information is received using onboard sensors and communication network systems, i.e., infrastructure and other vehicles. Considering the available information, different motion planning and control techniques have been developed for autonomously driving in complex environments. The main goal is focused on executing strategies to improve safety, comfort, and energy optimization. One of the essential conditions for A V safety is ensuring safe interactions with other road users, including human-driven vehicles as well as pedestrians.