Results of the 2023 CommonRoad Motion Planning Competition for Autonomous Vehicles

TL;DR

This paper reports the results of the 2023 CommonRoad Motion Planning Competition, comparing various autonomous vehicle motion planning approaches across diverse traffic scenarios based on a standardized benchmark suite.

Contribution

It provides a comprehensive comparison of different motion planning methods on a common benchmark, highlighting strengths and weaknesses in safety, efficiency, and rule compliance.

Findings

Identifies top-performing algorithms in various traffic scenarios

Highlights trade-offs between safety and efficiency

Provides insights into the state-of-the-art in autonomous vehicle motion planning

Abstract

In recent years, different approaches for motion planning of autonomous vehicles have been proposed that can handle complex traffic situations. However, these approaches are rarely compared on the same set of benchmarks. To address this issue, we present the results of a large-scale motion planning competition for autonomous vehicles based on the CommonRoad benchmark suite. The benchmark scenarios contain highway and urban environments featuring various types of traffic participants, such as passengers, cars, buses, etc. The solutions are evaluated considering efficiency, safety, comfort, and compliance with a selection of traffic rules. This report summarizes the main results of the competition.