In response to increasing public transportation demands and environmental concerns, the RABus project explores the integration of automated shuttle buses (SAE Level 4) in Friedrichshafen and Mannheim to enhance urban and rural mobility. This research focuses on obstacle detection and avoidance, emphasizing the role of AI in improving automated driving safety. However, limited training data introduces AI uncertainty, affecting system reliability. Traditional safety assessments are insufficient for complex scenarios, leading to the adoption of scenario-based validation methods. This paper presents a scenario description method that combines the Operational Design Domain (ODD) and traffic behavior. By analyzing the ODD and hazard factors, a systematic approach to creating a test scenario catalog is proposed to evaluate the safety and reliability of obstacle detection systems in automated shuttle buses, addressing the need for a robust testing framework.
A Conceptual Framework to Operational Design Domain (ODD)-Based Scenario Generation for Technical Evaluation Obstacle Detection in Automated Shuttle Bus
Communic.Comp.Inf.Science
International Symposium on Intelligent Technology for Future Transportation ; 2024 ; Helsinki, Finland October 20, 2024 - October 22, 2024
2025-03-12
11 pages
Article/Chapter (Book)
Electronic Resource
English
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