An Analysis of Testing Scenarios for Automated Driving Systems

2021 
Automated Driving System refers to a vehicle system where hardware and software are collectively capable of on-road operational and tactical functions and such functions involve the detection, recognition, classification of objects and response to events. Many automotive companies are incorporating automated driving into their current R&D and are transforming their business models. To both conventional and disruptive manufacturers, safety is always one of the top priorities. Appropriate verification and validation procedures are needed and should be followed to mitigate unreliability and hazardousness. Sufficient testing scenario should be considered and planned to simulate and cover functional and non-functional requirements. Disengagement ratio serves as an indicator during performance evaluations because analysing root causes of both technical and non-technical disengagements is pivotal especially during testing strategy planning. Autonomous Vehicle Disengagement Reports and Autonomous Vehicle Collision Reports from the Department of Motor Vehicles (DMV), California, USA are collectively used for the purpose of this research. And the analytical result shows there is no clear relationship between mileage and disengagements. Influencing factors are generated and consolidated from the mentioned reports and are proposed in addition to a Society of Automotive Engineers International (SAE International) standard. Stakeholders will benefit from the presented rationales and consider the suggestive parameters throughout their developing and testing activities. This paper further recommends testing management for automated driving systems, especially test driver management and test routes planning. And the recommendations are in accordance with the analytical results and feedback from KPMG s Global Automotive Executive Surveys.
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