| Popis: |
To embrace safety while bringing autonomous vehicles (AVs) to public roads, AV manufacturers need to validate and verify the functionality and reliability of the control software. Real-road testing is time-consuming, tedious, costly, and unsafe for validation. Hence, simulation testing has been playing an important role in the market as a viable solution. This paper presents an approach that exploits both methods to find edge case scenarios and evaluates the software reliability of an existing AV shuttle, iseAuto, currently operating at the Tallinn University of Technology campus. To show the method’s effectiveness, a range of scenarios are generated and simulated for avoidance maneuvers by means of a low-fidelity simulator. Then, the scenarios that are found to be jeopardizing the AV are filtered and simulated by a high-fidelity simulator with the AV control software in the loop. Finally, to investigate the methodology and simulation reliability, a real study case is proposed using the AV shuttle. Results of the study suggest that the proposed toolchain is capable of tuning simulation models for automated driving development as well as validating safe AV operations. |
