Safe at any speed: A simulation-based test harness for autonomous vehicles

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Abstract

The testing of Autonomous Vehicles (AVs) requires driving the AV billions of miles under varied scenarios in order to find bugs, accidents and otherwise inappropriate behavior. Because driving a real AV that many miles is too slow and costly, this motivates the use of sophisticated 'world simulators', which present the AV's perception pipeline with realistic input scenes, and present the AV's control stack with realistic traffic and physics to which to react. Thus the simulator is a crucial piece of any CAD toolchain for AV testing. In this work, we build a test harness for driving an arbitrary AV's code in a simulated world. We demonstrate this harness by using the game Grand Theft Auto V (GTA) as world simulator for AV testing. Namely, our AV code, for both perception and control, interacts in real-time with the game engine to drive our AV in the GTA world, and we search for weather conditions and AV operating conditions that lead to dangerous situations. This goes beyond the current state-of-the-art where AVs are tested under ideal weather conditions, and lays the ground work for a more comprehensive testing effort. We also propose and demonstrate necessary analyses to validate the simulation results relative to the real world. The results of such analyses allow the designers and verification engineers to weigh the results of simulation-based testing.

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Abbas, H., O’Kelly, M., Rodionova, A., & Mangharam, R. (2019). Safe at any speed: A simulation-based test harness for autonomous vehicles. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11267 LNCS, pp. 94–106). Springer Verlag. https://doi.org/10.1007/978-3-030-17910-6_8

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