Autonomous vehicles (AV) leverage Artificial Intelligence to reduce accidents and improve fuel effciency while sharing the roads with human drivers. Current AV prototypes have not yet reached these goals, highlighting the need for better development and testing methodologies. AV testing practices extensively rely on simulations, but existing AV tools focus on testing single AV instances or do not consider human drivers. Thus, they might generate many irrelevant mixed-traffic test scenarios. The Flexcrash platform addresses these issues by allowing the generation and simulation of mixed-traffic scenarios, thus enabling testers to identify realistic critical scenarios,
trac experts to create new datasets, and regulators to extend consumer testing benchmarks.