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Adaptive Testing Environment Generation for Connected and Automated Vehicles with Dense Reinforcement Learning
A common approach involves designing testing scenarios based on prior knowledge of CAVs (e. g., surrogate models), conducting tests in these scenarios, and subsequently evaluating CAVs' safety performances.
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