Monotonicity-Based Symbolic Control for Safety in Driving Scenarios

2022 
We use a monotonicity-based approach to design a safety controller in two realistic driving situations: a vehicle-following scenario and an unprotected left turn scenario. For each scenario we construct a symbolic abstraction of the system and efficiently synthesize a safety controller by exploiting the monotonicity property of the dynamics. We show how monotonicity property makes it possible to deal with complex scenarios, such as the vehicle following scenario with safe impact and left turn scenario, while handling model uncertainty.
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