Muhammad Abdullah
Safety evaluation of critical maneuvers in simulated road traffic scenarios.
Rel. Francesco Paolo Deflorio, Matteo Ferraro, Giuseppe Calcagno. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Meccanica (Mechanical Engineering), 2026
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Abstract
The safety of critical maneuvers of autonomous vehicles is a very important part of vehicular prototype, assessed within the simulation environment of CARLA (Car Learning to Act). The simulation environment features a cluster configuration of twelve sensors installed on the ego car achieving Level 3 autonomous control on the figure eight highway of the Town 04 environment: along with 20 background cars (controlled traffic). The testing environment covers 30 different test cases by testing the sensors output with different weathers/time of day and different levels of progressive ADAS configurations, from only emergency braking to complete Level 3 ADAS package enforcement. Longitudinal control is managed using a PID controller with anti-windup, while a time-based sensor fusion persistence mechanism ensures perception continuity during weather-induced sensor degradations.
The outputs are assessed using several important parameters such as Time-to-Collision (TTC), radar false positive (FPR) and false negative rates (FNR), variance of headway distances (σ), dropout rates of sensors, Real-Time Factor (RTF), and the number of fatal collisions that occur during the simulated cases
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