Risk-Based Collision Avoidance in Semi-Autonomous Vehicles

Although there have been a number of advances in active vehicle safety, such as Autonomous Emergency Braking[2] and Steering[5], there is significant room for improvement. By using a riskminimization approach that utilizes a neural network trained from simulation and re-evaluates its control decision 30 times per second, we are able to significantly improve upon Autonomous Emergency systems. In extreme simulation scenarios, we are able to reduce the rate of collision/going offroad by 39.41% when compared to Autonomous Emergency systems. For these simulations, we reduce the overall rate of collision/going offroad from 46.15% for Autonomous Emergency systems to 27.72% with our system.