A new automotive system architecture for minimizing rear-end collisions

Abstract

Advanced Driver Assistance Systems, more frequently referred to as ADAS, are intelligent systems integrated into newer automotive vehicles to improve safety and minimize accidents. These systems utilize radar, sonar, lidar and camera sensors mounted around the vehicle to maintain situational awareness of the vehicle and the surrounding environment. The majority of ADAS that focus on collision avoidance modify the host vehicle's operation. Some existing ADAS will stop the vehicle, sound an audible alert, initiate internal warning lights or dash warning messages, and prevent lane change operations. The ADAS proposed and detailed here focuses on enabling the host vehicle to communicate with the inbound vehicle's driver via the brake lights so that the driver has the opportunity to modify the inbound vehicle's operation before a collision occurs. This is called the Aft Collision Assist (ACA). This work presents the Model Based System Engineering (MBSE) diagrams, SIMULINK models and simulation of the ACA, data derivation utilized in the simulations, validation with empirical data, and future work for optimizing the ACA's algorithms.