Systems Engineering of an Advanced Driver Assistance System for Student-Engineered PHEV Chevrolet Camaro 2019-01-0876
Current Advanced Driver Assistance Systems (ADAS) often interact directly with the driver aiding with either warnings or direct intervention. This work explores the development of an ADAS system to provide lane departure warning (LDW), forward collision warning (FCW), and a recommended following distance (RFD) for a custom plug-in hybrid-electric vehicle (PHEV). The system utilizes off-the-shelf hardware with in-house computer vision and sensor fusion algorithms to create a low-cost SAE level-0 driver assistance system. The system utilizes an automotive-grade radar sensor as well as a USB camera to detect, classify, and track target vehicles. The system was fully developed and tested within an academic year aided by a well-documented design process. This work will illustrate the systems engineering methods for outlining customer requirements, technical requirements, component selection, software development, simulation, integration, and validation. The results of the system were sufficient for the scope of the project. Similar system engineering processes could be implemented for higher level SAE systems in the future.