Modeling & Simulation, Testing & Validation (MSTV)


by Diego Lodato; Raj Kamalanathsharma; Maurice Farber


The automotive and defense industries are going through a period of disruption with the advent of Connected and Automated Vehicles (CAV) driven primarily by innovations in affordable sensor technologies, drive-by-wire systems, and Artificial Intelligence-based decision support systems. One of the primary tools in the testing and validation of these systems is a comparison between virtual and physical-based simulations, which provides a low-cost, systems-approach testing of frequently occurring driving scenarios such as vehicle platooning and edge cases and sensor-spoofing in congested areas. Consequently, the project team developed a robotic vehicle platform—Scaled Testbed for Automated and Robotic Systems (STARS)—to be used for accelerated testing elements of Automated Driving Systems (ADS) including data acquisition through sensor-fusion practices typically observed in the field of robotics. This paper will highlight the implementation of STARS as a scaled testbed for rapid prototyping, accelerated testing and verification and validation (V&V), and its applicability as a simulation tool for additional CAV concepts, such as modeling edge cases like swarm behaviors for route delivery and vehicle cyber security testing on sensors.