Heuristic-Based Architecting for Autonomous Vehicle Systems

systems architecting;heuristic architecting;autonomous vehicles

Humans have always had a need to improve travel, whether that be for ourselves or for the goods we need. Technological advancements have all fundamentally performed the task of moving people and goods with the objective to continuously improve convenience and be more efficient. There is another pending revolution in human mobility, one that is leading towards autonomous transportation where the human driver is replaced, and the driving of the vehicle is performed autonomously by machine. With continued research and technology, automotive Original Equipment Manufacturers (OEMs) have started to implement autonomous enabled features to transform today’s vehicles traveling our roads to driverless vehicles. This paper evaluates the fundamental problem of architecting a system responsible of transporting occupants and cargo from point A to point B via autonomous vehicles (AVs) and compares it to current architecture being proposed by OEMs. To facilitate the mission, the authors studied the user needs of an AV, performed functional analysis and how they relate to each other. Utilizing guiding heuristics and lessons learned, the current architecture is examined and critiqued. The results show that the current methodology used by OEMs is to simply create smarter vehicles within a non-intelligent infrastructure. The heuristics, or in other words the process to learn and improve using experiences, give insights and guidance on how to address the main high-level functions to enable an elegant and robust architecture for autonomous transportation.