Perception System Architecture for Self-Driving Vehicles: A Cyber- Physical Systems Framework

Abstract

Abstract This research is seeking for design the autonomous vehicle's perception system from the perspective of cyber-physical system. The perception system is considered a cyber and physical component. This research takes a systemic approach. Unified Modeling Language (UML) has been applied to design perception systems. The perceptual system was created using the 3 common UML diagrams. The findings show that UML can be used as a powerful tool for modeling every type of complex system. The sensors utilized in the tasks of the perception layer are shown in use case diagrams. To recognize surrounding things and avoid obstacles, a variety of technologies including cameras, LiDAR, RADAR, ultrasonic sensors, GPS, and GNSS are utilized in 2/3-d object detection, speed and distance detection, localization, and mapping. The class diagram displays the perception system's structural elements. The perception system's task execution was shown in the sequence diagram. The engineers can improve the functionality and security of autonomous vehicles by using UML to create a precise and organized description of the perception system. The model in which designed in this paper can improve autonomous vehicles' perception system performance, driving safety, and self-confidence of vehicles. this model is an innovative model based on the cyber-physical systems approach and with the UML modeling method. other models in the literature are pipeline modular and/or see the perception layer tasks in isolation.