Cooperative Edge Extension for Automated Driving

E/E architectures are continuously evolving to meet newly emerging demands. In recent years, major drivers of this evolution have been the increasing software-defined nature of vehicles and the push toward automated driving. Key technologies such as edge-enhanced functions, vehicle-to-vehicle communication, and service-oriented architectures are therefore the focus of current research efforts. This paper presents a vision of how these technologies can be used to enable cooperation between vehicles, illustrated by using parked vehicles as edge nodes. Automated driving beyond SAE Level 4 remains an especially challenging task in dense urban environments. One major impediment is the presence of view obstructions caused by parked vehicles. These obstructions significantly increase the risk of missing or misinterpreting vulnerable road users such as pedestrians or cyclists. One possible approach to counteract this problem is the use of edge nodes that support object detection or even trajectory planning. Current research primarily considers smart traffic infrastructure, roadside units, and other vehicles as potential edge nodes. Including parked vehicles as edge nodes means that, instead of acting solely as obstacles, they leverage their built-in sensors to contribute to cooperative awareness. While such cooperation will enhance the safety of automated vehicles in urban areas, several challenges arise. In this paper, we discuss how data traceability, decision-making in the presence of conflicting information, and incentive mechanisms for owners of parked vehicles can be addressed. Furthermore, the paper outlines requirements for future cooperative architecture and highlights the role of edge-enhanced functions, V2V communication, and service-oriented architectures in enabling fully automated driving.