Collaborative Autonomous Driving: Vision and Challenges
Zheng Dong, Weisong Shi, Guangmo Tong, Kecheng Yang
Abstract
This paper discusses challenges in computer systems research posed by the emerging autonomous driving systems. We first identify four research areas related to autonomous driving systems: real-time and embedded systems, machine learning, edge computing, and cloud computing. Next, we sketch two fatal accidents caused by active autonomous driving, and uses them to indicate key missing capabilities from today's systems. In light of these research areas and shortcomings, we describe a vision of digital driving circumstances for autonomous vehicles and refer to autonomous vehicles as "clients" of this digital driving circumstance. Then we propose a new research thrust: collaborative autonomous driving. Intuitively, requesting useful information from a digital driving circumstance to enable collaborative autonomous driving is quite sophisticated (e.g., collaborations may come from different types of unstable edge devices), but it also provide us various research challenges and opportunities. The paper closes with a discussion of the research necessary to develop these capabilities.