Communication Challenges in Infrastructure-Vehicle Cooperative Autonomous Driving: A Field Deployment Perspective

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Abstract
We have commercially deployed an infrastructure-vehicle cooperative autonomous driving system and verified its superiority over on-vehicle only autonomous driving systems. However, we have also identified network communication as the main technical roadblock for reliable cooperative autonomous driving. Hence, the goal of this article is to help the communications research community to better understand the real-world communication challenges in cooperative autonomous driving, as well as to introduce practical solutions for establishing a good baseline for further research and development efforts. Specifically, we introduce the real-world network communication challenges: first, the current mobile network bandwidth is constraining the uploading of raw sensing data, which is crucial for cloud-based applications such as deep learning model training and high-definition map generation etc. Second, the network latency jitters remain high for a considerable portion of a vehicle's trip, greatly impacting the reliability and safety of the operations of autonomous vehicles. To address these two challenges, we have developed, deployed, and verified two practical solutions. First, a sensing compression strategy to cope with the network bandwidth challenge. Second, an adaptive fusion engine to cope with the latency variation challenge.

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