Joint Communication and Control System Design for Connected and Autonomous Vehicle Navigation

Document Type

Conference Proceeding

Publication Date

5-2019

Publication Title

Proceedings of the IEEE International Conference on Communications (ICC)

Abstract

Connected and autonomous vehicles (CAVs) can play an important role in improving on-road safety and providing convenience in our daily lives. To perform autonomous path tracking and navigation, CAVs can exploit vehicle-to-everything (V2X) communications to determine their vehicle dynamics parameters, such as location, heading angle, and curvature, which can be then used as inputs to their control system. However, the interference and uncertainty of the wireless channels can increase the transmission delay on the vehicle dynamics and, thus, impair the CAV’s ability to track its target path. In this paper, the problem of joint communication network and control system design is studied to solve the path tracking problem for CAVs. In particular, a novel approach is proposed to maximize the number of reliable V2X transmitter-receiver pairs while jointly considering the stability of the controller and the state of the wireless network. Based on the proposed joint communication and control design, the maximum transmission delay which can prevent instability in the controller is determined. Then, the reliable V2X links maximization problem is decomposed into two equivalent sub-problems. The first sub-problem is the control mechanism design in which a dual update method is used to determine the headway distance parameter that is used by the control system. The second sub-problem uses the outcome of the first sub-problem to optimize the power allocation for the communication system. To solve this power allocation problem, a novel risk-based approach that uses the so-called conditional value at risk (CVaR) from financial engineering is proposed to find an approximated solution. Simulation results validate the theoretical results and show that the proposed joint design can improve the number of reliable V2X pairs by as much as 50% compared to a baseline that optimizes the communication and control systems independently.

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