Performance of Cooperative Detection in Joint Communication-Sensing Vehicular Network: A Data Analytic and Stochastic Geometry Approach

TL;DR

This paper introduces a novel cooperative detection model using joint communication and sensing (JCS) for urban autonomous vehicles, employing stochastic geometry and GIS data to optimize infrastructure deployment amidst urban obstacles.

Contribution

It develops a stochastic geometry-based analysis of JCS channel characteristics and obstacle effects, proposing deployment optimization strategies for urban vehicular networks.

Findings

High successful detection and communication probabilities under LoS and NLoS conditions.

Effective deployment strategies improve urban JCS network performance.

Simulation results validate the proposed model and optimization methods.

Abstract

The increasing complexity of urban environments introduces additional uncertainty to the deployment of the autonomous vehicular network. A novel road infrastructure cooperative detection model using Joint Communication and Sensing (JCS) technology is proposed in this article to simultaneously achieve high-efficient communication and obstacle detection for urban autonomous vehicles. To suppress the performance fluctuation caused by shadowing and obstruction to the JCS signals, we first derive the statistic of road obstacles from the Geographic Information System (GIS). Then, the analysis of JCS channel characteristics and shadowing factors are presented using Line-of-Sight and Non-Line-of-Sight (LoS and NLoS) channel models under the complex urban scenario. A stochastic geometry approach is applied to analyze the interference factors and the probability distribution of successful JCS detection and communication. Simulations have been made to verify the cooperative detection model by probability analysis based on LoS and NLoS channels, and the numerical results demonstrate several different optimization methods for the deployment of JCS road infrastructures. Finally, we simulated and analyzed a deployment optimization method for JCS road infrastructures that complied with the standard of urban traffic-spot structure placement.