首页|CAV driving safety monitoring and warning via V2X-based edge computing system
CAV driving safety monitoring and warning via V2X-based edge computing system
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Driving safety and accident prevention are attracting increasing global interest.Current safety moni-toring systems often face challenges such as limited spatiotemporal coverage and accuracy,leading to delays in alerting drivers about potential hazards.This study explores the use of edge computing for monitoring vehicle motion and issuing accident warnings,such as lane depar-tures and vehicle collisions.Unlike traditional systems that depend on data from single vehicles,the cooperative vehicle-infrastructure system collects data directly from connected and automated vehicles(CAVs)via vehicle-to-everything communication.This approach facilitates a comprehensive assessment of each vehicle's risk.We propose algorithms and specific data structures for evalu-ating accident risks associated with different CAVs.Furthermore,we examine the prerequisites for data accuracy and transmission delay to enhance the safety of CAV driv-ing.The efficacy of this framework is validated through both simulated and real-world road tests,proving its utility in diverse driving conditions.
driving safetyaccident preventionconnected and automated vehiclesedge computing
Cheng CHANG、Jiawei ZHANG、Kunpeng ZHANG、Yichen ZHENG、Mengkai SHI、Jianming HU、Shen LI、Li LI
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Department of Automation,Tsinghua University,Beijing 100084,China
College of Electrical Engineering,Henan University of Tech-nology,Zhengzhou 450001,Chin
Nebula Link Technology Co.,Ltd.,Beijing 100080,China
Department of Civil Engineering,Tsinghua University,Beijing 100084,China
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