摘要详情

ID / 提交时间

117 / 2023-09-20 11:54:46

标题

Overview of Sensing Attacks on Autonomous Vehicle Technologies and Impact on Traffic Flow

关键字

Autonomous vehicles technologies,Sensing attacks,Baseline Scenarios,Traffic impact

主题及专题

Special Sessions > SS02 - Intelligent Robot, Artificial Intelligence Methods and Its Applications

状态

终稿

作者

Zihao Li / Texas A&M University

Sixu Li / Texas A&M Univeristy

Hao Zhang / Texas A&M University

Yang Zhou / Texas A&M University

Siyang Xie / Cruise LLC

Yunlong Zhang / Texas A&M University

摘要

While perception systems in Connected and Autonomous Vehicles (CAVs), which encompass both communication technologies and advanced sensors, promise to significantly reduce human driving errors, they also expose CAVs to a variety of cyberattacks. These include both communication and sensing attacks, which have the potential to jeopardize not only individual vehicles but also overall traffic safety and efficiency. While much research has focused on communication attacks, sensing attacks, which are equally critical, have garnered less attention. To address this gap, this study offers a comprehensive review of potential sensing attacks and their impact on target vehicles, focusing on commonly deployed sensors in CAVs such as cameras, LiDAR, Radar, ultrasonic sensors, and GPS. Based on this review, we discuss the feasibility of integrating hardware-in-the-loop experiments with microscopic traffic simulations. We also design baseline scenarios to analyze the macro-level impact of sensing attacks on traffic flow. The aim of this study is to bridge the research gap between individual vehicle sensing attacks and broader macroscopic impacts, thereby laying the foundation for future systemic understanding and mitigation.