In this paper, we address the problem of secure pose estimation of an autonomous vehicle (AV) under cyber attacks. An extended Kalman filter (EKF) is used to fuse measurements from multiple sensors including GPS, LIDAR, and IMU. To deal with the possible sensor attacks, we design a cumulative sum (CUSUM) detector to monitor the inconsistency between the predicted pose via mathematical model and the sensor measurement. An EKF reconfiguration scheme is proposed to mitigate the influence of sensor attacks once the compromised sensor is identified. The feasibility and effectiveness of the proposed secure pose estimation method are validated using a simulation platform built on Autoware and Gazebo.
Secure Pose Estimation for Autonomous Vehicles under Cyber Attacks
2019 IEEE Intelligent Vehicles Symposium (IV) ; 1583-1588
2019-06-01
1789207 byte
Conference paper
Electronic Resource
English
SECURE POSE ESTIMATION FOR AUTONOMOUS VEHICLES UNDER CYBER ATTACKS
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