Print Email Facebook Twitter Detecting Malicious Behavior In Cooperative Autonomous RC Cars Title Detecting Malicious Behavior In Cooperative Autonomous RC Cars Author Tombakaitė, Gabriele (TU Delft Mechanical, Maritime and Materials Engineering) Contributor Ferrari, R. (mentor) Keijzer, T. (mentor) Wahls, S. (graduation committee) Degree granting institution Delft University of Technology Programme Mechanical Engineering | Systems and Control Date 2020-10-20 Abstract Sensors are used all around us in various industries, for instance: agricultural, medical,aerospace and automotive. It is important for these industries to have reliable sensor data because the functionality of technologies depends on it. In this work, the industry of inter-est is automotive, specifically in the field of Cooperative Adaptive Cruise Control (CACC). The control of vehicles depends on measurement data from radars, which are carried by each vehicle in a platoon. If these measurements are faulty, it could affect CACC and cause a crash. This work models the Radio Control (RC) vehicle, implements CACC and aims to identify such faults in the radar measurement data before they could impact the behavior of the platoon. The results are obtained in simulation, comprising the mathematical model of the vehicles, the implemented CACC controller and a virtual radar exposed to 4 different faults, with which the chosen method for fault detection is evaluated. The results of the CACC operating in ideal conditions and with faulty measurement data are depicted. The work ends with analysing the results and concluding, whether the chosen method is capable of identifying the faulty measurement data. Subject CACCPlatooningFault detection To reference this document use: http://resolver.tudelft.nl/uuid:6da365dc-b3d0-4cc0-aa6e-347afcb958b0 Part of collection Student theses Document type master thesis Rights © 2020 Gabriele Tombakaitė Files PDF G_Tombakaite_Thesis.pdf 4.28 MB Close viewer /islandora/object/uuid:6da365dc-b3d0-4cc0-aa6e-347afcb958b0/datastream/OBJ/view