Development of a simulation platform for safety impact analysis considering vehicle dynamics,sensor errors,and communication latencies: Assessing cooperative adaptive cruise control under cyber attack |
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| Affiliation: | 1. Link Lab & Department of Civil and Environmental Engineering, University of Virginia, P.O. Box 400742, Charlottesville, VA 22904, United States;2. Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Institute for Advanced Study, Tongji University, China, 4800 Cao''an Hwy, Jiading Qu, Shanghai, China;3. Turner Fairbank Highway Research Center, Federal Highway Administration, 6300 Georgetown Pike, McLean, VA 22101, United States;1. Department of Civil and Environmental Engineering, University of Delaware, United States;2. John A. Reif, Jr. Department of Civil and Environmental Engineering, New Jersey Institute of Technology, United States;1. Department of Electrical and Computer Engineering, University of California, Davis, CA, USA;2. Department of Civil and Environmental Engineering, University of California, Davis, CA, USA;3. Department of Computer Science, University of California, Davis, CA, USA;1. Department of Civil and Coastal Engineering, University of Florida, Gainsville, FL, USA;2. Department of Electrical Engineering, Florida Polytechnic University, Lakeland, FL, USA;3. Department of Electrical and Computer Engineering at Florida International University, Miami, FL, USA |
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| Abstract: | While safety is one of the most critical contributions of Cooperative Adaptive Cruise Control (CACC), it is impractical to assess such impacts in a real world. Even with simulation, many factors including vehicle dynamics, sensor errors, automated vehicle control algorithms and crash severity need to be properly modeled. In this paper, a simulation platform is proposed which explicitly features: (i) vehicle dynamics; (ii) sensor errors and communication delays; (iii) compatibility with CACC controllers; (iv) state-of-the-art predecessor leader following (PLF) based cooperative adaptive cruise control (CACC) controller; and (v) ability to quantify crash severity and CACC stability. The proposed simulation platform evaluated the CACC performance under normal and cybersecurity attack scenarios using speed variation, headway ratio, and injury probability. The first two measures of effectiveness (MOEs) represent the stability of CACC platoon while the injury probability quantifies the severity of a crash. The proposed platform can evaluate the safety performance of CACC controllers of interest under various paroxysmal or extreme events. It is particularly useful when traditional empirical driver models are not applicable. Such situations include, but are not limited to, cyber-attacks, sensor failures, and heterogeneous traffic conditions. The proposed platform is validated against data collected from real field tests and tested under various cyber-attack scenarios. |
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| Keywords: | Connected and automated vehicle simulation Safety Cooperative adaptive cruise control Vehicle dynamics Equipment failure |
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