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  • 标题:Hybrid Verification Technique for Decision-Making of Self-Driving Vehicles
  • 本地全文:下载
  • 作者:Mohammed Al-Nuaimi ; Sapto Wibowo ; Hongyang Qu
  • 期刊名称:Journal of Sensor and Actuator Networks
  • 电子版ISSN:2224-2708
  • 出版年度:2021
  • 卷号:10
  • 期号:3
  • 页码:42
  • DOI:10.3390/jsan10030042
  • 出版社:MDPI Publishing
  • 摘要:The evolution of driving technology has recently progressed from active safety features and ADAS systems to fully sensor-guided autonomous driving. Bringing such a vehicle to market requires not only simulation and testing but formal verification to account for all possible traffic scenarios. A new verification approach, which combines the use of two well-known model checkers: model checker for multi-agent systems (MCMAS) and probabilistic model checker (PRISM), is presented for this purpose. The overall structure of our autonomous vehicle (AV) system consists of: (1) A perception system of sensors that feeds data into (2) a rational agent (RA) based on a belief–desire–intention (BDI) architecture, which uses a model of the environment and is connected to the RA for verification of decision-making, and (3) a feedback control systems for following a self-planned path. MCMAS is used to check the consistency and stability of the BDI agent logic during design-time. PRISM is used to provide the RA with the probability of success while it decides to take action during run-time operation. This allows the RA to select movements of the highest probability of success from several generated alternatives. This framework has been tested on a new AV software platform built using the robot operating system (ROS) and virtual reality (VR) Gazebo Simulator. It also includes a parking lot scenario to test the feasibility of this approach in a realistic environment. A practical implementation of the AV system was also carried out on the experimental testbed.
  • 关键词:self-driving vehicle; formal verification; model checking; rational agent; decision-making; ROS self-driving vehicle ; formal verification ; model checking ; rational agent ; decision-making ; ROS
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