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Driving Authority Allocation Strategy Based on Driving Authority Real-Time Allocation Domain

Ziyu Zhang, Chunyan Wang, Wanzhong Zhao, Can Xu, Guoping Chen

2021IEEE Transactions on Intelligent Transportation Systems37 citationsDOI

Abstract

In the switching process of driving authority for man-machine cooperative driving, it should be ensured that the driver can take over the vehicle safely, stably and efficiently. This paper proposes a driving authority allocation strategy based on real-time allocation domain (RAD), which mainly includes the establishment of RAD and the dynamic optimization. The RAD is a comprehensive dynamic allocation internal, whose range is determined by the corresponding allocation values of driver’s cognitive state, driver’s muscle state and environment state. The dynamic optimization is to search for the optimal driving authority in RAD at any time, and its optimization objectives and constraints all contain time-varying parameters. This work proposes an improved simulated annealing algorithm to solve this problem. Simulation results show that the proposed driving authority allocation strategy can effectively allocate the driving authority according to the current condition and driver’s state, and ensure the safety, stability and efficiency of the take-over process.

Topics & Concepts

Process (computing)Simulated annealingOptimal allocationComputer scienceDomain (mathematical analysis)State (computer science)Time domainEngineeringMathematical optimizationAlgorithmOperating systemMathematical analysisMathematicsComputer visionAutonomous Vehicle Technology and SafetyHuman-Automation Interaction and SafetyTraffic control and management
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