Development of Safety control for Hidden Mode Hybrid Systems andVerification in the Multi-vehicle lab.

Safety Control in Hybrid Systems;Intelligent Transportation Systems;Collision Avoidance;Electrical Engineering;Engineering;Electrical Engineering: Systems

Verma, RajeevSun, Jing ;

University of Michigan

关键词: Safety Control in Hybrid Systems;    Intelligent Transportation Systems;    Collision Avoidance;    Electrical Engineering;    Engineering;    Electrical Engineering: Systems;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/86477/rajverma_1.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

In this thesis, we consider the safety control problem for Hidden Mode Hybrid Systems(HMHS), which are a special class of hybrid automata in which the mode is not availablefor control. For these systems, safety control is a problem with imperfect state information.We tackle this problem by introducing the notion of non-deterministic discrete informationstate and by then translating the problem to one with perfect state information. The perfectstate information control problem is obtained by constructing a new hybrid automaton,whose discrete state is an estimate of the HMHS mode and is thus available for control.This problem is solved by computing the capture set and the least restrictive control mapfor the new hybrid automaton. Sufficient conditions for the termination of the algorithm that computes the capture set are provided. We show that the solved perfect state informationcontrol problemis equivalent to the original problemwith imperfect state information undersuitable assumptions on the original HMHS.A multi-vehicle roundabout test-bed is developed that employs scaled vehicles that aredesigned to have longitudinal dynamical response similar to a full scale vehicle. The applicationof the proposed formal hybrid control approach to the collision avoidance problem between an autonomous vehicle and a human driven vehicle at a traffic intersection is experimentallyillustrated in the multi-vehicle test-bed. We model the human driving behaviorthrough a hybrid automaton, whose current mode is determined by the driver’s decisions.On the autonomous vehicle, we implement formal methods for safety control, in whicha mode estimator identifies in real time the current human driving behavior and uses thisinformation to update a hybrid feedback map. The experimental results demonstrate thatthe solution proposed in this thesis is substantially less conservative than solutions employing worst-case design. Furthermore, they also demonstrate that, in structured tasks, humanbehavior can be reliably modeled and recognized for safety-critical closed loop controlapplications.