Application of networked discrete event system theory on intelligent transportation systems
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Application of networked discrete event system theory on intelligent transportation systems Jiayuan Liang1 · Chaohui Gong2 · Yunfeng Hou1 · Miao Yu2 · Weilin Wang2 Received: 20 November 2019 / Revised: 11 May 2020 / Accepted: 14 May 2020 © South China University of Technology, Academy of Mathematics and Systems Science, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract The responses of vehicles to the changes in traffic situations inevitably have delays in observing an event and implementing a control command, which often causes fatal accidents. So far, the methods for handling delays are empirical and cannot be mathematically proven. To eliminate the accidents caused by such delays, in this paper, we develop mathematically provable methods to handle these delays. Specifically, we use networked discrete event systems to model the process of driving vehicles and present a supervisory controller for handling delay situations. The method developed in this paper could serve as a new start for modeling and controlling the responsive behaviors of self-driving vehicles in the future. Keywords Discrete event systems · Automata · Supervisory control · Automated driving systems
1 Introduction To avoid accidents, we need to consider the delays in drivers’ responses to traffic situations. An example of this situation is that the traffic signal is switching to red when a full-speed vehicle goes through an intersection. To handle this, the green signal for the conflict path usually starts about 5 s later after the red signal switches on. This empirical measure accommodates the vehicle response delay to changing traffic signals and helps to avoid potential collisions. * Chaohui Gong [email protected] Jiayuan Liang [email protected] Yunfeng Hou [email protected] Miao Yu [email protected] Weilin Wang [email protected] 1
School of Optical‑Electrical and Computer Engineering, University for Shanghai Science and Technology, Shanghai 200093, China
Zhejiang Research Center on Smart Rail Transportation, PowerChina Huadong Engineering Corporation Limited, Hangzhou, Zhejiang 311225, China
2
Many traffic regulations are to prevent accidents caused by response delays or at least mitigating their consequences. For example, the 2-s rule in driving aims to allow for the reaction time to unexpected event occurrences. At a high-level, the dynamics of driving a vehicle consist of occurrences of events that change driving conditions and traffic situations that could potentially lead to an accident. Discrete event system (DES) models such dynamics are driven by asynchronous occurrences of events. The events in driving vehicles include arriving at an intersection, switching the signal to red, entering a street section, etc. In the DES model of driving a vehicle, we emphasize delays in the driver’s responses to changing traffic situations. In 1987 Ramadge and Wonham initiated the field of supervisory control of a discrete event system, which aims to prevent undesired event sequences [1]. T
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