Journal of Transportation Systems Engineering and Information Technology ›› 2022, Vol. 22 ›› Issue (1): 152-162.DOI: 10.16097/j.cnki.1009-6744.2022.01.017

Previous Articles     Next Articles

Utility Simulation Evaluation of Dynamic Fines Strategy for Illegal Parking Based on Evolutionary Game

MOU Zhen-hua1 , WANG Han-bing1 , LIN Ben-jiang2 , CHEN Yi-qun1, JIN Cheng-cheng1 , CHEN Yan-yan* 3   

  1. 1. School of Transportation Engineering, Shandong Jianzhu University, Jinan 250101, China; 2. Jinan Urban Planning and Design Institute,Jinan 250000, China;3. College of Metropolitan Transportation, Beijing University of Technology, Beijing 100124, China
  • Received:2021-08-19 Revised:2021-10-28 Accepted:2021-11-02 Online:2022-02-25 Published:2022-02-23
  • Supported by:
    The Ministry of Education of Humanities and Social Science Project(19YJC630124)。

基于演化博弈的违章停车动态罚金策略效用仿真评价

牟振华1,汪寒冰1,林本江2,陈逸群1,金程程1,陈艳艳* 3   

  1. 1.山东建筑大学,交通工程学院,济南 250101;2. 济南市规划设计研究院,济南250000; 3. 北京工业大学,城市交通学院,北京 100124
  • 作者简介:牟振华(1983- ),男,山东高唐人,教授,博士。
  • 基金资助:
    教育部人文社科基金

Abstract: This paper aims to study the inhibitory effect of the improved dynamic fines strategy on illegal parking and obtain the optimal solution of the strategy. In this paper, the drivers and law enforcers are the two groups of players in the game. Based on the improved copy dynamic equation, the dynamic fines optimal control model is established with the goal of minimizing the total social cost. Then the equilibrium point and stability of the model are discussed, and the optimal solution of the model is solved by the Pontryagin principle of minimum. Finally, simulation tests were carried out on the violation restraint effect and the strategy cost of the dynamic fines strategy before and after the improvement. The simulation results show that: (1) The improved dynamic fines model can find a reasonable evolution direction of the parking violation problem, which can reduce the intensity of law enforcement while continuously reducing the probability of violation; (2) In a critical state, that is, the dynamic fine coefficient tends to a stable value, and the law enforcer maintains a short-term continuous law enforcement state. The improved dynamic fines strategy can reduce the amount of fines by changing the commonly used fine methods to realize the governance of illegal parking problems; (3) In terms of the efficiency of governing illegal parking, the critical state is compared with the most sensitive state, that is, continuous law enforcement is twice as fast as dynamic law enforcement; (4) Compared with the dynamic fines strategy before the improvement, the improved dynamic fines strategy has stronger violation restraint, lower strategy cost, and longer-lasting law enforcement effectiveness. The required enforcement is lower andthere will be no recurrence of illegal parking cycles in a short period of time

Key words: urban traffic, parking fines, asymmetric evolutionary game, dynamic fines strategy, dynamic optimal control

摘要: 为研究改进后的动态罚金策略对违章停车现象的抑制作用及策略最优解,本文以驾驶员和执法者两类群体作为博弈主体,在改进的复制动态方程基础上,以社会总成本最小为目标建立动态罚金最优控制模型。讨论了该模型的均衡点及其稳定性,并通过庞特里亚金极小值原理求解该模型的最优解。并对改进前、后动态罚金策略的违章抑制作用和策略成本进行数据仿真检验,仿真结果显示:改进后的动态罚金模型能够找到违章停车问题的合理演化方向,在不断降低违章概率的同时还能减少执法力度;在临界状态下,即动态罚金系数趋于稳定值、执法者保持短时间的持续执法状态,改进的动态罚金策略通过改变常用的罚款方式,即降低罚款金额实现对违章停车问题的治理(在治理违章停车的效率上,临界状态与敏感度最高状态相比,即连续执法与动态执法相比治理速度提高了1倍);改进后的动态罚金策略较改进前的违章抑制性更强、策略成本更低、执法效力更持久、所需执法力度更低,且短时间内不会出现违章停车周期复现的情景。

关键词: 城市交通, 违章停车罚金, 非对称演化博弈, 动态罚金策略, 动态最优控制

CLC Number: