基于博弈论的城市道路违章停车治理

尤冬梅

交通运输研究 ›› 2017, Vol. 3 ›› Issue (3) : 30-35.

PDF(1309 KB)
PDF(1309 KB)
交通运输研究 ›› 2017, Vol. 3 ›› Issue (3) : 30-35.
专题

基于博弈论的城市道路违章停车治理

  • 尤冬梅
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Urban Parking Violation Governance Based on Game Theory

  • YOU Dong-mei
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文章历史 +

摘要

为改善违章停车问题、提高城市管理水平,运用博弈论理论对城市道路违章停车进行分析 与研究。将停车问题涉及的监督部门、执法人员、驾驶人视为互相竞争者,考虑博弈各方的支付函数和效用最大化,建立监管部门与驾驶人、驾驶人与驾驶人之间的混合博弈模型,得出监管部 门执法成本和驾驶员违章成本的纳什均衡值,获得了违章停车行为中各方的最优效用。研究结果表明:在一定的执法成本下,交通执法者会采取相应的执法力度,驾驶人违章停车的概率会降 低。同时,驾驶人违章收益期望值越高,其违章停车的可能性会越大。不同驾驶人违章停车亦存在博弈现象,是否同时选择违章停车取决于共同的违章成本。当违章成本处于一定水平之下时,驾驶员之间的违章行为会发生传播效应。

Abstract

In order to improve the problem of parking violation and increase the level of urban management, the game theory was used to analyze and study urban parking violation. The supervision department, law enforcement officers and drivers were considered as competitors. Considering the payment function and utility maximization of the game participants, the mixed game model between the supervision department and drivers, and that between drivers and drivers were established. The Nash equilibrium values of regulatory costs and drivers′ illegal costs were obtained, and the optimal utility of each participant was gained. The results show that traffic enforcers will take the corresponding law enforcements under certain law enforcement cost, and the probabilities of parking violation will reduce. At the same time, the higher the drivers′ expected values on parking violation, the greater the possibilities of parking violation will be. There are also game phenomenon of different drivers′ parking violation, whether they have the same violation choice depends on the common violation cost. When the violation cost is below a certain level, the driver′s violation behaviors will spread.

关键词

交通管理 / 违章停车 / 停车政策 / 博弈论 / 纳什均衡

Key words

traffic management / parking violation / parking policy / game theory / Nash equilibrium

引用本文

导出引用
尤冬梅. 基于博弈论的城市道路违章停车治理[J]. 交通运输研究. 2017, 3(3): 30-35
YOU Dong-mei. Urban Parking Violation Governance Based on Game Theory[J]. Transport Research. 2017, 3(3): 30-35

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