• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

理解自行车手交通违法行为与执法策略之间的相互作用：基于演化博弈论的分析。

Understanding the Interaction between Cyclists' Traffic Violations and Enforcement Strategies: An Evolutionary Game-Theoretic Analysis.

机构信息

School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China.

Department of Traffic Engineering & Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, 4800 Cao'an Road, Shanghai 201804, China.

出版信息

Int J Environ Res Public Health. 2020 Nov 15;17(22):8457. doi: 10.3390/ijerph17228457.

DOI:10.3390/ijerph17228457
PMID:33203158
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7697453/
Abstract

An evolutionary game-theoretic analysis method is developed in this study to understand the interactions between cyclists' traffic violations and the enforcement strategies. The evolutionary equilibrium stabilities were analysed under a fixed (FPS) and a dynamic penalty strategy (DPS). The simulation-based numerical experiments show that: (i) the proposed method can be used to study the interactions between traffic violations and the enforcement strategies; (ii) FPS and DPS can reduce cyclists' probability of committing traffic violations when the perceived traffic violations' relative benefit is less than the traffic violation penalty and the enforcement cost is less than the enforcement benefit, and using DPS can yield a stable enforcement outcome for law enforcement compared to using FPS; and (iii) strategy-related (penalty amount, enforcement effectiveness, and enforcement cost) and attitudinal factors (perceived relative benefit, relative public image cost, and cyclists' attitude towards risk) can affect the enforcement strategy's impacts on reducing cyclists' traffic violations.

摘要

本研究采用进化博弈理论分析方法，研究了自行车骑行者交通违法行为与执法策略之间的相互作用。在固定罚款策略（FPS）和动态罚款策略（DPS）下，分析了进化均衡稳定性。基于模拟的数值实验表明：（i）所提出的方法可用于研究交通违法行为与执法策略之间的相互作用；（ii）当感知到的交通违法行为的相对收益小于交通违法行为的罚款和执法成本小于执法收益时，FPS 和 DPS 可以降低自行车骑行者交通违法行为的概率，与使用 FPS 相比，使用 DPS 可以为执法带来更稳定的执法结果；（iii）策略相关因素（罚款金额、执法效果和执法成本）和态度因素（感知的相对收益、相对公共形象成本和自行车骑行者对风险的态度）会影响执法策略对减少自行车骑行者交通违法行为的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/c6a9f869592a/ijerph-17-08457-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/c09fc6b7d8fa/ijerph-17-08457-g0A1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/2966cc716a25/ijerph-17-08457-g0A2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/b55c473b9c1b/ijerph-17-08457-g0A3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/15d3e5a41a4c/ijerph-17-08457-g0A4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/7640f6628690/ijerph-17-08457-g0A5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/ccaf1495fbd8/ijerph-17-08457-g0A6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/57b396bd325e/ijerph-17-08457-g0A7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/55772da38b0f/ijerph-17-08457-g0A8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/05f4561a9d3d/ijerph-17-08457-g001a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/969510dc701b/ijerph-17-08457-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/7cccf694b268/ijerph-17-08457-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/514572765965/ijerph-17-08457-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/e58f1142498c/ijerph-17-08457-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/938b095e69cf/ijerph-17-08457-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/6fce93628bb5/ijerph-17-08457-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/2b44e5d1cdc2/ijerph-17-08457-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/ab5beaff1e1b/ijerph-17-08457-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/c6a9f869592a/ijerph-17-08457-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/c09fc6b7d8fa/ijerph-17-08457-g0A1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/2966cc716a25/ijerph-17-08457-g0A2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/b55c473b9c1b/ijerph-17-08457-g0A3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/15d3e5a41a4c/ijerph-17-08457-g0A4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/7640f6628690/ijerph-17-08457-g0A5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/ccaf1495fbd8/ijerph-17-08457-g0A6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/57b396bd325e/ijerph-17-08457-g0A7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/55772da38b0f/ijerph-17-08457-g0A8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/05f4561a9d3d/ijerph-17-08457-g001a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/969510dc701b/ijerph-17-08457-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/7cccf694b268/ijerph-17-08457-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/514572765965/ijerph-17-08457-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/e58f1142498c/ijerph-17-08457-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/938b095e69cf/ijerph-17-08457-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/6fce93628bb5/ijerph-17-08457-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/2b44e5d1cdc2/ijerph-17-08457-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/ab5beaff1e1b/ijerph-17-08457-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d71d/7697453/c6a9f869592a/ijerph-17-08457-g010.jpg

相似文献

1
Understanding the Interaction between Cyclists' Traffic Violations and Enforcement Strategies: An Evolutionary Game-Theoretic Analysis.理解自行车手交通违法行为与执法策略之间的相互作用：基于演化博弈论的分析。
Int J Environ Res Public Health. 2020 Nov 15;17(22):8457. doi: 10.3390/ijerph17228457.
2
Speed enforcement in Norway: Testing a game-theoretic model of the interaction between drivers and the police.挪威的速度执法：测试驾驶员与警察互动的博弈论模型。
Accid Anal Prev. 2015 Nov;84:128-33. doi: 10.1016/j.aap.2015.08.017. Epub 2015 Sep 3.
3
Assessing the efficiency of priorities for traffic law enforcement in Norway.评估挪威交通执法优先级的效率。
Accid Anal Prev. 2012 Jul;47:146-52. doi: 10.1016/j.aap.2012.01.017. Epub 2012 Feb 8.
4
Social Influence and Different Types of Red-Light Behaviors among Cyclists.社会影响与自行车骑行者的不同类型闯红灯行为
Front Psychol. 2016 Nov 22;7:1834. doi: 10.3389/fpsyg.2016.01834. eCollection 2016.
5
Red-light running behavior of cyclists in Italy: An observational study.意大利自行车闯红灯行为：一项观察性研究。
Accid Anal Prev. 2018 Nov;120:219-232. doi: 10.1016/j.aap.2018.08.013. Epub 2018 Aug 29.
6
The impact of traffic violations on the estimated cost of traffic accidents with victims.交通违法行为对有受害者的交通事故预估成本的影响。
Accid Anal Prev. 2010 Mar;42(2):709-17. doi: 10.1016/j.aap.2009.10.020. Epub 2009 Nov 22.
7
The impacts of non-motorized traffic enforcement cameras on red light violations of cyclists at signalized intersections.非机动交通执法摄像头对信号控制交叉口自行车闯红灯行为的影响。
J Safety Res. 2022 Dec;83:310-322. doi: 10.1016/j.jsr.2022.09.005. Epub 2022 Sep 20.
8
Impact evaluation of camera enforcement for traffic violations in Cali, Colombia, 2008-2014.哥伦比亚卡利市 2008-2014 年交通违规行为摄像执法效果评估。
Accid Anal Prev. 2019 Apr;125:267-274. doi: 10.1016/j.aap.2019.02.002. Epub 2019 Feb 22.
9
Traffic law enforcement in Hyderabad, India.印度海得拉巴的交通执法。
Int J Inj Contr Saf Promot. 2005 Sep;12(3):167-76. doi: 10.1080/17457300500088840.
10
An integrated approach to evaluate policies for controlling traffic law violations.一种综合的方法来评估控制交通违法行为的政策。
Accid Anal Prev. 2010 Mar;42(2):427-36. doi: 10.1016/j.aap.2009.09.004. Epub 2009 Oct 1.

本文引用的文献

1
Investigating the Impacts of Real-Time Weather Conditions on Freeway Crash Severity: A Bayesian Spatial Analysis.研究实时天气条件对高速公路事故严重程度的影响：贝叶斯空间分析。
Int J Environ Res Public Health. 2020 Apr 17;17(8):2768. doi: 10.3390/ijerph17082768.
2
Investigation on the Injury Severity of Drivers in Rear-End Collisions Between Cars Using a Random Parameters Bivariate Ordered Probit Model.基于随机参数双变量有序概率模型的汽车追尾事故中驾驶员损伤严重程度的研究。
Int J Environ Res Public Health. 2019 Jul 23;16(14):2632. doi: 10.3390/ijerph16142632.
3
(E-)Cyclists running the red light - The influence of bicycle type and infrastructure characteristics on red light violations.
（电动）自行车闯红灯——自行车类型和基础设施特征对闯红灯行为的影响。
Accid Anal Prev. 2019 Jan;122:99-107. doi: 10.1016/j.aap.2018.10.002. Epub 2018 Oct 16.
4
Red-light running behavior of cyclists in Italy: An observational study.意大利自行车闯红灯行为：一项观察性研究。
Accid Anal Prev. 2018 Nov;120:219-232. doi: 10.1016/j.aap.2018.08.013. Epub 2018 Aug 29.
5
Analysis of hourly crash likelihood using unbalanced panel data mixed logit model and real-time driving environmental big data.利用非平衡面板数据混合逻辑回归模型和实时驾驶环境大数据分析小时级事故可能性
J Safety Res. 2018 Jun;65:153-159. doi: 10.1016/j.jsr.2018.02.010. Epub 2018 Apr 25.
6
Crash Frequency Modeling Using Real-Time Environmental and Traffic Data and Unbalanced Panel Data Models.使用实时环境和交通数据以及不平衡面板数据模型的碰撞频率建模
Int J Environ Res Public Health. 2016 Jun 18;13(6):609. doi: 10.3390/ijerph13060609.
7
A study of driver's route choice behavior based on evolutionary game theory.基于进化博弈理论的驾驶员路径选择行为研究
Comput Intell Neurosci. 2014;2014:124716. doi: 10.1155/2014/124716. Epub 2014 Dec 29.
8
More screen operation than calling: the results of observing cyclists' behaviour while using mobile phones.使用手机时屏幕操作多于通话：观察骑自行车者行为的结果
Accid Anal Prev. 2015 Mar;76:42-8. doi: 10.1016/j.aap.2015.01.004. Epub 2015 Jan 12.
9
A hazard-based duration model for analyzing crossing behavior of cyclists and electric bike riders at signalized intersections.一种基于风险的持续时间模型，用于分析信号交叉口处自行车骑行者和电动自行车骑行者的过街行为。
Accid Anal Prev. 2015 Jan;74:33-41. doi: 10.1016/j.aap.2014.10.014. Epub 2014 Oct 22.
10
Prospect theory based estimation of drivers' risk attitudes in route choice behaviors.基于前景理论的驾驶员路线选择行为风险态度估计
Accid Anal Prev. 2014 Dec;73:1-11. doi: 10.1016/j.aap.2014.08.004. Epub 2014 Aug 27.