考虑奖惩机制下城市道路预约出行模式效益研究  

Research on the Benefits of Urban Road Travel Reservation Mode Considering Reward and Punishment Mechanism

作　　者：陈恒瑞 周睿予 陈红[2] CHEN Heng-rui;ZHOU Rui-yu;CHEN Hong(School of Transportation,Fujian University of Technology,Fuzhou 350001,Fujian,China;College of Transportation Engineering,Chang'an University,Xi'an 710064,Shaanxi,China)

机构地区：[1]福建理工大学交通运输学院,福建福州350001 [2]长安大学运输工程学院,陕西西安710064

出　　处：《中国公路学报》2025年第2期258-273,共16页China Journal of Highway and Transport

基　　金：国家自然科学基金项目(52302385);福建理工大学科研启动项目(GY-Z23212)。

摘　　要：面向提高城市交通需求管理措施精细化水平的现实需求,探究了引入奖惩措施后城市道路预约出行模式对异质用户及路网的影响。既有道路预约出行模式研究存在偏重于静态的出行方案评价,道路预约容量确定缺乏理论依据,且出行服务手段片面化、用户出行选择同质化以及未充分考虑个体出行的多维决策变量环境和城市多模式交通协同作用的问题。鉴于此,首先采用删失数据模型和乘积极限法估计道路容量分布函数,引入持续流动指数,确定预约路段的最佳预约总量;其次,引入针对用户的补贴激励和违约惩罚机制,构建基于智能体的多目标优化模型。一方面,综合考虑管理者和出行者利益,构建多目标优化模型,优化设计面向社会效益最大化的出行奖惩方案。另一方面,在个体出行的多维决策变量环境下,基于用户预约出行信息、路网实时交通态势研判、道路供需匹配现状等多源交通信息,构建基于智能体的多模式动态交通仿真模型。研究结果表明:①道路最佳预约总量的范围为道路实际通行能力的0.79~0.89;②实施预约出行策略后路网交通性能及拥堵时空分布不均衡得到了显著改善,具体而言,引入奖惩机制后路网机动车流量及平均饱和度较策略实施前分别改善了4.8%和13.3%;③引入奖惩机制后,参与预约出行的用户比例增加了48.5%,且出行者调整出行时间的意愿显著增强;④时间价值不同的异质出行者受预约出行策略的影响呈现出显著的差异。研究结果揭示了预约出行模式对用户出行模式转变和系统运行性能提升的具体效益,为城市交通拥堵治理提供了新的思路和方法,助力城市交通系统的可持续发展。To address the practical need for enhancing the refinement level of urban traffic demand management measures,this study explores the impact of introducing a subsidy and penalty mechanism into urban road travel reservation strategy(TRS)on heterogeneous users and the road network.Existing studies on TRS predominantly focus on static evaluations and lack the theoretical foundation for determining optimal reservation volume.Thus,they exhibit limitations in travel service methods and homogeneous travel choices.They also do not sufficiently consider the multidimensional decision variables of individual travel and the synergetic effects of urban multimode transportation.First,the road capacity distribution function was estimated using censored data models and the product limit method,introducing the sustained flow index to determine the optimal reservation volume for reserved roads.Second,a subsidy incentive and default penalty mechanism was introduced for users,to build an agent-based multi-objective optimization model,with the objective of designing travel incentive schemes aimed at maximizing social benefits,considering the interests of both managers and travelers.Within the context of multidimensional decision variables in individual travel,an agent-based multimode dynamic traffic simulation model was constructed based on users'travel reservation information,real-time traffic conditions,and the current state of road supply and demand matching multiple traffic information sources.The results indicate that:the optimal reservation volume ranged from approximately 0.79 to 0.89 of the actual road capacity.After implementing TRS,traffic performance and spatial-temporal distribution of congestion in the road network significantly improved.Specifically,with the introduction of the reward and punishment mechanism,the motor vehicle flow and average saturation of the road network improved by 4.8%and 13.3%,respectively,compared to without the strategy implementation.After introducing the reward and punishment mechanism,the prop

关 键 词：交通工程 城市交通 多模式动态交通仿真 预约出行 交通拥堵 最佳预约容量 

分 类 号：U491[交通运输工程—交通运输规划与管理]