机构地区:[1]北京工业大学,交通工程北京市重点实验室,北京100124 [2]北京工业大学,交通运输部城市公共交通智能化行业重点实验室,北京100124 [3]北京工业大学,北京市城市交通运行保障工程技术研究中心,北京100124
出 处:《交通运输工程与信息学报》2024年第2期1-20,共20页Journal of Transportation Engineering and Information
基 金:教育部人文社会科学研究规划基金项目(23YJAZH228);北京市自然科学基金-丰台轨道交通前沿研究联合基金项目(L231025)。
摘 要:科学评价公交服务水平是优化公交系统性能的前提,能为政策制定与管理措施的改进提供方向,对促进公共交通优先发展有重要意义。针对评价维度单一导致的系统整体水平反映不充分的问题,本文从公交系统运营效率、运营服务质量、满意度及智能化等四个方面介绍国内外的最新研究现状,归纳总结了公交系统运营效率与服务质量评价的科学问题,包括时刻表优化以及效率评价指标选取、指标主观性的弱化、目标群体的划分与研究视角的选取;归纳分类了公交运营效率与服务质量评价的研究内容与模型,运营效率评价中较多考虑线路、线网相关指标,运营服务质量评价中较多考虑基础设施相关指标,用户满意度评价中较多选取乘客感受相关指标,智能化评价中较多选取数据处理与信息服务能力相关指标;分析了不同评价维度指标选取的共性与差异性,以及交叉指标之间的相互作用对公交系统整体评价的影响。最后提出未来研究方向:构建公交服务评价体系时应考虑企业、政府与乘客三者视角,提升评价体系完备性;评价过程中需注重多模式交通特性,将系统协同化、网联化、智慧化等因素纳入指标范围,并协同考虑城市的地域特点及出行需求特点;根据技术革新及行业发展态势,对于社区公交、无障碍公交、需求响应公交等多样性的公交运营模式,公交应急服务水平与绿色出行也需构建相应指标。The scientific assessment of the levels of bus service is a prerequisite for optimizing bus system performance,as it provides directions for policy formulation and guiding improvements in management measures.The assessment has significant importance in promoting the prioritized devel‐opment of public transport.As the overall level of the bus system is not fully shown because of the single evaluation dimension,this study introduced the latest domestic and international research on the operational efficiency,operational service quality,satisfaction,and intelligence of bus systems.The study discussed the scientific challenges in evaluating bus operational efficiency and service quality,covering aspects such as the optimization of timetables,selection of efficiency evaluation metrics,reduction of metric subjectivity,definition of target groups,and selection of research per‐spectives.It categorized and outlined the content and models used to evaluate bus operation efficien‐cy and operational service quality.When evaluating operational efficiency,the focus is on metrics re‐lated to bus lines and networks,whereas the evaluation of operational service quality focuses on met‐rics associated with infrastructure.Satisfaction evaluation primarily incorporates metrics related to passengers,whereas data processing and information service capabilities are primarily considered when evaluating intelligence.This study analyzed the similarities and differences in metric selection across various evaluation dimensions and explored the impact of the interaction between crossed met‐rics on the comprehensive evaluation of the system.Finally,the following directions for future re‐search are proposed.When building a bus service evaluation system,the enterprises,governments,and passengers should be considered to enhance the completeness of the evaluation system.During the evaluation process,it is necessary to emphasize the characteristics of multimode transportation.Factors such as system collaboration,networking,and intellig
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