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摘要: 为探究城市自行车交通系统出行品质的影响因素，从道路设施和路网两方面进行评价方法综述；在自行车道路设施评价方面，考虑了自行车交通流、自行车道设计要素、自行车出行环境、骑行者感知等方面因素，建立了自行车道通行能力、自行车道服务水平、自行车道安全性评价、骑行者压力、骑行者满意度等评价方法；在自行车路网评价方面，应用复杂网络、空间句法等拓扑分析方法，建立了自行车可达性、可骑行性等评价方法。研究结果表明：自行车道路设施评价方法中，评价对象从自行车向多模式交通转变，评价指标考虑了机动车、公交车、行人等因素对骑行的影响，评价角度从道路设计者向骑行者转变，逐步以骑行者感知代替设计者经验进行评价等级划分，骑行者感知数据多采用问卷、实验室录像、实地试验和虚拟环境试验等方法获取数据，建模方法以离散选择模型、统计分析、线性回归模型、结构方程模型为主，研究集中于心理感知的量测方法及影响机理，仍需深入研究生理感知对骑行者的影响机理，并结合个体性差异细化感知影响机理；自行车路网评价方法中，以复杂网络、空间句法为主的拓扑分析方法验证了路网拓扑关系对骑行者出行量的影响，自行车可达性考虑了骑行距离、出行目的地对骑行的影响，可骑行性综合考虑了路段设施与路网结构对骑行需求的影响，还需深入研究自行车路段设施与路网特性协同作用机理；未来需完善自行车道路设施全阶段评价体系，建立考虑自行车道路设施和路网结构的协同评价及优化方法，为自行车交通系统出行品质提升提供理论参考。Abstract: In order to investigate the influencing factors of travel quality for urban bicycle traffic system, a comprehensive review of the evaluation methods was carried out from the aspects of both road facilities and road networks. In the evaluation of road facilities, factors such as bicycle traffic flow, bicycle lane design elements, bicycle travel environment, and cyclist perception were considered, and evaluation methods such as bicycle lane passing capacity, bicycle lane service level, bicycle lane safety evaluation, cyclist stress, and cyclist satisfaction were established. In the evaluation of road networks, topological analysis methods such as complex networks and space syntax were applied, and evaluation methods such as bicycle accessibility and bikeability were established. Research results show that in the evaluation method of road facilities, the evaluation subject shifts from bicycles to multimodal transportation, and the evaluation metrics consider the impact of motor vehicles, buses, pedestrians, and other factors on cycling. The evaluation perspective transitions from focusing on road designers to cyclists, progressively substituting designer experiences with cyclist perceptions to determine evaluation levels. The data of cyclist perception is obtained by questionnaires, laboratory videos, field experiments, and virtual environment experiments, and the modeling methods are mainly discrete choice models, statistical analysis, linear regression models, and structural equation models. The research focuses on the measurement method and influencing mechanism of psychological perception. The influencing mechanism of the physiological perception of cyclists still needs to be studied in depth, and the influencing mechanism needs to be refined by taking into account individual differences. In the evaluation method of road network, the topological analysis method mainly based on complex network and spatial syntax verifies the influence of the topological relationship of road networks on the travel frequency of cyclists. Bicycle accessibility takes into account the influence of cycling distance and travel destinations on cycling, and bikeability comprehensively considers the influence of road facilities and road network structure on cycling demand. The synergistic mechanism of road facilities and road network characteristics still needs to be studied in depth. In the future, it is necessary to improve the evaluation system for road facilities of bicycles at all stages and establish synergistic evaluation and optimization methods that consider both road facilities and road network structure, and provide theoretical references for improving the travel quality of bicycle traffic systems.
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图 2 城市自行车交通系统出行品质评价方法
Figure 2. Travel quality evaluation method for urban bicycle traffic systems
图 3 骑行者满意度影响因素词云分析
Figure 3. Word cloud analysis of influencing factors of cyclist satisfaction
图 4 骑行者舒适度评价变量出现次数分布
Figure 4. Frequency distribution of cyclists' comfort evaluation variables
表 1 自行车道服务水平发展及影响因素
Table 1. Level of service development and influencing factors of bicycle lane
年份 研究者 数据来源 感知因素 服务水平分级 影响因素 1995 Botma[37] 现场调查/实验室录像 未考虑 6 障碍、延误、平均行程速度 1996 Dixon[38] 现场调查 出行者经验 6 设施供应、冲突、速度差、机动车服务水平、维护情况、是否存在运输需求管理计划或者过境的多式联运 1997 Landis等[39] 现场骑行 出行者感知 6 机动车交通量、车道数、机动车速度、重型车辆比例、土地利用强度、路侧停车数量、路面状况、外侧车道有效宽度 2000 HCM2000[16] 现场调查/实验室录像 未考虑 6 超车数、控制延误 2003 Landis等[40] 现场调查/实验室录像 出行者感知 6 骑行过街距离、机动车交通量、进口车道数、自行车道与外侧车道宽度 2007 Petritsch等[41] 现场调查/实验室录像 出行者感知 6 机动车交通量、车道数、机动车车速、重型车辆比例、路面状况、道路有效宽度 2008 Dowling [42] 现场调查/实验室录像 出行者感知 6 车道数、机动车交通量、机动车车速、重型车辆比例、路面状况、外侧车道有效宽度、路侧停车数量 2010 Li等[43] 现场调查 未考虑 6 超车数 2010 HCM2010[17] 现场调查/实验室录像 出行者感知 6 车道数、机动车交通量、机动车车速、重型车辆比例、路面状况、外侧车道有效宽度、路侧停车数量 2012 於昊等[44] 现场调查/实验室录像 出行者感知 6 共享道有效宽度、障碍物密度、交通冲突强度、各种非机动车速度和流量比例 2016 HCM2016[18] 现场调查 出行者感知 6 相遇数、主动超车数、道路宽度、中心线有无、延误超车数 2016 方雪丽等[45] 实验室录像 出行者感知 4 机动车流量、助动车混入率、非机动车道宽度、路面铺装质量、路边停车比例、上坡情况、路边遮阳比例、重型车流量 2017 同济大学交通运输工程学院[46] 实验室录像 出行者感知 4 机动车流量、助动车流量、助动车混入率、非机动车道宽度、路面铺装质量、路边停车比例、是否存在上坡、路边遮阳比例、重型车流量、绿视率、植物种类多样性、整洁度 2017 Beura等[47] 现场调查 出行者感知 6 道路宽度、机动车交通量、路面状况、自行车停车延迟、土地利用模式、街道停车周转率 2017 Beura等 [48] 现场调查 出行者感知 6 车道宽度、路面状况、交通量、交通速度、路边商业活动、未经授权中断公共交通、停车车辆启动并入、车道出现高交通量的频率 2018 Majumdar等[49] 现场调查 出行者感知 6 街头停车场数量、机动车辆数量、土地利用类型、路面状况评分、第85分位机动车速度 2019 Okon等[50] 视频调查 出行者感知 6 人行道与自行车道分离方式、自行车速度、机动交通量、与行人的冲突、自行车道宽度、外部车道、路面状况、树木、阳光、性别、骑车者的经验 2019 Zhang等[51] 现场调查/仿真试验 出行者感知 5 车流密度、速度道路宽度、车辆混合比、骑车人特征 2020 Beura等[52] 现场调查 出行者感知 6 引道有效宽度、引道高峰小时交通量、交叉口行人量、直行自行车道路上的转弯车辆交通量、直行自行车道路上的平均停车延误、街道停车周转量、周边发展模式 2022 HCM2022[19] 现场调查 出行者感知 6 相遇数、主动超车数、道路宽度、中心线有无、延误超车数 
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表 2 骑行安全评价方法
Table 2. Evaluation methods of riding safety
评价方法 评价对象 数据获取方法 研究方法 主要变量 BSIR(1987)[55] 路段 实地调查 多元线性回归 年平均日交通量、限速、车道数、外侧车道宽度、路面因素 RCI(1991)[56] 路段 实地调查 多元线性回归 年平均日交通量、限速、车道数、外侧车道宽度、路面因素、位置因素 MRCI(1994)[56] 路段 实地调查 多元线性回归 年平均日交通量、限速、重型车辆比例、车道数、外侧车道宽度、路面因素、位置因素 IHS(1994)[57] 路段 实地调查 多元线性回归 平均日交通量、限速、重型车辆比例、直行车道数、外侧车道宽度、路面因素、邻近路段的土地利用强度、路缘开口(或路边停车)频率 BCI(1997)[58] 路段 实地调查 多元线性回归 外侧车道宽度、外侧车道机动车交通量、右转交通量、重型车辆交通量、机动车速度、停车占有率是否超过30% CRC(2003)[59] 路段 实地调查 多元线性回归 路肩宽度、骑行空间、小汽车流量、道路材料、重型卡车流量、路侧情况、转向可见度 RBCI(2003)[60] 路段 实地调查 多元线性回归 路肩宽度、小汽车流量、是否有重型卡车、路侧情况 PSC(2023)[61] 路段 实地调查 有序回归模型 自行车道设计形式、道路标线、标志、交通量、车辆停放情况 BRSR(2003)[62] 路段、交叉口 新泽西州交通部数据库 多元Logistic 平均日交通量、车道宽度、竖向坡度、道路分级、单行道、人口密度 BISI(2007)[63] 交叉口 实地调查 多元线性回归 平均日交通量、过街骑手直行道路的转弯车辆、限速、直行车道数、右转车道数、自行车交叉口左转车道数、自行车交叉口右转车道数、是否存在自行车道、是否有路边停车、交叉口交通信号控制 PBIS(2018)[64] 交叉口 在线视觉调查 有序Probit 直行交通量、直行车道数、右转车道数、是否存在自行车道、是否存在人行横道、自行车箱、单行道、交叉口交通信号控制、交叉口类型、绿化 BSSI(2020)[65] 交叉口 实地调查、问卷调查 多元线性回归 自行车流量、是否存在铺装路肩、是否存在路缘匝道、是否存在自行车道、自行车停车站点、自行车等待区、标志标线、自行车租赁计划
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表 3 骑行者感知导向的自行车道路设施评价方法对比
Table 3. Comparison of evaluation methods of cyclists' perception oriented bicycle road facilities
方法类别 研究方法 评价对象 调查方法 特点 骑行者压力评价 归纳分析[78-80] 路段、交叉口 调查问卷、实地调查 评价标准基于研究者经验制定，考虑了骑行者类型的影响，评价变量较少，缺乏表征骑行者感知的深度研究 骑行者满意度评价 问卷数据分析[88-89]、结构方程模型[90-91, 94]、线性回归模型[92]、二元有序Probit模型[93] 公共自行车系统、路段 问卷调查 评价标准基于对调查问卷数据的分析，既有对自行车道路的评价也有对公共自行车系统的评价，评价方法较主观，不同研究中的骑行者满意度结果往往不具有可比性 骑行者舒适度评价 有序Probit模型[100]、多维统计分析[101]、多元线性回归[102]、XGBoost方法[103]、逐步回归[104]、遗传聚类[104] 路段 问卷调查、在线调查、实验室录像、骑行试验、实地调查 评价标准基于骑行者评价，研究多学科的角度，从路面属性、自行车结构、人体结构等方面对舒适度进行了评价，综合多学科知识对舒适度进行评价还需进一步探索 骑行者感知疲劳评价 试验数值对比分析[117]、多元线性回归[119-120] 路段 虚拟环境试验、骑行试验 评价标准基于试验测得的骑行者疲劳数值量化了骑行者感知，综合了医学、运动学方面的相关知识，评价角度较为客观，但数据规模较难扩大，数据获取较为困难
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表 4 自行车可达性模型对比
Table 4. Comparison of common accessibility models
类别 方法 文献 阻抗 优点 缺点 适用性 集计模型 空间阻隔模型 [157] 骑行距离、骑行出行时间、出行费用等 形式、含义简单 忽略了土地利用与交通需求；过多关注交通因素，应用范围非常有限 地理学、交通网络 累积机会模型 [150]、[153]~[155]、[158] 骑行时间、费用等 可解释性高 未考虑度量点和吸引点之间的作用及其效应随距离的衰减；衰减阈值难确定，取值为无穷大时失去意义 自行车基础设施规划(等时线、等费用线) 空间相互作用模型 [149]、[152] 仅骑行者出行距离 通俗易懂、意义明确，可解释性好、易于理解，同时数据容易获取 无法计算小区本身的可达性；仅考虑目的地对出发点的吸引力，未考虑对起点的需求；仅考虑不同区位的可达性，对个体的因素考虑较少 各种机会和设施的可达性研究 非集计模型 效用模型 [156] 交通因素、土地因素等 可利用非集计模型的结论 所需数据量大并且难于获取；不能有效体现土地利用、供给情况 边际效用分析 时空相互作用模型 [151] 各种机会 考虑了个体之间的差异以及时间、空间的约束情况 未考虑机会供给之间的竞争关系；所需数据量较大 分析骑行者个体效用
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