英文原文
Appendix G: Bicycle Quality of Service on Rural Highways, Survey of Bicyclists. The user survey aims to identify the drives and constraints on rural cycling, either for commuting or leisure, for different user types. The results will indicate which variables are more relevant to users to cycle (or not) on rural highways. Based on the results, we will recommend future research on improving and revising existing HCM’s BLOS evaluation and Green Book design guidance to accommodate users’ revealed preferences. The survey was designed in LimeSurvey and contained the following main sections: Introduction and welcome, Bicyclist segmentation, Choice tasks, Instructions for rural highway scenarios, Rural highway scenarios (first four choice tasks), Rural highway scenarios (second four choice tasks), User type specific questions, Leisure cycling experience on rural highways, Typical cycling experience, Closing. A total of 1650 persons entered the survey and 1049 completed the survey (63.57 percent of respondents). The respondents are primarily males (N = 701, 67.93%), aged 60 or more (N = 513, 49.71%), with high annual household income (N = 460, 44.57%) and commuting by car (N = 422, 40.89%) or bicycle (N = 174, 16.86%). Most respondents were all-year-round (N = 685, 66.38%) or seasonal cyclists (N = 200, 19.38%). The elements that survey respondents felt were most important when riding their bicycles were clearance, automobile traffic volume, and speed. Among them, clearance was the most relevant in the three analyses. Clearance-related elements presented the largest log odds in the stated rank of elements, the presence of the shoulder and its width had the highest impact on the probability of being selected in one scenario in the choice task, and bicycle infrastructure produced the highest log-odds to move to a higher comfort category in the stated cycling comfort evaluation. The conclusions of the study are limited to the designed questionnaire and the collected responses. The survey was targeted at individuals who cycle on rural highways, and therefore, the extrapolation of these results to the overall cycling population or urban cyclists in specific geographical areas should be undertaken with caution. Based on these conclusions, the recommendations of the study are: HCM bicycle analysis procedure should be revisited for rural highways, as the perception of cyclists differs from urban segments. BLOS scores by context classification (rural, rural–town) and facility type (shared lanes, paved shoulder) should be distinct, as their sensitivity to variables differed. For that, subjective comfort levels should be collected at least based on shoulder width, speed, automobile traffic volume, presence of heavy vehicles, pavement conditions, and context classification. Other aspects include maintenance of paved shoulders, grades, or intersections. Grades should be represented with caution, as they could be misinterpreted by scenery quality. It is recommended to derive criteria following the HCM-LOS approach to provide more sensitivity to infrastructure changes. LTS bicycle analysis procedure should be revisited for rural highways. LTS criteria should account for clearance and traffic volume and could include the effect of speed, pavement quality, and terrain. Sensitivity to elements seemed to be equal across all groups, and the more confident groups generally had a more significant likelihood of selecting to cycle in each scenario. More research is required to validate LTS-based design criteria with user comfort perception and to choose the most appropriate target user(s). For bicycle operational analyses on rural highways, with an increased project complexity and detail level, the HCM analysis procedure is preferred. This method is sensitive to more variables; therefore, specific countermeasures' impact is covered (e.g., increasing bicycle lane width). LTS could also be used, although the results may be less sensitive to improvements beyond changes to facility type, automobile running speed, or automobile traffic volume. For planning applications, such as regional transport planning or transportation system plans, the LTS approach is preferred. These applications may not require a specific analysis of the facility but rather an overview of which users would be served to identify key locations where the bicycle network should be improved. For such applications, the LTS is preferred. The HCM analysis procedure should not be used, as data availability would be limited. More research is needed to define target bicycle users, identify their main characteristics, and evaluate their comfort level in different environments. Both classifications by confidence and frequency could be combined. Seasonal variations must be considered when classifying cyclists by their frequency. The most representative bicyclist user for rural highways, and therefore target user, is “enthused and confident.” For some sites where moderate bicycle volumes are expected, the target bicycle user should be “interested but concerned.” This research points to the need for future discussions on the role of bicycle user segmentation for operational analyses and the need for a planning methodology. If the HCM analysis procedure aligns with the current LTS-based design criteria, different LOS thresholds should be considered for bicycle users. The most important characteristics have been identified, but specific criteria and thresholds still need to be defined. On the other hand, a planning methodology for bicycle mode based on the LTS should be developed based on users’ perceptions and incorporated into NCHRP Report 825: Planning and Preliminary Engineering Applications Guide to the Highway Capacity Manual (Dowling et al. 2016). Even though this effort was intended for rural highways, it could also provide a sound basis for a potential review of cycling performance evaluation on urban streets.
中文翻译
附录G：农村公路自行车服务质量调查，骑行者调查。用户调查旨在识别不同用户类型在农村骑行（无论是通勤还是休闲）的驱动因素和限制因素。结果将表明哪些变量对用户在农村公路上骑行（或不骑行）更为相关。基于这些结果，我们将建议未来的研究，以改进和修订现有的HCM BLOS评估和绿皮书设计指南，以适应用户揭示的偏好。该调查在LimeSurvey中设计，包含以下主要部分：介绍和欢迎、骑行者分类、选择任务、农村公路场景说明、农村公路场景（前四个选择任务）、农村公路场景（后四个选择任务）、用户类型特定问题、农村公路休闲骑行体验、典型骑行体验、结束部分。共有1650人进入调查，1049人完成调查（占受访者的63.57%）。受访者主要为男性（N = 701，67.93%），年龄在60岁或以上（N = 513，49.71%），家庭年收入高（N = 460，44.57%），通勤方式为汽车（N = 422，40.89%）或自行车（N = 174，16.86%）。大多数受访者为全年骑行者（N = 685，66.38%）或季节性骑行者（N = 200，19.38%）。调查受访者认为骑行时最重要的元素是侧向净空、汽车交通量和速度。其中，侧向净空在三个分析中最为相关。侧向净空相关元素在陈述排名中呈现最大的对数几率，路肩的存在及其宽度在选择任务中对场景被选中的概率影响最大，自行车基础设施在陈述骑行舒适度评估中产生最高的对数几率以移动到更高的舒适类别。该研究的结论受限于设计的问卷和收集的回应。调查针对在农村公路上骑行的个体，因此，将这些结果外推到整体骑行人群或特定地理区域的都市骑行者时应谨慎。基于这些结论，研究的建议是：应重新审视农村公路的HCM自行车分析程序，因为骑行者的感知与都市路段不同。根据背景分类（农村、农村-城镇）和设施类型（共享车道、铺装路肩）的BLOS评分应有所区别，因为它们对变量的敏感性不同。为此，应至少基于路肩宽度、速度、汽车交通量、重型车辆存在、路面条件和背景分类收集主观舒适度水平。其他方面包括铺装路肩的维护、坡度或交叉口。坡度应谨慎表示，因为它们可能被误解为风景质量。建议遵循HCM-LOS方法推导标准，以提供对基础设施变化的更高敏感性。应重新审视农村公路的LTS自行车分析程序。LTS标准应考虑侧向净空和交通量，并可包括速度、路面质量和地形的影响。对所有群体的元素敏感性似乎相等，更自信的群体通常更有可能选择在每个场景中骑行。需要更多研究来验证基于LTS的设计标准与用户舒适度感知，并选择最合适的目标用户。对于农村公路的自行车运营分析，随着项目复杂性和细节水平的提高，首选HCM分析程序。该方法对更多变量敏感；因此，涵盖特定对策的影响（例如，增加自行车道宽度）。LTS也可使用，尽管结果可能对设施类型、汽车运行速度或汽车交通量变化之外的改进敏感性较低。对于规划应用，如区域交通规划或交通系统规划，首选LTS方法。这些应用可能不需要对设施进行具体分析，而是概述哪些用户将被服务，以识别自行车网络应改进的关键位置。对于此类应用，LTS是首选。不应使用HCM分析程序，因为数据可用性有限。需要更多研究来定义目标自行车用户，识别其主要特征，并评估他们在不同环境中的舒适度水平。基于信心和频率的分类可以结合。按频率分类骑行者时必须考虑季节性变化。农村公路最具代表性的自行车用户，因此目标用户是“热情且自信的”。对于某些预计自行车流量适中的地点，目标自行车用户应为“感兴趣但担忧的”。这项研究指出需要未来讨论自行车用户细分在运营分析中的作用以及规划方法的需求。如果HCM分析程序与当前基于LTS的设计标准一致，应考虑自行车用户的不同LOS阈值。最重要的特征已被识别，但具体标准和阈值仍需定义。另一方面，应基于用户感知开发基于LTS的自行车模式规划方法，并将其纳入NCHRP报告825：公路容量手册的规划和初步工程应用指南（Dowling等人，2016年）。尽管这项努力旨在农村公路，但它也可为都市街道骑行性能评估的潜在审查提供坚实基础。
文章概要
本文基于一项针对农村公路自行车服务质量的骑行者调查，分析了不同用户类型的骑行偏好和影响因素。调查结果显示，侧向净空、汽车交通量和速度是骑行者最重视的元素，其中侧向净空的影响最大。研究还探讨了骑行者分类（如全年骑行者、季节性骑行者）和信心水平（如热情且自信、感兴趣但担忧）对骑行舒适度和选择行为的影响。结论建议重新审视农村公路的HCM和LTS分析程序，以适应骑行者的感知差异，并提出了未来研究和规划方法的建议。
高德明老师的评价
用12岁初中生可以听懂的语音来重复翻译的内容：这个调查就像问很多骑自行车的人，他们在乡下路上骑车时最在意什么。结果发现，大家最关心的是路边有没有足够宽的地方让他们安全骑车，还有路上汽车多不多、开得快不快。研究还把人分成几类，比如一年到头都骑车的人和只在某些季节骑车的人，看看他们有什么不同。最后，专家们建议，以后设计乡下自行车道时，要更多考虑这些发现，让骑车更安全、更舒服。
TA沟通分析心理学理论评价：从TA沟通分析心理学角度看，这项调查体现了骑行者“成人自我状态”在理性决策中的应用。骑行者通过评估路肩宽度、交通量等客观因素（成人自我状态），做出是否骑行的选择，这反映了他们基于现实信息的适应性行为。同时，骑行者分类（如“热情且自信” vs “感兴趣但担忧”）可视为不同“自我状态”的体现：“热情且自信”骑行者可能更多处于“成人自我状态”或“自由儿童自我状态”，表现出积极和自信；而“感兴趣但担忧”骑行者可能更多处于“适应儿童自我状态”，表现出谨慎和担忧。调查中的选择任务和舒适度评估，促进了骑行者“成人自我状态”与环境的互动，有助于提升自我觉察和决策能力。
在实践上可以应用的领域和可以解决人们的十个问题：这项研究可在交通规划、公共政策、社区教育和心理健康促进等领域应用。基于TA沟通分析心理学，它可以解决人们的十个问题：1. 帮助骑行者通过理性评估（成人自我状态）减少骑行焦虑；2. 促进交通规划者设计更安全的自行车道，增强公众信任；3. 支持社区教育项目，提升骑行者的自信和技能；4. 协助政策制定者制定基于用户需求的法规，改善公共沟通；5. 鼓励家庭通过共同骑行活动，加强亲子互动和情感连接；6. 为企业提供员工通勤方案，提高工作满意度和生产力；7. 帮助学校开展骑行安全教育，培养学生的责任感和独立性；8. 支持环保倡导，通过骑行促进可持续生活方式；9. 协助心理健康工作者利用骑行作为减压工具，提升情绪调节能力；10. 促进社会包容，为不同能力骑行者提供定制化设施，增强社会归属感。