• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文学位 >Travel Mode Choice Framework Incorporating Realistic Bike and Walk Routes.
【24h】

Travel Mode Choice Framework Incorporating Realistic Bike and Walk Routes.

机译：结合现实的自行车和步行路线的出行模式选择框架。

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

For a number of reasons---congestion, public health, greenhouse gas emissions, energy use, demographic shifts, and community livability to name a few---the importance of walking and bicycling as transportation options will only continue to increase. Currently, policy interest and infrastructure funding for nonmotorized modes far outstrip our ability to model bike and walk travel. To ensure scarce resources are used most effectively, accurate models sensitive to key policy variables are needed to support long-range planning and project evaluation, and to continue adding to our growing understanding of key factors driving walk and bike behavior. This research attempts to synthesize and advance the state of the art in trip-based, nonmotorized mode choice modeling.;Over the past fifteen years, efforts to model the decision to walk or bike on a given trip have been hampered by the lack of a comprehensive behavioral framework and inconsistency in measurement scales and model specification. This project develops a mode choice behavioral framework that acknowledges the importance of attributes along the specific walk and bike routes that travelers are likely to consider, in addition to more traditional area-based measures of travel environments. The proposed framework is applied to a revealed preference, GPS-based travel dataset collected from 2010-2013 in Portland, Oregon. Measurement of nonmotorized trip distance, built environment, tour-level variables, and attitudinal attributes as well as mode availability are explicitly addressed. Route and mode choice models are specified using discrete choice techniques, and predicted walking and bicycling routes are tested as inputs to various mode choice models.;Results suggest strong potential for predicted route measures to enhance walk and bicycle mode choice modeling. Findings also support the specific notion that bicycle and pedestrian infrastructure contribute not only to route choice but also to the choice of whether to bike or walk. For decisions to bicycle, availability of low-traffic routes may be particularly important to women. Model results further indicate that land use and built environments around trip ends and a person's home still have important effects on nonmotorized travel when controlling for route quality. Both route and area travel environment impacts are mostly robust to the inclusion of residential self-selection variables, consistent with the idea that built environment differences matter even for households that choose to live in a walkable or bikeable neighborhood. The combination of area and route-based built environment measures alongside trip context, sociodemographic, and attitudinal attributes provides a new perspective on nonmotorized travel behavior relevant to both policy and practice.
机译：由于多种原因-拥堵，公共卫生，温室气体排放，能源使用，人口变化和社区宜居性-仅举几例说明步行和骑自行车的重要性，因为运输选择只会不断增加。当前，对非机动模式的政策兴趣和基础设施资金远远超过了我们对自行车和步行旅行进行建模的能力。为了确保最有效地利用稀缺资源，需要对关键政策变量敏感的准确模型来支持长期计划和项目评估，并继续加深我们对驱动步行和骑自行车行为的关键因素的认识。这项研究试图在基于出行的非机动模式选择建模中综合并提高技术水平。在过去的十五年中，由于缺乏模型设计，阻碍了对在某次出行中步行或骑车的决策建模的努力。全面的行为框架，以及测量规模和模型规格不一致。该项目开发了一种模式选择行为框架，该框架确认了旅行者可能会考虑的特定步行和自行车路线属性的重要性，以及更传统的基于区域的出行环境度量。拟议框架适用于2010年至2013年在俄勒冈州波特兰市收集的基于GPS的偏好旅行数据集。明确解决了非机动出行距离，建筑环境，游览级别变量和态度属性以及模式可用性的测量问题。使用离散选择技术指定路线和模式选择模型，并测试预测的步行和骑行路线作为各种模式选择模型的输入。结果表明，预测的路线测量方法具有增强步行和自行车模式选择建模的强大潜力。研究结果还支持自行车和行人基础设施不仅有助于选择路线，而且有助于选择骑自行车还是步行的特定观念。对于骑自行车的决定，低交通路线的可用性对女性尤其重要。模型结果进一步表明，在控制路线质量时，土地使用和旅程终点周围的建筑环境以及人的家对非机动出行仍然具有重要影响。路线和区域出行环境的影响在包括居民自我选择变量方面都最有力，这与以下观点一致：即使选择住在步行或骑自行车的家庭，建筑环境差异也很重要。基于区域和基于路线的建筑环境措施以及旅行环境，社会人口统计和态度属性的结合，为与政策和实践相关的非机动旅行行为提供了新的视角。

著录项

  • 作者

    Broach, Joseph Paul.;

  • 作者单位

    Portland State University.;

  • 授予单位 Portland State University.;
  • 学科 Transportation.;Urban planning.
  • 学位 Ph.D.
  • 年度 2016
  • 页码 163 p.
  • 总页数 163
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号