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首页> 外文期刊>Transportation >Exploring the impact of walk-bike infrastructure, safety perception, and built-environment on active transportation mode choice: a random parameter model using New York City commuter data
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Exploring the impact of walk-bike infrastructure, safety perception, and built-environment on active transportation mode choice: a random parameter model using New York City commuter data

机译：探索步行自行车基础设施，安全感知和内置环境对主动交通方式选择的影响：使用纽约市通勤者数据的随机参数模型

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摘要

This study estimates a random parameter (mixed) logit model for active transportation (walk and bicycle) choices for work trips in the New York City (using 2010-2011 Regional Household Travel Survey Data). We explored the effects of traffic safety, walk-bike network facilities, and land use attributes on walk and bicycle mode choice decision in the New York City for home-to-work commute. Applying the flexible econometric structure of random parameter models, we capture the heterogeneity in the decision making process and simulate scenarios considering improvement in walk-bike infrastructure such as sidewalk width and length of bike lane. Our results indicate that increasing sidewalk width, total length of bike lane, and proportion of protected bike lane will increase the likelihood of more people taking active transportation mode This suggests that the local authorities and planning agencies to invest more on building and maintaining the infrastructure for pedestrians. Further, improvement in traffic safety by reducing traffic crashes involving pedestrians and bicyclists, will increase the likelihood of taking active transportation modes. Our results also show positive correlation between number of non-motorized trips by the other family members and the likelihood to choose active transportation mode. The model would be an essential tool to estimate the impact of improving traffic safety and walk-bike infrastructure which will assist in investment decision making.
机译：这项研究估计了纽约市工作旅行的主动出行（步行和骑自行车）选择的随机参数（混合）logit模型（使用2010-2011年地区家庭出行调查数据）。我们探讨了交通安全，步行自行车网络设施以及土地使用属性对纽约市上下班通勤的步行和自行车模式选择决策的影响。应用随机参数模型的灵活计量经济结构，我们捕获了决策过程中的异质性，并考虑了步行自行车基础设施的改进（例如人行道宽度和自行车道长度）来模拟情景。我们的结果表明，增加人行道宽度，自行车道的总长度以及受保护的自行车道的比例，将增加更多人采取主动交通方式的可能性。这表明地方当局和规划机构将更多投资用于建设和维护基础设施。行人。此外，通过减少涉及行人和骑自行车的人的交通事故来改善交通安全，将增加采取主动交通方式的可能性。我们的研究结果还显示，其他家庭成员的非机动出行次数与选择主动交通方式的可能性之间存在正相关。该模型将是评估改善交通安全和步行自行车基础设施的影响的重要工具，这将有助于投资决策。

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