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首页> 外文期刊>Transportation Research >Planning car-lite neighborhoods: Does bikesharing reduce auto-dependence?
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Planning car-lite neighborhoods: Does bikesharing reduce auto-dependence?

机译：规划汽车精简社区：自行尼克斯队是否减少了自动依赖性？

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Bike enthusiasts argue that bikesharing programs can be an important element of sustainable mobility planning in the urban cores of large metropolitan areas. However, the objective longterm impact of bikesharing on reducing auto-dependence is not well-examined, as prior studies have tended to rely on self-reported subjective mode substitution effects. We use a unique longitudinal dataset containing millions of geo-referenced vehicle registrations and odometer readings in Massachusetts over a six-year period -the Massachusetts Vehicle Census -to examine the causal impact of bikesharing on various metrics of auto-dependence in the inner core of Metro Boston. The difference-in-differences (DiD) framework is extended to accommodate spatial spillover effects with the inclusion of a spatial autoregressive lag leading to the spatial DiD (SpDiD) model. We also account for seasonal variation in bikeshare operations, where several stations are shut down for the winter months, by setting up a dynamic treatment definition. We find that a new bikeshare station reduces vehicle ownership per household by 2.2%, vehicle miles traveled per person by 3.3%, and per-capita vehicular GHG emissions by 2.9%. We also find strong evidence to support the use of bikesharing as a first/last-mile connector to mass transit. Auto-dependence reductions are around 10% (more than thrice as high as average) where bikeshare connections to transit stations are less than one kilometer long. Finally, we find that vehicle ownership reductions are almost immediate and last up to a year, while vehicle use and emission reductions are lagged over 1.5 years. These sizeable and measurable auto-substitution effects do support some of the claims of bikesharing advocates. These findings are especially important in the post-COVID-19 era, as cities strive to counter the pandemic-inspired safety skepticism about non-car travel.
机译：自行车爱好者认为，人均计划可以成为大都市区城市核心可持续行动规划的重要因素。然而，由于现有研究倾向于依赖于自我报告的主观模式替代效应，因此尚未充分考虑到降低自动依赖性的客观的长期影响。我们使用一个独特的纵向数据集，其中包含数百万个地理参考的车辆注册和在马萨诸塞州的地理读取的车程读数 - 马萨诸塞州车辆人口普查 - 检查自行车对内核的自动依赖性各种度量的因果影响地铁波士顿。差异差异（DID）框架延伸以适应空间溢出效应，包括纳入空间自回归滞后，导致空间（SPDID）模型。我们还考虑了Bikeshare操作的季节性变化，通过建立动态治疗定义，几个站将在冬季关闭。我们发现，新的Bikeshare Station将每家家庭的车辆所有权降低2.2％，每人的车里每人行驶3.3％，人均车辆温室气体排放量为2.9％。我们还发现有权证据支持使用双蓄能作为批量转抵的第一/最后一英里连接器。自动依赖性减少约为10％（超过平均值的三倍），其中与运输站的Bikeshare连接较长。最后，我们发现车辆所有权减少几乎是立即的，持续到一年，而车辆使用和排放减少则滞后于1.5亿。这些相当性和可测量的自动替代效果确实支持了均方位的一些权利要求。这些调查结果在Covid-19时代尤为重要，因为城市努力反击关于非汽车旅行的大流行激发安全怀疑论。

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