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The effects of smart-parking on transit and traffic: Evidence from SFpark

机译:智能停车场对公交和交通的影响:SFpark的证据

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To alleviate many parking-related externalities, several rapidly growing cities globally are optimizing parking through "smart-parking" programs, involving measures such as adjusting parking prices based upon demand, making payments easier, and significantly improving parking-related information dissemination. There are few rigorous empirical estimates regarding the efficacy of these policies, particularly for outcomes such as transit ridership or traffic flow, which are of key policy relevance. Exploiting features of the roll out of SFpark, a smart-parking program for the city of San Francisco, we are able to estimate its effect upon public transit usage and traffic flow. Using a difference-in-difference strategy and a rich micro data-set on transit bus ridership along with data from SFpark, we find that SFpark led to a significant increase in bus ridership and a reduction in traffic flow. A back-of-the-envelope calculation suggests that the economic benefits resulting from avoided pollution and reduced congestion consequent to SFpark is larger than the approximate nominal costs of the program. Overall, our results suggest that smart-parking programs can help mitigate many traffic-related externalities, yielding significant economic benefits. (C) 2019 Elsevier Inc. All rights reserved.
机译:为了减轻许多与停车相关的外部性,全球几个快速发展的城市正在通过“智能停车”计划来优化停车,这些措施包括根据需求调整停车价格,使付款更容易以及显着改善与停车相关的信息传播。对于这些政策的有效性,很少有严格的经验估计,特别是对于诸如过境乘车或交通流量之类的结果而言,这些估计与政策的重要性相关。利用针对旧金山市的智能停车程序SFpark推出的功能,我们能够估算其对公共交通使用和交通流量的影响。通过使用差异策略和关于公交车乘客量的丰富微数据集以及SFpark的数据,我们发现SFpark导致公交车乘客量的显着增加和交通流量的减少。粗略计算表明,SFpark避免了污染并减少了拥堵,所产生的经济效益大于该计划的名义成本。总体而言,我们的结果表明,智能停车计划可以帮助缓解许多与交通相关的外部因素,从而产生可观的经济效益。 (C)2019 Elsevier Inc.保留所有权利。

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