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Empirical analysis of delivery vehicle on-street parking pattern in Manhattan area/ created by

By: Contributor(s): Material type: TextTextSeries: Journal of urban planning and development ; Volume 142, number 2Reston : ASCE, 2016Content type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISSN:
  • 07339488
Subject(s): LOC classification:
  • HT169 JOU
Online resources: Abstract: Parking in big cities is never easy. Policy-makers and transportation planners have developed many strategies to accommodate increasing parking demand. However, most of them focus on passenger vehicles, and analysis of delivery vehicle parking is still limited. This study uses recent disaggregate data of freight delivery patterns collected in the Manhattan area, which is rarely available in freight studies, to explore the factors influencing delivery vehicle on-street parking characteristics and drivers’ behavior. A duration model is used to analyze delivery vehicle on-street parking duration, and a count data model is used to analyze the parking frequency of delivery tours. With the outputs of these models, the effectiveness of different traffic-management and parking-management strategies are assessed. The results show that policies encouraging smaller delivery vehicle, higher loading efficiency, and shorter parking duration will reduce congestion and economic losses. The results also demonstrate the value of disaggregate data in freight studies, implying the need for larger-scale and more-detailed data collection for future studies.
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Parking in big cities is never easy. Policy-makers and transportation planners have developed many strategies to accommodate increasing parking demand. However, most of them focus on passenger vehicles, and analysis of delivery vehicle parking is still limited. This study uses recent disaggregate data of freight delivery patterns collected in the Manhattan area, which is rarely available in freight studies, to explore the factors influencing delivery vehicle on-street parking characteristics and drivers’ behavior. A duration model is used to analyze delivery vehicle on-street parking duration, and a count data model is used to analyze the parking frequency of delivery tours. With the outputs of these models, the effectiveness of different traffic-management and parking-management strategies are assessed. The results show that policies encouraging smaller delivery vehicle, higher loading efficiency, and shorter parking duration will reduce congestion and economic losses. The results also demonstrate the value of disaggregate data in freight studies, implying the need for larger-scale and more-detailed data collection for future studies.

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