Development of a Delivery Time-Period Selection Model for Urban Freight Using GPS Data
Developing policy instruments related to urban freight, such as congestion pricing, urban consolidation schemes, and off-hours delivery, requires an understanding of the distribution of shipment delivery times. Furthermore, agent-based urban freight simulators use relevant information (shipment deli...
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MDPI AG
2025-02-01
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| Series: | Smart Cities |
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| Online Access: | https://www.mdpi.com/2624-6511/8/1/31 |
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| author | Ryota Kodera Takanori Sakai Tetsuro Hyodo |
| author_facet | Ryota Kodera Takanori Sakai Tetsuro Hyodo |
| author_sort | Ryota Kodera |
| collection | DOAJ |
| description | Developing policy instruments related to urban freight, such as congestion pricing, urban consolidation schemes, and off-hours delivery, requires an understanding of the distribution of shipment delivery times. Furthermore, agent-based urban freight simulators use relevant information (shipment delivery time distribution or vehicle tour start time distribution) as input to simulate tour generation. However, studies focusing on shipment delivery time-period selection modeling are very limited. In this study, we propose a method using GPS trajectory data from the Tokyo Metropolitan Area to estimate a shipment delivery time-period selection model based on pseudo-shipment records inferred from GPS data. The results indicate that shipment distance, size, and destination attributes can explain the delivery times of goods. Moreover, we demonstrate the practicality of the model by comparing the simulation result with the observed data for three areas with distinct characteristics, concluding that the model could be applied to urban freight simulation models for accurately reproducing spatial heterogeneity in shipment delivery time periods. This study contributes to promoting smart city development and management by proposing a method to use big data to better understand deliveries and support the development of relevant advanced city logistics solutions. |
| format | Article |
| id | doaj-art-a52347050aed4d7b87c0c7bbc646ea01 |
| institution | OA Journals |
| issn | 2624-6511 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Smart Cities |
| spelling | doaj-art-a52347050aed4d7b87c0c7bbc646ea012025-08-20T02:04:07ZengMDPI AGSmart Cities2624-65112025-02-01813110.3390/smartcities8010031Development of a Delivery Time-Period Selection Model for Urban Freight Using GPS DataRyota Kodera0Takanori Sakai1Tetsuro Hyodo2Course of Maritime Technology and Logistics, Tokyo University of Marine Science and Technology, 2-1-6 Etchujima Koto-ku, Tokyo 135-8533, JapanDepartment of Logistics and Information Engineering, Tokyo University of Marine Science and Technology, 2-1-6 Etchujima Koto-ku, Tokyo 135-8533, JapanDepartment of Logistics and Information Engineering, Tokyo University of Marine Science and Technology, 2-1-6 Etchujima Koto-ku, Tokyo 135-8533, JapanDeveloping policy instruments related to urban freight, such as congestion pricing, urban consolidation schemes, and off-hours delivery, requires an understanding of the distribution of shipment delivery times. Furthermore, agent-based urban freight simulators use relevant information (shipment delivery time distribution or vehicle tour start time distribution) as input to simulate tour generation. However, studies focusing on shipment delivery time-period selection modeling are very limited. In this study, we propose a method using GPS trajectory data from the Tokyo Metropolitan Area to estimate a shipment delivery time-period selection model based on pseudo-shipment records inferred from GPS data. The results indicate that shipment distance, size, and destination attributes can explain the delivery times of goods. Moreover, we demonstrate the practicality of the model by comparing the simulation result with the observed data for three areas with distinct characteristics, concluding that the model could be applied to urban freight simulation models for accurately reproducing spatial heterogeneity in shipment delivery time periods. This study contributes to promoting smart city development and management by proposing a method to use big data to better understand deliveries and support the development of relevant advanced city logistics solutions.https://www.mdpi.com/2624-6511/8/1/31shipmenttime-period choiceGPS dataurban freightcity logisticsfreight modeling |
| spellingShingle | Ryota Kodera Takanori Sakai Tetsuro Hyodo Development of a Delivery Time-Period Selection Model for Urban Freight Using GPS Data Smart Cities shipment time-period choice GPS data urban freight city logistics freight modeling |
| title | Development of a Delivery Time-Period Selection Model for Urban Freight Using GPS Data |
| title_full | Development of a Delivery Time-Period Selection Model for Urban Freight Using GPS Data |
| title_fullStr | Development of a Delivery Time-Period Selection Model for Urban Freight Using GPS Data |
| title_full_unstemmed | Development of a Delivery Time-Period Selection Model for Urban Freight Using GPS Data |
| title_short | Development of a Delivery Time-Period Selection Model for Urban Freight Using GPS Data |
| title_sort | development of a delivery time period selection model for urban freight using gps data |
| topic | shipment time-period choice GPS data urban freight city logistics freight modeling |
| url | https://www.mdpi.com/2624-6511/8/1/31 |
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