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Identifying intercity freight trip ends of heavy trucks from GPS data

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  • Yang, Yitao
  • Jia, Bin
  • Yan, Xiao-Yong
  • Li, Jiangtao
  • Yang, Zhenzhen
  • Gao, Ziyou

Abstract

The intercity freight trips of heavy trucks are basic data for transportation system planning and management. In recent decades, extracting intercity freight trips from GPS data has gradually become the main alternative to traditional surveys. Identifying freight trip ends (origin and destination) is the first task in trip extraction. Although many trip end identification methods have been proposed in previous studies, most of these studies subjectively determined key parameters and ignored the complex characteristics of truck trajectory and freight activities. In this paper, we propose a data-driven trip end identification method based on massive GPS data of heavy trucks in China. First, we capture heavy truck trajectory characteristics under the influence of GPS drift to identify truck stops from GPS data. Second, we analyze the temporal characteristics of truck activities and use freight-related point-of-interest (POI) data and highway network GIS data to identify valid trip ends from truck stops. The results of method validation suggest that the accuracy of our proposed method is significantly improved in comparison with the benchmark methods. We further extract intercity freight trips from the identified trip ends and analyze the spatiotemporal characteristics of intercity freight trips in China.

Suggested Citation

  • Yang, Yitao & Jia, Bin & Yan, Xiao-Yong & Li, Jiangtao & Yang, Zhenzhen & Gao, Ziyou, 2022. "Identifying intercity freight trip ends of heavy trucks from GPS data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
  • Handle: RePEc:eee:transe:v:157:y:2022:i:c:s1366554521003458
    DOI: 10.1016/j.tre.2021.102590
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    1. Sanchez-Diaz, Ivan, 2020. "Assessing the magnitude of freight traffic generated by office deliveries," Transportation Research Part A: Policy and Practice, Elsevier, vol. 142(C), pages 279-289.
    2. Lyons, Liliana & Lozano, Angélica & Granados, Francisco & Guzmán, Alejandro, 2017. "Impacts of time restriction on heavy truck corridors: The case study of Mexico City," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 119-129.
    3. Qiufang Shi & Xiaoyong Yan & Bin Jia & Ziyou Gao, 2020. "Freight Data-Driven Research on Evaluation Indexes for Urban Agglomeration Development Degree," Sustainability, MDPI, vol. 12(11), pages 1-16, June.
    4. de Vries, Jelle & de Koster, René & Rijsdijk, Serge & Roy, Debjit, 2017. "Determinants of safe and productive truck driving: Empirical evidence from long-haul cargo transport," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 97(C), pages 113-131.
    5. Demir, Emrah & Bektaş, Tolga & Laporte, Gilbert, 2014. "A review of recent research on green road freight transportation," European Journal of Operational Research, Elsevier, vol. 237(3), pages 775-793.
    6. Siripirote, Treerapot & Sumalee, Agachai & Ho, H.W., 2020. "Statistical estimation of freight activity analytics from Global Positioning System data of trucks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    7. Oka, Hideki & Hagino, Yasukatsu & Kenmochi, Takeshi & Tani, Ryota & Nishi, Ryuta & Endo, Kotaro & Fukuda, Daisuke, 2019. "Predicting travel pattern changes of freight trucks in the Tokyo Metropolitan area based on the latest large-scale urban freight survey and route choice modeling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 129(C), pages 305-324.
    8. Meixu Chen & Dani Arribas-Bel & Alex Singleton, 2019. "Understanding the dynamics of urban areas of interest through volunteered geographic information," Journal of Geographical Systems, Springer, vol. 21(1), pages 89-109, March.
    9. Kwon, Okyu & Son, Woo-Sik & Jung, Woo-Sung, 2016. "The double power law in human collaboration behavior: The case of Wikipedia," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 85-91.
    10. Hess, Stephane & Quddus, Mohammed & Rieser-Schüssler, Nadine & Daly, Andrew, 2015. "Developing advanced route choice models for heavy goods vehicles using GPS data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 29-44.
    11. Yang, Lin & Zhang, Fayong & Kwan, Mei-Po & Wang, Ke & Zuo, Zejun & Xia, Shaotian & Zhang, Zhiyong & Zhao, Xinpei, 2020. "Space-time demand cube for spatial-temporal coverage optimization model of shared bicycle system: A study using big bike GPS data," Journal of Transport Geography, Elsevier, vol. 88(C).
    12. Tomaschitz, Roman, 2020. "Multiply broken power-law densities as survival functions: An alternative to Pareto and lognormal fits," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    13. Laranjeiro, Patrícia F. & Merchán, Daniel & Godoy, Leonardo A. & Giannotti, Mariana & Yoshizaki, Hugo T.Y. & Winkenbach, Matthias & Cunha, Claudio B., 2019. "Using GPS data to explore speed patterns and temporal fluctuations in urban logistics: The case of São Paulo, Brazil," Journal of Transport Geography, Elsevier, vol. 76(C), pages 114-129.
    14. Mulholland, Eamonn & Teter, Jacob & Cazzola, Pierpaolo & McDonald, Zane & Ó Gallachóir, Brian P., 2018. "The long haul towards decarbonising road freight – A global assessment to 2050," Applied Energy, Elsevier, vol. 216(C), pages 678-693.
    15. Sharman, Bryce W. & Roorda, Matthew J., 2013. "Multilevel modelling of commercial vehicle inter-arrival duration using GPS data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 56(C), pages 94-107.
    16. Amer, Ahmed & Chow, Joseph Y.J., 2017. "A downtown on-street parking model with urban truck delivery behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 51-67.
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    5. Basso, Franco & Núñez, Matías & Paredes-Belmar, German & Pezoa, Raúl & Varas, Mauricio, 2024. "Estimation of stops of last-mile delivery vehicles: An application in the food industry in the city of Santiago de Chile," Journal of Transport Geography, Elsevier, vol. 116(C).
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