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Statistical estimation of freight activity analytics from Global Positioning System data of trucks

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  • Siripirote, Treerapot
  • Sumalee, Agachai
  • Ho, H.W.

Abstract

To optimally plan/design freight-related infrastructures, it is crucial to understand the activities of freight-related traffic. This paper proposes a statistical approach to estimate truck activities and freight analytics from Global Positioning System (GPS) data of trucks. Commodities carried are also determined by the locations and types of truck stops. With the estimated activities and commodities carried, the characteristics of trip chains for different commodities are then determined and analysed. An empirical example from Thailand is adopted to illustrate the proposed approaches in estimating activities, activity patterns, commodity trip chains and status of trips legs from the collected truck GPS data.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:transe:v:140:y:2020:i:c:s1366554520306372
    DOI: 10.1016/j.tre.2020.101986
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    3. 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).
    4. Wu, Jishi & Feng, Tao & Jia, Peng & Li, Gen, 2024. "Spatial allocation of heavy commercial vehicles parking areas through geo-fencing," Journal of Transport Geography, Elsevier, vol. 117(C).
    5. Chen, Liao & Ma, Shoufeng & Li, Changlin & Yang, Yuance & Wei, Wei & Cui, Runbang, 2024. "A spatial–temporal graph-based AI model for truck loan default prediction using large-scale GPS trajectory data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).
    6. Yang, Zhiwei & Chen, Xiaohong & Deng, Jihao & Li, Tianhao & Yuan, Quan, 2023. "Footprints of goods movements: Spatial heterogeneity of heavy-duty truck activities and its influencing factors in the urban context," Journal of Transport Geography, Elsevier, vol. 113(C).
    7. Fu, Hao & Lam, William H.K. & Shao, Hu & Kattan, Lina & Salari, Mostafa, 2022. "Optimization of multi-type traffic sensor locations for estimation of multi-period origin-destination demands with covariance effects," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    8. Demissie, Merkebe Getachew & Kattan, Lina, 2022. "Estimation of truck origin-destination flows using GPS data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 159(C).

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