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

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. © 2020 Elsevier Ltd