Abstract
Despite the broad application of advanced fleet management systems (FMSs) in third-party logistics (3PL) companies, there is a marginally limited understanding of how to employ them to enhance transport energy efficiency. In a case study of a Chinese 3PL company, this paper analyzed data obtained from the online FMS to assess drivers’ awareness of fuel-saving factors. A questionnaire was primarily designed to investigate the drivers’ awareness of fuel-saving factors based on the reliability and validity test. Then, Extreme Gradient Boosting (XGBoost), a machine learning algorithm, was utilized to explore the intrinsic impacts of various factors on fuel consumption with the outputs providing the evaluation basis for individual awareness of the drivers. The results show a significant deviation in the driver’s awareness of fuel-saving factors, among which the three indicators of engine speed, idling condition, and rolling without engine load are seriously underestimated, while the indicators related to the environment are seriously overestimated due to social expectations. In addition, the average speed was found to be the most important fuel-saving indicator besides the load. Based on these findings, this paper recommends that the 3PL companies choose a route with more freeways when planning, and the mileage should be controlled within 800 km as far as possible.
Highlights
Fossil fuels remain the primary source of energy for freight movements
This paper developed a method based on the advanced fleet management systems (FMSs), which can be applied to 3PL companies to investigate the awareness of their fleet drivers on fuel-saving factors, so as to formulate effective eco-driving management strategies
Its innovation and contribution can be summarized in the following aspects: (i) Demonstrated how to make full use of the fuelrelated data obtained from advanced on-board FMS of 3PL companies to contribute to road freight decarburization
Summary
Fossil fuels remain the primary source of energy for freight movements. Freight transportation is thereby often considered as one of the most difficult economic activities to decarbonize. As reported by International Energy Agency [1] and International Transport Forum [2], road freight transport consumed roughly 30% of the energy produced and 53% of the total international trade-related carbon emissions Such an international background puts forward strict requirements for developing low-carbon transportation of the third-party logistics (3PL) company. We constructed a comprehensive methodologic framework to show how the advanced on-board measurement system could be used to mine these internal data relating to fuel consumption, so as to contribute to the decarbonization of logistics transportation. E first one was to design a questionnaire for the fleet of data providers, and investigate in detail the cognitive level of each driver on the contributing factors of fuel consumption in the real world.
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