Regional Truck Travel Characteristics Analysis and Freight Volume Estimation: Support for the Sustainable Development of Freight

Sustainability Pub Date : 2024-07-24 DOI:10.3390/su16156317
Shuo Sun, Mingchen Gu, Jushang Ou, Zhenlong Li, Sen Luan
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Abstract

In the field of freight transport, the goal of sustainable development requires us to improve the efficiency of freight transport while reducing its negative impact on the environment, such as reducing carbon emissions and noise pollution. There is no doubt that changes in freight characteristics and volumes are compatible with the objectives of sustainable development. Thus, mining the travel distribution and freight volume of trucks has an important supporting role in the freight transport industry. In terms of truck travel, most of the traditional approaches are based on the subjective definition of parameters from the trajectory data to obtain trips for certain vehicle types. As for freight volume, it is mostly estimated through manual surveys, which are heavy and inaccurate. In this study, a data-driven approach is adopted to obtain trips from the trajectory data of heavy trucks. Combined with the traffic percentage of different vehicle types collected by highway traffic survey stations, the trips of heavy trucks are extended to all trucks. The inter-city and intra-city freight volumes are estimated based on the average truck loads collected at the motorway entrance. The results show a higher proportion of intra-city trips by trucks in port cities and a higher proportion of inter-city trips by trucks in inland cities. Truck loading and unloading times are focused in the early morning or at night, and freight demand in Shandong Province is more concentrated in the south. These results would provide strong support for optimizing freight structures, improving transportation efficiency, and reducing transportation costs.
区域卡车出行特征分析和货运量估算:支持货运的可持续发展
在货运领域,可持续发展的目标要求我们提高货运效率,同时减少对环境的负面影响,如减少碳排放和噪音污染。毫无疑问,货运特征和货运量的变化符合可持续发展的目标。因此,挖掘卡车的出行分布和货运量对货运业具有重要的支撑作用。在卡车出行方面,大多数传统方法都是根据轨迹数据主观定义参数,从而得到某些车辆类型的出行次数。至于货运量,大多通过人工调查估算,工作量大且不准确。本研究采用数据驱动法,从重型卡车的轨迹数据中获取出行量。结合公路交通调查站收集的不同类型车辆的交通比例,将重型卡车的行程扩展到所有卡车。根据在高速公路入口处收集到的卡车平均载重量,估算出城市间和城市内的货运量。结果显示,港口城市的卡车市内出行比例较高,内陆城市的卡车市际出行比例较高。卡车装卸时间集中在清晨或夜间,山东省的货运需求更集中在南部。这些结果将为优化货运结构、提高运输效率、降低运输成本提供有力支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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