下一代货运车辆调查:用司机活动调查补充卡车GPS跟踪

A. Alho, Linlin You, Fangping Lu, L. Cheah, Fang Zhao, M. Ben-Akiva
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引用次数: 14

摘要

公路货运车辆的运营因行业类型、运输商品或地理范围等多种因素而有很大差异。车辆跟踪是了解操作模式的最常用方法之一,支持gps的设备的日益普及为其提供了便利。我们描述了一种方法,该方法将车辆跟踪数据与日常驾驶员活动调查相结合,以收集与货运车辆操作相关的静态和动态数据。该调查旨在实现创新的数据分析和建模。我们详细介绍了在新加坡展示的数据收集方法,并说明了城市货运领域感兴趣的三个数据驱动的见解:(1)货运车辆过夜停车,(2)旅游模式和相关车辆使用特征,以及(3)商品流动模式。分析所展示的独特见解证实了所描述的数据收集方法在进一步了解货运车辆操作方面的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Next-generation freight vehicle surveys: Supplementing truck GPS tracking with a driver activity survey
Freight road vehicle operations vary widely depending on a multitude of factors such as industry type, commodities transported or geographical scope. Vehicle tracking is one of the most common approaches to understand operation patterns and it has been facilitated by the increasing availability of GPS-enabled devices. We describe a method that supplements vehicle tracking data with day-to-day driver activity surveys to collect static and dynamic data related to freight vehicle operations. The survey was designed to enable innovative data analysis and modelling. We detail the data collection method demonstrated in Singapore and illustrate three data-driven insights which are of interest in the urban freight domain: (1) freight vehicle overnight parking, (2) tour patterns and associated vehicle usage characteristics, and (3) commodity flow patterns. The unique insights demonstrated by the analyses corroborate the potential of the described data collection method to further understand freight vehicle operations.
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