实时卡车特征描述系统:货运流动性生活实验室(FML2)的试点实施

Yiqiao Li , Andre Y.C. Tok , Guoliang Feng , Stephen G. Ritchie
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引用次数: 0

摘要

加利福尼亚州拥有多个主要货运门户和物流设施,为本州和全美提供服务。但是,由于缺乏全面详细的卡车活动数据,对卡车,尤其是目前对我们的供应链和货运系统至关重要的重型卡车对经济、环境和当地社区的影响的衡量仍然不足。本文介绍了具有实时性、可扩展性和成本效益的 "货运流动生活实验室"(FML2)的试点实施情况。该系统提供卡车多种属性的特征,如卡车车身类型、基于车轴和车辆总重等级 (GVWR) 的分类,目前部署在南加州主要货运走廊沿线的 30 个检测点,以支持货运建模和分析需求。本文详细介绍了 FML2 的设计,从边缘数据处理、预测模型开发、通信架构、后台数据存储到可视化分类结果的实时数据仪表板。文末还介绍了三个案例研究,以展示 FML2 的潜力,供研究人员和从业人员进一步深入了解卡车活动。
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Real-time truck characterization system: A pilot implementation of the Freight Mobility Living Laboratory (FML2)

California possesses multiple major freight gateway and logistics facilities that serve both the state and the entire U.S. But the economic, environmental, and local community impacts of trucks, especially heavy-duty trucks that are currently essential to our supply chains and freight transportation system remain poorly measured due to the lack of comprehensive and detailed truck activity data. This paper describes the pilot implementation of the real-time, scalable, and cost-efficient Freight Mobility Living Laboratory (FML2). This system provides truck characterizations across multiple attributes, such as truck body types, axle-based and Gross Vehicle Weight Rating (GVWR)-based classification and is currently deployed at 30 detection locations in Southern California along major freight corridors to support freight modeling and analysis needs. This paper details the design of the FML2 from edge data processing, predictive model development, communication architecture, and backend data storage to the real-time data dashboard to visualize the classification results. Three case studies have been presented at the end of the paper to demonstrate the potential of FML2 for use by both researchers and practitioners to gain further insights on truck activities.

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来源期刊
Transportation Research Interdisciplinary Perspectives
Transportation Research Interdisciplinary Perspectives Engineering-Automotive Engineering
CiteScore
12.90
自引率
0.00%
发文量
185
审稿时长
22 weeks
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