Truck Activity Monitoring System for Freight Transportation Analysis

Autor: Craig R. Rindt, Andre Tok, Sarah Hernandez, Yue (Ethan) Sun, Kyung (Kate) Hyun, Kyungsoo Jeong, Stephen G. Ritchie
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Zdroj: BASE-Bielefeld Academic Search Engine
DOI: 10.3141/2610-11
Popis: Understanding truck activity is an essential component of strategic freight planning and programming. However, recent studies have revealed a significant void in the availability of detailed truck activity data. Although some existing detectors are capable of providing truck counts by axle configuration, higher-resolution data that indicate truck body configuration, industry served, and commodity carried cannot be obtained from existing sensors. This paper presents the newly developed Truck Activity Monitoring System, which leverages existing in-pavement traffic sensors to provide truck activity data in California. Existing inductive loop detector sites were updated with inductive signature technology and advanced truck classification models were implemented to provide detailed truck count data with more than 40 truck body configurations. The system has been deployed to more than 90 detector locations in California to provide coverage at state borders, regional cordons, and significant metropolitan truck corridors. An interactive geographic information system website provides users with advanced visual analytics and access to archived data across all deployed locations. The case studies presented in this paper demonstrate the potential of the data obtained from this system in analyzing and understanding current and historical industry-specific truck activity.
Databáze: OpenAIRE