Use of Vehicle Telematics Data to Characterize Drayage Heavy-Duty Truck Idling. Issue 11 (November 2020)

• Record Type: Journal Article
• Authors: Farzaneh, Reza; Johnson, Jeremy; Jaikumar, Rohit; Ramani, Tara; Zietsman, Joe
• Is Part Of: Transportation research record. Volume 2674:Issue 11(2020)
• Page Start: 542
• Page End: 553
• Publication Date: 2020-11
• Subjects: Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.1177/0361198120945990
• Languages: English
• ISSNs: 0361-1981

Abstract

The goal of this study is to evaluate potential air-quality applications of global positioning system (GPS) data from trucks in the Houston–Galveston Area Council's (H-GAC) Drayage Loan Program (DLP), along with data collection using portable activity measurement systems (PAMS). PAMS data were collected at 1 Hz frequency from 39 heavy-duty trucks. Of these, 31 were diesel-powered DLP participant trucks operating in the Houston area and the remainder were local CNG trucks. The DLP participant trucks were also being tracked by H-GAC via GPS. PAMS and GPS data were used for data analyses to provide insight into idling events, truck activity (vehicle miles traveled and speeds), and geospatial analysis of trip origins and destinations. Finally, the GPS and PAMS datasets for the DLP participant trucks were used to analyze differences between GPS and PAMS data for vehicle idling and activity. The data analyses were conducted using an integrated data analytics tool (Microsoft Power BI), which allowed for data integration, analysis, dashboarding, and mapping on a single platform. The study results show that 91% of DLP participant truck activities occur during the day, with low average speeds largely from extensive idling. The data analytics system developed in this study can be used to identify, implement, and measure performance of idling reduction strategies for a specific region and operation type. For example, the data can be used to investigate whether a battery–electric air conditioning system is effective for the operation of a target fleet.