Route-based Freight Activity Metrics along the California State Highway System through a Pilot Multi Sensor Fusion System
Caltrans has over 140 Weigh-In-Motion (WIM) and approximately 4000 Census stations throughout the state of California. In addition, UCI has partnered with Caltrans and the California Air Resources Board to deploy dozens of sites with inductive signature technology and ten sites with Automated License Plate Readers in strategic truck corridors within Southern California. These sensor technologies possess unique yet complementary surveillance characteristics: WIM systems measure axle spacing and weights that yield axle-based classifications; inductive signature-based models developed by the University of California, Irvine (UCI) can both predict a truck’s body configuration (which can infer its vocation and industry affiliation) as well as track them over dozens of miles by matching unique characteristics found within their inductive signatures; while ALPR systems can be used to match trucks over even longer distances across the State Highway System (SHS) through license plate matching. While some level of vehicle tracking can be achieved via telematics data such as global positioning system (GPS) and cellular systems, the datasets from these sources nevertheless possess several drawbacks – such as sampling penetration, sampling bias and data quality – that limit their benefits to state agencies. In contrast, several detector sites in Southern California are currently deployed with a combination of the aforementioned sensor technologies as a part of UCI’s Freight Mobility Living Laboratory (FML2) testbed, which offer a timely and prime opportunity to investigate the synergies of sensor fusion across these technologies to obtain better truck activity metrics that can benefit Caltrans and several other State, regional and local agencies. The objective of this study is to develop and demonstrate a prototype truck tracking system that integrates WIM, ALPR and Inductive Signature-based technologies that can estimate path-based volumes by vehicle categories. The study will leverage several current and upcoming multi-sensor detector testbed locations at I-710 near the Port of Long Beach (ALPR, inductive signature technology), I405 at Van Nuys (WIM, ALPR and inductive signature technology) and SR-60 at Chino (ALPR and inductive signature technology). Trucks may traverse different routes between these locations. Hence, additional standalone inductive signature sites between these multi-sensor sites will serve as intermediate sensor locations to determine route pathways in the development and testing of the proposed truck tracking system. The data from this tracking system will drive a new FML2 dashboard interface that will be developed as a part of this study to display interactive freight activity metrics such as route heatmaps by truck type.
Language
- English
Project
- Status: Programmed
- Funding: $100000
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Contract Numbers:
65A0674
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Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
METRANS Transportation Consortium
University of Southern California
Los Angeles, CA United States -
Project Managers:
Hong, Jennifer
Bruner, Britain
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Principal Investigators:
Ritchie, Stephen
- Start Date: 20240101
- Expected Completion Date: 20241231
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers
Subject/Index Terms
- TRT Terms: Automatic license plate readers; Data fusion; Sensors; Truck traffic; Vehicle detectors; Weigh in motion
- Geographic Terms: California
- Subject Areas: Data and Information Technology; Freight Transportation; Highways;
Filing Info
- Accession Number: 01893871
- Record Type: Research project
- Source Agency: Pacific Southwest Region University Transportation Center
- Contract Numbers: 65A0674
- Files: UTC, RIP
- Created Date: Sep 21 2023 2:05PM