Investigation of Truck Data Collection using LiDAR sensing technology along Rural Highways

LiDAR is an emerging technology that can provide detailed point-cloud measurements of objects. The purpose of this study is to investigate the use of LiDAR technology for accurate classification of trucks according to the established FHWA scheme along rural highway corridors as an alternative to in-pavement detector infrastructure – such as inductive loop sensors and piezo-based automatic vehicle classifiers which is not widely deployed along many rural highway corridors – and temporary sensors such as pneumatic road tubes, which expose workers to live traffic. This research will also investigate anonymous tracking of trucks with LiDAR across two locations using advanced algorithms. This can be used to measure spatial activity and travel time performance of trucks along instrumented corridors.

Language

• English

Project

• Status: Active
• Funding: $135,000.00
• Sponsor Organizations:

  California Department of Transportation

  1227 O Street
  Sacramento, CA  United States  95843
• Managing Organizations:

  METRANS Transportation Center

  University of Southern California
  Los Angeles, CA  United States  90089-0626
• Project Managers:

  Brinkerhoff, Cort

• Performing Organizations:

  University of California, Irvine

  Institute of Transportation Studies
  4000 Anteater Instruction and Research Building
  Irvine, CA  United States  92697
• Principal Investigators:

  Ritchie, Stephen

• Start Date: 20200501
• Expected Completion Date: 20210430
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers

Subject/Index Terms

• TRT Terms: Highway corridors; Infrastructure; Tracking systems; Trucks
• Subject Areas: Bridges and other structures; Data and Information Technology; Freight Transportation; Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01741803
• Record Type: Research project
• Source Agency: METRANS Transportation Center
• Files: RIP
• Created Date: Jun 2 2020 2:46PM