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Investigation of Truck Data Collection using LiDAR Sensing Technology along Rural Highways

Status

Complete

Project Timeline

May 1, 2020 - September 30, 2021

Principal Investigator

Stephen Ritchie

Project Team

Andre (Yeow Chern) Tok, Craig Rindt, Koti Allu, Zhe (Jared) Sun

Sponsor, Program & Award Number

Caltrans // PSR UTC Caltrans Match: 131973292
(Subcontract to University of Southern California)
(Also see this project page)

Areas of Expertise

Freight, Logistics, & Supply Chain Intelligent Transportation Systems, Emerging Technologies, & Big Data

Team Departmental Affiliation

Civil and Environmental Engineering

Project Summary

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.

Related Publications

working paper | Aug 2020

Lidar Based Reconstruction framework for Truck Surveillance

Read more
research report | Sep 2021

Investigation of Truck Data Collection using LiDAR Sensing Technology Along Rural Highways

Read more

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