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

Ritchie, Stephen G.; Tok, Andre; Li, Yiqiao; Sun, Jared; Allu, Koti R

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

2021-09-01
By Ritchie, Stephen G. ; Tok, Andre ; Li, Yiqiao

File Language:

English

Details

Creators:

Ritchie, Stephen G. ; Tok, Andre ; Li, Yiqiao ; Sun, Jared ; Allu, Koti R
Corporate Creators:

METRANS Transportation Center (Calif.) ; Pacific Southwest Region 9 UTC, University of Southern California ; University of California, Irvine
Corporate Contributors:

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
Subject/TRT Terms:
Publication/ Report Number:

PSR-19-51
Resource Type:

Tech Report
Geographical Coverage:

United States
Corporate Publisher:

METRANS Transportation Center (Calif.)
Abstract:

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.
Format:

PDF
Funding:

65A0674 TO 036
Download URL:

https://rosap.ntl.bts.gov/view/dot/67947/dot_67947_DS1.pdf
File Type:

[PDF - 3.82 MB]
Collection(s):

Autonomous Vehicles ; University Transportation Centers
Main Document Checksum:

urn:sha-512:5a5c7edf0a91450d5c1020b45629a726c71f038072d0a339e6029076f8831ec99e6d27ebe96e0b39db6c577b978c347dea290913a558cab964f94ea4aa6e7c06

File Language:

English

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