Airborne LiDAR : a new source of traffic flow data, research implementation plan.

Grejner-Brzezinska, Dorota A.; Ohio State University. Center for Mapping

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Airborne LiDAR : a new source of traffic flow data, research implementation plan.

2005-10-01
By Grejner-Brzezinska, Dorota A.

[PDF-522.76 KB]

English

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Creators:

Grejner-Brzezinska, Dorota A.
Corporate Creators:

Ohio State University. Center for Mapping
Corporate Contributors:

Ohio. Office of Aerial Engineering ; Ohio. Dept. of Transportation ; United States. Federal Highway Administration

Ohio. Office of Aerial Engineering ; Ohio. Dept. of Transportation ; United States. Federal Highway Administration Less -
Subject/TRT Terms:

[+]

Motor Vehicles--Ohio--Remote Sensing Optical Radar Optical Radar--Ohio Remote Sensing Traffic Flow Traffic Flow--Ohio--Remote Sensing
Publication/ Report Number:

FHWA/OH-2005/14
Resource Type:

Tech Report
Geographical Coverage:

Ohio
Edition:

Research implementation plan.
Corporate Publisher:

Ohio State University. Center for Mapping
Abstract:

LiDAR (or airborne laser scanning) systems became a dominant player in high-precision spatial data acquisition in the late 90's. This new technology quickly established itself as the main source of surface information in commercial mapping, delivering surface data at decimeter-level vertical accuracy in an almost totally automated way. With increasing point density, new systems are able to support object extraction, such as extracting building and roads from LiDAR data. Acquiring flow data in a timely manner is essential for many transportation processes, especially for traffic monitoring and management. Ground-based systems typically use loop detectors and video cameras. These systems provide excellent data at a local scale, but consequently are less appropriate for monitoring flow patterns over longer road segments. Remote sensing sensors, especially airborne systems, however, show somewhat complimentary characteristics; namely the acquired data can effectively support flow information extraction in a dynamic manner. Not only can vehicle counts and velocities be estimated but also complex flow patterns such as slowdowns and intersection/ramp turning movements can be identified and quantified. Using LiDAR data for traffic flow estimates is a novel concept. In a sense, extracting vehicles over transportation corridors represents the next step in complexity by adding the temporal component to the LiDAR data feature extraction process. Vehicles are moving at highway speeds and the scanning acquisition mode of the LiDAR poses a serious challenge for the data extraction process.
Format:

PDF
Funding:

134145
Collection(s):

US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:8a8714234878ef07b08c05c45700b0b042963b3679b683124441bbed1f9ea6b4
Download URL:

https://rosap.ntl.bts.gov/view/dot/5728/dot_5728_DS1.pdf
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Airborne LiDAR : a new source of traffic flow data, research implementation plan.

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