Journal
TRANSPORTATION RESEARCH RECORD
Volume 2672, Issue 45, Pages 14-22Publisher
SAGE PUBLICATIONS INC
DOI: 10.1177/0361198118775839
Keywords
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Funding
- SOLARIS Institute, a Tier 1 University Transportation Center (UTC) [DTRT13-G-UTC55]
- Nevada Department of Transportation (NDOT) [P224-14-803/TO #13]
- Nevada Department of Transportation
- Regional Transportation Commission of Washoe County, Nevada
- City of Reno
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High-resolution vehicle data including location, speed, and direction is significant for new transportation systems, such as connected-vehicle applications, micro-level traffic performance evaluation, and adaptive traffic control. This research developed a data processing procedure for detection and tracking of multi-lane multi-vehicle trajectories with a roadside light detection and ranging (LiDAR) sensor. Different from existing methods for vehicle onboard sensing systems, this procedure was developed specifically to extract high-resolution vehicle trajectories from roadside LiDAR sensors. This procedure includes preprocessing of the raw data, statistical outlier removal, a Least Median of Squares based ground estimation method to accurately remove the ground points, vehicle data clouds clustering, a principle component-based oriented bounding box method to estimate the location of the vehicle, and a geometrically-based tracking algorithm. The developed procedure has been applied to a two-way-stop-sign intersection and an arterial road in Reno, Nevada. The data extraction procedure has been validated by comparing tracking results and speeds logged from a testing vehicle through the on-board diagnostics interface. This data processing procedure could be applied to extract high-resolution trajectories of connected and unconnected vehicles for connected-vehicle applications, and the data will be valuable to practices in traffic safety, traffic mobility, and fuel efficiency estimation.
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