Safety Assessment of Urban Intersection Sight Distance Using Mobile LiDAR Data
Omar Kilani,
Maged Gouda,
Jonas Weiß and
Karim El-Basyouny
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Omar Kilani: Department of Civil & Environmental Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada
Maged Gouda: Department of Civil & Environmental Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada
Jonas Weiß: Department of Electrical and Computer Engineering, Technical University of Munich, 80333 Munich, Germany
Karim El-Basyouny: Department of Civil & Environmental Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada
Sustainability, 2021, vol. 13, issue 16, 1-22
Abstract:
This paper proposes an automated framework that utilizes Light Detection and Ranging (LiDAR) point cloud data to map and detect road obstacles that impact drivers’ field of view at urban intersections. The framework facilitates the simulation of a driver’s field of vision to estimate the blockage percentage as they approach an intersection. Furthermore, a collision analysis is conducted to examine the relationship between poor visibility and safety. The visibility assessment was used to determine the blockage percentage as a function of intersection control type. The safety assessment indicated that intersections with limited available sight distances (ASD) exhibited an increased risk of collisions. The research also conducted a sensitivity analysis to understand the impact of the voxel size on the extraction of intersection obstacles from LiDAR datasets. The findings from this research can be used to assess the intersection without the burden of manual intervention. This would effectively support transportation agencies in identifying hazardous intersections with poor visibility and adopt policies to enhance urban intersections’ operation and safety.
Keywords: intersection sight distance; urban intersection safety; mobile lidar data; voxel size; collision analysis; point cloud data (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:13:y:2021:i:16:p:9259-:d:616623
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