Use of Light Detection and Ranging Data to Identify and Quantify Intersection Obstruction and Its Severity

Abstract

The identification of obstructions at intersections is crucial for roadway safety improvement. Field measurements used to identify intersection obstructions, however, are labor intensive, costly, and dangerous. This study explores the feasibility of identifying obstructions at intersections by using light detection and ranging (LiDAR) data already available for flood analysis. Because it can model three-dimensional objects, emerging LiDAR technology provides a good way to identify intersection obstructions. The objective of this study was to propose a methodology that could identify intersection obstructions by using LiDAR technology, three-dimensional terrain modeling, a plane-of-sight, and geographic information system spatial analysis. The methodology that was sought was also one that could quantify the severity levels of intersection obstructions and, potentially, be used to prioritize improvements for network-level safety. With the use of LiDAR data already available from Savannah, Georgia, experimental tests were conducted to identify obstructions at intersections. The intersection obstructions, identified with the proposed methodology, were compared with those obtained with the use of the 100-ft (30.5-m) line-of-sight (LOS) method. Results showed that the proposed method correctly identified 92% of intersection obstructions, compared with 64% identified by the LOS method. The severity levels of intersection sight distance obstructions also were quantified. Results showed that the proposed methodology provided a feasible platform and method for transportation agencies to use emerging LiDAR technology to identify intersection obstructions.