Assessing visibility at highway-rail grade crossings using light detection and ranging (LiDAR) technology

Abstract

In 2022, 2034 incidents occurred at highway-rail grade crossings (HRGCs) in the United States, posing significant risks such as fatalities, injuries, and property damage. These incidents underscore the need for effective prevention and mitigation strategies. With over 212,000 public and private HRGCs nationwide, safety monitoring is challenging, as traditional inspections primarily rely on manual assessments. Obstructed sightlines at HRGCs further increase safety risks by limiting road users' ability to see approaching trains. Although previous studies have addressed behavioral and safety issues, the literature currently lacks quantitative data analysis of sightlines at HRGCs. This study aims to address this gap by utilizing remote sensing techniques to identify and quantify sightline visibility. We studied 12 HRGCs using geospatial analysis in ArcGIS Pro through Viewshed and Observer Points analysis, integrating United States Geological Survey (USGS) Light Detection and Ranging (LiDAR) data with United States Federal Railroad Administration (FRA) crossing reports. Our findings indicate that sightline issues in the case studies reviewed are primarily linked to traffic control devices, environmental factors, and geometric conditions. Additionally, the results suggest that USGS LiDAR data and geospatial analysis offer potentially rapid and cost-effective methods for identifying sightline safety issues at HRGCs.

Keywords

• Highway-rail grade crossings
• Sightlines
• Geospatial analysis
• LiDAR data