Develop a Tool for Sight Distance Analysis Using GIS and LiDAR Data

Details

• Creators:
  Zhou, Huaguo ; Yang, Fangjian
• Corporate Creators:
  Auburn University. Highway Research Center
• Corporate Contributors:
  Alabama. Department of Transportation
• Subject/TRT Terms:
  • Intersections
  • Sight distance
  • Triangles
  • Geographic information systems
  • Laser radar
  • Unsignalized intersections
  • GIS
  • LiDAR Data
• Publication/ Report Number:
  931-063
• Resource Type:
  Tech Report
• Geographical Coverage:
  Alabama ; United States
• Corporate Publisher:
  Alabama. Department of Transportation
• Abstract:
  Intersection Sight Distance (ISD) plays a critical role in ensuring roadway safety, particularly at unsignalized intersections where the lack of adequate visibility can result in severe accidents. Traditional ISD assessment methods often rely on manual measurements, which can be time-consuming, costly, and prone to inaccuracies. This study aims to address these limitations by developing an automated GIS-based tool that leverages LiDAR data to evaluate ISD at two-way stop-controlled (TWSC) intersections in Alabama. This tool facilitates efficient screening of large road networks, calculates the recommended ISD, and identifies sight distance obstructions. The method involves generating a digital surface model and conducting line-of-sight analyses while allowing users to customize such parameters as observer position, vehicle type, and vegetation exclusion. The developed method was applied to 13 intersections in Auburn, Alabama, and the results were validated against traditional field measurements. The comparison revealed that discrepancies mainly stemmed from human error in field assessments, dynamic changes in the environment, and the time lag between LiDAR data collection and field evaluation.
• Format:
  PDF
• Funding:
  931-063
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/85696/dot_85696_DS1.pdf
• File Type:
  [PDF - 3.03 MB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:ca60678bce7f81d6694f7ec0913aef757435ac495ad5f3c2a31f0d8be466bee13a2f7734b3683fed2c5523171db19daddf7dbc41a34c0d7d7439fd25dd9c6204