An Enhanced Network-Level Curve Safety Assessment and Monitoring Using Mobile Devices – Refinement and Field Evaluation

Details

• Creators:
  Tsai, Yichang (James) ; Mohammadi, Mohsen ; Yu, Pingzhou (Lucas) ; Yang, Zhongyu
• Corporate Creators:
  Georgia Institute of Technology
• Corporate Contributors:
  Georgia. Department of Transportation. Office of Performance-Based Management & Research ; United States. Department of Transportation. Federal Highway Administration
• Subject/TRT Terms:
  Ball Bank Indicator Countermeasures Curve Advisory Speed Curve Inventory Curve Warning Sign Design Data Analysis Evaluation Fatalities Highway Curves Horizontal Curve Safety Mobile Applications Monitoring MUTCD Ran Off Road Crashes Real Time Control Safety Analysis Speed

  More +
• Publication/ Report Number:
  FHWA-GA-26-2501
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final Report (January 2025 – January 2026)
• Corporate Publisher:
  Georgia. Department of Transportation. Office of Performance-Based Management & Research
• Abstract:
  Horizontal curves represent a small portion of the roadway network yet account for nearly one-quarter of fatal crashes, most of which involve vehicles running off the road due to excessive speed. Installing advisory speed signs before horizontal curves is a key countermeasure used by safety engineers to reduce curve-related fatalities, and identifying curves in need of such signs requires a proactive, data-driven approach. Recent NCHRP IDEA projects (214 and 248) introduced a low-cost, smartphone-based framework that leverages built-in GPS and IMU sensors to estimate curve superelevation and advisory speed in real time. Although these projects established the fundamental methodology, comprehensive evaluation of the framework’s accuracy and repeatability under real world conditions remains limited. This study addresses that gap through a rigorous field assessment comparing smartphone-derived measurements with high-precision 3D laser ground reference (GR) data and evaluating consistency across different vehicles and drivers. Two field sites in Georgia were selected to assess accuracy and repeatability, respectively. At the accuracy site on SR 190 (Pine Mountain), seventy test runs produced an overall superelevation RMSE of approximately 1.35 percent, and approximately 95% of advisory speed errors were within ±3 mph. Advisory speed RMSE values ranged from 1.3 to 2.1 mph across curves with varying radii. At the repeatability site on SR 136 (Cloudland Canyon), four of five vehicles produced consistent measurements, with a mean pointwise superelevation standard deviation of 0.535 percent and advisory speed standard deviation averaging 0.6 mph; one vehicle showed a systematic offset attributable to calibration or mounting issues. Overall, the findings demonstrate that the smartphone-based framework enables accurate, repeatable, and real-time curve advisory speed assessments suitable for field deployment. Real-time verification in the field reduces the need for return trips, improving efficiency and lowering costs for agencies, particularly in rural areas. As a low-cost and scalable solution, it supports more frequent curve assessments at both project and network levels, advancing proactive safety management to identify high-risk locations and implement countermeasures before crashes occur.
• Format:
  PDF
• Funding:
  PO#0020683
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:5ecfcd2cc5deaaea430398d5a5eb7298121297c664afbdd85ec2643ae7bafba4b2ea4e0144d8a2ac4f3aa006a43828796152ce83be04abcbb5f4baa7243223f0
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/91916/dot_91916_DS1.pdf
• File Type:
  [PDF - 2.35 MB ]