A Comparative Analysis of Surrogate Safety Indicators for Road Hazard Assessment Using Smartphone GPS Data

Document Type : Original Article

Authors

1 Department of Civil Engineering, Faculty of Engineering, Shahid Bahonar University of Kerman, Kerman, Iran

2 Faculty of Civil Engineering, Iran University of Science and Technology, Tehran, Iran

3 Department of Civil Engineering, Faculty of Engineering, University of Gonabad, Gonabad, Iran

Abstract

Road Safety Assessment (RSA) can be conducted through two primary approaches: (1) the reactive approach, which relies on historical crash data; and (2) the proactive approach, which employs Surrogate Safety Indicators (SSIs). In the reactive approach, hazard potential is evaluated directly by measuring accident frequency, whereas in the proactive approach, SSIs must be validated against actual safety measures. However, few studies have systematically compared multiple SSIs to determine which indicators provide the most reliable correlation with actual crash occurrence, particularly in rural contexts where data collection is challenging. The purpose of this research is to compare 39 SSIs within the proactive RSA framework to identify potential hazards on rural road segments. An observational study was conducted employing Pearson correlation analysis, using vehicle velocity data collected via GPS-enabled smartphones from 100 vehicles across 125 km of rural roads. The analysis divided the road network into uniform 5-km segments and evaluated various crash severity levels, including fatal, injury, and total crashes. Among 39 proposed indicators, the deceleration frequency indicator (DNM1, counting all decelerations during braking without predefined thresholds) demonstrates the strongest correlation with crash data (r = 0.803 for property-damage crashes), establishing it as a highly robust proactive safety measure for rural road networks. Additionally, results revealed that traditional metrics like average vehicle velocity alone were poor predictors of safety compared to comprehensive deceleration-based measures, emphasizing the necessity of granular kinematic data. The findings enable transportation agencies to implement cost-effective, smartphone-based safety monitoring systems for real-time identification of high-risk rural road segments.

Keywords

Main Subjects

References

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Civil Engineering and Applied Solutions
Volume 3, Issue 2
April 2027
Pages 37-48

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History

  • Receive Date: 23 April 2026
  • Revise Date: 25 May 2026
  • Accept Date: 16 June 2026
  • First Publish Date: 16 June 2026

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