Using Interactive Highway Safety Design Model (IHSDM) to Evaluate the Safety of Signalized Intersections at Kerbala City

Saed, Mustafa Mohammad Redha Mohammed; Ewadh, Hussein Ali · 2024 · Crossref

DOI: 10.1007/978-981-97-9368-6_33

archive: archived pipeline: cataloged verified

Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)

Summary

This study addresses the need for region-specific calibration of accident predictive algorithms for two-lane highways, specifically within Guilan Province, Iran. The Interactive Highway Safety Design Model (IHSDM) relies on Accident Modification Factors (AMFs) and base models that may not accurately reflect local conditions due to differences in driving behavior, vehicle types, and geometric standards. The research aims to develop and validate local AMFs and a calibrated base model using Poisson regression, comparing these results against standard IHSDM values to determine their applicability and accuracy for the region. The methodology utilized accident statistics from 2014–2015 for 18 two-lane highways totaling 246 km. Data collection involved police records for non-intersection accidents, geometric reports, and field surveys to measure variables such as lane width, shoulder width, driveway density, roadside slope, distance to roadside objects, and terrain type. Due to limited permanent traffic recording stations, Average Daily Traffic (ADT) was estimated via short-term counts. The study employed a Poisson regression model to analyze the relationship between accident frequency and geometric/traffic variables. Variables such as roadside slope and shoulder falling were consolidated into a Roadside Hazard Rating (RHR) to reduce covariance issues. Driveway density was excluded from the final model due to lack of statistical significance. The results yielded a final regression model with an R-squared value of 0.939, identifying ADT, shoulder width, lane width, RHR, and terrain type as significant predictors. A calibration factor of 1.3628 was derived by comparing predicted accidents against observed data, indicating higher risk levels in the study area compared to the US-based base model. The study found that the locally derived AMFs for lane width and shoulder width were significantly higher than those in the IHSDM, particularly for narrower dimensions, suggesting that the standard model underestimates risk in this context. Conversely, the AMFs for RHR showed a stronger correlation with accident frequency in the local model, highlighting the critical role of roadside design in regional safety. The significance of this work lies in demonstrating that generic safety models require regional calibration to be effective. The inclusion of ADT as a power function in the local base model provided a more accurate representation of safety behavior across varying traffic volumes compared to the constant rate assumed in some standard models. The findings suggest that while the IHSDM provides a useful framework, the specific AMFs for lane and shoulder widths should be adjusted for Guilan Province to better reflect local safety risks. The study concludes that regression-based calibration using local data offers a viable method for improving accident prediction accuracy in regions lacking comprehensive before-and-after study data.

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed.

Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• roadway lighting effects

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Empirical Findings: crash risk outcomes