Safety performance of passing zone segments on two-lane rural highways in Pennsylvania: Comparing crash modification factors from causal inference and unobserved heterogeneity models

Research output: Contribution to journalArticlepeer-review

Abstract

Passing zones on two-lane rural highways are marked based on minimum passing sight distance criteria associated with the 85th-percentile speed or posted speed limit along the roadway segment. Although passing-related crashes account for a relatively small proportion of total reported crashes on two-lane rural highways, past research suggests that they tend to result in more severe injuries than non-passing-related crashes. However, the safety performance of roadway segments with passing zones has not been quantified or compared to segments with no passing zones. The purpose of this paper is to use data from Pennsylvania to compare the safety performance of two-lane rural highways with and without the presence of passing zone markings. Total crashes, fatal plus injury crashes, and target crashes are used to estimate crash modification factors (CMFs) for the presence of passing zones. A second objective of the paper is to compare the CMFs developed using two different methodological approaches: the propensity scores-potential outcomes causal inference framework and unobserved heterogeneity (random parameters) models. The results indicate that the CMFs developed using these two approaches are similar, although the CMFs from the unobserved heterogeneity models tended to estimate slightly fewer expected crashes in passing zone segments than the causal inference method. When compared to road segments without passing zones, those with passing zones experienced fewer total crashes, fatal and injury crashes, and head-on plus sideswipe crashes by 11.2 %, 12.2 %, and 10.6 %, respectively, based on the causal inference method.

Original languageEnglish (US)
Article number108165
JournalAccident Analysis and Prevention
Volume220
DOIs
StatePublished - Sep 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Human Factors and Ergonomics
  • Safety, Risk, Reliability and Quality
  • Public Health, Environmental and Occupational Health
  • Law

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