Elderly Pedestrian Fatal Crash-Related Contributing Factors: Applying Empirical Bayes Geometric Mean Method

Subasish Das, Apoorba Bibeka, Xiaoduan Sun, Hongmin “Tracy” Zhou, Mohammad Jalayer

Research output: Contribution to journalArticle

Abstract

Recent statistics show that around 20% of all pedestrian fatalities (1,002 out of 5,376) in 2015 were pedestrians over the age of 65. There is a need to identify issues associated with elderly pedestrian crashes to develop effective countermeasures. This study aimed to determine the key associations between contributing factors of elderly pedestrian crashes. The authors analyzed three years (2014 to 2016) of elderly pedestrian fatal crashes from the Fatality Analysis Reporting System in the United States by using empirical Bayes (EB) data mining. The findings of this study revealed several association patterns with high crash potential for elderly pedestrians that include backing vehicle-related crashes for female pedestrians (especially those aged 79 and above), segment-related crashes at night for 65 to 69 year-old male pedestrians, crossing an expressway at night for male pedestrians, especially the 65 to 69 year group, failure to yield while crossing at intersections, and crashes occurring in the dark with poor street lighting. The findings of this study could help authorities determine effective countermeasures for this group of vulnerable road users.

Original languageEnglish (US)
Pages (from-to)254-263
Number of pages10
JournalTransportation Research Record
Volume2673
Issue number8
DOIs
Publication statusPublished - Aug 1 2019

    Fingerprint

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Mechanical Engineering

Cite this