4.4 Article

Are Older Drivers Safe on Interchanges? Analyzing Driving Errors Causing Crashes

期刊

TRANSPORTATION RESEARCH RECORD
卷 2675, 期 12, 页码 635-649

出版社

SAGE PUBLICATIONS INC
DOI: 10.1177/03611981211031232

关键词

-

资金

  1. University of North Florida and Florida International University

向作者/读者索取更多资源

Older drivers are more prone to making driving errors that can result in crashes, especially in locations with complex roadway features and high traffic conflicts. Understanding the factors that contribute to driving errors on interchanges is crucial for developing countermeasures to ensure safety for all road users. Results from a study in Florida using crash data from 2016-2018 revealed the importance of various factors such as driver gender, interchange type, distracted driving, lighting condition, area type, speed limit, time of day, and horizontal alignment in influencing driving errors on interchanges.
Older drivers are prone to driving errors that can lead to crashes. The risk of older drivers making errors increases in locations with complex roadway features and higher traffic conflicts. Interchanges are freeway locations with more driving challenges than other basic segments. Because of the growing population of older drivers, it is vital to understand driving errors that can lead to crashes on interchanges. This knowledge can assist in developing countermeasures that will ensure safety for all road users when navigating through interchanges. The goal of this study was to determine driver, environmental, roadway, and traffic characteristics that influence older drivers' errors resulting in crashes along interchanges. The analysis was based on three years (2016-2018) of crash data from Florida. A two-step approach involving a latent class clustering analysis and the penalized logistic regression was used to investigate factors that influence driving errors made by older drivers on interchanges. This approach accounted for heterogeneity that exists in the crash data and enhanced the identification of contributing factors. The results revealed patterns that are not obvious without a two-step approach, including variables that were not significant in all crashes, but were significant in specific clusters. These factors included driver gender and interchange type. Results also showed that all other factors, including distracted driving, lighting condition, area type, speed limit, time of day, and horizontal alignment, were significant in all crashes and few specific clusters.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.4
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据