Do factors associated with older pedestrian crash severity differ? A causal factor analysis based on exposure level of pedestrians

Abstract

Objective

Older pedestrians are more likely to have severe or fatal consequences when involved in traffic crashes. Identifying the factors contributing to the severity and possible interdependencies between factors in specific exposure areas is the first step to improving safety. Therefore, examining the causal factors’ impact on pedestrian-vehicle crash severity in a given area is vital for formulating effective measures to reduce the risk of pedestrian fatalities and injuries.

Methods

This study implements the Thiessen polygon algorithm deployed to define older pedestrians’ exposure influence area. Enabling trip characteristics and built environment information as exposure index settings for the background of the pedestrian severity causal analysis. Then, structural equation modeling (SEM) was applied to conduct a factor analysis of the crash severity in high- and low-exposure areas. The SEM evaluates latent factors such as driver risk attitude, risky driving behavior, lack of risk perception among older pedestrians, natural environment, adverse road conditions for driving or walking, and vehicle conditions. The SEM crash model also establishes the relationship between each latent factor.

Results

In total, drivers’ risky driving behavior (0.270, p < 0.05) in low-exposure areas significantly impacts older pedestrian crash severity more than in high-exposure areas. Lack of risk perception among older pedestrians (0.232, p < 0.05) is the most critical factor promoting crash severity in high-exposure areas. The natural environment (0.634, p < 0.05) in high-exposure areas positively influences older pedestrians’ lack of risk perception more than in low-exposure areas.

Conclusions

Significant group differences (p-values ∼ 0.001-0.049) existed between the causal factors of the high-exposure risk areas and the low-exposure risk factors. Different exposure intervals require detailed scenarios based on the critical risks identified. The crash severity promotion measures in different exposure areas can be focused on according to the critical causes analyzed. Those clues, in turn, can be used by transportation authorities in prioritizing their plans, policies, and programs toward improving the safety and mobility of older pedestrians.

Keywords:

• Pedestrian safety
• older pedestrian crash
• structural equation modeling
• factor analysis

Acknowledgements

The authors also thank Mr. Janson at the University of Colorado Denver for providing analysis support.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

We do not have permission to share research data.

Additional information

Funding

This work was supported by the Beijing Natural Science Foundation of China under grant number J210001. This work was partly supported by the University of Colorado Denver and the Mountain Plains Consortium, a University Transportation Center funded by the U.S. Department of Transportation.