Investigating the risk factors associated with pedestrian injury severity in Illinois

doi:10.1016/j.jsr.2016.03.004

Journal of Safety Research

Volume 57, June 2016, Pages 9-17

https://doi.org/10.1016/j.jsr.2016.03.004 Get rights and content

Highlights

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We examined the confounding factors that affect the injury severity of pedestrians in single-vehicle, single-pedestrian cashes in Illinois considering the ordered nature of severity.
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Factors like older pedestrians, not wearing contrasting clothing, adult drivers, drunk drivers, and darkness increase injury severity.
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Factors like crossing the street at crosswalks, older drivers, urban areas, and presence of traffic control devices decrease injury severity.
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Three different ordered-response models were compared in terms of performance.
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Partial proportional odds model was found to outperform the other ordered-response models.

Abstract

Introduction

Pedestrians are known as the most vulnerable road users, which means their needs and safety require specific attention in strategic plans. Given the fact that pedestrians are more prone to higher injury severity levels compared to other road users, this study aims to investigate the risk factors associated with various levels of injury severity that pedestrians experience in Illinois.

Method

Ordered-response models are used to analyze single-vehicle, single-pedestrian crash data from 2010 to 2013 in Illinois. As a measure of net change in the effect of significant variables, average direct pseudo-elasticities are calculated that can be further used to prioritize safety countermeasures. A model comparison using AIC and BIC is also provided to compare the performance of the studied ordered-response models.

Results

The results recognized many variables associated with severe injuries: older pedestrians (more than 65 years old), pedestrians not wearing contrasting clothing, adult drivers (16–24), drunk drivers, time of day (20:00 to 05:00), divided highways, multilane highways, darkness, and heavy vehicles. On the other hand, crossing the street at crosswalks, older drivers (more than 65 years old), urban areas, and presence of traffic control devices (signal and sign) are associated with decreased probability of severe injuries.

Conclusions and practical applications

The comparison between three proposed ordered-response models shows that the partial proportional odds (PPO) model outperforms the conventional ordered (proportional odds—PO) model and generalized ordered logit model (GOLM). Based on the findings, stricter rules to address DUI driving is suggested. Educational programs need to focus on older pedestrians given the increasing number of older people in Illinois in the upcoming years. Pedestrians should be educated to use pedestrian crosswalks and contrasting clothing at night. In terms of engineering countermeasures, installation of crosswalks where pedestrian activity is high seems a promising practice.

Introduction

Despite considerable advances in the vehicle industry and safety of occupants, the safety of pedestrians as the most vulnerable road users is yet a major concern. Overall road fatalities as well as driver and pedestrian fatalities were calculated by running a query on the Fatality Analysis Reporting System (FARS) database spanning from 2004 to 2013—a 10-year time interval (NHTSA, 2015). Within this time period, the total number of traffic fatalities decreased by 23.6% in 2013 compared to 2004 (an average decrease of 2.9% per year), and the total driver fatalities decreased by 28.9%. However, the total number of pedestrian fatalities increased by 15.9% (from 4028 fatalities in 2004 to 4668 fatalities in 2013). It should also be noted that the share of driver fatalities dropped from 54.1% in 2004 to 50.3% in 2013, while these numbers for pedestrians are 9.4% and 14.3%, respectively. Specifically related to Illinois, the share of pedestrians increased from 11.5% in 2004 to 12.6% in 2013, while the total number of traffic fatalities dropped by 26.9%.

With the number of cars and total vehicle miles traveled (VMT) increasing in the upcoming years, the need for more robust safety interventions based on actual crash data analysis is warranted. In this study, the Illinois pedestrian crash data (those caused by single vehicles without any passengers colliding with single pedestrians) were analyzed using ordered-response models to consider the ordered nature of crash severity. The main objective is for the results of this study to provide meaningful insight into pedestrian crash severity for the state of Illinois. Addressing this particular consideration as the main objective to save lives by suggesting safety measures, this study also compares performances of three different ordered-response models.

The rest of this paper is organized as follows: A review of prior research on pedestrian injury severity is provided in Section 2. The database used for analysis along with descriptive statistics of the possible risk factors are presented in Section 3. Ordered-response models (i.e., conventional ordered logit, generalized ordered logit model, and partial proportional odd model), their formulations, and their applications as well as pseudo-elasticity are discussed in Section 4. In Section 5, the proposed model is applied to the crash data set and parameter estimates, and average direct pseudo-elasticities for each injury severity level are calculated. Finally, Section 6 concludes this paper and provides safety recommendations.

Section snippets

Prior research

Several studies in the past have analyzed pedestrian crashes and the level of severity incurred by these road users and identified the role of possible risk factors as well as appropriate countermeasures using a variety of statistical methods (Roudsari et al., 2005, Nasar and Troyer, 2013, Al-Shammari et al., 2009, Tarko and Azam, 2011, Sarkar et al., 2011, Strandroth et al., 2011, Oh et al., 2005, Mohamed et al., 2013, Ulfarsson et al., 2010, Eluru et al., 2008, Cinnamon et al., 2011, Gårder,

Data

The data used in this study are based on the police-reported roadway crash data in Illinois, which is accessible through the Illinois crash database. The database is separated into three different text files (crash, person, and vehicle), including a wide range of various characteristics and information regarding each of these categories. The crash file includes information such as type of collision (pedestrian, fixed object, etc.), temporal distributions of the crash (e.g., weekend/weekday,

Methodology

As mentioned in the previous section, in this study the dependent variable (pedestrian injury severity) represents an ordered outcome (ascending from no/possible injury to severe injury). Therefore, an ordered-response model is appropriate to analyze the data. Three ordered-response models that have previously been used in the literature will be introduced in the following sub-sections, including conventional ordered logit (proportional odds—PO) model, generalized ordered logit model (GOLM),

Results and discussion

While fitting any ordered-response model using the available data, the parallel line assumption needs to be checked in order to choose between three abovementioned models (PO, GOLM, and PPO). In doing so, a Brant test was used, and as mentioned earlier, this test can be conducted for both the entire model (including all the variables) and each single parameter separately. Using the Brant test, it was found that the parallel line assumption for some variables is violated, therefore necessitating

Conclusions and recommendations

This paper employed a partial proportional odds (PPO) model to analyze and identify risk factors of pedestrian injury severity in pedestrian–vehicle crashes using Illinois crash data from 2010 to 2013. To offset the effect of the presence of other accompanying passengers in the vehicle and accompanying persons with the pedestrian, the focus of this research was set at single-driver, single-pedestrian crashes. Three severity levels based on the injury severity sustained by the pedestrian (as the

Acknowledgments

This study was sponsored by the Illinois Center for Transportation (ICT).

Mahdi Pour-Rouholamin, S.M.ASCE, is currently a doctoral candidate at the Auburn University's Samuel Ginn College of Engineering. Since the beginning of his career as a safety engineer, he has focused on various safety-related topics. His main research interests include crash data analysis, traffic operations and safety, traffic modeling, operational effects of geometrics, and intelligent transportation systems.

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Huaguo Zhou, Ph.D., P.E., is an associate professor in the Department of Civil Engineering at Auburn University. He earned a doctorate of philosophy degree in civil engineering from the University of South Florida. He is a fellow of ITE and a licensed professional engineer in Florida.

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