A multinomial logit model of pedestrian-vehicle crash severity in North Carolina

Chen, Zhe; Fan, Wei

doi:10.1016/j.ijtst.2018.10.001

Cited by 97 publications

(54 citation statements)

References 18 publications

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“…This could be because of more traffic control devices on urban roadways. These results were exactly as found in [24,30].…”

Section: Roadway Characteristicssupporting

confidence: 91%

“…Finally, the roadway surface factor indicates that the dryness or wetness of the road had an effect on the likelihood of a fatality. Both dryness and wetness reduced the likelihood of fatal crashes for young and middle-aged drivers, similar to findings in Chen and Fan [24]. However, driving on a dry roadway surface lessened the likelihood (coefficient of −0.46) more than driving on a wet surface (coefficient of −0.39) for young drivers.…”

Section: Roadway Characteristicssupporting

confidence: 78%

“…There are numerous models used in crash severity analysis in literature. However, MNL is the most used statistical approach for establishing the significance of predictor variables in determining the outcome of response variables [24]. The MNL model does not put a restriction on the coefficient of predictor variables in different severity functions, thereby making it possible to observe the impact of a single variable on different injury outcomes [25].…”

Section: Model Formationmentioning

confidence: 99%

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Age-Related Differences in Motor-Vehicle Crash Severity in California

Adebisi

Masaki

Sobanjo

2019

Safety

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With ongoing changes in the age distribution of drivers in the United States, it is important to obtain insights on how to make the roadways equally safe for drivers across different age groups. In light of this, the objective of this study is to examine various crash characteristics and make recommendations on how to potentially improve roadway safety for all age groups. Using the Highway Safety Information System (HSIS) data, this study investigates the factors influencing motor-vehicle crash injury severity for young (aged 16–25), middle-aged (aged 26–64), and older drivers (above 64) in the state of California. A multinomial logit model was used to separately model crashes involving each age group and to evaluate the weight of different predictor variables on driver injury severity. The predictor variables were classified into four—driver, roadway, accident and environmental characteristics. Results suggest that there are close relationships between severity determinants for young and middle-aged drivers. However, older drivers tend to be most cautious among all age groups under all environmental and roadway conditions. Young drivers are more likely to explore their driving skills due to newness to driving. Middle-aged drivers are familiar with driving and tend to demonstrate less cautious behaviors, especially male drivers. Another insight obtained from this study is that older driver behavior is less dynamic compared to other age groups; their driving pattern is usually regular regardless of the surrounding conditions.

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“…This could be because of more traffic control devices on urban roadways. These results were exactly as found in [24,30].…”

Section: Roadway Characteristicssupporting

confidence: 91%

Section: Roadway Characteristicssupporting

confidence: 78%

Section: Model Formationmentioning

confidence: 99%

See 1 more Smart Citation

Age-Related Differences in Motor-Vehicle Crash Severity in California

Adebisi

Masaki

Sobanjo

2019

Safety

View full text Add to dashboard Cite

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“…In particular, Pour-Rouholamin et al's study [33] of children-involved crashes shows that pedestrian injury is more serious when children are younger. Chen and Fan [38] also noted that the age of a pedestrian has an effect on the crash fatality rates, but not on other severity levels. In addition, Haleem et al [39] studied the severity of pedestrian injuries at signalized and non-signalized intersections in Florida, U.S., and stated that very old people involved in crashes at both signalized and non-signalized intersections had similar levels of severe injuries; however, middle-aged individuals were more likely to suffer serious injuries at non-signalized intersections.…”

Section: Individual Characteristics Of Pedestrian-vehicle Crashesmentioning

confidence: 99%

A Multilevel Model Approach for Investigating Individual Accident Characteristics and Neighborhood Environment Characteristics Affecting Pedestrian-Vehicle Crashes

Park

2020

IJERPH

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Walking is the most basic movement of humans and the most fundamental mode of transportation. To promote walking, it is necessary to create a safe environment for pedestrians. However, pedestrian-vehicle crashes still remain relatively high in South Korea. This study employs a multilevel model to examine the differences between the lower-level individual characteristics of pedestrian crashes and the upper-level neighborhood environmental characteristics in Seoul, South Korea. The main results of this study are as follows. The individual characteristics of pedestrian-vehicle crashes are better at explaining pedestrian injury severity than built environment characteristics at the neighborhood level. Older pedestrians and drivers suffer more severe pedestrian injuries. Larger vehicles such as trucks and vans are more likely to result in a high severity of pedestrian injuries. Pedestrian injuries increase during inclement weather and at night. The severity of pedestrian injuries is lower at intersections and crosswalks without traffic signals than at crosswalks and intersections with traffic signals. Finally, school zones and silver zones, which are representative policies for pedestrian safety in South Korea, fail to play a significant role in reducing the severity of pedestrian injuries. The results of this study can guide policymakers and planners when making decisions on how to build neighborhoods that are safer for pedestrians.

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“…There is a large number of statistical techniques, such as binary logistic regression [13], ordered probit models [6,16], mixed logit models [17,18], and multinomial logit models [19,20], which can be applied to explore crash severity. However, traffic accidents often happen under different conditions, which make traffic safety data deeply heterogeneous and thus difficult to model [21].…”

Section: Literature Reviewmentioning

confidence: 99%

Investigating the Risk Factors Associated with the Severity of the Pedestrians Injured on Spanish Crosstown Roads

et al. 2019

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According to the Spanish General Traffic Accident Directorate, in 2017 a total of 351 pedestrians were killed, and 14,322 pedestrians were injured in motor vehicle crashes in Spain. However, very few studies have been conducted in order to analyse the main factors that contribute to pedestrian injury severity. This study analyses the accidents that involve a single vehicle and a single pedestrian on Spanish crosstown roads from 2006 to 2016 (1535 crashes). The factors that explain these accidents include infractions committed by the pedestrian and the driver, crash profiles, and infrastructure characteristics. As a preliminary tool for the segmentation of 1535 pedestrian crashes, a k-means cluster analysis was applied. In addition, multinomial logit (MNL) models were used for analysing crash data, where possible outcomes were fatalities and severe and minor injured pedestrians. According to the results of these models, the risk factors associated with pedestrian injury severity are as follows: visibility restricted by weather conditions or glare, infractions committed by the pedestrian (such as not using crossings, crossing unlawfully, or walking on the road), infractions committed by the driver (such as distracted driving and not respecting a light or a crossing), and finally, speed infractions committed by drivers (such as inadequate speed). This study proposes the specific safety countermeasures that in turn will improve overall road safety in this particular type of road.

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A multinomial logit model of pedestrian-vehicle crash severity in North Carolina

Cited by 97 publications

References 18 publications

Age-Related Differences in Motor-Vehicle Crash Severity in California

Age-Related Differences in Motor-Vehicle Crash Severity in California

A Multilevel Model Approach for Investigating Individual Accident Characteristics and Neighborhood Environment Characteristics Affecting Pedestrian-Vehicle Crashes

Investigating the Risk Factors Associated with the Severity of the Pedestrians Injured on Spanish Crosstown Roads

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