Author Information

Fanny KristianssonFollow

Is this project an undergraduate, graduate, or faculty project?

Undergraduate

individual

Daytona Beach

Poster Session; 5-minute Oral Presentation; 10-minute Oral Presentation

Authors' Class Standing

Fanny Kristiansson, Senior

Lead Presenter's Name

Fanny Kristiansson

Faculty Mentor Name

Hongyun Chen

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Abstract

This study investigated the characteristics of the nighttime crashes at freeway mainline segments and the contributing factors to injury levels. The nighttime crash rate is 1.6 times more than daytime and the fatality rate is higher. In this study five injury levels, no injury, possible injury, non-incapacitating injury, capacitating injury, and fatal injury, were considered. Crash data (2005-2010) were collected for interstate highways in Florida. The no injury level was used as the baseline. Multinomial logit model (MNL) was selected to estimate the explanatory variables at 95% confidence. Contributing factors included driver-conditions, geometric-conditions, vehicle-conditions, crash-conditions, and environmental-conditions. This study concluded that safety equipment reduces crashes, alcohol, drugs and young drivers increase the likelihood of severe crashes.

Did this research project receive funding support (Spark, SURF, Research Abroad, Student Internal Grants, or Ignite Grants) from the Office of Undergraduate Research?

No

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Understanding the Contributing Factors to Nighttime Crashes at Freeway Mainline Segments

This study investigated the characteristics of the nighttime crashes at freeway mainline segments and the contributing factors to injury levels. The nighttime crash rate is 1.6 times more than daytime and the fatality rate is higher. In this study five injury levels, no injury, possible injury, non-incapacitating injury, capacitating injury, and fatal injury, were considered. Crash data (2005-2010) were collected for interstate highways in Florida. The no injury level was used as the baseline. Multinomial logit model (MNL) was selected to estimate the explanatory variables at 95% confidence. Contributing factors included driver-conditions, geometric-conditions, vehicle-conditions, crash-conditions, and environmental-conditions. This study concluded that safety equipment reduces crashes, alcohol, drugs and young drivers increase the likelihood of severe crashes.

 

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