Abstract for presentation (Poster or Podium) with a Paper in the Conference Proceedings
Rail Transport
Paul Olukoye Omulokoli, n/a
GRADUATE RESEARCH ASSISTANT
South Carolina State University
Orangeburg, South Carolina, United States
Paul Olukoye Omulokoli, n/a
GRADUATE RESEARCH ASSISTANT
South Carolina State University
Orangeburg, South Carolina, United States
Judith Mwakalonge, Academic Supervisor
Associate Professor
South Carolina State University
Orangeburg, South Carolina, United States
Saidi Siuhi, Professor
Assistant Professor
South Carolina State University
ORANGEBURG, South Carolina, United States
PAUL OLUKOYE OMULOKOLI
South Carolina State University
Orangeburg, South Carolina, United States
Due to the mass of trains, crashes at highway-rail-grade crossings result in fatal and high severity injuries to the occupants of the vehicles. Different factors have been shown to contribute to the crash occurrence at these crossings. The study examines these contributory factors for crashes at highway-rail-grade crossings in Texas, the state that recorded the highest rail crossing crashes in the USA between 2015 and 2021. The study will also investigate the variation in the influence of at-fault driver characteristics influencing the crash severity over time. The analysis will involve the use of three possible injury severity outcomes namely fatal injury severe injury and no injury or property damage only to investigate the factors which include the driver characteristics, crash characteristics, roadway characteristics, rail crossing characteristics, and environmental characteristics. The study will use crash data from the Texas Department of Transportation and crash inventory information from the Federal Rail Administration to develop a merged database with crash data and crossing characteristics. The data will be analyzed using the appropriate model to determine the contributing factors that increase the risk of being involved in fatal crashes, severe injury crashes and property damage only crashes. The temporal stability of at-fault driver characteristics such as age, gender and injury severity will also be assessed on a year-to-year basis, and results obtained used to propose recommendations to ensure the relevant agencies identify the long-term trends and by predicting the high-risk factors, develop better safety countermeasures to reduce crashes.