Modeling and predicting vehicle accident occurrence in Chattanooga, Tennessee.

Journal: Accident; analysis and prevention
Published Date:

Abstract

Given the ever present threat of vehicular accident occurrence endangering the lives of most people, preventative measures need to be taken to combat vehicle accident occurrence. From dangerous weather to hazardous roadway conditions, there are a high number of factors to consider when studying accident occurrence. To combat this issue, we propose a method using a multilayer perceptron model to predict where accident hotspots are for any given day in the city of Chattanooga, TN. This model analyzes accidents and their associated weather and roadway geometrics to understand the causes of accident occurrence. The model is offered as a live service to local law enforcement and emergency response services to better allocate resources and reduce response times for accident occurrence. Multiple models were made, each having different variables present, and each yielding varying results.

Authors

  • Jeremiah Roland
    University of Tennessee at Chattanooga Department of Engineering and Computer Science, United States. Electronic address: fpf852@mocs.utc.edu.
  • Peter D Way
    University of Tennessee at Chattanooga Department of Engineering and Computer Science, United States.
  • Connor Firat
    University of Tennessee at Chattanooga Department of Engineering and Computer Science, United States.
  • Thanh-Nam Doan
    University of Tennessee at Chattanooga Department of Engineering and Computer Science, United States.
  • Mina Sartipi
    University of Tennessee at Chattanooga Department of Engineering and Computer Science, United States.