Development of a prediction model for crash occurrence by analyzing traffic crash and citation data : final report.

Details

• Creators:
  Gonzalez-Velez, Enrique ; Gonzalez-Bonilla, Armando
• Corporate Creators:
  University of Puerto Rico (Mayaguez Campus). Dept. of Civil Engineering & Surveying
• Corporate Publisher:
  Transportation Informatics University Transportation Center
• Corporate Contributors:
  Transportation Informatics University Transportation Center
• Subject/TRT Terms:
  • Logistic regression analysis
  • Accident analysis
  • Accident characteristics
  • Driver errors
  • Traffic violations
  • Traffic accidents
  • Collisions
  • Accident data
  • Accident records
  • Traffic citations
  More +
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Description:
  It is commonly acknowledged that factors such as human factors, vehicle characteristics, road design and environmental factors highly contribute to the occurrence of traffic crashes (WHO, 2004). Since human factors usually have the most significant influence on traffic crash occurrence, studies normally focus on the effect that some driver characteristics have on the occurrence of a traffic crash, such as age, gender, alcohol usage and driving. One of the topics that these types of studies explore is the effect that a driver’s traffic violations and crash history has on the same driver being involved in a future vehicle crash. This research project aims to estimate the likelihood of a driver being involved or not in a vehicle crash by performing stepwise multiple logistic regression analyses. The data used was obtained by performing a survey on a sample of the driving population of Puerto Rico. Information such as age, gender, years of driving experience, daily hours spent driving and traffic violation and crash history were determined for a sample of the driving population of Puerto Rico. Results indicate that years of driving experience, gender and traffic violations history are significantly associated with being involved in a vehicle crash.
• Format:
  PDF
• Funding:
  DTRT13-G-UTC48
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/32820/dot_32820_DS1.pdf
• File Type:
  [PDF - 1.65 MB]
• Collection(s):
  University Transportation Centers ; US Transportation Collection
• Main Document Checksum:
  urn:sha256:3ff42c5bb01e5c12078e4cd6a5b5009caeb788852363018471b0b656aa114433