Analysis of train collision risk in the United States: 2001 to 2015

Tejashree Turla, Xiang Liu, Zhipeng Zhang, Zheyong Bian

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Railways have a substantial contribution to the economy of the United States. However, a train accident can result in casualties and extensive damages to infrastructure and the environment. Most of the prior research focused on derailments or grade-crossing accidents rather than the study of train collisions. The Federal Railroad Administration (FRA) identifies over 300 causes for all types of accidents, among which we aim to recognize the major factors that cause train collisions. Evaluating how collision frequency and severity vary with the accident cause is the key part of this research, in order to identify, evaluate and mitigate transportation risk. This paper presents a statistical analysis of passenger and freight train collisions in the United States from 2001 to 2015 to statistically analyze train collision frequency, severity, accident cause, and safety risk. The analysis finds that human errors and signal failures are among the most common causes of train collisions in U.S. in the 15-year study period. There is a significant decline in the overall train collision frequency by year. By observing these trends with respect to train collisions, possible accident prevention strategies could be developed and implemented accordingly.

Original languageEnglish (US)
Title of host publication2018 Joint Rail Conference, JRC 2018
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791850978
StatePublished - 2018
Event2018 Joint Rail Conference, JRC 2018 - Pittsburgh, United States
Duration: Apr 18 2018Apr 20 2018

Publication series

Name2018 Joint Rail Conference, JRC 2018


Other2018 Joint Rail Conference, JRC 2018
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Transportation
  • Mechanical Engineering
  • Electrical and Electronic Engineering
  • Automotive Engineering


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