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Point-process modeling of secondary crashes

Author

Listed:
  • Samarth Motagi
  • Sirish Namilae
  • Audrey Gbaguidi
  • Scott Parr
  • Dahai Liu

Abstract

Secondary crashes or crashes that occur in the wake of a preceding or primary crash are among the most critical incidents occurring on highways, due to the exceptional danger they present to the first responders and victims of the primary crash. In this work, we developed a self-exciting temporal point process to analyze crash events data and classify it into primary and secondary crashes. Our model uses a self-exciting function to describe secondary crashes while primary crashes are modeled using a background rate function. We fit the model to crash incidents data from the Florida Department of Transportation, on Interstate-4 (I-4) highway for the years 2015–2017, to determine the model parameters. These are used to estimate the probability that a given crash is secondary crash and to find queue times. To represent the periodically varying traffic levels and crash incidents, we model the background rate, as a stationary function, a sinusoidal non-stationary function, and a piecewise non-stationary function. We show that the sinusoidal non-stationary background rate fits the traffic data better and replicates the daily and weekly peaks in crash events due to traffic rush hours. Secondary crashes are found to account for up to 15.09% of traffic incidents, depending on the city on the I-4 Highway.

Suggested Citation

  • Samarth Motagi & Sirish Namilae & Audrey Gbaguidi & Scott Parr & Dahai Liu, 2023. "Point-process modeling of secondary crashes," PLOS ONE, Public Library of Science, vol. 18(12), pages 1-16, December.
    • Handle: RePEc:plo:pone00:0295343
    DOI: 10.1371/journal.pone.0295343
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    References listed on IDEAS

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    1. Sabique Islam & Sirish Namilae & Richard Prazenica & Dahai Liu, 2020. "Fuel shortages during hurricanes: Epidemiological modeling and optimal control," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-20, April.
    2. Aït-Sahalia, Yacine & Cacho-Diaz, Julio & Laeven, Roger J.A., 2015. "Modeling financial contagion using mutually exciting jump processes," Journal of Financial Economics, Elsevier, vol. 117(3), pages 585-606.
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