Probabilistic pedestrian safety modeling in intersections using a surrogate safety measure

Kaveh Gharieh, Farbod Farzan, Mohsen A. Jafari, Tao Gang

Research output: Contribution to conferencePaper

1 Citation (Scopus)

Abstract

This paper represents traffic conflict technique as a surrogate for real crashes that can be used to develop safety models in intersections. It focuses on pedestrian and crossing/merging vehicles safety in intersections. The high cost of pedestrian crashes to society is the main reason to study pedestrian safety. Training safety models with near miss events would be beneficial due to the fact that frequency of pedestrian crashes is low. In the proposed methodology, a pedestrian's risk is presented as a binomial categorical variable (low risk and high risk). The model is applied to each pedestrian movement at the intersection, so each crosswalk can be compared. By applying the statistical significance test, pedestrian flow and vehicle flow turns out to be the both dominant factors affecting the pedestrians' safety. In addition, finding out the vehicles hot spot locations in an intersection is of great importance. In this paper, a regression model is presented for the number of vehicle-vehicle near misses. Crossing vehicles flow turns out to be more effective on the near miss occurrence compared to the merging vehicles flow. Therefore, the results show the necessity of applying a countermeasure (i.e. protected left turn) to enhance the intersection safety.

Original languageEnglish (US)
StatePublished - Jan 1 2014
Event21st World Congress on Intelligent Transport Systems: Reinventing Transportation in Our Connected World, ITSWC 2014 - Detroit, United States
Duration: Sep 7 2014Sep 11 2014

Other

Other21st World Congress on Intelligent Transport Systems: Reinventing Transportation in Our Connected World, ITSWC 2014
CountryUnited States
CityDetroit
Period9/7/149/11/14

Fingerprint

Pedestrian safety
pedestrian
Merging
Crosswalks
significance test
Statistical tests
statistical significance
traffic
regression

All Science Journal Classification (ASJC) codes

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

Keywords

  • Multinomial logistic regression
  • Pedestrian and vehicle safety
  • Surrogate safety measure

Cite this

Gharieh, K., Farzan, F., Jafari, M. A., & Gang, T. (2014). Probabilistic pedestrian safety modeling in intersections using a surrogate safety measure. Paper presented at 21st World Congress on Intelligent Transport Systems: Reinventing Transportation in Our Connected World, ITSWC 2014, Detroit, United States.
Gharieh, Kaveh ; Farzan, Farbod ; Jafari, Mohsen A. ; Gang, Tao. / Probabilistic pedestrian safety modeling in intersections using a surrogate safety measure. Paper presented at 21st World Congress on Intelligent Transport Systems: Reinventing Transportation in Our Connected World, ITSWC 2014, Detroit, United States.
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Gharieh, K, Farzan, F, Jafari, MA & Gang, T 2014, 'Probabilistic pedestrian safety modeling in intersections using a surrogate safety measure', Paper presented at 21st World Congress on Intelligent Transport Systems: Reinventing Transportation in Our Connected World, ITSWC 2014, Detroit, United States, 9/7/14 - 9/11/14.

Probabilistic pedestrian safety modeling in intersections using a surrogate safety measure. / Gharieh, Kaveh; Farzan, Farbod; Jafari, Mohsen A.; Gang, Tao.

2014. Paper presented at 21st World Congress on Intelligent Transport Systems: Reinventing Transportation in Our Connected World, ITSWC 2014, Detroit, United States.

Research output: Contribution to conferencePaper

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N2 - This paper represents traffic conflict technique as a surrogate for real crashes that can be used to develop safety models in intersections. It focuses on pedestrian and crossing/merging vehicles safety in intersections. The high cost of pedestrian crashes to society is the main reason to study pedestrian safety. Training safety models with near miss events would be beneficial due to the fact that frequency of pedestrian crashes is low. In the proposed methodology, a pedestrian's risk is presented as a binomial categorical variable (low risk and high risk). The model is applied to each pedestrian movement at the intersection, so each crosswalk can be compared. By applying the statistical significance test, pedestrian flow and vehicle flow turns out to be the both dominant factors affecting the pedestrians' safety. In addition, finding out the vehicles hot spot locations in an intersection is of great importance. In this paper, a regression model is presented for the number of vehicle-vehicle near misses. Crossing vehicles flow turns out to be more effective on the near miss occurrence compared to the merging vehicles flow. Therefore, the results show the necessity of applying a countermeasure (i.e. protected left turn) to enhance the intersection safety.

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Gharieh K, Farzan F, Jafari MA, Gang T. Probabilistic pedestrian safety modeling in intersections using a surrogate safety measure. 2014. Paper presented at 21st World Congress on Intelligent Transport Systems: Reinventing Transportation in Our Connected World, ITSWC 2014, Detroit, United States.