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10.1016_j.procs.2018.04.037.pdf (1.19 MB)

Prediction of Traffic Conflicts at Signalized Intersections using SSAM

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journal contribution
submitted on 2024-07-09, 13:26 and posted on 2024-07-09, 13:26 authored by Deepti Muley, Mohammad Ghanim, Mohamed Kharbeche

The use of microsimulation to model the vehicles movement and pedestrian movements within a traffic network is widely undertaken to test and evaluate operational performance of a traffic network under different traffic conditions and control schemes. However, few studies have used microsimulation techniques to study pedestrian-vehicle interactions and potential conflicts, as safety assessment tool. This paper demonstrates the use of microsimulation environment to predict vehicle-vehicle and pedestrian-vehicle conflicts at signalized intersections. A case study from Doha in the State of Qatar was used as a study site. The real-life conflicts were observed and recorded, along with traffic and pedestrians’ data. The studied intersection is then modeled and calibrated using VISSIM microsimulation tool, where vehicles and pedestrians’ trajectories were generated. Then, Surrogate Safety Assessment Model (SSAM) was used to analyze the simulated trajectories to identify potential conflicts within the study area. The results showed that potential conflicts could be reasonably predicted. Moreover, microsimulation can be used to predict the location of potential conflicts while scenario testing and the results can be determined to assess the impact of geometric improvement in reducing potential conflicts.

Other Information

Published in: Procedia Computer Science
License: http://creativecommons.org/licenses/by-nc-nd/4.0/
See article on publisher's website: https://dx.doi.org/10.1016/j.procs.2018.04.037

Funding

Qatar National Research Fund (NPRP8-365-2-150), Investigating Pedestrian Crossing Behavior to Improve Pedestrian Accident Rates and Severities in the State of Qatar.

History

Language

  • English

Publisher

Elsevier

Publication Year

  • 2018

License statement

This Item is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Institution affiliated with

  • Qatar University
  • College of Engineering - QU
  • Qatar Transportation and Traffic Safety Center - CENG

Geographic coverage

Qatar