Istrazivanja i projektovanja za privreduJournal of Applied Engineering Science


DOI: 10.5937/jaes0-45808 
This is an open access article distributed under the CC BY 4.0
Creative Commons License

Volume 21 article 1158 pages: 1179-1191

Ayoub Laarej
Laboratoire de Matière Condensée et Sciences Interdisciplinaries (LaMCScl), URL-CNRST, P. O. Box 1014, Faculty of Sciences, Mohammed V University in Rabat, Morocco

Noureddine Lakouari
Department of Computer Science, Instituto Nacional de Astrofisica, Optica y Electronica, Luis Enrique Erro 1, Tonanzintla, 72840, Puebla, Mexico; Consejo Nacional de Humanidades, Ciencias y Tecnologías (Conahcyt), Insurgentes Sur 1582, Mexico City, 03940, Mexico

Azeddine Karakhi
Laboratoire de Matière Condensée et Sciences Interdisciplinaries (LaMCScl), URL-CNRST, P. O. Box 1014, Faculty of Sciences, Mohammed V University in Rabat, Morocco

Hamid Ez-Zahraouy*
Laboratoire de Matière Condensée et Sciences Interdisciplinaries (LaMCScl), URL-CNRST, P. O. Box 1014, Faculty of Sciences, Mohammed V University in Rabat, Morocco

Traffic bottleneck is considered as one of the major causes of the disturbance in traffic flow. The understanding the dynamics between vehicles and bottlenecks is crucial for enhancing traffic flow and ensuring road safety. This research examines a two-lane traffic cellular automaton model to understand the effects of static (e.g., lane reductions) and dynamic (e.g., slow-moving vehicles) bottlenecks on traffic flow and road safety. We found that at low vehicle densities, slow vehicles gravitate towards the open lane, while faster vehicles switch lanes to overtake, returning to their original lane post-bottleneck. At high densities, traffic flow near static bottlenecks ceases, independent of bottleneck length. Safety analysis shows that extended static bottlenecks reduce rear-end collision risk due to fewer lane changes and increased vehicle stationarity. At maximum density, gridlock nullifies the chance of such collisions. Our findings provide actionable insights for traffic planning focused on bottleneck management to improve road safety.

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