In today’s urbanized world, cities are grappling with new challenges arising from population growth and rapid urbanization. Among these challenges, mobility stands out as a significant concern, as many cities were not initially designed to accommodate the surge in population. Enhancing mobility within smart cities has become a crucial endeavor in order to mitigate traffic congestion and promote sustainability by reducing greenhouse gas emissions. Additionally, improving mobility in smart cities contributes to enhancing the overall quality of life for citizens. Addressing vehicle behavior is crucial in reducing traffic congestion and improving commuting efficiency. Despite having robust infrastructures, disruptive driving habits such as aggressive driving, improper lane usage, and non-compliance with traffic rules can hinder the flow of traffic. By promoting responsible and considerate driving practices, we can optimize traffic flow and create a more efficient and stress-free commuting experience for individuals. Understanding the dynamics of mobility on highways is crucial for identifying the causes of traffic congestion. By analyzing these patterns, valuable insights can be gained, leading to the development of effective solutions for improving traffic flow. This study aims to investigate these aspects and propose strategies to contribute to overall mobility enhancements. To achieve this goal, a novel stochastic model based on the product form that accurately represents overtaking behaviors on highways is presented in this study. The model offers valuable insights into the dynamics of overtaking and provides a comprehensive understanding of this critical aspect of highway traffic. The paper presents a detailed model description and numerical resolution to calculate rewards such as delays and congestion.


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    Title :

    Analytical Study for Vehicle Mobility Modeling


    Contributors:
    Ben-Othman, J. (author) / Mokdad, L. (author)


    Publication date :

    2023-10-26


    Size :

    601646 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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