The integration of Connected Vehicles into conventional traffic systems presents significant challenges due to the diverse behaviors and objectives of different drivers. Conventional vehicle drivers typically follow User Equilibrium principles, aiming to minimize their individual travel times without considering the overall network impact. In contrast, Connected Vehicle drivers, guided by real-time information from central authorities or private service providers, can adopt System Optimum strategies or Cournot-Nash oligopoly behaviors, respectively. The coexistence of these distinct player classes in mixed-traffic environments complicates the task of achieving optimal traffic flow and network performance. This paper presents a comprehensive framework for optimizing mixed-traffic road networks through a multiclass traffic assignment model. The framework integrates three distinct types of players: conventional vehicle drivers adhering to User Equilibrium principles, Connected Vehicle drivers following System Optimum principles under a central governing authority, and Connected Vehicle drivers operating under Cournot-Nash oligopoly conditions with access to services from private companies. The methodology includes defining a model to achieve optimal mixed equilibria, designing an algorithm for multiclass traffic assignment, formulating strategic games to analyze player interactions, and establishing key performance indicators to evaluate network efficiency and effectiveness. The framework is applied to a real-world road network, validating its practicality and effectiveness through computational results. The extraction and analysis of computational results are used to propose optimal traffic management policies for mixed-traffic environments. The findings provide significant insights into the dynamics of mixed traffic networks and offer practical recommendations for improving traffic management in increasingly complex urban transportation systems.

Cooperative Intelligent Transport Systems (C-ITS) address contemporary transportation challenges, as Connected Vehicles (CVs) can play a pivotal role in enhancing efficiency and safety. The role of central governing authorities in shaping traffic management policies for CVs influences decision-making processes and system performance. In this work, the role of central governing authorities in the traffic management of a mixed traffic network is examined, integrating System Optimum principles with game theory. More specifically, we introduce and develop a framework that models and analyses the strategic interactions between different stakeholders in a mixed traffic environment, considering central governing authorities with varying levels of control. The results indicate how the various levels of control of a central governing authority may have an impact on the network in terms of traffic measures. Through a strategic games analysis, the trade-offs associated with centralized control mechanisms are demonstrated and recommendations are offered for policymakers and practitioners to optimize traffic management strategies.

Nowadays, traffic management challenges in the era of digital transport are rising, as the interactions of various stakeholders providing such technologies play a pivotal role in shaping traffic dynamics. The objective of this paper was to present a game-theory-based framework for modeling and optimizing urban traffic in road networks, considering the co-existence and interactions of different players composed of drivers of conventional vehicles, central governing authorities with traffic management capabilities, and competitive or cooperative connected mobility private service providers. The scope of this work was to explore and present the outcomes of diverse mixed equilibrium conditions in the road network of the city of Thessaloniki (Greece), integrating the principles of user equilibrium, system optimum, and Cournot oligopoly. The impacts of varying network attributes were systematically analyzed to provide quantitative indicators representing the overall network performance. Analysis of the results provided insights into the sensitivity and the resilience of the road network under various prevalence schemes of drivers of conventional vehicles, representing the user equilibrium characteristics, or drivers relying on traffic guidance provided by a central governing authority, representing the system optimum principles as well as the cooperation and competition schemes of private connected mobility providers with certain market shares in the network.