Vehicular traffic under conditions of dynamic assignment and instantaneous network state information as a complex system

The proposed contribution addresses vehicular traffic on large networks. Typically what is considered is a regional sized network, such as the Ile-de-France network in which the number of daily car trips exceeded 14.5 million in 2018. In order to carry out a trip a traveler chooses his departure time and path, the result of which is called traffic assignment. The standard behavioral assumption for departure time and path choice is that the traveler minimizes his travel cost (travel time + monetary cost). The travel cost expresses the network supply, which depends on the traffic assignment. Since paths which are attractive in terms of their cost attract much demand and thus see their attractiveness diminish, traffic assignment must be viewed as an equilibrium process, which can be calculated as a fixed point [1]. The fixed point is not necessarily unique, a fact liable to induce chaotic behavior in path choice [2]. The choice of departure time need not be stable as shown in [3]. The impact of travel information systems on assignment dynamics was analyzed in [4] and leads to possibly chaotic behavior. The new systems of information (vehicle-to-vehicle communication, internet/portable operators, crowd sourcing) provide instantaneous travel time and network state information. They provide a communication both instantaneous and long-range between travelers in the network. When the path choice is determined based on such information, strong nonlinear feedback and dis-utilities occur [5]. [6] considers the impact of various types of information on combined departure and path choice in a simple setting, showing potential chaotic behavior. The object of the contribution is to analyze vehicular traffic as a complex system when the dynamic assignment process is governed by instantaneous travel time and traffic state information. The traffic flow model is simplified but recaptures essential features (travel time, congestion, competition for intersection resources). The proportion of travelers benefiting from instantaneous network information constitutes a parameter of the study. Travelers who do not benefit of instantaneous information rely on historical information.
References
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