Traffic flow control in vehicular communication networks

Abstract

Control of conventional transportation networks aims at bringing the state of the network (e.g., the traffic flows in the network) to the system optimal (SO) state. This optimum is characterized by the minimality of the social cost function, i.e., the total cost of travel (e.g., travel time) of all drivers. On the other hand, drivers are assumed to be rational and selfish, and make their travel decisions (e.g., route choices) to optimize their own travel costs, bringing the state of the network to a user equilibrium (UE). In this paper we study the SO and UE of the future connected vehicular transportation network, where users consider the travel cost and the utility from data communication when making their travel decisions. We leverage the data communication aspect of the decision making to influence the user route choices, driving the UE state to the SO. We propose an algorithm for calculating the SO state, and the values of the data communication utility that drive the UE to the SO. This result provides a guideline on how the communication system operator can adjust the parameters of the communication network (e.g., data pricing and bandwidth) to achieve the optimal social cost. We also discuss the insights on a secondary optimization that the operator can conduct to maximize its own utility without deviating the transportation network state from the SO.