A Multiagent Based Road Pricing Approach for Urban Traffic Management

Traffic is a social system composed by different interacting entities and its optimization is not a trivial task. When drivers and infrastructure co-adapt to deal with the varying demand and infrastructure changes, respectively, centralized traffic optimization approaches face many difficulties. This work presents a multiagent based approach that uses variable road pricing to improve traffic efficiency. While infrastructure updates roads prices to cope with the varying demand, drivers try to adapt themselves to the road network changes in order to minimize their costs. Drivers have different preferences, caring either about their travel time (being hasty) or credit expenditure (being economic). Results show that the proposed road pricing approach benefits the hasty drivers, while more sophisticated pricing update policies need to be developed in order to create better alternatives for economic drivers.