A microsimulation based analysis of the price of anarchy in traffic routing: The enhanced Braess network case. Issue 4 (15th June 2022)

• Record Type: Journal Article
• Authors: Belov, Aleksandr; Mattas, Konstantinos; Makridis, Michail; Menendez, Monica; Ciuffo, Biagio
• Is Part Of: Journal of intelligent transportation systems. Volume 26:Issue 4(2022)
• Page Start: 448
• Page End: 460
• Publication Date: 2022-06-15
• Subjects: Connected and automated vehicles -- Price of Anarchy -- system optimal assignment -- user equilibrium -- vehicle routing; Intelligent transportation systems -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.312
• DOI: 10.1080/15472450.2021.1904920
• Languages: English
• ISSNs: 1547-2450

Abstract

Abstract: In the scientific literature, the ratio between the total travel cost under a user equilibrium assignment and the total travel cost under a system optimum assignment is typically referred to as the Price of Anarchy (PoA), i.e., the level of inefficiency that can be eliminated by centralized control in routing. Recently, this concept has been attracting renovated attention due to the new opportunities offered by vehicles' connectivity and automation. The new technologies could allow individual prescriptions centrally managed to achieve benefits in network performance. However, considering the infrastructure that such a system would need and the ethical implications it could have (related to privacy, equity, etc.), it is necessary to carefully quantify its actual benefits. Existing PoA related studies do not fully capture the essential realism of traffic dynamics and show contradictory results. Moreover, there are no studies that explore the relation of the PoA and driving behavior (e.g., reaction time, acceleration, deceleration, aggressiveness, etc.), which is very important for designing the algorithms of automated driving. In this light, the present paper investigates the PoA over a Braess-like network using the most detailed way to model traffic—the microscopic simulation with parameters defining the driving behavior. The magnitude of the PoA has been studied over a wide range of combinations of the model input parameters. Results show that the PoA can be much higher than that obtained in theoretical studies. In addition, results are used to reveal some PoA features of real traffic networks and propose further research directions.