Balancing traffic flow by influencing drivers' route choices to alleviate congestion is becoming increasingly more appealing in urban traffic planning. Here, we introduce a discrete dynamical model comprising users who make their own routing choices on the basis of local information and those who consider routing advice based on localized inducement. We identify the formation of traffic patterns, develop a scalable optimization method for identifying control values used for user guidance, and test the effectiveness of these measures on synthetic and real-world road networks.
|Journal||Physical Review Research|
|Publication status||Published - 2 Sep 2020|
Bibliographical notePublished by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.
Funding: B.L. and D.S. acknowledge support from the Leverhulme Trust
(RPG-2018-092), European Union’s Horizon 2020 research and innovation programme under the Marie SkłodowskaCurie Grant Agreement No. 835913. D.S. acknowledges support from the EPSRC programme grant TRANSNET (EP/R035342/1). A.Y.L. acknowledges support from the Laboratory Directed Research and Development program of Los Alamos National Laboratory under Projects No. 20190059DR and No. 20200121ER.
- statistical physics, routing, traffic
Li, B., Saad, D., & Lokhov, A. Y. (2020). Reducing urban traffic congestion due to localized routing decisions. Physical Review Research, 2, [032059(R)]. https://doi.org/10.1103/PhysRevResearch.2.032059