Minimizing traffic congestion through continuous-time route reservations with travel time predictions

Road traffic congestion occurs as demand exceeds infrastructure's capacity. In this work we propose a continuous-time route reservation architecture to efficiently manage vehicle routing decisions thus to eliminate congested conditions. The related problem is formulated as a mixed integer linear programme (MILP) that routes vehicles while avoiding road segments that reach their critical density. To reduce the high computational complexity of the MILP approach we develop a heuristic algorithm, which is shown to perform well compared to the MILP formulation. The heuristic algorithm is used to conduct extensive microsimulations across a real network topology of the San Francisco area. Finally, an extension of the proposed architecture is also developed where the modeling uncertainties are considered through a time-varying regression method making able in real-time accurate travel-time predictions minimizing the reservation errors."© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. C. Menelaou, S. Timotheou, P. Kolios, C. G. Panayiotou and M. Polycarpou, "Minimizing traffic congestion through continuous-time route reservations with travel time predictions," in IEEE Transactions on Intelligent Vehicles. doi: 10.1109/TIV.2018.2886684 This work is partially funded by the Republic of Cyprus through the Research Promotion Foundation (Project:CULTURE/BRNE/0517/14