Implications of user and system optimum based traffic control considering autonomous fleets In transportation modeling, after defining a road network and its origindestination (OD) matrix, the next important question is how to assign traffic among ODpairs. In our days, the technology of advanced traveler information systems (ATIS) makes it possible to realize the xe2x80x9cuseroptimalxe2x80x9d solution. At the same time, with the advent of the Cooperative Intelligent Transport Systems (CITS) it is possible to solve the traffic assignment problem in xe2x80x9csystemoptimalxe2x80x9d way. The difference in transportation performance between useroptimal and systemoptimal principles is discussed in the paper. The main purpose of this research is to investigate what are the implications of the user and system optimal traffic assignment considering the autonomous vehicle fleets.

Routing a Fleet of Automated Vehicles in a Capacitated Transportation Network Routing of a fleet of automated unitoccupancy vehicles in a capacitated transportation network is an emerging problem that needs to be addressed to realize largescale automated transportation systems. We adopt an existing networkflowbased model for the problem and present a new reformulation based on DantzigWolfe decomposition. This reformulation allows us to apply the column generation solution technique which, in turn, enables us to solve largescale problem instances with tens of thousands of requests on networks with thousands of links. We empirically compare our method to the stateoftheart approach on several standard benchmark instances and find that the computational time of our solution approach scales qualitatively better in all tested problem instance parameters: namely, in the size of the transportation network, in the magnitude of demand intensity, and in the number of demand flows.