Abstract

Route guidance systems (RGSs), due to recent advances in technology, are emerging as a low-cost and fast solution to the congestion problem in urban areas. Route guidance with the aim of minimising total travel time (system optimum) causes longer paths, and consequently, more unfairness between individual users. Moreover, more congestion is created when guiding the users to their shortest paths (user equilibrium) to provide fairness among them. Therefore, an RGS that is able to combine these two inconsistent objectives, i.e. minimising total congestion of the network, and travel unfairness between individual travellers, would be of great value. To this end, a forced-node RGS is proposed in this study. The guidance task is delegated to some of the network nodes (e.g. intersections and roundabouts) in a distributed and autonomous way, similar to the routing operation in computer networks. Then, by applying a novel idea in transforming the demand rates, a non-recursive algorithm is proposed and compared with well-known traffic assignment methods; i.e. the classic user equilibrium and system optimal traffic assignment methods. Computational results affirmed the applicability of the forced-node RGS through the incorporation of both system and users’ benefits in different proportions.

Full Text
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