Stability of transportation networks under adaptive routing policies

Stability of transportation networks under adaptive routing policies

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Article ID: iaor201530384
Volume: 81
Start Page Number: 886
End Page Number: 903
Publication Date: Nov 2015
Journal: Transportation Research Part B
Authors: , ,
Keywords: quality & reliability, vehicle routing & scheduling, networks: flow, queues: applications, markov processes, networks
Abstract:

Growing concerns regarding urban congestion, and the recent explosion of mobile devices able to provide real‐time information to traffic users have motivated increasing reliance on real‐time route guidance for the online management of traffic networks. However, while the theory of traffic equilibria is very well‐known, fewer results exist on the stability of such equilibria, especially in the context of adaptive routing policy. In this work, we consider the problem of characterizing the stability properties of traffic equilibria in the context of online adaptive route choice induced by GPS‐based decision making. We first extend the recent framework of ‘Markovian Traffic Equilibria’ (MTE), in which users update their route choice at each intersection of the road network based on traffic conditions, to the case of non‐equilibrium conditions, while preserving consistency with known existence and uniqueness results on MTE. We then exhibit sufficient conditions on the network topology and the latency functions for those MTEs to be stable in the sense of Lyapunov for a single destination problem. For various more restricted classes of network topologies motivated by the observed properties of travel patterns in the Singapore network, under certain assumptions we prove local exponential stability of the MTE, and derive analytical results on the sensitivity of the characteristic time of convergence to network and traffic parameters. The results proposed in this work are illustrated and validated on synthetic toy problems as well as on the Singapore road network with real demand and traffic data.

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