Improving regional road network resilience by optimised traffic guidance

In this paper, a new approach for improving the traffic performance of regional road networks during the recovery period following a disaster life cycle is presented. Regional road networks are often uncongested and have sparse and long-spanning link densities. Consequently, they are more impacted by natural disasters and thereby by potential road closures that may be imposed afterwards. Information about road closures after disruptive events can be transmitted through roadside information dissemination methods such as variable message signs, Cooperative-Intelligent Transport Systems or highway advisory radio. This paper proposes an optimisation model to find optimal location of roadside guidance devices across a regional road network for improving total travel time (TTT) within the network. To achieve this, firstly, a network design model is formulated using a bi-level framework and implemented to find the optimal locations of roadside guidance devices that lead to reducing the TTT of a disrupted network. Secondly, two methods for solving the formulated problem are presented, an exact solution method called SO-relaxation that cuts the solution space using system optimum traffic assignment. The other method is a hybrid-genetic algorithm (GA) that is a heuristic solution method. Results show that locating guidance devices optimally in a disrupted network leads to a more resilient road network in which the post-disaster TTT of the network during recovery phase is less than when no action is taken. It is also shown that the improvement achieved by roadside guidance is a function of available resources and the road users willingness to obey the guidance provided.

Language

  • English

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Filing Info

  • Accession Number: 01644202
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Aug 29 2017 10:07AM