Abstract
We present an improved ant colony algorithm-based approach to assess the vulnerability of a road network and identify the critical infrastructures. This approach improves computational efficiency and allows for its applications in large-scale road networks. This research involves defining the vulnerability conception, modeling the traffic utility index and the vulnerability of the road network, and identifying the critical infrastructures of the road network. We apply the approach to a simple test road network and a real road network to verify the methodology. The results show that vulnerability is directly related to traffic demand and increases significantly when the demand approaches capacity. The proposed approach reduces the computational burden and may be applied in large-scale road network analysis. It can be used as a decision-supporting tool for identifying critical infrastructures in transportation planning and management.
Highlights
As a primary infrastructure of the modern city, a robust transportation network is one of the preconditions of a flourishing economy and a high standard of living-class life
Note that the distance used in the improved ant colony algorithm should be replaced by travel time, so ηij = 1/(dij + djE) should be expressed as ηij = 1/(Tij + TjE)
The improved ant colony algorithm adopted in this paper reduces the calculation time to 4/5 of the time required by the traditional traffic assignment method
Summary
As a primary infrastructure of the modern city, a robust transportation network is one of the preconditions of a flourishing economy and a high standard of living-class life. There are many events emergencies, such as traffic congestion, traffic accidents, road maintenance, bad weather, and terrorist activities, that can have a tremendous impact on the operational performance of the road network and can make some road segments impassible. Its optimal path searching procedure is very similar to the process of how vehicles select routes; we will use the ant colony algorithm to solve the traffic assignment problem. The objective of the proposed study is to develop methods for evaluating and determining the vulnerable road segments in a road network.
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