Using Topological Statistics to Bias and Accelerate Route Choice: Preliminary Findings in Synthetic and Real-World Road Networks

@inproceedings{Stefanello2016UsingTS,
  title={Using Topological Statistics to Bias and Accelerate Route Choice: Preliminary Findings in Synthetic and Real-World Road Networks},
  author={Fernando Stefanello and Bruno Castro da Silva and Ana L. C. Bazzan},
  booktitle={ATT@IJCAI},
  year={2016}
}
This paper discusses the first steps towards the definition of novel statistics and metrics that characterize networks in terms of the complexity they pose to the traffic assignment problem. Here, we follow an approach in which the assignment emerges from routes selected by learning agents. Specifically, we deal with issues related to how routes are coupled. We first define and quantify route coupling, i.e., how much a given route is coupled with other routes that can be used by learning agents… CONTINUE READING