Reference
Z. Cong, B. De Schutter, and R. Babuška, "Ant colony routing algorithm
for freeway networks,"
Transportation Research Part C,
vol. 37, pp. 1-19, Dec. 2013.
Abstract
Dynamic traffic routing refers to the process of (re)directing vehicles at
junctions in a traffic network according to the evolving traffic conditions.
The traffic management center can determine desired routes for drivers in order
to optimize the performance of the traffic network by dynamic traffic routing.
However, a traffic network may have thousands of links and nodes, resulting in
a large-scale and computationally complex nonlinear, non-convex optimization
problem. To solve this problem, Ant Colony Optimization (ACO) is chosen as the
optimization method in this paper because of its powerful optimization
heuristic for combinatorial optimization problems. ACO is implemented online to
determine the control signal - i.e., the splitting rates at each node. However,
using standard ACO for traffic routing is characterized by four main
disadvantages: 1. traffic flows for different origins and destinations cannot
be distinguished; 2. all ants may converge to one route, causing congestion; 3.
constraints cannot be taken into account; and 4. neither can dynamic link
costs. These problems are addressed by adopting a novel ACO algorithm with
stench pheromone and with colored ants, called Ant Colony Routing (ACR). Using
the stench pheromone, the ACR algorithm can distribute the vehicles over the
traffic network with less or no traffic congestion, as well as reduce the
number of vehicles near some sensitive zones, such as hospitals and schools.
With colored ants, the traffic flows for multiple origins and destinations can
be represented. The proposed approach is also implemented in a simulation-based
case study in the Walcheren area, the Netherlands, illustrating the
effectiveness of the approach.
Publisher page
Downloads
BibTeX
@article{ConDeS:13-028,
author = {Cong, Zhe and De Schutter, Bart and Babu{\v{s}}ka, Robert},
title = {Ant Colony Routing Algorithm for Freeway Networks},
journal = {Transportation Research Part C},
volume = {37},
pages = {1--19},
month = dec,
year = {2013}
}