Affiliation:
1. Cairo University, Egypt
Abstract
Traffic Routing System (TRS) is one of the most important intelligent transport systems which is used to direct vehicles to good routes and reduce congestion on the road network. The performance of TRS mainly depends on a dynamic routing algorithm due to the dynamic nature of traffic on road network. AntNet algorithm is a routing algorithm inspired from the foraging behavior of ants. TAntNet is a family of dynamic routing algorithms that uses a threshold travel time to enhance the performance of AntNet algorithm when applied to traffic road networks. TAntNet-1 and TAntNet-2 adopt different techniques for path update to fast direct to the discovered good route and conserve on this good route. TAntNet-3 has been recently proposed by inspiring the scout behavior of bees to avoid the bad effect of forward ants that take bad routes. This chapter presents a new member in TAntNet family of algorithms called TAntNet-4 that uses two scouts instead of one compared with TAntNet-2. The new algorithm also saves the discovered route of each of the two scouts to use the best of them by the corresponding backward ant. The experimental results ensure the high performance of TAntNet-4 compared with AntNet, other members of TAntNet family.
Reference32 articles.
1. AntNet routing algorithm for data networks based on mobile agents. Inteligencia Artificial.;B.Barán;RevistaIberoamericana de Inteligencia Artificial,2001
2. Artificial Bee Colony Algorithm and Its Application to Generalized Assignment Problem
3. Boehlé, J. L., Rothkrantz, L. J. M., & van Wezel, M. (2008). CBPRS: A City Based Parking and Routing System (No. ERS-2008-029-LIS). Erasmus Research Institute of Management (ERIM), Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
4. Ant Colony Optimization Applied to Route Planning Using Link Travel Time Predictions
5. Cooperative Ant Colony Optimization in Traffic Route Calculations