Transport modeling: An artificial immune system approach

Dušan Teodorović; Jovan Popović; Panta Lučić

doi:10.2298/YJOR0601003T

Authors

Dušan Teodorović Department of Civil and Environmental Engineering Virginia Polytechnic Institute and State University, Northern Virginia Center; Faculty of Transport and Traffic Engineering, Belgrade
Jovan Popović Faculty of Transport and Traffic Engineering, Belgrade
Panta Lučić CSSI, Inc., Washington

DOI:

https://doi.org/10.2298/YJOR0601003T

Keywords:

Uncertainty modelling, fuzzy sets, artificial immune system, transportation, traffic

Abstract

This paper describes an artificial immune system approach (AIS) to modeling time-dependent (dynamic, real time) transportation phenomenon characterized by uncertainty. The basic idea behind this research is to develop the Artificial Immune System, which generates a set of antibodies (decisions, control actions) that altogether can successfully cover a wide range of potential situations. The proposed artificial immune system develops antibodies (the best control strategies) for different antigens (different traffic "scenarios"). This task is performed using some of the optimization or heuristics techniques. Then a set of antibodies is combined to create Artificial Immune System. The developed Artificial Immune transportation systems are able to generalize, adapt, and learn based on new knowledge and new information. Applications of the systems are considered for airline yield management, the stochastic vehicle routing, and real-time traffic control at the isolated intersection. The preliminary research results are very promising.

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Transport modeling: An artificial immune system approach

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