Computational Intelligence Techniques in Transportation and Communication Planning and Traffic Control

Complex traffic and transportation problems call for development of modern intelligent systems that merge knowledge, techniques, and methodologies from various scientific areas. The new generation of intelligent traffic, transportation, and communication systems should be able to generalize, adapt, and learn based on new knowledge and new information. Modern intelligent systems are based on computational tools that are capable to compute with words (Fuzzy Logic), learn and adapt (Artificial Neural Networks), and perform systemized random search and optimization (Genetic Algorithms). This collection of computational tools has been known as Soft Computing. The algorithms based on Swarm Intelligence concepts represent special class of algorithms within computational intelligence. These algorithms are characterized by existing of group of agents created by an analogy with herds of land animals, fish schools, flocks of birds, and social insects. There are numerous traffic, transportation, logistic, and communication problems where Computational Intelligence techniques could apply. The models that enable better transportation and communication system utilization, as well as mitigation of traffic congestion, transportation costs reduction, and level of service improvement will be developed within the proposed research project. The project research outputs will be of a great benefit to academic community, transportation companies, and specialized government agencies.