Bio-inspired computational optimization of speed in an unplanned traffic and comparative analysis using population knowledge base factor

Abstract

Bio- inspired Computational Optimization of Speed in Unplanned Traffic and the comparative analysis is a very promising research problem. Searching for an efficient optimization method or technique to formulate optimal solution of a given problem in hand is very challenging and thereby to increase the traffic flow in an unplanned zone is a widely concerning issue. However, there has been a limited research effort on the optimization of the lane usage with speed optimization. This paper presents a novel technique to solve the problem optimally using the knowledge base analysis of speeds of vehicles, using partial modification of Bio Inspired Algorithm (Ant Colony Optimization) which, in turn will act as a guide and baseline for designing lanes optimally to provide better optimized traffic with less number of transitions between lanes. © 2012 Springer-Verlag GmbH.