Search

One of the major problems of both developed and developing countries is traffic congestion in urban road transportation systems.Some of the adverse consequences of traffic congestion are loss of productive time,delay in transportation,increase in transportation cost,excess fuel consumption,safety of people,increase in air pollution level and disruption of day-to-day activities.Researches have shown that among others,traditional traffic control system is one of the main reasons for traffic congestion at traffic junctions.Most countries through out the world use pre-timed/ fixed cycle time traffic control systems.But these traffic control systems do not give an optimal signal time setting as they do not take into account the time dependent heavy traffic conditions at the junctions.They merely use a predetermined sequence or order for both signal phase change and time setting.Some times this also leads to more congestion at the junctions.As an improvement of fixed time traffic control method, fuzzy logic traffic control model was developed which takes into account the current traffic conditions at the junctions and works based on fuzzy logic principle under imprecise and uncertain conditions.But as a real life situation,in addition to uncertainty and impreciseness there is also indeterminacy in traffic signal control constraints which fuzzy logic can not handle.The aim of this research is to develop a new traffic signal control model that can solve the limitations of fixed time signal control and fuzzy logic signal control using a flexible approach based on interval-valued neutrosophic soft set and its decision making technique,specially developed for this purpose.We have developed an algorithm for controlling both phase change and green time extension / termination as warranted by the traffic conditions prevailing at any time.This algorithm takes into account the existing traffic conditions,its uncertainty and indeterminacy.The decision making technique developed allows both phase change and green time setting to be managed dynamically,depending on the current traffic intensity and queuing of vehicles at different lanes,as opposed to an order or a pre-determined sequence followed in existing traffic control models. [ABSTRACT FROM AUTHOR]