One of the major problems of both developed and developing countries is trac congestion in urban road transportation systems.Some of the adverse consequences of trac congestion are loss of productive time ,delay in trans- portation,increase in transportation cost,excess fuel consumption,safety of people,increase in air pollution level and dis- ruption of day-to-day activities.Researches have shown that among others,traditional trac control system is one of the main reasons for trac congestion at trac junctions.Most countries through out the world use pre-timed/ xed cycle time trac control systems.But these trac control systems do not give an optimal signal time setting as they do not take into account the time dependent heavy trac 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 xed time trac control method , fuzzy logic trac control model was developed which takes into account the current trac 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 trac signal control constraints which fuzzy logic can not handle.The aim of this research is to develop a new trac signal control model that can solve the limitations of xed time signal control and fuzzy logic signal control using a exible 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 trac conditions prevailing at any time.This algorithm takes into account the existing trac con- ditions,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 trac intensity and queuing of vehicles at dierent lanes ,as opposed to an order or a pre-determined sequence followed in existing trac control models.