An accelerated-time simulation for traffic flow in a smart city

Traffic control is one of the most important problems related with urban development. Current trends for traffic control are based on the use of smart traffic lights and signals as a part of smart cities’ projects. Different cities are currently involved in the design and implementation of smart traffic control. Since the cost of physically installing these systems is very high, in terms of both money and resources, accelerated‐time simulations of traffic flow using smart traffic lights and signals significantly reduce these costs. In this work we present a new model for accelerated‐time simulations for traffic flow within. The philosophy of this model is based on previous works of the authors, where accelerated‐time simulations for car traffic in a motorway or a roundabout and baggage traffic in an airport were developed. The philosophy of this model combines ideas from cellular automata and neural network theories, obtaining a mixed model. This system was developed using a Computer Algebra System (CAS) called Maxima for mathematical computations and a Java based interface for graphical display. Maxima allows the system to support the use of ad hoc distribution functions for the different events dealt with in the simulations. The interface provides a friendly framework for entering input data and visualizing the simulations, providing also some statistical data.