Controlling urban traffic flow is very essential in smart city design; so, advanced analytical tools are needed to lower congestion and increase mobility. This work explores the use of dynamical system analysis along with queuing theory to maximize traffic flow in smart cities. We expand a mathematical version combining dynamical system analysis to assess the responsiveness and stability of traffic systems beneath distinctive conditions with queuing concept to control the stochastic nature of site visitors glide. Several simulations illustrate how nicely our approach predicts visitor’s patterns and optimize signal timings, therefore lowering wait times and raising universal visitors’ throughput. The method is tested the usage of real-global visitors statistics, consequently proving its possibility for large city implementation. Our findings show the requirement of an incorporated analytical framework that handles the difficulties of urban site visitors control through combining the blessings of each dynamical systems and queuing theory, finally generating smarter, extra responsive cities of the future.