in this paper, the advantage of reinforcement learning to develop a new traffic shaper is invoked in order to obtain a reasonable utilization of bandwidth while preventing traffic overload in other parts of the network. this leads to a reduction in the total number of packet droppings in the whole network. the method is implemented in a novel proposed intelligent simulation environment. keeping...

the paper discusses the current state of research concerning railway network timetabling and traffic management. timetable effectiveness is governed by frequency, regularity, accurate running, recovery and layover times, as well as minimal headway, buffer times and waiting times. analytic (queuing) models and stochastic microsimulation are predominantly used for estimation of waiting times and ...

Traffic Simulation plays an important role in both today’s traffic research and in many traffic applications such as traffic flow prediction, instant detection and traffic control. The term simulation is taken broadly to mean a model which tries to represent or reflect actual traffic performance and takes in equilibrium models. To some extent, models imitate stages in the development of the fie...