Congestion on urban transportation networks around the world is frequently encountered and its economic and environmental footprint cannot be ignored. One of the solutions used to alleviate this problem is deployment of Intelligent Transportation Systems (ITS). The effectiveness of ITS solutions to manage traffic demand more efficiently relies heavily on accurate travel time prediction, which is a difficult task to achieve using currently available simulation methods. This study proposes an urban network simulation model named CTM-URBAN, a modified version of the Cell Transmission Method (CTM) which was originally developed to simulate highway traffic. CTM-URBAN is a simple and versatile simulation framework designed to simulate more realistically traffic flows in an urban network with various traffic control devices. CTM-URBAN allows building, calibrating, and maintaining a large simulation network with a minimum of effort. A case study is presented to demonstrate that CTM-URBAN is able to predict travel time through signal-controlled intersections more accurately than the original CTM based on comparison with results from a microscopic simulator
