In response to the need to improve road traffic operation, researchers implement advanced technologies and integration of systems and data, and develop state-of-the-art applications to assist traffic engineers. This SpringerBrief introduces three novel Web applications which can be an exceptional resource and a good visualization tool for traffic operators, managers, and analysts to monitor the congestion, and analyze incidents and signal performance measures. The applications offer more detailed analysis providing users with insights from different levels and perspectives. The benefit of providing these automated and interactive visualization tools is more efficient estimation of the local transport networks performance, thus facilitating the decision making process in case of emergency events.

The rapid growth of urban population and numbers of private cars in this modern era, results in increasingly urgent transportation problem in cities throughout the world. Road traffic congestion is an omnipresent problem, which leads to delays, time loss, human stress, energy consumption, environmental pollution e.c.t. In order to decrease traffic congestion, there is a need for simulating and optimizing traffic control and improving traffic management. There are different ways for traffic congestion monitoring and analysis such as using video monitoring and surveillance systems, or static and dynamic sensors which allow traffic management in real time. There are also other methods using non real time analysis where traf?c congestion can be extracted from historical patterns of traf?c congestion. The historical patterns can be gained from the stored travel time and speed data. The goal of enhancing driver convenience is achieved by providing applications based on road traffic condition that mainly identifies congestion status. This paper presents a web application which uses live traffic congestion data from Google Maps traffic layer for real time congestion calculation. A technique utilized for estimating the level of congestion is image processing. The main objective is to provide an automated and yet interactive visualization tool for congestion analysis in real time. The aim is reducing the traffic congestion on roads which will lead to decrease in the number of accidents. It can provide important data which can help road traffic management. Thus, it is mainly dedicated to traffic managers, operators and analysts. Nevertheless it can be implemented also by road users. Unlike most sensor based applications, it makes quantified congestion data available even in regions with limited traffic data information.