The most advanced ITS systems have considerable historic databases on traffic measurements, network performances in terms of vehicles’ mobility (flows, density, speed), anomalies and events, parking areas occupation etc. Most of the ITS systems have not been designed for the processing and presentation of a large quantity of data; this doesn’t allow to take easily and prompt decisions based on objective and significant data, such as incidents, accidents or any breakdown.     

The most innovative ones provide dashboards of synthesis, available also on big size touch-screen which reproduce, in advanced visible forms (i.e. thermographies), the key performance indicators, from which recurrent congestions, their evolution, the need for infrastructural or demand interventions (i.e. road closure or new roads, off street parkings) can be derived.

M-TRAFFIC also includes advanced techniques: through data mining and big data analytics techniques combined with predictive models, it offers improved support to the mobility managers duties.


The most advanced traffic management and control systems use ITS to improve infrastructures and real time monitoring of traffic. They have to react to within-day dynamic, keeping also in mind day-to-day data. Time to intervene is therefore faster, and the more information and sources can be taken into account, the more traffic control strategies and information services to the users can be pro-active:

  • traffic management and control strategies (including adaptive) in most cases make use of data from conventional or wireless sensors’ networks; this is used to monitor traffic status and to feed the predictive models used for management and control.  In the future they will use in return also real time floating car data to predict queues, congestions and to plan fast track paths; they can also improve the vehicle speed control strategies while approaching traffic lights.  
  • in the events management (i.e. sport and music events, exhibitions…) intermodal strategies will be supported (i.e. park&ride, fast track paths) by shuttles or special lines depending on the real charge or on the traffic demand towards predefined destinations. These “situational” strategies require the coordination of several players in the urban mobility management. 

M-TRAFFIC offers more integrated methods that combine smart logical architectures to connect different databases with the power of information processed in real time, thanks to traffic predictive models for traffic demand and flow distribution on the network. The package of M-TRAFFIC applications also include data collected from community networks activities (i.e. daily click-streams on the web or smartphones, activities from check-in services of social networks), which offer unprecedented opportunities to business analytics in traffic domain.  


End-user applications and services are maybe the most striking evidence of Movalia’s innovation: in order to access mobility information, the users can progressively avoid to describe the context; they will be guided through choices more and more adequate to their requirements.

In addition, one of the characterizing aspects of future mobility services will be the increasing capacity of using the user not only as the information addressee but also as a “source”. Advanced ITS services make already large use of vehicles’ speed information (floating-car data) collected by black-boxes or M2M interfaces of on-board devices; they also collect travel times through smartphones blue-tooth interfaces. Through these contents, the traffic flow monitoring and control can be significantly improved.