The general goal of STREET-FLOW is to develop a high-performance single-gantry free-flow system to identify and classify vehicles on urban roads, with plans to be able to integrate with Smart City platforms. This system must provide for each vehicle that transports the information corresponding to the registration, identification tag (if incorporated), vehicle class, direction and speed, also having all the sensing equipment in a single arch or mechanical structure fixation, unlike current multi-lane systems.
In order to provide such information also in situations of traffic congestion and slow traffic (more complicated to obtain), the system will have the novel incorporation of a sensor based on Doppler effect.
The management of urban mobility in cities requires systems to obtain highly reliable information on road traffic, especially in terms of vehicle identification and categorization. The trend in these systems implementation is to obtain the minimal impact on the environment and traffic, and offer an easy integration into ICT platforms, from which data can be distributed as well as coordinate their functioning with other systems. The current free-flow systems fulfill part of these requirements because their installation does not require intervention in the firm and because vehicles must not stop or reduce their speed. However, they need to distribute their sensor equipment in several frames (two or three), separated enough to process in a timely and synchronized way the obtained data. This makes them poorly suited for installation in urban environments, where roads may be short or have difficult paths, and where special care must be taken in the use of spaces to minimize environmental and visual impacts.
With STREET-FLOW all free-flow sensors (antennas, cameras, lasers) are focused on a single gantry which allows important savings in the CAPEX and OPEX associated to the physical infrastructure involved thanks to algorithmic and programming conceived and implemented by Tecsidel. This allows to collect, process and add, in a short time, the data supplied by the mentioned sensorization.
