Skip to main content



Reporting period: 2017-05-01 to 2017-08-31

Growing mobility needs raises demands for improved traffic management methods. Road passenger transport is expected to grow in the EU by 17% in the next 20 years. In order to control and supervise this growth in mobility in a sustainable manner, it will be essential to streamline urban transport management by developing innovative systems aimed at improving mobility and infrastructure planning. It has been estimated that over $1 trillion can be saved in the next 20 years through a more efficient infrastructure productivity plan, 25% related to road networks alone.
However, proper analysis and planning is required to create optimized infrastructure at the lowest possible cost. To analyse and predict road infrastructure needs for both public and private players, it is essential to extract large amounts of accurate data about volume, direction, intensity and distribution of road traffic. The lack of reliable and relevant data constitutes the main problem behind the current generation of traffic management systems. With traditional traffic data from currently used roadside sensors, it is possible to extract information about the numbers and speed of the detected vehicles, but it is not possible to identify the origin or the destination of said vehicles. It is therefore also impossible to perform accurate simulations through statistical analysis.
With SMApp, we will integrate the data from ALPR cameras to automatically reconstruct traffic flows between origin and destination nodes of any given road network. Infrastructure planning simulations based on accurate traffic flow distribution have consistently been proven to provide the best possible feedback to road authorities for optimized road infrastructure planning. Additionally, the use of intelligent modular traffic management systems, such as SMApp, has been estimated to lead to a 20% reduction in congestion time and up to 40% increase in capacity for motorways and a potential 30% reduction of emissions.
The complete evaluation of all technical and commercial requirements for the successful development of SMApp allowed us to validate the final feasibility of the project, in addition to its impressive commercial potential:
On the technical side, we were able to validate the technical feasibility of the remaining development tasks for the SMApp application, divided into 3 different categories: Business Logic implementation, Data Storage/Communication and User Interface/Business Intelligence. We designed a complete technical work plan that will allow us to reach a TRL9 at the end of the Phase II project, and identified the main technical risks for the implementation, as well as the corresponding mitigation strategies.
On the commercial front, we performed a complete market study, identifying the different types of users, segments, drivers, competitors and risks/barriers, in addition to a detailed examination of the current situation for each target country for SMApp in the EU and LATAM. We were also able to appropriately position SMApp as a product in the current market context, with adapted pricing, partnership, distribution, dissemination and expansion strategies. These strategies will cover multi-faceted pre-commercialization and dissemination measures, involving strong partnerships with private and public entities as well as an ambitious market awareness plan with the organization of targeted events.
In addition to this, we were able to validate the complete Freedom-to-Operate of SMApp on a global scale, perform a regulatory analysis of the functional background and a detailed data management strategy. As a result of this, we were able to design a specific action plan that will help us ensure full compliance with GDPR and maximize protection for our own IP.
SMApp perfectly complements the current technology that is unable to identify vehicles and itineraries and focuses on statistical figures of volume, velocity, capacity and density. The data from SMAPP will therefore be optimal to perform data quality cross-checks with the current data from inductive loop detectors. Our data processing algorithms will be able to reconstruct traffic flows using multiple data types and data sources. This enables self-calibration, verification and validation of the measurements, resulting in data validation without human intervention. Apart from the immediate benefit of bias removal and noise suppression in the automatic decision making, it also provides important hardware calibration parameters.
With SMApp, we will also be able to automate data collection, processing, analysis and simulations to provide unequivocal strategic feedback for road authorities and infrastructure planners in order to build efficient road networks. SMAPP will provide support in the decision-making process in 2 different areas: 1) the routine planning of day-to-day road conditions by authorities and 2) the planning of future road infrastructure and the evaluation of the best value-for-money for different possible alternatives.
According to the EC’s Joint Research Centre, traffic congestion is the main challenge for transport policy. Congestions cost every year nearly €110 billion to the EU’s economy (0.7 % of the EU's GDP). Congestion mitigation is therefore the main priority of most road infrastructure, traffic management and road charging measures. Road network efficiency is a main priority for EU transport policy, as expressed through the EC’s “Roadmap to a Single European Transport Area”. SMApp responds to this need for resource efficient road infrastructure by enabling objective and more data-driven decision making for infrastructure planning.