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Mantis is a cloud-based Intelligent Traffic Solution built around a unique algorithm which forecasts traffic evolution saving costs and reducing emissions

Project description

Be proactive rather than reactive with a pioneering intelligent traffic solution

Most of us have experienced the frustration of coming to a standstill in traffic, thanking our phone navigation systems for suggesting alternative routes and then getting stuck in another traffic jam with all the people who followed similar advice. Not only does this lead to increased emissions from cars idling or creeping along without going into third gear, but it also contributes to lost productivity. The Swedish SME Ximantis has come up with a pioneering algorithm to predict congestion up to half an hour before it occurs. The EU-funded Mantis project is helping the team bring its cloud-based intelligent traffic solution to the people who need it.

Objective

Anyone who has ever been stuck in a traffic jam knows the frustration of sitting still in a car on the road and waiting. For road users in metropolitan areas of Germany, France, UK and USA, according to a European study conducted in 2014, this happens on average 36 hours every year. Traffic congestion costs society billions of dollars every year in the form of fuel costs, lost productivity and impact on the environment and public health. In Europe alone, the annual price tag for congestions is €200 billion, which is approximately 2% of total GDP. The Cebr estimates that, every year, vehicle idling releases 15,434 kilotons of CO2 equivalent into the atmosphere across the UK, France, Germany and the US alone. Navigation systems (Google Maps, Waze, TomTom and others) reroute users after congestion is formed, observed and reported. By then, the information cannot meaningfully impact the gridlock. Their rerouting efforts, on the other hand, cause additional congestion on the suggested alternative routes. Mantis is a cloud-based Intelligent Traffic Solution built around a unique algorithm which forecasts traffic evolution using scalable parallelization. Analysing historical and real-time data, the Mantis application predicts future traffic congestion 30 minutes before they even happen. The algorithm relies on stochastic processes which, among other things, are responsible for modelling chaotic systems such as the stock market and the weather. Mantis is poised to disrupt the automotive navigation system market estimated to be valued at €22.6 billion in 2025.

Call for proposal

H2020-EIC-SMEInst-2018-2020

See other projects for this call

Sub call

H2020-SMEInst-2018-2020-1

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Coordinator

XIMANTIS AB
Net EU contribution
€ 50 000,00
Address
Alexandros sopasakis, kullatorpen 6
439 33 Onsala
Sweden

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SME

The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Yes
Region
Södra Sverige Västsverige Hallands län
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Links
Other funding
€ 21 429,00