MarshallAI selected to the next phase of the AI4Cities project

Sep 28, 2021

MarshallAI found 4% CO2 traffic emissions savings potential in the AI4Cities project

MarshallAI continues to the 2nd phase of the EU-funded AI4Cities project, in collaboration with Dynniq Finland Oy. Together we are creating Intelligent Interconnected Intersections (Ix3) to make traffic in cities more efficient by reducing emissions, congestion and wasted time with increased traffic safety. We are developing the Ix3 to take traffic management systems to a totally new autonomous, optimized and advanced level.

AI4Cities is a three-year EU-funded project bringing together leading European cities looking for artificial intelligence solutions to accelerate carbon neutrality. The project consists of two lots - mobility and energy. The organising cities participating in the mobility challenge are Paris, Amsterdam, Helsinki, Tallinn and Stavanger, all looking for solutions that ultimately contribute to reduced CO2 emissions.

The programme received around hundred applications interested in the overall 4,6 million euros funding in March. In June we announced that we are among the 21 selected suppliers in the first phase for smart mobility. Based on the work carried out during this phase, AI4Cities has chosen MarshallAI and Dynniq to be among the 10 mobility consortiums continuing to the 2nd phase, ending Jan 20th 2022. After the development of the prototypes, three participants will during the spring 2022 be selected for the mobility third phase, where a series of larger-scale pilots will be undertaken.

A major source of CO2 emission in cities is traffic. The Intelligent Interconnected Intersections system addresses the CO2 emission reduction target by making traffic management more efficient. Reducing congestion also leads to increased quality of life. Further the solution brings cost-efficiency from lower amounts of different sensors and from increased amount of data at hand for planning purposes, using deep learning-based artificial intelligence and visual sensing. When the traffic light management system understands the actual situation in the entire area, traffic can be managed in a much more optimal way leading to reduced CO2 emissions.

The Ix3 solution is based on MarshallAI’s machine vision platform for replication of human sensing, integrated to Dynniq’s traffic-light control system. The solution analyses the traffic in intersections based on traffic cameras and uses this information to dynamically adjust the traffic lights according to the current situation. The inputs provided are much richer than the one coming from traditional sensors, for example induction loops or pedestrian push buttons, including among other metrics the amount and type of current traffic users from and to different directions.

With the Ix3 solution, we enable two types of improvements, without compromising traffic safety:

  • traffic optimisation, removing dead seconds without any negative effects for any traffic user
  • traffic prioritisation, promoting certain traffic users

Live sensing during the first phase identified a potential to reduce CO2 emissions by more than 37 thousand tonnes in the average European city. This equates to the average emissions of more than 8 000 cars or roughly 4% of the current typical traffic emissions in such a city. The Ix3 solution combats traffic in multiple ways, understands the number of vehicles and their types, and allows cities to prioritise specific traffic users.

Read more about AI4Cities or contact us to learn more about our unique traffic management solutions.

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