The acquisition of RoadBotics, an American start-up specializing in the image analysis of road infrastructures, is a further illustration of Michelin’s ambitions around tires, in particular in the field of mobility intelligence. An interview with Lorraine Frega, member of the Group Executive Committee.
What are your ambitions around tires?
Michelin’s connected Services & Solutions around tires are part of the Group’s strategy and proof of its willingness to contribute to a sustainable future. In 2030, Michelin’s activities around and beyond tires will represent 20 to 30% of its revenue.
Today, we have historic knowledge about tire and vehicle usage, driving behavior and expertise in valorizing mobility data. Our clients benefit from this combination of know-how, in particular through customized services and solutions that make their activities safer, more effective and more sustainable. In addition, by reinforcing people safety, connected mobility is also at the heart of human challenges and Group’s commitments. That’s part of the Group’s belief that it is its responsibility to make mobility safer worldwide.
How will the acquisition of RoadBotics support your growth ambitions around tires, and more particularly in the mobility intelligence?
The acquisition of RoadBotics will enable Michelin to consolidate its offer in data intelligence. With a more accurate understanding of driving behaviors thanks to RoadBotics’s imaging technology, the Group will be able to complement its expertise and improve the value proposition to its clients, who manage road infrastructures. By combining the expertise of RoadBotics and MICHELIN DDi in driving data analysis, Michelin plans to accelerate the development of the MICHELIN DDi “Safer Roads” solution in North America, and eventually in Europe. This acquisition is a continuation of the partnership around mobility data, established last year with Arity.
What is the RoadBotics computer vision technology about?
RoadBotics’ computer vision* technology transforms visual data from road infrastructures collected with cameras, mainly with smartphones, into actionable data to enable decision-making by road infrastructure managers.
It allows them, for example, to detect at-risk areas, to identify and prioritize maintenance to be carried out on their networks.
* Computer vision describes an artificial intelligence technique enabling the analysis of images collected by equipment such as cameras. This AI-based technique helps to recognize images, understand them and process the resulting information.