Public procurement notice: Voluntary Ex Ante Transparency Notice
Published: 2019-06-26
Buyer: Statens vegvesen
Country: NO
Contract type: Services
Procedure: Contract award without prior publication
CPV classification: 72000000
Estimated value: 3600000 NOK

Technical requirements: Υπηρεσίες τεχνολογίας των πληροφοριών: παροχή συμβουλών, ανάπτυξη λογισμικού, Διαδίκτυο και υποστήριξη
Voluntary Ex-ante Notice — Development of and Research on the use of Machine-learning for the Identification of Vehicles with Magnet Sensors (1)
The Norwegian Public Roads Administration intends to enter into a contract with Euroskilt AS for the development of and research on the use of AI/machine-learning for detailed categorisation and identification of different vehicles with magnet sensors, without the use of personal data or registration numbers. In addition the system must be able to categorise heavy traffic, light vehicles, motor cycles, mopeds, etc., and, in accordance with NorSIKT, be able to detect bicycles, distinguish between buses and other heavy traffic, as well as vehicles with different types of fuel, such as fossile fuel, electricity and hydrogen. Tests will be carried out to establish whether the system can distinguish each individual vehicle from each other and follow them between different zones in a busy tunnel in a non-homogeneous traffic situation. The intention is to have an overview of all vehicles in real time in a tunnel during an event, which can then be used for evacuation and fire-fighting purposes.
The Norwegian Public Roads Administration intends to enter into a contract with Euroskilt AS for the development of and research on the use of AI/machine-learning for detailed categorisation and identification of different vehicles with magnet sensors, without the use of personal data or registration numbers. In addition the system must be able to categorise heavy traffic, light vehicles, motor cycles, mopeds, etc., and, in accordance with NorSIKT, be able to detect bicycles, distinguish between buses and other heavy traffic, as well as vehicles with different types of fuel, such as fossile fuel, electricity and hydrogen. Tests will be carried out to establish whether the system can distinguish each individual vehicle from each other and follow them between different zones in a busy tunnel in a non-homogeneous traffic situation. The intention is to have an overview of all vehicles in real time in a tunnel during an event, which can then be used for evacuation and fire-fighting purposes. The work is to be completed and a final report submitted by the end of 2019. This procurement is planned to be carried out as a direct procurement as the Contracting Authority believes that there are legal grounds in this procurement to not hold a tender competition, cf. the Public Procurement Regulations §2-5. The procurement is for research and development, where known technology is used for new purposes within tunnel safety. The assignment is not fully financed by the Contracting Authority, and the results from the assignment do not belong to the Contracting Authority in their entirety. The system with machine-learning and the composition of magnet sensors was developed by Disruptive Engineering AS, which is a sub-supplier of Euroskilt AS. Disruptive Engineering AS has a monopoly on the algorithms for machine-learning. The Norwegian Public Roads Administration has examined whether there are other potential suppliers, but has not found another supplier in the market who can deliver a system with AI/machine-learning for recognising magnetic signatures with a high level of detail, and sensors with a sufficiently high density of measuring points to achieve this in the given time period. The provision for signing a contract is thereby considered to be met. The notice is published in accordance with the Public Procurement Regulations §21-5.
The Norwegian Public Roads Administration intends to enter into a contract with Euroskilt AS for the development of and research on the use of AI/machine-learning for detailed categorisation and identification of different vehicles with magnet sensors, without the use of personal data or registration numbers.
This procurement is planned to be carried out as a direct procurement as the Contracting Authority believes that there are legal grounds in this procurement to not hold a tender competition, cf. the Public Procurement Regulations §2-5. The procurement is for research and development, where known technology is used for new purposes within tunnel safety. The assignment is not fully financed by the Contracting Authority, and the results from the assignment do not belong to the Contracting Authority in their entirety. The system with machine-learning and the composition of magnet sensors was developed by Disruptive Engineering AS, which is a sub-supplier of Euroskilt AS. Disruptive Engineering AS has a monopoly on the algorithms for machine-learning. The Norwegian Public Roads Administration has examined whether there are other potential suppliers, but has not found another supplier in the market who can deliver a system with AI/machine-learning for recognising magnetic signatures with a high level of detail, and sensors with a sufficiently high density of measuring points to achieve this in the given time period. The provision for signing a contract is thereby considered to be met. The notice is published in accordance with the Public Procurement Regulations §21-5.
The system with machine-learning and the composition of magnet sensors was developed by Disruptive Engineering AS, which is a sub-supplier of Euroskilt AS. Disruptive Engineering AS has a monopoly on the algorithms for machine-learning.
The Norwegian Public Roads Administration intends to enter into a contract with Euroskilt AS for the development of and research on the use of AI/machine-learning for detailed categorisation and identification of different vehicles with magnet sensors, without the use of personal data or registration numbers. In addition the system must be able to categorise heavy traffic, light vehicles, motor cycles, mopeds, etc., and, in accordance with NorSIKT, be able to detect bicycles, distinguish between buses and other heavy traffic, as well as vehicles with different types of fuel, such as fossile fuel, electricity and hydrogen. Tests will be carried out to establish whether the system can distinguish each individual vehicle from each other and follow them between different zones in a busy tunnel in a non-homogeneous traffic situation. The intention is to have an overview of all vehicles in real time in a tunnel during an event, which can then be used for evacuation and fire-fighting purposes. The work is to be completed and a final report submitted by the end of 2019.


Winner: Euroskilt AS
Award value: 3600000