TNO IVS is contributing to policy making with the Dutch ministry, Dutch type approval body RDW and the European Partners in Connected, Cooperative & Automated Mobility (CCAM). TNO IVS is involved in consumer testing through Euro NCAP. In this way, we contribute to policy, testing and creating technical proof of concepts to accelerate the safe adoption of automated driving. In scenario-based assessment methodology, TNO is one of the leading parties in Europe.

What will be your role?

You will be involved in developing new features for the TNO StreetWise pipeline, coding deterministic algorithms in Python. Together with our partners, we define the roadmap and upcoming sprints for the development of this pipeline. Your role is to turn loose requirements into functionality that can be used directly. Naturally, this is tested thoroughly. Besides, you will develop knew knowledge, also for our governmental partners. To make sure that they have all the required information, now and in the upcoming years, to safely assess new vehicles, including end-2-end AI systems.

Functie-eisen

Experience with programming in Python (> 2 years).
M.Sc. degree in data science, automotive, software engineering or similar.
Capable of organizing your own work independently.
Familiar with Agile way of working and version management (such as Git/CI-CD).
Interest to connect software with the end user application and the methodology for safety assessment.
Proficient in speaking and writing in Dutch and English.

If you have experience in software simulation, software testing, software architecture, databases or cloud platforms (Microsoft Azure), this is an advantage.

Competenties

Your responsibilities will include:

Develop and improve deterministic detection and analysis algorithms in Python.
Work together with the team on test and deployment of new elements of the pipeline.
Align with team members and the product owner to verify your assumptions and approaches.
Enjoy the teamwork and contribute to it.
Contribute to the team meetings with ideas, suggestions and solutions.
Process real-world driving data sets on a cloud platform.
Develop yourself and join other IVS projects to broaden your scope and impact.
You are a starter with expertise in data analytics / data science/ AI approaches.
Good knowledge of statistics.

Bedrijfsinformatie

Our growing mobility demands coincide with unprecedented societal and environmental challenges. The department TNO Integrated Vehicle Safety (IVS) is part of the unit Mobility and Built Environment (MBE) in which we work on big societal challenges in the field of transport, infrastructure, and housing. At IVS we develop technology and assessment methodologies to accelerate the deployment of Connected and Cooperative Automated Mobility (CCAM) systems that contribute to ‘zero calamities’, ‘zero emissions’ and ‘zero loss’. We support industrial partners and policymakers in their innovation processes for smart vehicles and complex CCAM systems that enhance our mobility and logistics.

In order to make our vehicles and mobility system safer, more sustainable and more efficient, IVS combines extensive knowledge on vehicle automation technologies with innovative safety assessment methodologies.

To make sure that automated driving is introduced on public roads in a safe and responsible way, we need to prove that automated driving functions can handle all situations it encounters on the road. To describe the possible situations that can be encountered on the road, TNO has developed the TNO StreetWise data processing pipeline, which automatically detects and classifies scenarios from real-world data from vehicles driving on public road. The TNO StreetWise pipeline uses sensor data from vehicles to detect vehicle activities, which are used to mine scenarios describing the interaction between the vehicles. The detected scenarios are parametrized and stored in a scenario database that can be used for testing automated driving functions. The TNO StreetWise pipeline has been developed with several industry partners. Adoption by industry is growing and already led to many new features. In the past years, driving competency is added to the pipeline and more and more the focus is now on the safety of (end-2-end) AI systems.

Due to the application of StreetWise to the safety assessment of high-risk systems, explainability and reproducibility of the results is of the highest importance. This limits the use of artificial intelligence algorithms and creates a preference for conventional deterministic algorithms.

Uiteraard staat deze vacature open voor iedereen die zich hierin herkent.