Validation of AI - A step towards Automotive AI management System

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Type vacancy
Education field
Automotive Engineering, Toegepaste Wiskunde, Elektrotechniek, Engineering (algemeen), ICT, Mechatronica
Autonoom Rijden, Data/ICT, Electronica en besturingssystemen

The company:

RDW is the Netherlands Vehicle Authority in the mobility chain. RDW has developed extensive expertise through its years of experience in executing its statutory and assigned tasks. Tasks in the area of the licensing of vehicles and vehicle parts, supervision and enforcement, registration, information provision and issuing documents. Tasks that RDW carries out in close cooperation with various partners in the mobility chain. This provides RDW with a clear position in this chain, with its mission being: RDW stands for safety, sustainability and legal certainty in mobility.


You work for the Vehicle Regulation & Licensing (VRT) division. You are part of the Applied Innovation team that focuses on knowledge and product development for the development of new legislation, new licensing frameworks and working methods for vehicle innovation. We take a learning-by-doing approach, developing new products and knowledge and then validating them by also applying them, including by conducting practical trials on public roads.

Assignment/ work/ activities:

One of the major drawbacks of AI is the black box nature of it. This is more significant in the automotive industry where the OEMs can not or would not share their AI models or systems with the type approval authorities. This is backed by the rationale that since it is a piece of software and is developed across many suppliers it is near to impossible to assess or audit the model or the system. The main objective of this assignment is to propose a framework which can be used to validate an AI system keeping in mind the black box nature of the AI. There are many existing frameworks which validate AI keeping the black box nature in mind, but they are not robust enough to validate a complex and multi-modal system like an autonomous vehicle. Additionally there are no existing frameworks which are suited for the automotive industry. The main research tasks are as follows:

  • Identify the integral components that needs to be audited for a successful assessment of AI in an autonomous vehicle.
  • Develop/Propose an Artificial Intelligence Management System(AIMS) which can be applicable to level 3 and beyond systems.
  • Propose an integration of AIMS with the Safety Management System found in R157 by UNECE or NATM audit guidelines proposed by VMAD SG3.

We offer:

  • An interesting and challenging internship position for 6 months, starting from September 2022 (or as soon as possible)
  • An allowance of €586,80 per month (based on a 36-hour work week)
  • The possibility to (partly) work from home
  • The supervisor will assure their full availability as well as a friendly environment

You have/ competences/ skills:

You are a 3rd or 4th year student with a healthy dose of energy, perseverance and a solution-oriented mind.

You have the expertise in Artificial Intelligence in Automotive Engineering.

Then you are at the right place at RDW!


Do you want to know more about this assignment? Please contact Shubham Koyal (Advisor), or +31 6 50746485 or Espedito Rusciano (senior advisor), or +31 6 25764089.

Do you want to apply? Please hit the button down below.

Apply now with ACE

Please mention 'ACE internship / graduation 2023' when applying for a project! The Automotive Center of Expertise is a partnership between the Universities of Applied Sciences Automotive (HAN, Fontys) and the automotive industry. Partner companies of ACE are selected companies that have a close bond with education. These ACE Partners are preferred companies and are known for high-level assignments, excellent guidance/coaching and innovative topics.

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Why with ACE

  • Network with other ACE interns / graduates and join our automotive network.
  • Gain acces to knowledge at other automotive companies and graduates trough the ACE network.
  • Eligible for the ACE student award with your graduation assignment.