Internship | Development of a Context-Aware AI Driver Assistant

TNO; Netherlands; On-site; EUR 6,000 - 7,000; Full time

Job summary

TNO seeks an intern to develop a context-aware AI driver assistant within the MARQ Digital Lab. You will connect the driving simulator (SCANeR) to a locally hosted LLM on GPU infrastructure and prototype real-time context delivery for safe, non-distracting AI support.

The project includes architectural design, latency evaluation, and integration with ROS 2, Docker, and Kubernetes where applicable. Open to HBO or Master’s students.

Qualifications

• C++ for integration with driving simulator software.
• Python for AI integration, rapid prototyping, and API development.
• Knowledge of AI/ML and LLMs; familiarity with prompt engineering.
• Experience with REST APIs or other communication mechanisms.
• Basic knowledge of Linux, Docker, and Git.
• ROS 2, Kubernetes or GPU computing experience is advantageous but not required.

Responsibilities

• Develop a context-aware AI driver assistant integrated with a driving simulator (SCANeR).
• Design and implement software architecture to connect the simulator to a locally hosted LLM on MARQ Digital Lab GPU infrastructure.
• Evaluate real-time context update frequency and latency for natural interaction.
• Produce a working proof-of-concept of AI-assisted driver coaching within simulation environments.
• Collaborate with researchers on AI evaluation and context incorporation.

Skills

C++

Python

REST APIs

Linux

Docker

Git

ROS 2

Kubernetes

GPU computing

Education

HBO

Master's

Tools

SCANeR

Docker

Git

ROS 2

Kubernetes

Job description

About this position

Within the MARQ Digital Lab, you will develop a context-aware AI assistant for a driving simulator. The assistant will leverage a Large Language Model (LLM) that receives real-time contextual information from the simulation, including the road environment, traffic situation, vehicle status, and driver behavior (e.g., eye tracking and driver inputs such as steering, throttle, and braking). Based on this information, the AI assistant should be able to answer driver questions and proactively provide warnings, explanations, and driving advice. You will design and implement a software architecture that connects the driving simulator (SCANeR) to a locally hosted LLM running on the GPU infrastructure of the MARQ Digital Lab. The project will investigate how simulation context can be efficiently supplied to the LLM, determine the update frequency required for real-time interaction, and evaluate which open-source LLM is best suited for this application. The final result will be a working proof-of-concept of an AI-powered driver assistant that combines natural language interaction with context-aware support during driving simulations. The solution will serve as a foundation for future research into AI-assisted driver coaching, Human-AI Interaction, and the validation of ADAS and CCAM systems within the MARQ Digital Lab.

Possible Research Questions

• How can simulation context be efficiently provided to an LLM in real time?
• Which open-source LLM is most suitable for a context-aware driver assistant?
• What system architecture and context update frequency are required for natural and timely interaction?
• How can an AI assistant effectively support drivers without becoming distracting?

Expected Deliverables

• A working proof-of-concept of a context-aware AI driver assistant.
• Integration with at least one simulation platform (SCANeR, and optionally CARLA or NVIDIA Isaac Sim).
• A locally hosted LLM running on the GPU infrastructure of the MARQ Digital Lab.
• An evaluation of system performance, latency, and applicability for research and validation of ADAS and CCAM systems.

What we expect from you

• C++ for integration with driving simulator software.
• Python for AI integration, rapid prototyping, and API development.
• Knowledge of Artificial Intelligence (AI) and Machine Learning.
• Familiarity with Large Language Models (LLMs) and prompt engineering.
• Experience with REST APIs or other communication mechanisms.
• Basic knowledge of Linux, Docker, and Git.
• Interest in automated driving (ADAS/CCAM), simulation, and Human-AI Interaction.
• Experience with ROS 2, Kubernetes, or GPU computing is considered an advantage but is not required.

This internship is suitable for both HBO and Master's students. For a Master's project, additional emphasis can be placed on system architecture, AI evaluation, explainable AI, and research into the effectiveness of context-aware driver assistance in advanced simulation environments.

What you’ll get in return

In addition, we offer you:

• A professional and innovative internship environment in which you actively contribute to societal and technological challenges, working alongside leading experts in your field.
• Personal and dedicated supervision, with focus on your learning objectives, development and study assignment.
• Room to develop: you gain relevant work experience, develop both your subject-specific and professional skills, and build a valuable network.
• Use of a laptop and the facilities you need to perform your work effectively.
• A monthly internship allowance of € 615 for a full-time internship, for MSc, BSc and vocational education (MBO) students.
• Up to eight hours of leave per internship month for a full-time internship, allowing you to balance your internship with your studies and personal life.
• A contribution towards travel expenses if you are not entitled to a student travel card.
• A free membership to Jong TNO: the network for young colleagues, where you can meet other TNO colleagues and participate in sports activities, professional and personal development activities, and social events such as the annual ski trip.

Interns at TNO must have a registered residential address in the Netherlands at the start of the internship. Carrying out internship activities from abroad is not possible. If you start an internship with us, we will also ask you to provide a Certificate of Conduct (VOG).

If you are an international student? Please note that you must have a BSN (Dutch citizen service number) before the start of your internship. Applying for a BSN can take several weeks, so make sure to start this process well in advance.

TNO as an employer

Our people are at the heart of TNO. Their curiosity, expertise and entrepreneurial mindset make it possible to deliver high-impact research and innovations that contribute to society’s sustainable wellbeing and prosperity. That is why we invest in an inspiring and inclusive working environment where colleagues can excel, have autonomy and continue to grow. Your talent and ambition have every opportunity to flourish at TNO. You work with experts (both within and beyond TNO), have access to advanced technology and the freedom to explore, experiment and innovate. Our strength lies in independence, reliability and collaboration. We find each other in wonder and ingenuity. We are driven to push boundaries. By working with businesses and government, and by connecting different perspectives, we strengthen our innovative capability and create responsible, meaningful results. At TNO, we believe this is our time to help society, government and business move forward faster. Together with driven colleagues, you turn knowledge into concrete innovations or ventures that truly make a difference by combining the power of science and entrepreneurship. And in doing so, you make your mark on our time.