Master's Thesis: Virtual Traffic Reconstruction and Scenario Generation for ADAS Validation

Technology, Data & Digital · Software & Web Development · Software Engineering · Data Science · Machine Learning

In short

Master's thesis focusing on virtual traffic reconstruction and scenario generation for ADAS validation. Students will work with real-world data and simulation technologies, with potential research directions in environment reconstruction or scenario extraction from sensor data. This temporary, on-site position in Gothenburg, Sweden, starts January 19, 2027.

Responsibilities

Investigate how real-world traffic data and simulation technologies can be used to support the validation of ADAS and autonomous driving functions.
Focus on either reconstructing virtual traffic environments using multi-sensor reference data (LiDAR, radar, camera, IMU) or extracting and interpreting traffic scenarios from real-world data into a formal scenario description language.
Explore challenges such as sensor synchronization, point-cloud density, occlusions, sensor coverage, and reconstruction fidelity.
Identify, represent, and convert recorded traffic situations into structured, simulation-ready scenarios.
Potentially explore how reconstructed environments and generated scenarios can support synthetic data augmentation and more comprehensive testing workflows.

Requirements

Master's students with an interest in autonomous driving, intelligent vehicles, and simulation-based validation.
Relevant academic backgrounds include Machine Learning and Deep Learning, Computer Vision, Robotics and Sensor Fusion, Signal Processing and Sensor Modelling.
Experience with Python is beneficial.
Experience with 3D data processing is beneficial.
Experience with simulation environments is beneficial.
Experience with autonomous driving systems is beneficial.

Desired Qualifications

Specific focus can be adapted to the students’ interests and technical backgrounds.
Potential areas of work include multi-sensor data processing and fusion, 3D scene and environment reconstruction, virtual traffic environments and sensor simulation, parameterized traffic scenario generation, evaluation of reconstruction quality and scenario realism, synthetic data generation and augmentation, and simulation-based ADAS validation.

Benefits

Opportunity to shape sustainable transport and infrastructure solutions.
Work with next-gen technologies and collaborative teams.
Complement real-world testing with virtual traffic environments and simulation-based testing.
Enable repeatable experiments, controlled variation of traffic scenarios, and generation of additional data for system validation.
Thesis level: Master’s thesis.
Starting date: January 19, 2027.
Application deadline: November 21, 2026.

Skills

Python3D data processingsimulation environmentsautonomous driving systemsMachine LearningDeep LearningComputer VisionRoboticsSensor FusionSignal ProcessingSensor Modelling

#ADAS#autonomous driving#validation#virtual traffic reconstruction#scenario generation#simulation

About Volvo Group

The Volvo Group is one of the world’s leading manufacturers of trucks, buses, construction equipment and marine and industrial engines. The Group also provides complete solutions for financing and service. The Volvo Group, with its headquarters in Gothenburg, employs about 100,000 people, has production facilities in 18 countries and sells its products in more than 190 markets.\n\n

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