Master’s Thesis - Time and Spatial Synchronization for ETSI CAM/CPM Cooperative Perception Systems
10.03.2026, Abschlussarbeiten, Bachelor- und Masterarbeiten
The Chair of Robotics, Artificial Intelligence, and Real-Time Systems offers a Master’s thesis on synchronization challenges in V2X cooperative perception systems based on ETSI CAM and CPM communication standards.
Motivation & Relevance
Vehicle-to-everything (V2X) communication enables cooperative perception by exchanging environmental information between vehicles and roadside infrastructure. ETSI standard messages such as Cooperative Awareness Messages (CAM) and Collective Perception Messages (CPM) provide the foundation for this information exchange. However, accurate fusion of perception data requires precise temporal and spatial synchronization. Clock drift, GNSS inaccuracies, and asynchronous sensor pipelines can lead to misaligned object states. These inconsistencies reduce the reliability of cooperative perception systems and may lead to incorrect object association or trajectory estimation. Developing robust synchronization strategies is therefore essential for scalable and reliable V2X deployments.
Project Description
In this thesis, you will analyze synchronization challenges in ETSI CAM/CPM-based cooperative perception systems and develop compensation mechanisms. Your system will:
- Analyze temporal offsets between roadside and vehicle perception systems
- Investigate clock drift, GNSS inaccuracies, and synchronization problems coming from the nature of individual agent V2X systems
- Develop algorithms for temporal alignment and interpolation
- Implement spatial alignment methods between different coordinate frames
- Evaluate the impact of synchronization errors on perception fusion
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Validate proposed solutions using V2X datasets or simulation environments
The goal is to improve cooperative perception reliability through robust synchronization methods.
Your Tasks
- Analyze time and spatial synchronization challenges in V2X systems
- Develop algorithms for temporal and spatial alignment
- Implement compensation strategies for latency and clock drift
- Evaluate synchronization impact on object association and tracking
- Validate methods using simulated or recorded V2X data
Profile
- Master’s student in Computer Science, Robotics, Electrical Engineering or related field
- Strong programming skills in Python or C++
- Interest in V2X systems and cooperative perception
- Basic understanding of coordinate transformations and sensor systems
- Experience with simulation tools (e.g., CARLA) is a plus
What you will gain
- Insight into ETSI V2X communication standards
- Expertise in synchronization challenges of distributed perception systems
- Hands-on experience with cooperative perception architectures
- Practical knowledge of real-world communication constraints
How to apply
Please send your CV and a transcript of your grades with your application.
Kontakt: erik-leo.hass@tum.de