Comparative Study on Data Abstraction Methodologies for Interoperable V2X Roadside Units (RSU)
| Title | Comparative Study on Data Abstraction Methodologies for Interoperable V2X Roadside Units (RSU) |
|---|---|
| Summary | It is a collaboration with MittLogik on development of Interoperable RSU Prototype focused on Vulnerable Road User (VRU) safety. |
| Keywords | pedestrian safety, computer vision, V2X communicationProperty "Keywords" has a restricted application area and cannot be used as annotation property by a user. |
| TimeFrame | february 26 - june 26 |
| References | |
| Prerequisites | Strong skills in embedded C/C++, data structures, computer networks, and a foundational understanding of V2X standards. |
| Author | |
| Supervisor | Elena Haller, MittLogik |
| Level | Master |
| Status | Open |
Comparative Study on Data Abstraction Methodologies for Interoperable V2X Roadside Units (RSU)
Project Context
Interoperable RSU Prototype focused on Vulnerable Road User (VRU) safety.
Summary
This thesis is a pre-study to inform the architecture of a proprietary interworking protocol. Theme: Embedded Systems, V2X Data Efficiency, Comparative Protocol Analysis.
Project Metadata
- Theme
- Embedded Systems, V2X Data Efficiency, Comparative Protocol Analysis
- Location
- Lund
- Timeline
- 2026-02-01 to 2026-10-31
Background
To achieve true RSU interoperability and scalability, the core RSU application must be decoupled from vendor-specific detection unit (DU) sensor data and diverse communication methods (e.g., C‑V2X/DSRC). The design of a lean, efficient Minimal Dataset Schema is critical for low-latency VAM (Vulnerable Road User Awareness Message) generation. This research will compare various approaches for defining this minimal schema, but will not disclose the final proprietary implementation.
Objectives
- Analyze DU Data Complexity: Analyze and characterize the data payload complexity and velocity from representative Computer Vision (CV) detection units (DU), identifying challenges in converting raw data (e.g., bounding boxes, tracking IDs) into V2X data elements.
- Compare Methodologies: Conduct a comparative study of different encoding methodologies for V2X safety applications, evaluating each based on latency, CPU overhead on embedded platforms, and message size efficiency.
- Define Abstraction Rules: Propose a set of general best-practice rules and conversion algorithms for mapping high-frequency CV tracking data onto the necessary minimal dataset fields required for standardized VAM generation (e.g., position, dynamics, object type).
Methodology
Comparative Review
Detailed review of three candidate serialization/encoding techniques (Objective 2) suitable for the RSU's embedded platform, including profiling their processing speed in a laboratory environment (simulation/modelling).
Algorithm Design
Design generalized algorithms and flowcharts for data aggregation and abstraction (Objective 3).
Expected Deliverables
- Comparative Analysis Report: A detailed technical report comparing the performance and suitability of the investigated data serialization methodologies for the RSU application.
- Generalized Abstraction Rules: A documented set of algorithms and principles for mapping complex detection data to V2X minimal datasets.
- Thesis Report: A thesis submitted for publication focusing on the methodologies, analysis, and generic findings. The final proprietary RSU protocol schema will not be documented or published.
