Detection Unit Imperfections and CPM Reliability in Interoperable RSUs
From ISLAB/CAISR
Jump to navigationJump to search| Title | Detection Unit Imperfections and CPM Reliability in Interoperable RSUs |
|---|---|
| Summary | Collaboration with Mittlogik: The project investigates how data and analysis quality affects reliability of collective perception services. |
| Keywords | RSU, CPM, reliability analysis, connectivityProperty "Keywords" has a restricted application area and cannot be used as annotation property by a user. |
| TimeFrame | Spring-Summer 2026 |
| References | |
| Prerequisites | Strong skills in C/C++, Python, and data analysis. Knowledge of real-time systems and a basic understanding of V2X (CPM) and sensor fusion concepts is required |
| Author | Mittlogik |
| Supervisor | Mittlogik, Elena Haller, Oscar Molina |
| Level | Master |
| Status | Open |
Background
Standardization bodies have defined the structure of Vehicle-to-Everything (V2X) messages such as the Collective Perception Message (CPM). However, the actual safety utility of these messages depends entirely on the quality of the data provided by the Detection Unit (DU). In real-world deployments, DUs (e.g., computer vision sensors) suffer from variable latency, measurement noise, and intermittent detection gaps.
This thesis investigates how these sensor imperfections propagate through the Roadside Unit (RSU) interworking protocol and affect the reliability and timeliness of safety warnings sent to vehicles.
Objectives
- Characterize DU Latency and Noise: Benchmark the latency and spatial accuracy of the selected DU under various conditions, such as varying numbers of detected objects and different lighting environments.
- Model Detection Imperfections: Develop a fault-injection framework capable of introducing artificial delays, noise, and dropped detections into the data stream between the DU and the RSU.
- Analyze CPM Reliability: Quantify the impact of detection imperfections on generated CPMs using metrics such as Age of Information (AoI), positional error, and message frequency stability.
- Evaluate System Robustness: Identify the system break-point, defined as the level of sensor latency or noise at which CPMs no longer provide a reliable safety benefit for vulnerable road user (VRU) protection.
Methodology
- Benchmarking: Conduct physical experiments to measure the baseline latency of the DU-to-RSU communication link.
- Fault Injection Framework: Implement a Python/C++ tool positioned between the DU and the RSU interworking module to simulate real-world errors, including noise, jitter, and packet loss.
- Stress Testing: Execute safety-critical scenarios, such as a pedestrian emerging from behind a vehicle, while injecting controlled levels of sensor imperfection.
- Data Analysis: Compare ground-truth pedestrian positions with RSU-reported positions contained in CPMs to calculate error margins and safety-critical delays.
Expected Deliverables
- Robustness Analysis Report: A comprehensive assessment of how sensor imperfections influence CPM quality and reliability.
- DU Performance Profile: A technical benchmark documenting the performance characteristics of the selected detection hardware.
- Recommendations for RSU Logic: Proposed software-level mitigation strategies, such as data smoothing or dead reckoning, to reduce the impact of sensor limitations.
