Efficient mining of relevant scenarios from data collection to processing
22 May 2025
Room 1
Developments in scenarios, simulation, validation and in-the-loop testing (continued)
High-quality data collection and selection are the cornerstones of ADAS and autonomous driving development. This presentation explores key prerequisites for successful test drives on public roads, focusing on ensuring data completeness, consistency and relevance. Topics include reference sensor calibration, field-of-view simulation and real-time diagnostics. Additionally, the presenter will discuss strategies for selecting relevant data during collection and after ingesting with pre-selection algorithms to optimize storage and processing. Attendees will gain practical insights to overcome technical challenges and streamline the data pipeline for cost-sensitive system performance.
- Techniques for ensuring data completeness and consistency during test drives
- Best practices for reference sensor calibration and integration
- Strategies for real-time diagnostics and time synchronization
- Approaches to selecting relevant data during collection and after ingesting for pre-selection
- Solutions for fleet-wide data handling and post-drive analysis