Schlechtriemen, Julian David: Probabilistic freespace prediction in structured traffic environments for trajectory planning. 2021
Inhalt
- Zusammenfassung
- Abstract
- Contents
- List of Figures
- List of Tables
- List of Abbreviations
- Introduction
- The Different Levels of Automation
- Level-1: Driver Assistance
- Level-2: Partial Automation
- Level-3: Conditional Automation
- Level-4: High Automation
- Level-5: Full Automation
- Fallback from Level-3 Driving
- Research Contribution
- System Design
- Maneuver recognition
- Prediction of Future Vehicle Positions
- Trajectory Planning in Structured Dynamic Environments
- Outline
- Background
- Safety of Automated Driving Functions
- Coordinate Systems
- Machine Learning
- Model Selection
- Evaluation Methods
- Evaluation Measures for Discrete Data
- Scoring Methods for Continuous Data
- Supervised Learning
- Unsupervised Learning
- Vehicle Dynamics
- System Concept and Architecture
- Introduction and Goals
- Architecture Constraints
- System Scope and Context
- Solution Strategy
- Building Block View
- Architecture Level (1) - Automated Driving Logic
- Architecture level (2) - Fallback Behavior Generation
- Runtime View
- Risks and Technical Debts
- Maneuver Recognition
- Problem Definition
- Literature
- Contribution
- Solution Design
- Environment Model
- Feature Selection Techniques
- Classification Methods
- Experiment I
- Experiment 2
- Probabilistic Position Prediction
- Problem Definition
- Literature
- Contribution
- Solution Design
- Features and Data Model
- Methods
- Metrics
- Experiment 1
- Experiment 2
- Trajectory Planning in Structured Dynamic Environments
- Problem Definition
- Related Work
- Contribution
- Solution Design
- Behavior Planning
- Interface Definition
- Sampling using Action Spaces
- Trajectory Generation based on Differential Flatness
- Experimental Results
- Conclusion
- Epilogue
- Publications
- References