Intro
Preface
Contents
Fundamentals on Vehicle and Tyre Modelling
1 Global Vehicle Modeling
1.1 Vehicle Dynamics
1.2 Dynamic Torsor Calculation
1.3 Exterior Forces Torsor Calculation
1.4 The Sprung Mass Dynamics
1.5 Model Simplification and Validation
2 Tire Modeling
2.1 Tire Physical Fundamentals
2.2 Tire Behavioural Models
2.3 Tire Models Linearization
2.4 Dynamic Saturation
2.5 Simulation of the Linearized Models
2.6 Tire Models Comparison
2.7 Validation and Relevance of Linearized Tire Models
References

1.4 Example: Longitudinal Vehicle Velocity
1.5 Summary
2 General Observer and Estimation Methods
2.1 Physics Driven Observer and Estimation Schemes
2.2 Kinematic Versus Dynamic Models for Estimation
2.3 Observability for Reliable State Observations and Estimates
2.4 Conclusion
3 Kalman Filter Based State Estimators for Vehicle Dynamics
3.1 Reference Data Description
3.2 Decoupled Vehicle State Estimation: Longitudinal Vehicle States
3.3 Lateral Vehicle State Estimation
4 Kalman Filter Based Estimators for Vehicle Dynamics with Unknown Tire Models

4.1 Coupled State/Input and State/Parameter Estimation
4.2 Lateral State/Force Estimation
4.3 Lateral State/Tire Parameter Estimation
4.4 Post-processing for Tire Model Extraction
5 Conclusion
References
Automated Driving Vehicles
1 Introduction
1.1 The Role of the Driver
1.2 Advanced Driver Assistance Systems and Automated Driving Systems
1.3 Concluding Remarks
2 Sensor Fusion
2.1 Sensor Fusion Configuration
2.2 Model-Based Approach
2.3 Data-Driven Approach
2.4 Safeguarding Sensor Fusion
3 Motion Planning for Autonomous Driving