Description
Advanced Driver Intention Inference: Theory and Design describes one of the most important function for future ADAS, namely, the driver intention inference. The book contains the state-of-art knowledge on the construction of driver intention inference system, providing a better understanding on how the human driver intention mechanism will contribute to a more naturalistic on-board decision system for automated vehicles.- Features examples of using machine learning/deep learning to build industry products- Depicts future trends for driver behavior detection and driver intention inference- Discuss traffic context perception techniques that predict driver intentions such as Lidar and GPS
Table of Contents
PART I: INTRODUCTION AND MOTIVATION1. Introduction and MotivationPART II: LITERATURE REVIEW. State-of-art of driver intention inference 2. Survey to Driver Intention InferencePART III: TRAFFIC CONTEXT PERCEPTION. Integrated lane detection systems3. Survey to Lane Detection Systems Integration and Evaluation4. Integrated Lane Detection Systems DesignPART IV: DRIVER BEHAVIOUR REASONING. Driving actions and secondary tasks recognition5. Driver Behaviour Recognition with Feature Evaluation6. Driver Behaviour Detection with an End-to-End ApproachPART V: DRIVER BRAKING AND LANE CHANGE MANOEUVERS. Intention inference7. Driver Braking Intensity Classification and Quantitative Inference 8. Driver Lane Change Intention InferencePART VI: CONCLUSION AND FINAL REMARKS9. Conclusions, Discussions and Directions for Future Work
