Fundamentals of Intelligent Driving Training Course

Introduction

• Defining intelligent driving and the rationale behind its adoption.
• A comparative analysis of intelligent driving versus traditional driving methods.
• An overview of intelligent driving capabilities and system architecture.
• Guidance on navigating the intelligent driving interface and workspace.

Understanding AI and Multi-Sensor Information Fusion

• The lifecycle of an intelligent driving session.
• The role of AI and multi-sensor data fusion in enhancing driving intelligence.
• Procedures for creating and importing 3D files into the intelligent driving environment.

Driving Skills and Techniques

• Practical application of driving skills and refined techniques.
• Optimizing and adjusting driving settings for performance.
• Methods for measuring, tagging, commenting, and annotating data.

Driving Scenarios and Situations

• Simulation of diverse driving scenarios and situational responses.
• Identifying potential hazards and executing appropriate risk mitigation strategies.
• Compliance with and application of road rules and regulations.
• Management of complex and dynamic driving environments.

Driving Performance and Evaluation

• Analyzing and assessing driving performance, behavior patterns, and feedback loops.
• Generating and presenting animations of driving sessions.
• Creating and reviewing static images and video recordings of sessions.
• Conducting clash detection tests and verifying the integrity of driving session data.

Driving Integration and Application

• Integrating acquired knowledge and skills with real-world driving challenges.
• Facilitating collaboration and connection with other drivers and instructors.
• Developing and acquiring material estimates for driving sessions.
• Animating driving timelines and validating the accuracy of driving schedules.

Troubleshooting

Summary and Next Steps