Introducing a Development Method for Active Perception Sensor Simulations Using Continuous Verification and...

Area of Science:

• Automotive Engineering
• Computer Science
• Robotics

Background:

• Real-world testing for automated driving functions faces limitations in cost, safety, and scalability.
• Accurate perception of the vehicle's environment relies on active sensors like lidar and radar.
• Ensuring the credibility of sensor simulations is a key challenge in developing automated driving systems.

Purpose of the Study:

• To present a novel method for efficient and credible realization and validation of active perception sensor simulations.
• To integrate a continuous verification and validation approach into the development process for safety-critical automated driving functions.
• To demonstrate practical approaches for validating measurement data and deriving acceptance criteria.

Main Methods:

• Iterative implementation of sensor effect requirements into the simulation.
• Continuous verification and validation at each iteration of the simulation development.
• Development of methods for validating measurement data and defining acceptance criteria.

Main Results:

• A novel method for efficient and credible active perception sensor simulation is proposed.
• The method integrates continuous verification and validation throughout the development process.
• Practical approaches for data validation and acceptance criteria derivation are presented.

Conclusions:

• The proposed method enhances the credibility of sensor simulations for automated driving functions.
• Continuous verification and validation are crucial for ensuring the safety augmentation of these systems.
• The approach, demonstrated with lidar simulation, offers a robust framework for sensor simulation development.