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Related Concept Videos

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Controller configurations are crucial in a car's cruise control system because they manage speed over time to maintain a consistent pace regardless of road conditions, thereby meeting design goals. In traditional control systems, fixed-configuration design involves predetermined controller placement. System performance modifications are known as compensation.
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In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
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Electrical engineering plays a pivotal role in our daily lives, with control systems at the heart of many applications, from home appliances to sophisticated space shuttles. Control systems manage and regulate the behavior of devices and processes, ensuring they function safely, correctly, and efficiently.
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Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
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The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
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Configurable Sensor Model Architecture for the Development of Automated Driving Systems.

Simon Schmidt1, Birgit Schlager2,3, Stefan Muckenhuber2,4

  • 1Volkswagen AG, 38436 Wolfsburg, Germany.

Sensors (Basel, Switzerland)
|July 24, 2021
PubMed
Summary

This study introduces a configurable sensor model architecture for developing automated driving systems. This flexible approach enhances sensor model reusability and adaptability in virtual vehicle environments.

Keywords:
automated drivingconfigurable sensor modelfunctional decompositionmodel reusabilitysensor effectssensor model architecturevirtual testing

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Area of Science:

  • Automotive Engineering
  • Computer Vision
  • Systems Engineering

Background:

  • Automated driving systems (ADS) require accurate environmental perception.
  • Virtual environments are crucial for developing and testing ADS.
  • Existing sensor models may lack flexibility and reusability.

Purpose of the Study:

  • To introduce a configurable sensor model architecture for ADS development.
  • To enhance the flexibility and reusability of sensor models.
  • To demonstrate a practical application of the proposed architecture.

Main Methods:

  • Utilizing model-based systems engineering (MBSE) principles.
  • Employing functional decomposition for modularity.
  • Combining individual sensor effects into a cohesive sensor behavior model.

Main Results:

  • A configurable sensor model architecture was successfully developed.
  • The architecture supports flexible and continuous use in automotive development.
  • Demonstrated application using geometric and object-dependent field of view (FoV) sensor effects.

Conclusions:

  • The configurable sensor model architecture improves reusability and adaptability.
  • This approach facilitates tailored sensor modeling for specific development needs.
  • The demonstrated application validates the architecture's practical utility for ADS.