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Sensor Simulation

Highly accurate environmental sensor simulation

Autonomous vehicles accurately find their way with the aid of sensors. To ensure this in every possible situation, vehicles, controllers, and sensors are efficiently validated at early development stages: they are tested in virtual test drives with an immense variety of test cases. dSPACE precisely addresses this requirement by offering “Sensor Simulation” a unique and complete solution based on simulating a sensor’s physical phenomena and properties.

  • SensorSim 1.1

    More realistic sensor simulation and higher performance.

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  • AI-in-the-Loop

    Presenting a new test system for validating an autonomous, AI-based vehicle using realistic sensor simulation.

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  • Cinema for Sensors

    The latest dSPACE developments for autonomous driving.

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  • Objective Capture

    Validating functions for autonomous driving by means of realistic sensor simulation.

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  • Sensor Simulation: Key to Autonomous Driving Development

    In this webinar recording dSPACE shows the different dSPACE solutions for sensor simulations: starting from ground truth sensor models to raw data stimulation via GPU-based physical sensor models.

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Realistic Sensor Models

Sensor Simulation contains models that create a virtual 3-D world to represent real objects in the surroundings of the vehicle. It also provides models of camera, radar, and lidar sensors to simulate the perception of this world. For this purpose, the model types simulate two essential aspects:

  • Sensor front end: The front end is the detection component of a sensor. In cameras, these are the lens and the analog-digital image converter. A radar front end model contains the signal modulation and the antenna pattern, for example. Whereas a lidar front end consists of the laser and LED characteristics as well as the composition of the photodetectors (receiving LEDs).
  • Sensor environment: The environment model follows the physical laws of signal propagation affected by material properties, and channel attenuation. It can simulate all details of the environment that can be detected by the relevant sensor. These include fellow vehicles, roads, traffic signs, roadside structures, etc.

The sensor models provide sensor-realistic simulation data that can be used to validate functions for autonomous driving or a subset of them, such as data fusion or object detection. For best performance, the sensor models can be executed on platforms, such as the Sensor Simulation PC, which is equipped with powerful graphics processor units (GPU).

Seamless Simulation

Sensor Simulation supports the reuse of models and test scenarios on different platforms. Therefore, tests created and used on the developer’s PC can be performed on a simulator or in the cloud and vice versa. This enables easy and fast scaling of parallelized tests. The entire validation process from software-in-the-loop (SIL) simulation to hardware-in-the-loop (HIL) simulation is supported. This enables versatile test methods with real and virtual ECUs or sensors.

Flexible Integration

Sensor Simulation provides flexibility via an application programming interface (API) to support customized solutions. The online postprocessing API is an efficient means of implementing sensor specific extensions directly in the product. It can be used for adapting the output format or integrating a sensor model of the sensor supplier, for example. The resulting custom code is executed on the GPU during the overall process. Therefore, you can use the same code in SIL and HIL domains.

Overview of Sensor Models

Camera Module

Realistic simulation of camera and fish-eye camera sensor.

Lidar Module

Realistic simulation of lidar signals.

Radar Module

Realistic simulation of radar signals.

Use Cases

Software-in-the-Loop (SIL) Simulation

Sensor simulation supports entirely software-based testing by means of the SIL method.

Hardware-in-the-Loop (HIL) Simulation

Sensor Simulation offers the option to test real sensors in combination with ADAS/AD control units in a closed loop.

Basic Information Product Information