QLabs Virtual QCar 2

Part No. QLabs Virtual QCar 2

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QLabs Virtual QCar 2 is a digital twin of the 1/10 scale self-driving car, enabling safe development and validation of autonomous algorithms with MATLAB or Python.

The Quanser Virtual QCar 2 is a fully instrumented, dynamically accurate digital twin of the physical QCar 2 1/10 scale self-driving car. It behaves the same way as the physical hardware and can be measured and controlled using MATLAB Simulink® or Python development environments. It can enrich your lectures and activities in traditional labs, or bring credible, authentic model-based lab experiences into your distance and online self-driving courses.
Same as the physical Qcar, the virtual system is a self-driving teaching and research platform complete with industrially relevant sensors such as LiDAR, 360° CSI cameras, an RGB-D camera, and inertial and odometric sensors.

The Quanser Virtual QCar 2 is a fully instrumented, dynamically accurate digital twin of the physical QCar 2 1/10 scale self-driving car. It behaves the same way as the physical hardware and can be measured and controlled using MATLAB Simulink® or Python development environments. It can enrich your lectures and activities in traditional labs, or bring credible, authentic model-based lab experiences into your distance and online self-driving courses.

Same as the physical Qcar, the virtual system is a self-driving teaching and research platform complete with industrially relevant sensors such as LiDAR, 360° CSI cameras, an RGB-D camera, and inertial and odometric sensors.

Specifications
CSI Cameras 4×160° FOV @820×410 resolution @30Hz
2D LiDAR 360° 384 points per scan @15Hz
RealSense RGB-D Camera RGB and Depth @640×480 resolution @30Hz
IMU 3-axis gyroscope and accelerometer
Minimum Specifications • Intel Core Ultra 5, Intel Core i5, Ryzen 5
• 8GB RAM
• Intel Iris or Arc integrated GPU
Recommended Specifications • Intel Core Ultra 7, Intel Core i7, Ryzen 7
• 16GB RAM
• Intel Arc integrated GPU, or discrete GPU (e.g. NVIDIA GeForce RTX 3050)
Recommended Research Specifications • Intel Core Ultra 7, Intel Core i7, Ryzen 7
• 32GB RAM
• Discrete GPU (e.g. NVIDIA GeForce RTX 3050)

• Academically appropriate
High-fidelity, credible lab experiences equivalent to using the physical lab equipment
• Comprehensive Resources
Innovative curriculum and research resources
• Open Access
Full access to the system through MATLAB Simulink® or PythonTM
• Scalable
12-month multi-seat subscription

• Sensor interfacing and kinematic modeling
• Occupancy grid mapping
• Sensor fusion
• Vehicle lateral and longitudinal control
• Image acquisition and camera interfacing
• Line detection
• Lane detection and keeping
• Object detection and classification

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