

rFpro
rFpro provides driving simulation software and Digital-Twins for Autonomous Driving, ADAS and Vehicle Dynamics development, testing and validation. It is being used to train, test and validate Supervised Learning systems for ADAS applications.
Sensor realistic simulation
Claytex develops camera, radar and LiDAR sensor models based on physics for use with rFpro. These models are representative of the real sensors and include weather and other noise effects.
Scenario based testing
Our Simulation Manager enables scenario based testing with support for OpenSCENARIO and OpenDRIVE. Define the intended trajectory for the ego vehicle, traffic and pedestrians and measure the system performance.
Measuring your performance
Simulation Manager for rFpro includes metrics that can be calculated to measure your system performance during a test. It provides an extendible plugin mechanism to allow you to add your own metrics to measure performance.
Ground truth
In simulation we can generate pixel perfect, labelled, ground truth data to train and test your perception layer. It can also be used to bypass the perception layer and focus on the planning and actuation part of the control system
Use your vehicle model
rFpro has interfaces to a wide range of vehicle dynamics software including Dymola, IPG CarMaker, SimPack, VI-Grade, Carsim, Simulink and also offers an open API enabling support for others
Driver-in-the-Loop or robot driver
Run tests as a Driver-in-the-Loop simulator or use our automated driver to run the vehicle through the test scenarios
Control system integration
Simulink toolboxes are available to provide easy integration into the simulator or connect to a HiL system to include the physical controller in the tests
Related Articles
- Generating an rFpro point cloud data known as PCD for Autoware usage
A point cloud is a set of data points in space where those points represent a 3D shape or object. Point clouds are used for multiple purposes including the creation and visualization of CAD models [1]. Given our work on Carla-Autoware and rFpro, this blog will focus on the different processes of generating pcds (Point Clouds) which are fundamental in […]
Read More » - Automated Testing Methodologies for Autonomous Vehicles
The safety of an autonomous vehicle is paramount, but testing systems needed to ensure fully safe system performance are in their infancy. The Simulation Cycle is the process of creating, running and analysing results from a scenario. In the cycle the scenarios are designed and created by the Test Manager and run in Simulation. Test automation using the Simulation Cycle can be conducted with Claytex’s Simulation Manager for rFpro.
Read More » - Integrated Development Framework for ROS based Autonomous Vehicles using AUTOWARE (Part II)
Following the first part of this blog series (Integrated Development Framework for ROS based Autonomous Vehicles using Autoware (Part I) – Claytex) where we covered aspects of our development framework, this post will cover our use of CARLA and AUTOWARE.AI. The overall goal of this work was to develop an interface between rFpro and AUTOWARE.AI so that we could substitute […]
Read More »









