As the world wakes up to the stringent safety tests that will be needed for self-driving cars, the team at Claytex has been working on identifying where they’re most needed, in a method we christened the Intersection Matrix Method. Consider a road network that a self-driving car developer wants...
The Simulation Manager tool, developed by Claytex, offers a wide range of methods to help engineers set up and test anything from sensor hardware in the loop to full autonomous driving. However, testing is useless unless the relevant data can be extracted from the simulation. This blog covers the...
What is a Map Sensor? For a vehicle driving along a road, it can be difficult to define it’s movement. A Map Sensor defines an objects position relative to the road
Virtual scenario based testing Committed to providing a new generation of autonomous vehicle simulation tools, the new Autonomous package of Modelica vehicle models is the latest product from Claytex designed to help you bring cutting edge Automation ideas into reality. Aimed at helping to create lean, fast-simulating, scalable, vehicle...
Many companies are currently developing radar sensors for the autonomous driving application and each system made available will have unique specifications and thus capabilities. To gain a sufficient amount of radar measurements in the real-world, to confirm that a given sensor meets certain requirements, will be both time consuming...
There is a lot of effort being put into the development of virtual test environments for ADAS and AV. One aspect that seems to be ignored by many is the need for high fidelity road models and vehicle dynamics models. Whilst in the early stages of the development of...
This week we will show you how to insert a state-of-the-art Lidar device within the virtual environment of rFpro. This will allow a user to easily stream and visualize the sensor output on any PC or storage device. The Velodyne HDL-32E is the latest Lidar device to be added...
Modern vehicles; modern challenges Vehicles are getting ever more complex, with subsystems becoming further interdependent with the wider system dynamics than ever before. Beyond this, modern vehicles now interact with their surroundings, reacting and responding to changes in the immediate environment. This is never truer than in autonomous vehicles....
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