Autonomous vehicle validation
Benefits of model based testing
in autonomous vehicle validation
A complete validation strategy
Create powerful test cases to validate your autonomous vehicles
We provide you directly in the MaTeLo tool different maneuvers libraries to manage unit tests (cut-in, cut-out, zip-in, merging, etc.) that you can use and adapt according to your functional requirements to create complex scenarios.
MaTeLo generates thousands of test combinatorics for each type of manoeuvre by varying the parameters (distances, inter-distances, speeds, events and external actions).
The tests generated by MaTeLo are graphical, reproducible and can be stored in any ALM or database. They can also be exported in different formats and can be executed in 3D simulation tools, such as SCANeR.
MaTeLo’s advanced algorithms will provide you a representative sample of variability and combinatorics with minimal redundancy, to simulate large driving distances and reduce simulation time.
Compliance with the SOTIF standard
The variability of a unit test case is in accordance with ISO 2626-2 and §10 of SOTIF: “Evaluate known use cases”.
MaTeLo can also execute and sequence unit test cases directly in the simulator, with the “on-line” generation method allowing a closed loop interface between MaTeLo and the simulation tool.
This method makes it possible to create unknown and unpredictable use cases as required by §11 of SOTIF.
Instanciation of the method with the SCANeR tool of AV Simulation
This demonstration project is integrated into MaTeLo and allows you to perform complete tests, including cut-in/cut-out, pedestrian crossing consideration, etc. You can directly execute this project and you have a proof of concept ready to use.
This example used in on-line mode in MaTeLo allows you to create a dynamic closed loop with SCANeR that takes care of the simulation.
Watch live the behaviour of the autonomous vehicle, its reactions in traffic and in an environment that is constantly changing and visualize in parallel the corresponding route in the MaTeLo model.
For each possible unit test, MaTeLo asks SCANeR to detect events in real time during the simulation with an initial variability defined by MaTeLo.