Ford Global Technolgoies, LLC

Evangelos Bitsanis

Frederic Stefan

Michael Marbaix

Alain Marie Roger Chevalier

Turgay Isik Aslandere

Alain Chevalier

A method for performing automatic valet parking, which includes selecting a road scenario applicable to a roadway; notifying a driver to release manual control elements of a motor vehicle and to leave the motor vehicle; checking whether the control elements have been released and the driver has left the motor vehicle and, in this case, entering an EXPLORE mode in which the motor vehicle is slowly driven autonomously and searches for a free car space or a parking space using the vehicle's own environmental sensors, before the motor vehicle is placed in a parking position; and then to change from the EXPLORE mode to a PARKING mode in which the motor vehicle is parked in the car space or in the parking space from the parking position by means of the longitudinal and lateral controllers and using the environmental data previously obtained from the environmental sensors in the EXPLORE mode.

Method for performing automatic valet parking

The invention relates to a system for performing a method for performing computer-aided simulations. The system loads an input dataset which is based on user interactions of a user indicating a manipulation of a representation of a component, provides a tracking dataset indicating changes in the representation through the manipulations by evaluating the input dataset, provides an output dataset which is based on evaluation of the tracking dataset by means of machine learning, where the output dataset assigns a model to the representation, and outputs the output dataset.

Advanced model mapping and simulations

A computer includes a processor and a memory, the memory including instructions executable by the processor to identify a diagnostic test to perform for a vehicle component, identify one of a plurality of XiL platforms on which to perform the diagnostic test, and perform the diagnostic test on the identified XiL platforms.

X-in-the-loop tests for self-driving motor vehicles

The disclosure relates to a method that models a motor vehicle sensor in a virtual test environment by way of definition. Using a sensor support, a raycast distribution shape, a group of raycast properties, a raycast reflection factor, and a raycast echo, a sensor in reality may be tested in a virtual environment to calibrate the sensor in reality. The sensor support is a virtual sensor support for a virtual sensor model, which forms a three-dimensional or two-dimensional avatar of the sensor in reality, in the virtual test environment. The sensor support has a sensor starting point that is used as an origin for a raycast distribution shape. The method extracts a special application of the sensor in reality in an application case, which is particularly useful for testing scenarios.

Method for modeling a motor vehicle sensor in a virtual test environment

A computer includes a processor and a memory, the memory storing instructions executable by the processor to collect control data indicating behavior of a vehicle controlled by a control program, collect virtual control data indicating behaviour of a virtual vehicle controlled by a virtual control program, and determine a difference between the control data and the virtual control data.

Test for self-driving motor vehicle

A method and an apparatus for testing software for autonomous vehicles by means of a loop simulation involves hardware in the form of one or more real autonomous vehicles able to carry out autonomous test drives in the real world. In response to a work order given by a user, a check is automatically carried out in order to determine which vehicles, among a plurality of real autonomous vehicles which are able to carry out autonomous test drives on globally distributed test tracks in the real world, are currently available for one or more tests defined in the work order. The performance of the software tests and the test drives is then automatically planned and coordinated.

Method and apparatus for testing software for autonomous vehicles

Test cases for autonomous vehicles are generated automatically by using data which have been collected from vehicles participating in public road traffic. A test planning system for autonomous vehicle includes defined application cases for autonomous vehicles. The vehicles are configured to identify test cases with prediction analyzes of a reference catalog of driving situations and the defined application cases, and compare, via a comparative analyzes, the test cases and the defined application cases to compile an expanded set of test cases, wherein the expanded set of test cases are compared to the defined application cases to output a complete set of test cases. The system also includes a central database configured to query the complete set of test cases.

Method and device for generating test cases for autonomous vehicles

A method of operating a motor vehicle includes detecting at least one motor vehicle driver response, producing a perception model based on the detected motor vehicle driver response, and analyzing the perception model to at avoid least one motor vehicle driver response by adjusting a parameter of the motor vehicle. Analysis of the perception model can also be carried out to predict a motor vehicle driver response, in particular during the generation of new control software for the vehicle.

Methods of operating a motor vehicle

A system and method for operating a vehicle having different operating modes affecting emissions include activating, by a vehicle controller, at least one of the different operating modes affecting emissions selected in response to an estimated population density of a designated area associated with a current location or an anticipated future location of the vehicle.

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Aachen, Germany

Evangelos Bitsanis