Aptiv Technologies Ag

Aptiv Technologies Limited

Peet Cremer

Mirko Meuter

Stephanie Lessmann

Yu Su

Weimeng Zhu

Jan Siegemund

Christian Nunn

Ido Freeman

Dennis Mueller

Adrian Becker

Lutz Roese-Koerner

Daniel Schugk

Christof Petig

Sven Labusch

Saeid Khalili Dehkordi

Igor Kossaczký

Sönke Behrends

Michael Arnold

Patrik Gebhardt

Ori Maoz

Pascal Colling

Dennis Müller

A computer implemented method for detecting objects includes providing signal representation data comprising range information, velocity information and angular information; for each of a plurality of spatial scales, determining respective scaled data for the respective spatial scale based on the signal representation data, to obtain a plurality of scaled data; providing the plurality of scaled data to a plurality of detectors; and each detector carrying out object detection based on at least one of the plurality of scaled data.

Method and system for object detection

Disclosed are aspects of a method, carried out by a vehicle data recording device, that includes downloading, from a host data collecting system, a recording target and determining a plurality of possible routes for the vehicle. The method also includes, for each route, generating a route encoding in numerical values an information on predicted values of the route for metrics, a metric being a function assigning a value representing an amount of progress in achieving an elementary recording target to a piece of data. The method additionally includes providing the route encodings and additional environmental information independent of the routes to a reinforcement learning agent that selects one of the routes to optimize a reward. The method further includes recording data from in-vehicle sources while the vehicle drives along the selected route and uploading at least part of the recording data to the host data collecting system.

Method of selecting a route for recording vehicle

Provided is a data transmission system, a vehicle comprising the data transmission system, a data transmission method and a computer program. Specifically, the system comprises a centralized controller, a publisher entity and a subscriber entity; wherein the publisher entity and the subscriber entity are compiled with a predefined data format; the publisher entity registers at the centralized controller with topic information; the centralized controller, upon registration of the publisher entity, stores the topic information with information for registering at the publisher entity; the subscriber entity subscribes at the centralized controller to the topic information; the centralized controller, upon subscription of the subscriber entity, provides to the subscriber entity information for registering at the publisher entity; and the subscriber entity creates the communication channel between the publisher entity and the subscriber entity based on the information for registering at the publisher entity.

Data transmission system, vehicle comprising the data transmission system, data transmission method and computer program

A device for image classification comprising a convolutional neural network configured to generate a plurality of probability values, each probability value being linked to a respective one of a plurality of predetermined classes and indicating the probability that the image or a pixel of the image is associated with the respective class, and the convolutional neural network comprises a plurality of convolutional blocks and each of the convolutional blocks comprises: a first convolutional layer configured to perform a pointwise convolution using a first kernel, a second convolutional layer configured to perform a depthwise convolution using a second kernel, wherein the second kernel has one of a single row and a single column, a third convolutional layer configured to perform a depthwise convolution using a third kernel, wherein the third kernel has a single column if the second kernel has a single row, and the third kernel has a single row if the second kernel has a single column, and a fourth convolutional layer configured to perform a convolution using a fourth kernel.

Device and a method for image classification using a convolutional neural network

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Düsseldorf, Germany

Peet Cremer