Aptiv Technologies Ag

Aptiv Technologies Limited

Zhiheng Niu

Weimeng Zhu

Arne Grumpe

Mirko Meuter

Stephanie Lessmann

Yu Su

Jan Siegemund

Adrian Becker

Markus Schoeler

Florian Kaestner

Florian Kästner

Alessandro Cennamo

Sven Labusch

Saeid Khalili Dehkordi

Simon Roesler

Moritz Luszek

Dominic Spata

Jittu Kurian

Marco Braun

Kevin Kollek

A computer implemented method for detection of objects in a vicinity of a vehicle comprises the following steps carried out by computer hardware components: acquiring radar data from a radar sensor; determining a plurality of features based on the radar data; providing the plurality of features to a single detection head; and determining a plurality of properties of an object based on an output of the single detection head.

Methods and systems for detection of objects in a vicinity of a vehicle

A method is provided for classifying a tracked object in an environment of a vehicle. The vehicle includes a plurality of radar sensors and a processing device configured to establish a neural network. According to the method, local radar detections are captured from an object in the environment of the vehicle via the radar sensors. Based on the local radar detections, point features and tracker features are determined. The point features are encoded via point encoding layers of the neural network, whereas the tracker features are encoded via track encoding layers of the neural network. A temporal fusion of the encoded point features and the encoded tracker features is performed via temporal fusion layers of the neural network. The tracked object is classified based on the fused encoded point and tracker features via classifying layers of the neural network.

Method for classifying a tracked object

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Wuppertal, Germany

Zhiheng Niu