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TERAKI setzt bei ML-basierten Radarerkennungssoftware auf den AURIX™ TC4x und ermöglicht so präzisere und sicherere ADAS- und AD-Anwendungen
TERAKI setzt bei ML-basierten Radarerkennungssoftware auf den AURIX™ TC4x und ermöglicht so präzisere und sicherere ADAS- und AD-Anwendungen
Market News
München und Berlin – 9. September 2022 – Autonomes Fahren (Autonomous Driving; AD) und fortschrittliche Fahrerassistenzsysteme (Advanced Driver Assistant System; ADAS) sind auf die präzise Erfassung der Fahrzeugumgebung angewiesen, um sicher zu navigieren. Hersteller auf der ganzen Welt haben sich darum für fortschrittliche Sensoren und Algorithmen entschieden, um die Erfassung zu verbessern und noch sicherer zu machen. TERAKI, ein Marktführer in der Verarbeitung der bei Egde-Sensoren anfallenden Daten, hat heute die neueste Radarerkennungssoftware vorgestellt, die statische und sich bewegende Objekte mit höherer Genauigkeit und geringerer Rechenleistung identifiziert. Die Real-Traffic-Lösung läuft auf ASIL-D-konformen AURIX™ TC4x-Mikrocontrollern der Infineon Technologies AG.
„Die Leistungsfähigkeit von Radarsystemen in Fahrzeugen hat sich in den letzten Produktgenerationen drastisch erhöht“, sagt Marco Cassol, Director of Product Marketing bei Infineon Automotive Microcontrollers. „Edge-KI-Verarbeitung ist eine der vielen Innovationen, die dazu beigetragen haben, dass wir die Radarleistung steigern konnten. Nun werden die einzigartigen Radar-Algorithmen von TERAKI in die neue Parallel Processing Unit (PPU) von Infineon implementiert, um die Radarleistung der nächsten Generation von Infineons AURIX TC4x-Bauteilen zu demonstrieren.“
„Wir haben unseren Algorithmus verfeinert, um mit weniger mehr zu erreichen“, sagt Daniel Richart, CEO von TERAKI. „Mit einem Minimum an Daten erkennen und klassifizieren unsere Lösungen statische und sich bewegende Objekte anhand von Radarsignalen und versorgen AD- und ADAS-Anwendungen mit den wesentlichen Informationen für die Beurteilung von Situationen und für die Entscheidungsfindung. Letztlich zielen wir darauf ab, die Sicherheit at the Edge zu gewährleisten, indem wir die Inferenzzeit und die benötigte Rechenleistung von ressourcenbeschränkten Geräten reduzieren.“
Da sich Radar zum Industriestandard für kostengünstige Signalverarbeitung entwickelt, wird es immer wichtiger, die Grenzen dieser Sensortechnologie zu überwinden. So können beispielsweise Interferenzen die Detektionsleistung des Radars stark beeinträchtigen. Dadurch kann es in schwierigen Situationen mit mehreren Zielen zu ungültigen Ergebnissen kommen, was ebenfalls hohe Verarbeitungsanforderungen mit sich bringt. Darüber hinaus erfordert die Präzision, die für zuverlässige Radarklassifizierungen erforderlich ist, mehr Datenpunkte pro Bild und eine Winkelauflösung von unter einem Grad, wenn statische und sich bewegende Objekte korrekt erkannt und klassifiziert werden sollen.
Der Ansatz des maschinellen Lernens (ML) von TERAKI soll diese Herausforderung bewältigen, indem er mit Rohdaten arbeitet und das Rauschen reduziert . Gleichzeitig fungiert er als kognitive Funktion, um Radarinformationen zu zerlegen, Ziele in einer verrauschten Umgebung zu identifizieren, zusammen mit Clustern und anderen Interferenzen, und die Rechenkapazität at the Edge zu verringern. Die ML-Detektion von TERAKI liefert mehr Punkte pro Objekt. Das führt zuweniger Fehlalarmen und damit zu mehr Sicherheit , insbesondere im Vergleich zu anderen Radarverarbeitungsmethoden wie CFAR.
Der auf dem AURIX TC4x von Infineon portierte ML-basierte Algorithmus von TERAKI reduziert die Radarsignale nach der ersten Fast Fourier Transformation (FFT) und erreicht so eine bis zu 25-mal niedrigere Fehlerrate bei fehlenden Objekten bei gleichem RAM/fps. Im Vergleich zu CFAR ist die Genauigkeit der Klassifizierung um bis zu 20 Prozent höher, und die Anzahl der gültigen Erkennungen steigt um 15 Prozent. Mit dieser Version verbessert TERAKI die Chipsatz-Architektur von Edge-Geräten und gewährleistet eine Echtzeit-Verarbeitungsleistung auf dem AURIX TC4x. Durch die Verwendung von 4- oder 5-Bit-Bitraten anstelle von 8- oder 32-Bit verringert das die Rechenanforderungen ohne Beeinträchtigung der F1-Scores. Auf diese Weise wird bis zu zweimalweniger Speicherplatz benötigt.
Über TERAKI
TERAKI ist ein in Berlin ansässiges KI-Softwareunternehmen, das sich auf sicherere autonome Mobilität mit geringeren Kosten spezialisiert hat. Die Software von TERAKI ermöglicht es L2-, L3- und L4-Fahrzeugen, Objekte in Echtzeit genauer zu erkennen und zu klassifizieren. Die TERAKI-Software selektiert und verarbeitet große Mengen an Sensordaten (Video, Radar und Lidar) zehn Mal effizienter und liefert zuverlässigere Entscheidungen für sicherere autonome Operationen. Zu den Anwendungsfällen gehören autonom fahrende Fahrzeuge wie Autos, Lieferroboter, Gabelstapler, Züge und mehr. TERAKI unterhält Partnerschaften mit führenden Chipsatz-Anbietern wie Infineon und Synopsys. Die Technologie von TERAKI soll ab 2024 in der ersten Serienproduktion von Autos eingesetzt werden. Das Unternehmen beschäftigt derzeit 50 Mitarbeiter und unterhält Büros in Berlin und Tokio. Weitere Informationen über TERAKI sind erhältlich unter teraki.com/news/ml-based-detector-infineon.
TERAKI Pressekontakt
Geert-Jan van Nunen, CCO
+49 30 2332 7456, gj.nunen@teraki.com
Pressefotos
TERAKI Applikation
Die einzigartigen Radar-Algorithmen von TERAKI sind nun in die neue Parallel Processing Unit von Infineon implementiert, um die Radarleistung der nächsten Generation von Infineons AURIX TC4x-Bauteilen zu demonstrieren
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TERAKI AURIX TC4x
Die einzigartigen Radar-Algorithmen von TERAKI sind nun in die neue Parallel Processing Unit von Infineon implementiert, um die Radarleistung der nächsten Generation von Infineons AURIX TC4x-Bauteilen zu demonstrieren
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Information Number : INFATV202209-116