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Neueste Veröffentlichungen und Patente zu autonomen Fahrzeugen

Autonome Fahrzeuge

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Dies ist unsere neueste Auswahl an weltweiten Veröffentlichungen und Patenten in englischer Sprache zum Thema Autonome Fahrzeuge, die in zahlreichen wissenschaftlichen Online-Zeitschriften zu den Themen autonomes Fahrzeug, Selbstfahren, LIDAR, Straßenkartierung, Flottenmanagement, Navigationsalgorithmus und Wegplanung veröffentlicht wurden.

Processor-implemented method and system of operation of high-resilient and robust navigation for autonomous systems in challenging environments

Patent published on the 2026-05-28 in WO under Ref WO2026107577 by MICRO ENG TECH INC [CA] (Ai Mengchi [ca], Elhabiby Mohamed Mamdouh [ca], El-sheimy Naser Mahmoud [ca])

Abstract: A processor-implemented method and system of operation of high-resilient and robust navigation for autonomous systems in challenging environments is provided. The method includes determining, by a high-definition map module, if a pre-built high-definition (HD) map is used for navigation based on the distinguished surrounding environments. The method further includes analyzing, by an analyzer module, a real-time environmental data from the LiDAR, Radar, and visual sensors to align with pre-existi[...]


Our summary: The method provides a robust navigation system for autonomous vehicles in challenging environments. It utilizes high-definition maps and real-time data from various sensors for accurate positioning. The system includes modules for map alignment, semantic consistency checks, and non-line-of-sight mapping.

Autonomous Navigation, High-Definition Mapping, Sensor Fusion, Real-Time Data Analysis

Patent

In-vehicle intelligent safety, surveillance and environmental monitoring platform

Patent published on the 2026-05-28 in WO under Ref WO2026109132 by JAAFAR AHMED MEDHAT ABDELDAYEM ABDELMOATY [EG] (Jaafar Ahmed Medhat Abdeldayem Abdelmoaty [eg])

Abstract: An integrated intelligent safety and surveillance system for vehicles combining multiple cameras (internal fisheye, front, rear), radar collision sensor, high-precision GPS unit, environmental sensors (temperature, humidity, air quality), and ambient LED lighting within a single embedded unit with internal battery and optional solar power. Features protocol-agnostic communication architecture (GSM/3G/4G/5G, Wi-Fi, Bluetooth, satellite, CAN bus) and supports multiple platforms (Android, Arduino, [...]


Our summary: This platform integrates multiple sensors and cameras for comprehensive vehicle monitoring and safety. It features protocol-agnostic communication and supports various platforms for enhanced functionality. The system targets commercial applications and provides real-time analytics for driving behavior and risk assessment.

Intelligent safety, Environmental monitoring, Collision warning, Vehicle surveillance

Patent

Annotation of dynamic obstacles for machine learned perception networks in autonomous and semi-autonomous machines and applications

Patent published on the 2026-05-28 in US under Ref US20260147121 by NVIDIA CORP [US] (Degirmenci Alperen [us], Howe Jonathan [us], Wehr David Ambrose [us], Ravishankar Deepak [us], Nimmagadda Sravya [us], Skinner James Michael [us], Panhuber Christian [de], Choi Jiwoong [us], Fischer Philipp [de], VÖgtle Lukas [de], Karmanov Ilia [ch], Al)

Abstract: In various examples, data collection vehicles or machines may be equipped with one or more LiDAR sensors (and/or other sensors), and the LiDAR sensor(s) may be used to collect frames of LiDAR data representing various real-world conditions. The LiDAR data may be processed using one or more deep neural networks (DNNs) such as a transformer neural network to generate auto-labels representing detected dynamic obstacles of any designated class. Tracking may be applied to generate object tracks (trac[...]


Our summary: The content discusses the use of LiDAR sensors for collecting data on dynamic obstacles in autonomous machines. It describes processing this data with deep neural networks to generate auto-labels for detected obstacles. The system also includes tracking and quality assessment to enhance the efficiency of human validation in labeling.

LiDAR, deep neural networks, auto-labeling, dynamic obstacles

Patent

Establishing drivers’ trust through event predictability

Patent published on the 2026-05-28 in US under Ref US20260145696 by AUTOBRAINS TECH LTD [IL] (Raichelgauz Igal [il], Cohen Ido [il])

Abstract: [0000] A method for establishing drivers trust through event predictability, the method includes obtaining, at a machine learning process, path information regarding a driving path of a driving by an autonomous vehicle; identifying, by the machine learning process based on the path information, a road scenario that is accommodated, at least in part, in a path segment of the driving path; determining an artificial intelligence model that is below a maturity threshold with respect to providing a d[...]


Our summary: The method focuses on enhancing driver trust through predictable events. It utilizes machine learning to analyze driving paths and road scenarios. The system generates visible indications for drivers when AI decision-making is below a certain maturity level.

machine learning, autonomous vehicles, event predictability, artificial intelligence

Patent

A photoelectric conversion device, a receiving sensor and a lidar

Patent published on the 2026-05-27 in EP under Ref EP4750272 by SUTENG INNOVATION TECH CO LTD [CN] (Chao Enfei [cn], Yao Guofeng [cn], Xia Chunqiu [cn])

Abstract: [0001] A photoelectric conversion device, a fabrication method, and an image sensor are disclosed. The device includes a substrate with at least two avalanche diode units. Each unit has a device region surrounded by a back-side deep trench isolation structure. At least one front-side trench isolation structure is disposed between any two adjacent units. A doped region, formed by outward diffusion from the front-side trench isolation structure, has a gradually decreasing doping concentration grad[...]


Our summary: The device features avalanche diode units with trench isolation structures. It includes a doped region that suppresses dark current. This design improves electrical performance and reliability.

photoelectric conversion, avalanche diode, dark current suppression, lidar

Patent

Detection of loss-of-control vulnerable road users in automotive environments

Patent published on the 2026-05-27 in EP under Ref EP4749587 by WAYMO LLC [US] (Kanehara Lenna [us], Sheu Kevin [us], Kunz Clayton Gregory [us])

Abstract: [0001] The disclosed systems and techniques are directed to identifying and responding to presence of vulnerable road users (VRUs) in driving environments that are at risk of loss of control of their driving trajectories. The techniques include collecting, using a sensing system of an autonomous vehicle, sensing data for an environment of the autonomous vehicle and processing the sensing data by one or more machine learning models to identify a plurality of reference points associated with a VRU[...]


Our summary: The system identifies vulnerable road users (VRUs) at risk of losing control in driving environments. It collects sensing data and processes it with machine learning models to find reference points related to VRUs. Based on height differentials, the system determines the risk and triggers avoidance actions in the autonomous vehicle.

vulnerable road users, loss of control, machine learning, autonomous vehicles

Patent

Modeling and Correction of Underwater Photon-Counting LiDAR Returns Based on a Modified Biexponential Distribution

Published on 2026-02-03 by Jie Wang, Wei Hao, Songmao Chen, Meilin Xie, Heng Shi, Xiangyu Li, Xuezheng Lian, Xiuqin Su, Runqiang Xing, Lu Ding @MDPI

Abstract: Laser pulses experience significant temporal broadening in underwater environments due to strong turbulence and scattering effects. As water turbidity increases, the likelihood of multiple scattering events rises, further intensifying pulse broadening and thereby degrading the ranging accuracy of underwater single-photon LiDAR systems. Accurate characterization of the return pulse shape is crucial for precise distance extraction, typically achieved via cross-correlation with the system&amp;r[...]


Our summary: This study introduces a Modified Biexponential Distribution model to accurately characterize the return pulse shape of underwater LiDAR systems. The model addresses the issues of pulse broadening caused by water turbidity and scattering, improving ranging accuracy. Experimental results show a significant reduction in Depth Absolute Error, confirming the model s effectiveness in enhancing underwater photon-counting LiDAR performance.

Photon-Counting, LiDAR, Biexponential Distribution, Underwater

Publication

Hybrid Mamba&ndash;Graph Fusion with Multi-Stage Pseudo-Label Refinement for Semi-Supervised Hyperspectral&ndash;LiDAR Classification

Published on 2026-02-03 by Khanzada Muzammil Hussain, Keyun Zhao, Sachal Perviaz, Ying Li @MDPI

Abstract: Semi-supervised joint classification of Hyperspectral Images (HSIs) and LiDAR-derived Digital Surface Models (DSMs) remains challenging due to scarcity of labeled pixels, strong intra-class variability, and the heterogeneous nature of spectral and elevation features. In this work, we propose a Hybrid Mamba&amp;ndash;Graph Fusion Network (HMGF-Net) with Multi-Stage Pseudo-Label Refinement (MS-PLR) for semi-supervised hyperspectral&amp;ndash;LiDAR classification. The framework employs a sp[...]


Our summary: This work presents a Hybrid Mamba-Graph Fusion Network (HMGF-Net) for semi-supervised hyperspectral-LiDAR classification. The framework integrates spectral-spatial HSI backbones and LiDAR CNN encoders with a graph fusion module for enhanced information propagation. Validation on benchmark datasets shows significant performance improvements over state-of-the-art methods, particularly in low-label scenarios.

Hybrid Mamba-Graph Fusion, Semi-Supervised Learning, Hyperspectral Classification, LiDAR Integration

Publication

Behandelte Themen: Autonome Fahrzeuge, Selbstfahren, LIDAR, Straßenkartierung, Flottenmanagement, Navigationsalgorithmus, Pfadplanung, Verstärkungslernen, Fahrspurerkennung, Doppelkamera, maschinelles Lernen, Wahrnehmungssensoren, semantische Grenzen, integrierte Sensorbaugruppe, Kartendaten, Diskrepanzen, Lärmbelästigung, städtische Umwelt, ISO 26262, ISO/PAS 21448, ISO 15118, ISO 26262-6 und ISO 21434.

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