Ensuring Trustworthiness of AI-Enhanced Embedded Systems


Artificial Intelligence (AI) is unlocking new capabilities in safety-critical systems, from enhanced motor control to autonomous driving. However, integrating AI safely remains a significant challenge due to its data-driven nature and operation in open and real-world variability. While established standards such as ISO 26262 and ISO 21448 provide a foundation for functional safety and intended ... » read more

Systematic Training and Validation of AI-based Systems With Digital Twins and Scenario Engineering


A new technical paper, "Towards Structured Training and Validation of AI-based Systems with Digital Twin Scenarios," was published by researchers at RWTH Aachen University and RIF e.V. Abstract "Artificial intelligence (AI) has emerged as a pivotal technology for autonomous systems across various domains, but quality assurance remains challenging due to limited training data and inadequate ... » read more

Survey of DL-Based LiDAR Super-Resolution For Autonomous Driving (University College London)


University College London researchers published "A Comprehensive Survey on Deep Learning-Based LiDAR Super-Resolution for Autonomous Driving." Abstract "LiDAR sensors are often considered essential for autonomous driving, but high-resolution sensors remain expensive while affordable low-resolution sensors produce sparse point clouds that miss critical details. LiDAR super-resolution addre... » read more

Autonomous Driving: Assessment Of YOLO Algorithms (RMIT et al.)


A new technical paper titled "Advances in You Only Look Once (YOLO) algorithms for lane and object detection in autonomous vehicles" was published by RMIT University, Kyungpook National University, Deakin University and the RCA Robotics Laboratory, Royal College of Art. Abstract "Ensuring the safety and efficiency of Autonomous Vehicles (AVs) necessitates highly accurate perception, especia... » read more

Autonomous Driving: Motion Planner Executed on Automotive-Grade Embedded HW (TU Munich)


A new technical paper titled "Towards Safe Autonomous Driving: A Real-Time Motion Planning Algorithm on Embedded Hardware" was published by researchers at TU Munich. Abstract "Ensuring the functional safety of Autonomous Vehicles (AVs) requires motion planning modules that not only operate within strict real-time constraints but also maintain controllability in case of system faults. Exis... » read more

Case Study : Autonomous Driving AI Domain Controller


Ambarella’s CV3-AD655 autonomous driving AI domain controller combines energy-efficient compute with Imagination’s IMG BXM GPU to deliver real-time surround-view visualisation for L2++/L3 vehicles. This case study explores the shift to centralized domain controllers, why Ambarella selected IMG BXM, and how this enables greater driver awareness and system trust. Read more here.   ... » read more

GPU Enables Surround View In Automotive Domain Controller


In recent years, the capabilities of Advanced Driver Assistance Systems (ADAS) have flourished. Nearly half of all car sales in the USA offer Level 2 capabilities (such as lane keeping and adaptive cruise control) or higher, and China is pushing the market further towards Level 3 (conditional automation with driver oversight) and beyond. The advanced functionality offered by these ADAS and a... » read more

ADAS/AD: Why An External Safety MCU Remains A Cornerstone For Safety Alongside SoC Safety Islands


Advanced driver-assistance systems (ADAS) and autonomous driving (AD) technologies are revolutionizing mobility, making vehicles smarter, safer, and increasingly autonomous. At the heart of these advancements are sophisticated computing architectures built on system-on-chips (SoCs) that manage complex tasks like perception, decision-making, and control. Many SoCs integrate a "Safety Island"—a... » read more

SDVs And AI Forcing Big Changes In Automotive


The automotive industry is undergoing a fundamental transformation that includes everything from software-defined vehicles, the injection of AI into nearly every facet of the design and use case of a vehicle, and a complete overhaul of traditional relationships between different tiers and OEMs. The switch to software-defined vehicles is a top priority for the automotive ecosystem. It enables... » read more

Overview Of The End-to-End Autonomous Driving through V2X Challenge (Tsinghua, HK Univ., Stanford, TU Munich et al.)


A new technical paper titled "Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition" was published by researchers at Tsinghua University, Hong Kong University, Stanford University, TU Munich, Imperial College of London et al. Abstract "With the rapid advancement of autonomous driving technology, vehicle-to-everything (V2X) communication has emerge... » read more

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