Browse Topic: Computer software and hardware
The automotive industry is evolving from a reactive, independently self-determined approach to cybersecurity, complicated by a complex supply chain. Over time, this has resulted in a fragmented industry comprised of any number of proprietary solutions verses a standardized, regulated paradigm to facilitate a platform-oriented approach. This document, an update on collaborative work from the SAE Vehicle Electrical Hardware Security Task Force (TEVEES18B) and GlobalPlatform Automotive Task Force, outlines this transition strategy. An extensible number of additional examples of use cases of Global Platform Technologies are explored in this document.
Software-defined vehicles (SDVs) are reshaping automotive control architectures by shifting intelligence to embedded systems, where computational efficiency is paramount. This paper presents a systematic evaluation of control strategies (PID, LQR, MPC) for the classical control problem involving inverted pendulum on a cart under strict embedded constraints representative of software-defined vehicle ECUs. The objective is to evaluate and compare the performance of advanced control algorithms under varying control objectives when deployed on microcontrollers with constrained computational and memory resources, representative of the limitations encountered in embedded platforms used for SDVs. Furthermore, the study illustrates systematic optimization strategies that enable these algorithms to achieve real-time execution within such resource-constrained environments. Each control strategy is implemented with careful consideration of algorithmic complexity, real-time responsiveness, and
The useability of development processes in the automotive sector has decreased in the past years to a level at which their application and true benefit to is being questioned. Such degradation can be attributed to new additions to the processes and introduction of FuSa and Cybersecurity standards. The processes try to keep up with the shift from the traditional ‘plan–implement–test–roll-out' methodology to more agile methods. In addition, process departments typically in charge of these processes, focus on compliance to the letter of the standard to achieve certification, often with little thought to the actual implementation and the process they will be used by their engineering teams. Process growth to meet the needs of new and more complex technologies often mandates the use of new tools, which if implemented incorrectly can lead to unnecessary bureaucracy and additional overheads. Furthermore, the language of these new processes is in a form from assessor, making it difficult for
Patching vulnerabilities in safety-critical domains such as automotive and aerospace is costly and complex. A small code modification can trigger a complete rebuild, producing a binary with widespread changes. This inflates patch size, complicates regression testing, and makes over-the-air (OTA) updates inefficient, as traditional binary patches often replace large portions of the executable. We present a binary rewriting–based experiment that shows the feasibility of a patch that updates only the affected bytes by computing the impact of a code change at the binary level. This produces minimal, localized patches rather than regenerated executables. The preliminary experiment shows that a single source change, which leads to thousands of modified bytes after recompilation, can be captured with only a few bytes using our method. For automotive and aerospace systems, this technique reduces patch size, conserves bandwidth, and minimizes disruption to certified software, offering a
The automotive industry is undergoing a fundamental transformation in Electrical/Electronic (E/E) architecture, evolving from traditional distributed and domain-based designs toward zonal configurations. The rapid growth of software-defined functionality, cross-domain integration, and centralized computing has exposed inherent limitations of legacy architectures in scalability, wiring complexity, and system integration. Zonal E/E architecture addresses these challenges by consolidating computing and Input/Output (I/O) resources into high-performance controllers distributed across physical zones of a vehicle. This transformation, however, cannot occur instantaneously, as contemporary vehicle designs and E/E system solutions are the result of decades of incremental development based on distributed and domain-based paradigms. Moreover, key enabling technologies for zonal E/E architecture—such as high-performance Central Compute Platform (CCP) and zonal controllers, high-speed automotive
Autonomous platforms such as self-driving vehicles, advanced driver-assistance systems (ADAS), and intelligent aerial drones demand real-time video perception systems capable of delivering actionable visual information at ultra-low latency. High-resolution vision pipelines are often hindered by delays introduced at multiple stages—sensor acquisition, video encoding, data transmission, decoding, and display—undermining the responsiveness required for safety-critical decision making. This study introduces a holistic system-level optimization framework that systematically reduces end-to-end video latency while maintaining image fidelity and perception accuracy. The proposed approach integrates hardware-accelerated encoding, zero-copy direct memory access (DMA), lightweight UDP-based RTP transport, and GPU-accelerated decoding into a unified pipeline. By minimizing redundant memory copies and software bottlenecks, the system achieves seamless data flow across hardware and software
With the rise of software-defined vehicles and the emergence of cyber threats to vehicular systems, developing teams are compelled to conduct extensive testing on both virtual and physical prototypes at an accelerated pace. This new development landscape necessitates diagnostic tools that are both precise and adaptable. However, proprietary systems dominate this field, often hindering accessibility for students and researchers due to high costs and restrictive licensing. This paper presents the design and implementation of an open-source, low-cost remote testing system tailored for automotive development and diagnostics. The proposed system utilizes Arduino and Raspberry Pi processing units, along with relay-based switching modules, to provide secure remote control of vehicle components through a web-based dashboard equipped with authentication, scheduling, and real-time synchronization capabilities. The tested prototype showcased robust scalability, secure session handling, and
The transition to software-defined vehicles (SDVs) necessitates a paradigm shift in both control strategies and vehicle architecture. The EU-funded R&D project SmartCorners addresses this challenge by developing integrated, modular, and scalable smart corner systems (SCS) that combine in-wheel motor (IWM)-based propulsion, brake blending, active suspension system, and steer-by-wire functionality in one module. These SCS can be retrofit or smoothly integrated into the highly adaptable skateboard chassis architecture of modern electric vehicles (EVs), enabling scalable deployment across diverse vehicle types. The central approach of this paper is the utilization of artificial intelligence (AI) and machine learning (ML) to implement multi-layer, data-driven control strategies, facilitating real-time actuation, fault mitigation, and user-centric EV architecture. The SmartCorners project strives to demonstrate significant enhancements, including improved real-world driving range due to
The automotive industry is subject to major transformation initiated by societal and economical pull (reducing emissions, zero fatalities, European competitiveness) and accelerated by technology push (electrification, Cooperative, Connected and Automated Mobility (CCAM), and Cooperative Intelligent Transport Systems (C-ITS)). Following this trend, the Software-Defined Vehicle (SDV) targets the integration of software (SW) development methodologies for vehicle development as well as the value delivery shift toward customers along the entire lifecycle. It promises to create benefits for the car manufacturers in terms of faster time to market, easier update – as well as for the car users (private persons, fleet operators) in terms of personalized user experience, upgradability. At the same time, SDV requires a much more integrated and continuous development framework to enable different experts to efficiently develop and validate concurrently the different parts of the vehicles, to gather
The rapid advancement of advanced driver assistance systems (ADAS), automated driving and electrification has significantly increased the software content and complexity within modern vehicles. Consequently, ensuring both high process quality and compliance or qualification with functional safety standards becomes critically important. Automotive Software Process Improvement and Capability Determination (ASPICE 4.0) focus on Process quality and Capability Maturity, while ISO 26262:2018 emphasizes engineering guidelines for functional safety and risk mitigation. The efficient integration of the process and standard remains a key challenge due to differences in their objectives, terminologies, and assessment criteria. The misalignment between ASPICE 4.0 and ISO 26262:2018 standard often results in duplicated efforts, rework of work products, and delays in product release schedules. This paper proposes a unified framework to bridge ASPICE 4.0 process areas with ISO 26262:2018 safety
Consider this: A new groundbreaking technology has just been developed that needs to be integrated into multiple types of aircraft as soon as possible. This could take years to accomplish, since each aircraft implements a different method of communicating with it, using different data transport protocols. Even worse, this new technology likely has proprietary information that needs to be transmitted to the aircraft in some format. All of these issues would require a different version of the technology for each aircraft.
The U.S. Army has selected two companies to develop prototype chassis and plug-in-cards for aviation and ground vehicles. The selection is the Army's latest milestone accomplishment in an effort to feature Modular Open System Approach (MOSA) -aligned embedded computing systems across all of the new investments it makes in technology upgrades for new and legacy vehicles. In a program update posted in September 2025, the Army selected General Dynamics Mission Systems and Pacific Defense as the lead developers for new C5ISR/EW Modular Open Suite of Standards (CMOSS) Mounted Form Factor prototypes. CMOSS is a set of standards developed by the U.S. Army to guide the design of embedded computing networks featured on Army vehicles.
Dassault Systèmes and NVIDIA have announced a long-term strategic partnership to establish a shared industrial architecture for mission-critical artificial intelligence across industries. Combining Dassault Systèmes' Virtual Twin technologies with NVIDIA AI infrastructure, open models and accelerated software libraries will establish science-validated industry World Models, and new ways of working through skilled virtual companions on the agentic 3DEXPERIENCE platform, that empower professionals with new expertise.
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