Browse Topic: Computer software and hardware

Items (6,531)
Global Navigation Satellite System (GNSS) receivers are widely being used in aerospace as well as automotive applications primarily for navigation applications. ISRO uses indigenously developed GNSS receivers in its Launch vehicles (LV) mainly for POD (Preliminary Orbit Determination) and for INS aiding in long duration missions. Advanced GNSS receivers are being developed and used in ISRO’s new generation launch vehicles for closed loop guidance (CLG) applications. Being used in CLG, continuous solution availability and robustness of GNSS solutions are of paramount importance. From April 2023 onwards, GNSS receivers on-board ISRO’s LV missions have shown degraded performance in terms of reduction in no. of satellites tracked and in some cases loss of GNSS solution as well. This was seen in multiple missions and was analyzed in detail. It was observed that there is nearly 3-4dB reduction in carrier to noise density (C/No) ratio and corresponding change in RF AGC gain is also observed
A, Mohammed BasimO T, Anand ShankaraV S, BijuV Gopal, BijuV S, VinojK, BalanC, Radhakrishna Pillai
Model-based development (MBD) and Model-based Testing are critical for airborne software compliance with DO-178C and its supplement DO-331, which specifically addresses model-based approaches for software levels A through D. Traditional manual methods increase the documentation and validation burden, leading to inconsistent implementations across the project, and raise the risk of missed defects or gaps in compliance. This paper presents an automation framework designed to align with DO-331 objectives by leveraging fine-tuned large language models (LLM) to automate the generation of high-level textual requirements and low-level model-based requirements. From these, comprehensive test cases are automatically derived, covering normal, edge, mutation based, and dynamic scenarios to ensure a thorough validation of model behavior. Utilizing AI agent, the framework extracts requirements and key parameters from documentation, enabling automated specification analysis and test script
Lalchandani, TusharPurushothaman, KalaivaniJeppu, YoganandaVijaya Kumar, Shree HarshaNatarajan, Akilandeswari
This paper presents an automated framework for security compliance and quality assurance in DevSecOps CI/CD pipelines, specifically designed for safety-critical avionics software. The framework integrates regulatory compliance checks, security validation, and robust verification directly into the software development lifecycle, supporting continuous integration and delivery for aerospace applications. Automated processes such as code compilation, coding standards compliance, Cyclomatic Complexity Measurement, Sources Line of Code and CRC validation on target hardware are seamlessly orchestrated to maintain consistency and reliability. The system generates comprehensive compliance reports, highlights coding standard violations and security issues, and notifies relevant stakeholders to facilitate timely resolution and corrective actions. As new code is checked in, the framework automatically initiates all verification and compliance tasks, ensuring that every software update is
Bhagwat, Shashank RaviChangappa, Naveen KumarNath, Sunny
This novel method deals with emulation of Strain of a Structural Measurement System which includes software validation, acceptance tests and training. Current methods for simulating strain and force data for developing and verifying data acquisition (DAQ) software typically rely on costly electronic simulators or specialized hardware, making it challenging and expensive for developers, researchers, and small organizations to test their solutions under realistic conditions. To verify DAQ software, multiple specialized hardware solutions are deployed, that include Electronic Simulators, Commercial DAQ Modules and Hydraulic/Pneumatic test rigs. These technologies pose a challenge with limited flexibility and scalability options for small-scale prototyping, especially in budget-constrained scenarios. The sensors on these equipment may or may not be company approved inducing acceptance challenges. Our invention is an inexpensive, scalable, and mechanically simple alternative. Using a 3D
Murthy, HarshaBhat Venkatesh, AditiK Padmanabhan, RahulMadhu, SheetalGarag, Naveen
This SAE Standard provides a framework for the management of software reliability within system reliability requirements. It is based around the Software Reliability Plan and Software Reliability Case and emphasizes the importance of evaluating progress towards meeting software reliability requirements throughout the project life-cycle.
G-41 Reliability
In 1994 the SAE G-11 Reliability, Maintainability, Supportability, and Logistics (RMSL) Division chartered a software committee, G-11SW, to create several software standards and guidance documents across the RMSL spectrum, including a software supportability program standard. The committee was formed as a cross section of international representatives from commercial industries and governments. The G-11SW committee has attempted to develop a standard that is consistent with a SAE G-11 system level supportability program standard and augmented by necessary software-specific support information. The G-11SW committee believes this document reflects the best current commercial practices, and meets the objectives of the United States Department of Defense Acquisition Reform initiative. This document is performance based and is intended to be used by industries to address market demands for supportable software products that facilitate system evolution, time to market, and implementation of
G-41 Reliability
This Surface Vehicle & Aerospace Recommended Practice offers best practices and a methodology by which IVHM functionality relating to components and subsystems should be integrated into vehicle or platform level applications. The intent of the document is to provide practitioners with a structured methodology for specifying, characterizing and exposing the inherent IVHM functionality of a component or subsystem using a common functional reference model, i.e., through the exchange of design-time data and the application of standard vehicle data communications interfaces. This document includes best practices and guidance related to the specification of the information that must be exchanged between the functional layers in the IVHM system or between lower-level components/subsystems and the higher-level control system to enable health monitoring and tracking of system degradation severity. The intent is to provide an IVHM system that can robustly report the degradation of a given
HM-1 Integrated Vehicle Health Management Committee
The aging of the population has been a key issue worldwide, with mobility and fall of the elderly an important problem to be solved. In this paper, we propose an elderly mobility assist system based on the intelligent power-assisted device consisting of an assistive cane and an intelligent companion. It has the functions of standing support after falling, daily support and on-site rest. The assistive cane adopts a two-stage expansion mechanism of crank and slider structure, which forms a stable triangular support after unfolding, so that the patient can stand safely. The intelligent companion platform is driven by drive wheels, equipped with pushrod motors and vacuum suction devices, it can automatically approach the user and form an stable support column when the cane is in the out-of reach range; the control system is designed by combining microcontroller, camera object recognition, wristband remote control, to realize automatic steering and autonomous navigation at differential
Yu, ChenxiWang, LongyiZhu, HuayunDong, YanMi, RuixueZhu, Lihong
In response to the problems of urban traffic congestion and the limited expansion of infrastructure, this paper conducts two core research focusing on the intelligent chassis system of split-type flying vehicle. Firstly, an autonomous navigation strategy for the intelligent chassis module is proposed based on chassis module Navigation 2 architecture, which fuses LIDAR and IMU positioning to plan paths using the A* global planning algorithm on a global cost map, and update the local cost map in real time with sensor data. It is orchestrated by the BT Navigator using a behavior tree, with failures handled by the Recovery Server, to achieve autonomous driving across multiple waypoints. In simulation and closed-field experiments, the system can stably reach the preset target points. The positioning accuracy and trajectory tracking performance can meet the design requirements. Secondly, a mechanical slide rail-type docking structure adapted to the split flying vehicle architecture is
Zhao, WenyuShi, QinJiang, CongHe, Zejia
The convergence of highly capable edge AI models and advanced commercial-off-the-shelf (COTS) edge AI accelerators is reshaping how computation is deployed across defense, aerospace, and commercial platforms. Mission-critical decisions increasingly must be made at the edge, onboard vehicles, satellites, and infrastructure nodes, where latency, connectivity, and power availability are constrained.
Automotive research landscape currently is driven by emerging technologies such as software-defined vehicles, advanced infotainment systems, and increasingly automated driving functions. This situation calls for a bigger need for efficient, comprehensive, and agile research methods. Traditional methods require significant manual effort, leading to information synthesis and dissemination bottlenecks. After doing a thorough research on how research is carried on in automotive companies, it is inferred that a lot of time is spent on gathering information and integrating it with proprietary knowledge rather than on analysis or synthesis of the information. There are tools and platforms with artificial intelligence (AI) advancement that help with deep research of a particular topic, and there are also tools and platforms that help with synthesis of proprietary information within automotive organizations. But there is a lack of a framework that dynamically integrates the aspect of deep
Vemuri, Pavan
Documenting and mapping using three-dimensional (3D) technologies have become essential in crime- and crash-scene investigations in recent years. Traditionally, this has been accomplished using terrestrial laser scanners (TLS), which often come with significant upfront costs. In contrast, Recon-3D, launched in 2022, leverages the capabilities of Apple’s light detection and ranging (LiDAR) sensor, available in Pro and Pro Max models since 2020. This study aims to evaluate the relative accuracy of documenting vehicles in both pre- and post-collision conditions using these technologies. A deviation analysis was conducted utilizing CloudCompare software to compare point cloud data collected from the Leica RTC360 laser scanner with that obtained from Recon-3D for 7 vehicles in a pre- and post-impact condition for a total of n = 14 vehicles. At the 1, 2, and 3 cm deviation thresholds, the average percent of points which fell below each threshold level for all vehicles was 66%, 91%, and 97
Lim, JihwaLiscio, Eugene
Software-defined vehicles offer customers a greater degree of customization of vehicle controls and driving experience. One such feature is user-adjustable tuning of vehicle ride and handling, where customers can vary ride height, damper stiffness, front-rear torque balance, and other aspects of vehicle dynamics. While promising a great customer experience, such a feature can expose the vehicle to a wider range of structural loads than those in the nominal design condition, particularly when such tuning is extended to cover spirited “sport” mode driving, off-road driving, etc. In this paper we present a novel methodology combining Road Load Data Acquisition (RLDA) data and real-world telemetry data to estimate the impact of user-adjustable vehicle-dynamics tuning on structural durability. In doing so, the method combines the physics of damage accumulation (from RLDA data) with user behavior (from telemetry data) to present an accurate assessment of the impact on durability, moving
Demiri, AlbionRamakrishnan, SankaranWhite, DylanKhapane, PrashantBorton, Zackery
Floating-point arithmetic is widely used in automotive embedded software to scale Controller Area Network signals and calibration parameters with fractional factors such as 0.1. However, floating-point operations, even on microcontrollers equipped with floating-point units, can increase execution time and CPU load. In AUTOSAR architectures, converting floating-point scaling to fixed-point is not trivial because scaling semantics must be integrated consistently across components, yet AUTOSAR platform toolchains offer only limited automation at the Application Data Type level. Although CompuMethod definitions can express scaling, integration typically remains manual and distributed across application software components, reducing consistency and reusability. This study presents an architecture-driven methodology that formalizes fixed-point scaling as a centralized architectural service, realized through a parser-driven fixed-point macro generation pipeline. Standardized CAN DBC and
Lee, HoseokKo, Donggun
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.
Mazzara, BillRawlings, Craig
The study presented in this paper explores the potential of five open-source Large Language Models (LLMs) with parameter counts between 32 billion and 49 billion to automate enhancements in code quality and developer productivity. The evaluated models – CodeLlama [1], Command-R [2], Deepseek R1-32B [3], Nemotron [4], and QwQ [5] - were assessed on their ability to refactor a large and complex automotive mechatronic C language function. This assessment focused on adherence to provided code quality standards and successful compilation of the refactored function within a larger code module. The evaluation also compared the impact of parameter count, hyperparameter tuning, model architecture, and fine-tuning. This comparison revealed that larger models showed superior overall performance, though with notable exceptions where smaller models performed better in specific rule categories. Additionally, hyperparameter tuning yielded modest improvements in performance. The study also highlighted
Struck, DanielKumaraswamy, Samanth
Crashes involving passenger vehicles increasingly include vehicles equipped with infotainment systems that are unsupported by commercial vehicle system forensics hardware and software. Examiners facing these systems must overcome challenges in acquiring and analyzing user data, requiring an understanding of both digital forensics principles and the proprietary characteristics of the modules. This paper presents a methodology for acquiring data from previously unsupported Lexus infotainment modules, including techniques to bypass CMD42 security locks on SD cards and extract data. Once acquired, the paper outlines methods for analyzing user data through data carving techniques, enabling recovery of information from binary images even when the full file system cannot be reconstructed. Emphasis is placed on maintaining the integrity of the evidence and validating findings through controlled testing. These validation procedures ensure that the recovered information is both accurate and
Burgess, Shanon
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
Weber, MatthiasKmiec, MateuszRomijn, MarcelNedkov, Detelin
The proven usefulness of large language models (LLMs) as tools for software development and the recent rapid increase in their capabilities have made it possible and attractive to extend their scope of application to almost all tasks in the engineering of complex and even safety-critical systems. While these tools promise substantial efficiency gains and improved engineering productivity, they remain prone to errors, and the generated artifacts may not meet the stringent quality requirements for safety-critical systems. In this paper, we systematically analyze potential applications of LLMs throughout the engineering lifecycle of safety-critical systems and identify associated risks as well as practical approaches to risk mitigation. We classify LLM-supported use cases according to LLM autonomy, impact, and artifact observability, and compare the corresponding mitigation strategies with established approaches used for traditional engineering automation. In addition, we examine the
Thomas, CarstenWagner, Michael
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
Awadhutkar, PayasSauceda, JeremiasTamrawi, Ahmed
The objective of this paper is to understand the effort required to integrate the hardware and software of in-vehicle cybersecurity systems. The in-vehicle cybersecurity method discussed is the SAE J1939-91C, which involves Network formation, Rekeying, and secure Message Exchange between Electronic Control Units (ECUs). The SAE J1939-91C network security protocol operates over a CAN-FD network to perform necessary cryptographic operations and key generation. To evaluate the method, test vectors were created to validate SAE J1939-91C key generations and cryptographic operations on the simulated ECU in-vehicle network system hardware (such as the Beacon or Pi devices). We introduce a lightweight, transport-agnostic benchmark comprising deterministic AES-CMAC test vectors and a simple verification utility, requiring no specialized hardware or build system. This minimal artifact set enables reproducible and machine-parsable validation of SAE J1939-91C security across diverse lab
Zachos, MarkMedam, Krishna Teja
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
Jiang, Shugang
Vehicle pitchover crashes can result in very severe accelerations and forces. Literature and test data available on pitchover crashes is sparse. This paper presents the results of a full-scale pitchover/rollover crash test using an instrumented vehicle in a controlled and documented off-road environment. The test vehicle was driven to the launch point by an off-board operator using remote steering and throttle controls. The test vehicle then experienced an airborne phase during which forward pitching occurred, followed by a front-to-ground impact which induced additional pitchover motion. Then, following the initial front and rear impacts, the vehicle transitioned from a pitchover to rollover motion before coming to rest. The resulting vehicle motion, vehicle damage markings, and ground markings were documented with various slow motion and real time camera views. The test vehicle was instrumented with accelerometers, rotation rate sensors, and other sensors, the results of which
Warner, MarkWarner, WyattSwensen, GrantPerl, Mark
Off-road vehicles are typically powered by diesel engines, sized to cover the highest peak loads in their dutycycles. Such applications can be designed with downsized engines, using hybridization to supplement engine power with electrical power for short periods. However, many applications are low-volume and specialized, making it impractical to deploy heavy engineering resources to optimize each one. For this reason, manufacturers tend to produce maid-of-all-work vehicles to cover every situation. This paper demonstrates the benefits of custom hybridization for specialist applications, and addresses the lack of accessible software tools for evaluating such opportunities. Analysis is applied with a fast, low-cost, Concept-based software tool named “ePOP Concept”, suited to original equipment manufacturers (OEMs) who seek to provide custom low-volume vehicles. It allows many different powertrain architectures to be evaluated rapidly at the product planning stage, and can be quickly set
De Salis, RupertFons, Daniel
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
Vupparige, VarunPandya, Vidit
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
Indrakanti, Rama Kiran Kumar
Reliable component libraries are the foundation of the engineering process and the starting point for all intelligence within CAD tools. In practice, however, libraries created and maintained by librarians often contain incomplete, inconsistent, or outdated data. This paper introduces the component data consistency and relationship inference AI system, developed within Amoeba software, which addresses these challenges by improving component library quality. The system uses AI to infer component attributes such as component type, gender, color, material, etc. Moreover, it can identify relationships such as the family a connector is associated with based on its attributes and geometry. The system improves data consistency in areas such as resolving mismatched wire size constraints imposed by the connector and cavity components. It also utilizes computer vision to identify common connector footprints, cavity sizes, and 2D symbol geometries. Deployed within Amoeba software, the system has
Phan, DungHorvat, Bryan
In recent years, the use of software-defined platforms has become increasingly prevalent. As a result, flashing ECUs has become an important factor in ensuring efficiency, quality, and compliance in vehicle production. Conventional approaches, such as final end-of-line flashing, are increasingly unsuitable for the growing amounts of data, complex dependencies, mixed physics and protocols, and traceability requirements. This SAE paper presents the current trends and challenges in ECU flashing. It highlights the impact of the exponential growth in software payloads and the necessary migration to offline and parallel workflows. This can only be achieved through closer integration with automated and robot-assisted production, considering the requirements of cybersecurity and verifiability. It also addresses the shift toward end-to-end flashing ecosystems, where updates are performed consistently from a single source covering the assembly line, warehouses, yards, workshops, and over-the-air
Böhlen, BorisBudak, OguzWells, Michael
Automated Driving Systems (ADS) rely on AI algorithms, machine learning, and sensor fusion to perform autonomous driving tasks. Safety challenges arise due to the probabilistic behavior of AI/ML algorithms and the need to ensure safety within defined Operational Design Domains (ODDs). Traditional standards such as ISO 26262[3] (Functional Safety) and ISO 21448[4] (SOTIF) address hardware and software failures or functional deficiencies but are insufficient for higher-level autonomous systems (SAE Levels 3–5). To close this gap, additional standards such as UL 4600[1] and ISO 5083[2] provide complementary frameworks for ADS safety assurance. UL 4600[1] establishes a claim-based safety case encompassing the vehicle, infrastructure, and processes, emphasizing structured arguments supported by evidence and reasoning. It offers guidance on autonomy functions, V & V, tool qualification, dependability, and safety culture. ISO 5083[2] focuses on design, verification, and validation of ADS
Mudunuri, Venkateswara RajuAlmasri, HossamFan, Hsing-Hua
Electronics is entering rapidly into all automotive subsystems, performing control and monitoring tasks apart from making the entire vehicle intelligent. Interface with the external automotive eco-system needs careful attention during the system design. It defines how seamlessly the electronic unit interacts with rest of the vehicle. It needs to do so in an effective manner without compromising on cost and other automotive application constraints. This paper focusses on the “smart switch building block” that forms heart of an automotive output interface echo system.: Its importance stems from the fact that, a smart switch is an indispensable building block for any electronic control system driving external loads. As various novel electical and electronics architectures are entering various vehicle segments, the need for a single reusable solution that will cater to 12 Volts to 48 Volts battery buses is increasingly being felt. However, no prevelant solution meets this requirement. Even
Vaidya, Vishwas Manohar
This paper presents the integration and validation of Adaptive Cruise Control (ACC) algorithms on a student-team-developed vehicle as part of the U.S. Department of Energy EcoCAR EV Challenge. The competition provided each team with a 2023 Cadillac Lyriq, which was modified to an all-wheel-drive configuration and re-architected to support the development of SAE Level 3 autonomous features including Adaptive Cruise Control (ACC), Automatic Intersection Navigation (AIN), Lane Centering Control (LCC), and Automatic Parking (AP). The scope of this paper, however, is limited to the development, implementation, and validation of a Level 2 longitudinal ADAS function. Higher-level automation requirements such as Operational Design Domain (ODD) definition and Driver Monitoring System (DMS) enforcement are addressed at the vehicle architecture and competition level but are not the focus of this work. The major contribution of this work is the development of ACC with Vehicle-to-Infrastructure
Gupta, IshikaEstrada, TylerTambolkar, PoojaMidlam-Mohler, Shawn
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
Pries, AndrewMohammad, Utayba
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
Ratz, FlorianArmengaud, EricFormento, CeciliaMoscone, GiuliaSorrentino, GennaroBisciaio, GiorgioSorniotti, AldoAmati, NicolaBraun, DanielDeibler, BerndBoxberger, ValeriusSottile, SalvatoreIvanov, ValentinFuse, HiroyukiKompara, Tomaž
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
Armengaud, EricPermann, RobertJoergler, SabrinaBarcelona, Miguel AngelGarcía, LauraRodriguez, José ManuelIvanov, ValentinLi, ZhenqianNguyen Quoc, TrieuRodrigues, SandyKowalczyk, BogdanAvdić Čaušević, Amra
This study presents the development and validation of a muddy water spray apparatus designed to simulate dust contamination on vehicle sensors for sensor cleaning system testing. It is important to have a constant and quantifiable test environment for the vehicle development process. For verifying the apparatus, muddy water, prepared by mixing standardized dust powder, salt, and water to maintain constant contamination test conditions, was sprayed onto glass specimens to evaluate equipment consistency. Deposited dust weight and thickness were measured across multiple spray cycles, with statistical analyses confirming consistent and reliable deposition. Paired t-tests indicated no significant difference between sample positions, demonstrating uniform spray distribution. The apparatus was further applied to individual infrared (IR) cameras to observe performance degradation under dry and wet contamination conditions showing statistically consistent increases in contamination levels
Jinhyeok, Gong
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
Ravi, ReshmaEaswaramoorthy, Prasad VigneshPromise, Dinu
Embedded vision systems are essential for contemporary applications, including robotics, advanced driver assistance systems (ADAS), and intelligent surveillance; yet they frequently experience diminished image quality due to resource constraints, environmental variability, and inconsistent illumination conditions. Such degradations impact multiple visual attributes—sharpness, contrast, color accuracy, noise levels, and structural similarity—that are critical for reliable perception in safety- and performance-driven domains. This study introduces a comprehensive system-level calibration architecture that integrates three coordinated layers: sensor-level adjustment, firmware optimization, and adaptive software enhancements. At the sensor level, exposure control, gain tuning, and white balance adjustments mitigate luminance imbalance and color shifts under changing light conditions. Firmware optimization leverages image signal processor (ISP) parameters to reduce temporal and spatial
Indrakanti, Rama Kiran KumarVishnoi, NitinKamadi, Venkata
The evolution toward software-defined vehicles (SDVs) is causing disruption to the traditional automotive supply chain and breaking down the common hierarchical OEM, tier 1 supplier, and tier 2 supplier relationships. With demands for faster software release cycles, more advanced software projects involving multi-party development, and considerations for end-to-end embedded and cloud integrations, new cybersecurity challenges are introduced that no single organization can address alone. Thus, this disruption creates new trust dependencies and requires new models for collaboration, transparency, and joint responsibility in cybersecurity. This paper presents a collaborative cybersecurity model, emphasizing shared responsibility during multi-party development between OEMs, tier 1 and 2 suppliers, engineering services organizations, and technology and services providers. As such, we explore collaborative approaches for each stage in the development lifecycle including design, development
Oka, Dennis KengoVinzenz, Nico
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