Browse Topic: Connectivity

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Historical Memory-Based Database Management System for Effective ADAS Configuration in Autonomous and Connected Vehicles2026-28-0057To be published on 02/01/2026
The ability to store data is crucial for an autonomous vehicle system. Memorizing traffic signs, including their locations, can be easier than trying to read and understand them on the fly. Using the vehicle's location and other vehicle data, decisions can be made faster when using existing memory data. This study outlines a technique that utilizes an environmental structure database as a tool for decision-making in diverse vehicle scenarios. By collectively learning and storing vehicle location, historical data, and past actions, this paper results in a way to predict the environmental structure in advance and use the necessary control signals to optimize vehicle operation. In a connected vehicle system, there can be many reasons and factors to be considered in various events such as vehicle speed, parking location, speed changes, speed bumps, braking, etc. These are stored in a separate database, and the accuracy of the results is increased by comparing the actual data at that time
Santhiyagu, Arulanantha Samy
NVH Challenges in Head Up Display (HUD) Design for Modern Connected Vehicles: Balancing Performance and Structural Dynamics2026-26-0354To be published on 01/16/2026
A more recent focus on driver comfort and the increasing demand for access to information make automotive OEMs provide advanced features such as Head Up Display systems. Even though HUD projects vital information onto the windshield/glass, its structural integration comes with significant noise and vibration challenges, leading to noisier in-cabin, display instability and haziness. This paper discusses the significant design parameters influencing the in-cabin NVH levels and functional effectiveness of HUD systems. The structure considered for analysis is the HUD assembly and its integration in vehicle. CCB turns out to be the critical component of the vehicle structure susceptible to road excitations although its mass dampens the vibrations inherently, due to the low mass of the HUD, relative oscillation between its projector, mirror, and either the windshield or display causes image distortion. In addition, the fan incorporated to cool the projector possess threat to in-cabin sound
Vardhanan K, Aravindha Vishnu, Naidu, Sudhakara, Titave, Uttam
Optimal test strategy for Clusters & CDCs in ever evolving multi power train vehicle ecosystem2026-26-0569To be published on 01/16/2026
Innovation in energy storage and generation system will lead to multiple power train solutions across the vehicle categories in the Automotive segment. With various options to the end consumer across different vehicle segments, the complexity associated with E/E Architecture and software engineering will be multi-fold both for the OEMs and Suppliers. Over the air updates shall become mandatory features to manage this complexity and to calibrate the vehicle features inline with changing trends and efficiency plus feature enhancements in post-market release scenarios. These upgrades are more common in digital clusters, in-vehicle entrainment and central digital cockpits. OEMs are introducing the vehicle platforms in multiple power train variants keeping comfort, instrument clusters and in-vehicle entertainment as core features across different power trains. A well-defined and managed comprehensive optimal test strategy and infrastructure will be critical to ensure seamless release of the
RAJARAM, Saravanan, Venkata, Parameswaran, Naik, Venkatesh
Development of a HIL Based Methodology for Over-The-Air Updates Validation2026-26-0480To be published on 01/16/2026
Over-the-Air (OTA) update technology has come forth as a transformative aider in the domain of automotive technology, allowing Original Equipment Manufacturers (OEMs) and Tier-1 suppliers of Electric vehicles (EVs) to frequently make software modifications, enhancements, and bug fixes that are essential to optimize the performance of powertrain components such as the motor controller unit (MCU), Battery Management System (BMS), and Vehicle Control Unit (VCU). This facilitates them to remotely supply updates to the vehicle firmware and software by giving inputs of calibration data without requiring physical access to the vehicle. However, as OTA updates have a direct impact on vehicle’s performance, safety and cybersecurity, a stringent e integration of Hardware-in-the-Loop (HIL) simulation into the OTA validation pipeline as a means to ensure reliability, safety, and functional correctness of updates before they are applied in the field. We present a structured approach of combining
Khare, Shivani, Karle, Ujjwala, Subramaniam, Anand
Self-supervised diagnostics & prognostics framework for predictive maintenance in electric vehicles2026-26-0673To be published on 01/16/2026
Predictive maintenance is essential for enhancing the reliability, safety, and operational efficiency of connected vehicles. However, traditional supervised learning approaches for fault prediction depend heavily on large, labeled datasets of failure events, which are often scarce and expensive to obtain in real-world automotive environments. This paper proposes an original self-supervised anomaly detection framework that predicts emerging failures using only healthy operational data, eliminating the need for explicit failure labels. The approach employs self-supervised pretext tasks, such as masked signal reconstruction and future telemetry prediction, to learn robust representations of normal multi-sensor behavior (e.g., temperature, pressure, current, vibration). An unsupervised anomaly detection model then identifies deviations from these learned patterns. This integrated with data-informed predictive models enable early detection of faults across critical subsystems such as
Kumar, Pankaj, Deole, Kaushik, Hivarkar, Umesh
High-Performance Computing for Software-Defined EV Powertrains: Design and Real-Time Validation with NXP S32E278 Domain Controller2026-26-0684To be published on 01/16/2026
Software-Defined Vehicles (SDVs) are redefining the automotive landscape by decoupling hardware from software and enabling dynamic, over-the-air updates, advanced control strategies, and real-time decision-making. To support this transformation, EV powertrain systems require high-performance computing (HPC) platforms capable of real-time control, data processing, and cross-domain communication. This paper introduces a fully SDV-compatible EV powertrain architecture built around the NXP S32E278 domain controller, which integrates a multi-core, lockstep-enabled processor specifically designed for zonal control and automotive functional safety. To meet the bandwidth and latency demands of modern SDV applications, the system replaces conventional CAN-based communication with automotive Ethernet, enabling gigabit data transfer, Time-Sensitive Networking (TSN), and low-latency coordination across software-defined control domains. The S32E executes critical functions such as field-oriented
Pawar, Ganesh, Inamdar, Sumer Deepak, Kumar, Mayank, Deosarkar, Pankaj, Tayade, Nikhil, Kanse, Dattatray, Chopade, Vipul
Considerations for Vulnerability Management in the Automotive Industry2026-26-0626To be published on 01/16/2026
With the emergence of Software-Defined Vehicles (SDVs), more complex software and connectivity technologies are introduced to support new advanced use cases such as phone as a key, smart parking and vehicle management. However, complex software functionality and external connectivity also increase the attack surface of vehicles and its ecosystem. In this paper, we first perform a classification of recent automotive cybersecurity attacks. We further perform an analysis of these attacks and associated vulnerabilities considering the application of best practices of vulnerability management approaches including Common Vulnerability Scoring System (CVSS), Exploit Prediction Scoring System (EPSS), and Stakeholder-Specific Vulnerability Categorization (SSVC). CVSS is a standardized framework used to assign severity scores to known vulnerabilities and helps organizations prioritize vulnerability remediation based on severity. EPSS is a predictive model that estimates the probability of a
Oka, Dennis Kengo, Vadamalu, Raja Sangili
Risk Based Security Monitoring Framework for CAN network2026-26-0616To be published on 01/16/2026
There is rapidly increasing advancement in Connectivity, Autonomous, Subscription and Electrification features in vehicles which are being developed. These trends have resulted in an increase in attack surface and security risks on vehicles. To handle these growing risks, it has become important to include passive security systems such as Intrusion detection systems (IDS) which can detect successful or possible attempts of intrusion into vehicle systems compromising their security. In vehicles based on Zonal Architecture, two types of IDS can be implemented, Network based IDS (NIDS) and Host Based IDS (HIDS). The NIDS is implemented in Gateway Electronic Control Unit (ECU) and can monitor multiple networks connected to Gateway, whereas the HIDS usually monitors one single host ECU. Extensive research material is available on NIDS for CAN Networks. For example, the CAN Network in a vehicle is monitored for various abnormal behaviours such as increased busload and invalid signal values
E L, Nanda Kumar, Mutagi, Megha, Sonnad, Preeti, Sharma, Dhiraj
Intelligent Sequential Charging Control via Fleet-Managed Cloud System2026-26-0207To be published on 01/16/2026
Electric Vehicles (EV) are increasingly becoming more and more popular in the markets, especially in the commercial vehicle segments. Amidst this, the need to find new elegant methods to perform charging of EV battery becomes extremely crucial. In areas with high demand and limited power capacity, performing charging for multiple vehicles necessitates efficient usage of charging infrastructure, which can’t be guaranteed by the traditional charging methods. Sequential charging is a new state of art technique for managing the charging of multiple EV’s simultaneously connected to a single charging station. Rather than dividing the available power equally among all connected vehicles or charging them one at a time, this technique dynamically allocates power based on various factors such as charging priority, vehicle needs and available infrastructure capacity. Currently, sequential Charging can only be implemented by a particular set of chargers that are interconnected via backend and
De, Abir, Bhattacharya, Ullash, Parihar, Aakash
Unlocking Edge AI in Software-Defined Vehicles: Balancing model complexity, compute resources, and data access2026-26-0686To be published on 01/16/2026
The potential of Edge AI in automotive goes beyond ADAS and automated driving. AI-driven optimizations in driving efficiency, in-cabin personalization, predictive maintenance, and enhanced safety require intelligent processing at the vehicle edge. However, integrating AI into current vehicle electrical/electronic architectures (EEAs) presents significant challenges. This paper examines how AI models can run on general-purpose ECUs, gateways, and domain controllers while balancing model complexity, compute resources, and data availability. We explore trade-offs, architectural choices, and the need for software configurability to ensure AI models evolve with new data and vehicle parameters. We conclude by providing a glimpse into Sonatus’ latest AI product that encapsulates a holistic approach optimized for vehicle platforms—spanning cloud-based model development, optimization, and validation to in-vehicle inference—that unlocks the potential of Edge AI and SDVs for the automotive
Khatri, Sanjay, Sah, Mohamadali
Next-Gen Automotive: Enablers and Monetization for Automotive SaaS and Software Defined Vehicles2026-26-0687To be published on 01/16/2026
The automotive industry is undergoing a paradigm shift, changing its model from hardware-centric products to software-driven platforms. It is driven by two underlying paradigms: the emergence of Software-Defined Vehicles (SDVs) and the increasing adoption of Automotive Software-as-a-Service (SaaS) models. Together, these trends are transforming the way the industry generates value, engages with customers, and builds new revenue models. This research examines the most important technical pillars underpinning next-generation automotive ecosystem creation. Of these pillars, centralized computing infrastructures, embedded cloud integration, efficient over-the-air (OTA) update engines, and enhanced cybersecurity models designed to protect larger numbers of connected vehicles are observed. It also evaluates the imperative significance of digital identity management to provide improved personalized experience, the critical role of edge computing to ensure real-time processing, and the promise
Saini, Gourav, Jahagirdar, Shweta, Khandekar, Dhiraj Baburao
Security monitoring for High Performance Vehicle Computers2026-26-0627To be published on 01/16/2026
With the increasing connectivity of modern vehicles, cybersecurity threats have become a critical concern. Intrusion Detection Systems (IDS) play a vital role in securing in-vehicle networks and embedded vehicle computers from malicious attacks. This presentation shares about an IDS framework designed specifically for POSIX-based operating systems used in vehicle computers, leveraging system-level monitoring, anomaly detection, and signature-based methods to identify potential security breaches. The proposed IDS integrates lightweight behavioral analysis to ensure minimal computational overhead while effectively detecting unauthorized access, privilege escalation, communication interface monitoring etc. By employing a combination of rules and systems datapoints, the system enhances threat detection accuracy without compromising real-time performance. Practical series deployments demonstrate the effectiveness of this approach in mitigating cyber threats in automotive environments
Shukla, Siddharth, Chatterjee lng, Avik
Software-Defined Vehicles: Architecting the Future of Intelligent and Connected Mobility2026-26-0691To be published on 01/16/2026
The rise of Software-Defined Vehicles (SDVs) marks a fundamental shift in automotive design, where software, rather than hardware, defines vehicle capabilities. This review explores the SDV paradigm within Intelligent Transportation Systems (ITS), emphasizing centralized computing, over-the-air (OTA) updates, and service-oriented architectures (SOA). Key enablers such as high-performance computing units, middleware platforms (e.g., AUTOSAR Adaptive), and digital twins support scalable, flexible software deployment and real-time functionality. Artificial Intelligence (AI) and Machine Learning (ML) enhance features like predictive maintenance, driver personalization, and autonomous decision-making. However, SDVs also introduce complex challenges, including software validation, real-time performance, and system interoperability. Cybersecurity becomes critical, especially as vehicles interface with cloud platforms, edge computing, and Vehicle-to-Everything (V2X) networks. The paper also
Ahmad, Aqueel, Hemanth, Khimavath, Kumar, Om, Kumar, Rajiv, Haregaonkar, Rushikesh Sambhaji
Swarm-Inspired Cooperative Mapping for Urban Autonomous Navigation2026-26-0635To be published on 01/16/2026
Urban autonomous vehicles today largely rely on individually built maps or centralized cloud services—both rigid under intermittent connectivity and rapid scene changes (construction, pop-up events). Inspired by how ant colonies collectively explore, we introduce a decentralized protocol: each vehicle broadcasts compressed “map particles” embedded with virtual pheromone values that highlight zones of high uncertainty or recent change. Neighboring vehicles incorporate these signals to prioritize sensing and route planning. A lightweight consensus algorithm merges local graphs into a shared dynamic map, resilient to network splits. The result, a bio-inspired SLAM that enables fleets to adapt on the fly to evolving cityscapes, boosting safety, efficiency, and robustness.
Bhargav, Anirudh S, Subbarao, Chitrashree
Real-time Intrusion Detection System (IDS) for Vehicle Networks Using Machine Learning for Predictive Threat Analysis2026-26-0617To be published on 01/16/2026
The rapid adoption of connected vehicle technologies and advanced driver assistance systems (ADAS) necessitates robust security mechanisms capable of identifying and mitigating sophisticated cyber threats in real-time. Traditional signature-based intrusion detection systems (IDS) are often inadequate in addressing the dynamic and evolving nature of automotive cybersecurity threats, particularly in modern vehicle networks like Controller Area Network (CAN), CAN with Flexible Data-Rate (CAN-FD), and Automotive Ethernet. This research introduces a novel Real-time Intrusion Detection System utilizing advanced Machine Learning (ML) techniques designed specifically for automotive network environments. The proposed IDS framework employs supervised and unsupervised ML algorithms, including anomaly detection, behavioral analytics, and predictive threat modeling, to achieve high accuracy and rapid threat identification capabilities. Through extensive testing in simulated and actual vehicle
chaudhary lng, Vikash, Desai, Manoj, Chatterjee, Avik
Cybersecurity in Automotive OTA Update Systems and Software Store2026-26-0621To be published on 01/16/2026
Automotive Over-the-Air (OTA) software updating has become a cornerstone of the modern connected vehicle, enabling manufacturers to remotely deploy bug fixes, security patches, and new features. However, this convenience comes with significant cybersecurity challenges. This paper provides a detailed examination of automotive OTA update security and the associated software store (software Applications & services store) mechanisms. I discuss the current industry standards and regulations - notably ISO/SAE 21434 and the United Nations Economic Commission for Europe (UNECE) regulations UN R155 (cybersecurity) and UN R156 (software updates) - and explain their relevance to secure OTA and software update management. I then explore the Uptane framework, an open and widely-adopted architecture specifically designed to secure automotive OTA updates. Next, OTA-specific threat models are analyzed, detailing potential attack vectors (such as malicious update injection, man-in-the-middle attacks
Kurumbudel, Prashanth Ram
Leveraging Telematics Big Data Analytics for Real-Time Monitoring of Catalytic Converter Failures and Root Cause Identification for Emission Compliance2026-26-0591To be published on 01/16/2026
The automotive industry is continuously evolving at high pace to meet rising customer expectations, reliability, reduced maintenance, and most relevant, compliance with stringent emission norms. Traditionally, the analysis of vehicle emissions relies heavily on periodic inspections and manual checks. These conventional methods are often time-consuming, prone to human error, and lack the ability to provide real-time insights. Also, identifying Catalytic converter failures due to non-manufacturing issues require meticulous physical inspections and historical data reviews, which are not always accurate or timely. Telematics or Connected cars technology being one of the major technological innovations in recent times revolutionizes these processes by enabling real-time data exchange between vehicles and external systems. The current study presents an innovative approach to utilizing telematics data for real-time monitoring of vehicle emissions and pinpointing Catalytic converter failures
DEV, Triyambak, Prasad, Kakaraparti Agam, Kalkur, Varun, Modak, Saikat, AGARWAL, Shashank, Chandra, Animesh, Paul, Varsha, Garg, Amit, Sundararaman, Venkataraman, Bose, Sushant
Feasibility and Performance of Post-Quantum Cryptography on Embedded Systems for Two-Wheeler Security2026-26-0622To be published on 01/16/2026
The proliferation of connectivity features (V2X, OTA updates, diagnostics) in modern two-wheelers significantly expands the attack surface, demanding robust security measures. However, the anticipated arrival of quantum computers threatens to break widely deployed public-key cryptography (RSA, ECC), rendering current security protocols obsolete. This paper addresses the critical need for quantum-resistant security in the automotive domain, specifically focusing on the unique challenges of two-wheeler embedded systems. This work presents an original analytical and experimental evaluation of implementing selected Post-Quantum Cryptography (PQC) algorithms, primarily focusing on NIST PQC standardization candidates (e.g., lattice-based KEMs/signatures like Kyber/Dilithium), on microcontroller platforms representative of those used in two-wheeler Electronic Control Units (ECUs) – typically ARM Cortex-M series devices characterized by limited computational power, memory (RAM/ROM), and strict
Mishra, Abhigyan
Reducing Risk in Safety Critical Systems through Early Safety Case Development and Dialectic Arguments2026-26-0044To be published on 01/16/2026
The rapid evolution of modern automotive systems—powered by advancements in autonomous driving, and connected vehicle technologies— pose fundamental challenges to design and integration. Ensuring the safety of these highly interconnected, software-driven systems, with the widespread reuse of components across platforms. This growing complexity calls for a more structured and rigorous approach to safety assurance than traditional methods. Traditional safety cases tend to take a linear, justification-focused approach that mainly focuses on positive assertions —statements of compliance or success—while giving limited attention to potential weaknesses, or gaps in supporting evidence. This practice may lead to criticism that such arguments are “too positive,” portraying an overly optimistic view of system safety without sufficiently acknowledging areas of unresolved risk. As a result, conventional approaches for developing safety case may overlook complex interactions, assumptions, and
Kumar, Amrendra, Bagalwadi, Saurabh, McMurran, Ross
Resilience Evaluation Method for Rail Transit Networks Considering Dynamic Passenger Flows2025-99-0438To be published on 12/10/2025
This study proposes an urban rail transit network resilience assessment method based on dynamic passenger flow, which quantifies the overall system performance from the structural and functional dimensions. At the structural level, the relative size of the largest pass subgraph is introduced to measure the network integrity, and the average node degree is used to evaluate the network connectivity; At the functional level, the passenger travel efficiency ratio is used to measure the operation efficiency of the supply side, and the proportion of unaffected passengers is used to evaluate the service support capability of the demand side. The weight of each index is determined by entropy weight method, and then the comprehensive performance evaluation model of rail transit system is constructed. Taking Nanjing Metro as an example, the empirical study shows that the performance change trend reflected by the introduction of dynamic passenger flow is significantly different from the
Wang, Junhang, Shao, Jiayu, Yang, Haofan, Zhang, Ning
A Study of Electro-Hydraulic Brake of Electric Automobiles and Intelligent Connected Vehicles2025-99-0402To be published on 12/10/2025
The traditional hydraulic braking system with vacuum booster technology is very mature, but it is not suitable for use in electric vehicles due to the lack of a vacuum source. The brake system by wire is an innovative electronic controlled braking technology, and the Electro-Hydraulic Brake is currently the most widely used brake system by wire in electric vehicles. The classification, structure, working principle, and advantages of Electro-Hydraulic Brake as a braking system for electric automobiles and intelligent connected vehicles are studied. The structure, working principle, advantages and disadvantages of Pump-Electro - Hydraulic Brake and Integrated Electro-Hydraulic Brake are compared and analyzed.
Song, Jiantong, Zhu, Chunhong, Ren, Xiaolong
Identification of Critical Risk Nodes and Vulnerability Analysis in Railway Networks2025-99-0425To be published on 12/10/2025
As the importance of railway networks in regional transportation and economic development continues to grow, identifying critical risk nodes and assessing network vulnerability is crucial for enhancing the stability and resilience of railway systems. This study focuses on the railway network of Shandong Province, constructing a topological model to systematically analyze the structural characteristics of the network, with a particular emphasis on key nodes. To identify these critical risk nodes, four modified weighted indicators were employed, combined with the mean-square deviation TOPSIS method to quantify node importance. The analysis identified Jinan, Linyi, and Yantai as key risk nodes, as they consistently ranked high across multiple indicators. Further vulnerability analysis reveals that the failure of these critical nodes would lead to significant declines in network efficiency and connectivity, with particularly high vulnerability observed when nodes with high weighted
Xu, Chang, Han, Wen, Fan, Hongxian, Dai, Hongna
Minimum Requirements to Support Traffic Signal Priority and PreemptionJ2945/B_202511 (Current)11/20/2025
When identifying the content of this report, one of the goals was that it supports a nationally interoperable method for connected vehicles (CVs) to make traffic signal priority and/or preemption (TSPP) requests of connected intersections (CIs) that support priority and/or preemption services. Given that, this report specifies the over-the-air (OTA) interface between CVs and CIs to support TSPP applications using updated revisions of the SAE J2735 Signal Request Message (SRM) and Signal Status Message (SSM) and the use of a Wireless Access in Vehicular Environments (WAVE) Service Advertisement (WSA) to advertise support for TSPP at a CI. Included are a concept of operations, requirements, design, and message structure definitions developed using a detailed systems engineering process.
null, null
Minimum Requirements to Support Traffic Signal Priority and Preemption™ SET FileJ2945/BS_202511 (Current)11/20/2025
Included in this set are the SAE J2945/B Standard which specifies the over-the-air (OTA) interface between connected vehicles (CVs) and connected intersections (CIs) to support traffic signal priority and preemption (TSPP) applications. It specifies the use of updated revisions of the SAE J2735 Signal Request Message (SRM) and Signal Status Message (SSM) and the use of a Wireless Access in Vehicular Environments (WAVE) Service Advertisement (WSA) to advertise support for TSPP at a CI. Included are a concept of operations, requirements, design, and the Abstract Syntax Notation One (ASN.1) message format, data frame, and data element definitions. Also included is the Abstract Syntax Notation One (ASN.1) file precisely defines the structure of the data used to implement applications conformant to the SAE J2945/B Standard. Using this ASN.1 specification, a compiler tool can be used to produce encodings to enable applications to easily encode and decode the Signal Request Message (SRM) and
Connected Transportation Interoperability Committee
Minimum Requirements to Support Traffic Signal Priority and Preemption™ ASN FileJ2945/BA_202511 (Current)11/20/2025
This Abstract Syntax Notation One (ASN.1) file precisely defines the structure of the data used to implement applications conformant to the SAE J2945/B Standard. Using this ASN.1 specification, a compiler tool can be used to produce encodings to enable applications to easily encode and decode the Signal Request Message (SRM) and Signal Status Message (SSM) messages, along with the Wireless Access in Vehicular Environments (WAVE) Service Advertisement (WSA) application data, defined in SAE J2945/B. Included in the ASN.1 file is the complete SAE J2735 ASN.1 along with the updates to the ASN.1 for the SRM and SSM defined in SAE J2945/B.
Connected Transportation Interoperability Committee
Technology Driven Solutions for Effective Tool Management2025-28-024911/06/2025
Tool management remains a persistent challenge in manufacturing, where misplaced or poorly calibrated tools such as torque guns and screwdrivers cause downtime, quality defects, and compliance risks. The Internet of Things (IoT) is transforming tool management from manual entries in spreadsheets and logs to real-time, data-driven solutions that enhance operational efficiency. With ongoing advancements in IoT architecture, a range of cost-effective tracking approaches is now available, including Ultra-Wideband (UWB), Bluetooth Low Energy (BLE), Wi-Fi, RFID, and LoRaWAN. This paper evaluates these technologies, comparing their trade-offs in accuracy, scalability, and cost for tool-management scenarios such as high-precision station tracking, zonal monitoring, and wide-area yard visibility. Unlike prior work that focuses on asset tracking in general, this study provides an ROI-driven, scenario-based comparison and offers recommendations for selecting appropriate technologies based on
Patel, Shravani Prashant
Vehicle to Vehicle Recharge and Power Sharing for Modular Public Transportation Systems: Design and Testing of the UNIFI fleet at ENEA CASACCIA Research Center2025-32-009511/03/2025
The synergistic adoption of automated driving technologies and the electrification of the vehicle power train offers the possibility of proposing new and innovative solutions for public transportation systems. In particular, an interesting solution is represented by modular systems in which multiple autonomous vehicles/transportation modules can be aggregated to form reconfigurable compositions according to desired transportation demand. In this work, a configurable connection between vehicles is adopted, as convoying ensures the possibility of power sharing between vehicles, allowing coordinated power management throughout the composition. Connected vehicles can also share power between batteries for battery recharge that is performed using a custom solution from a tram-like catenary. In this work, the authors design a demonstrator to investigate the feasibility of the proposed solution. Once designed, the proposed system has been assembled and tested at the ENEA Casaccia Research
Alessandrini, Adriano, Berzi, Lorenzo, Fabbri, Marco, Franci, Michael, Gulino, Michelangelo Santo, Pugi, Luca, Ortenzi, Fernando, Vitiello, Francesco
Intelligent Management of Exhibition Building Space: Structural Analysis and Crowd Evacuation Based on Space Syntax in the Dongguan Naval Battle Museum2025-99-002410/17/2025
Taking Dongguan Naval Battle Museum as a typical case, this study uses space syntax to conduct an in-depth structural analysis of space, study the topological relationship and connectivity pattern inside the exhibition building, and provide valuable insights for the spatial organization of the exhibition building. In addition, the study also explores the crowd evacuation aspect. Based on the understanding of spatial structure through space syntax, this study found that: (1) Dongguan Naval Battle Museum should use variables such as selectivity, global integration, harmonic mean depth, visual connectivity, first-order moment index, visual integration, and pedestrian flow simulation as much as possible to improve the environmental quality and help people evacuate smoothly. (2) The exhibition hall should guide arrival and evacuation in space with the highest or second highest values of variables such as connectivity, intensity, controllability, and pedestrian flow simulation. (3) Space No
Tang, Qiang, Song, Junxin, Chen, Yile, Zheng, Liang, Li, Xiaoye
A Distributed V2X Hardware-in-the-loop Test System Based on the PanoSim for Intelligent Connected Vehicles2025-99-004110/17/2025
Based on the similarity analysis of Intelligent Connected Vehicles (ICVs), a distributed V2X hardware-in-the-loop test system for ICVs is designed, including the PanoSim autonomous driving simulation engine, GNSS simulator, V2X simulator, and management and cooperative control software. The system integrates the major technologies of distributed interaction, including operation management, time synchronization, coordinate conversion, and data preprocessing, and realizes the spatial and temporal consistency of each simulation node. 89 V2X first-stage application scenarios (e.g., FCW, RLVW) and 5 V2X second-stage application scenarios (e.g., CLC) use case experimental results have proved the reliability of the system. The FCW use case experiment results show that its simulation results pass with high confidence. The study emphasizes the value of the system in reducing development costs, improving safety, and accelerating the deployment of V2X applications, while identifying future
Gao, Tianfang, Zhang, XingHui, Chen, Liang, Huang, Zhichen, Ni, Dong
Decision-Making Research for Intelligent Connected Vehicles Considering Adhesion Condition2025-99-002810/17/2025
The adhesion condition of the road surface is an important factor in the driving decision-making, and the lower the adhesion coefficient of the road, the greater the risk of safety. In order to study the development and progress in the research of the substances, a comparative analysis of Chinese and foreign references was carried out. The sensitive factors to the adhesion coefficient and influence of adhesion condition on driving were summarized. Then two main strategies to avoid a collision were presented, including longitudinal braking and lateral lane change. A detailed description of three methods used in automotive decision-making processes was offered, including rule-based method, supervised learning method, and reinforcement learning method, each characterized with certain attributes. Topics in the field of driving decision-making considering adhesion condition for intelligent connected vehicles were pointed out and future-oriented research formulations were provided. These
Wang, Hong, Hou, De-Zao
Reducing Powertrain Software Release Cycles from Months to Days: Streamlined Compliance and Rapid Deployment2025-01-037910/07/2025
The automotive industry's rapid shift towards electric and connected vehicles intensifies the demand for robust solutions addressing software integrity, cybersecurity, and stringent regulatory compliance, particularly concerning powertrain components and related control units. This paper addresses the significant challenge faced by automotive companies in efficiently managing and deploying an exponentially increasing number of software and hardware variants under the rigorous requirements of UNECE Regulation No. 156. This regulation mandates secure, traceable, and systematic software update processes for new vehicles and their components [1]. The proposed solution demonstrates a transformative approach that significantly reduces the software release cycle for Over-The-Air (OTA) updates which usually take 6 to 8 months to emerge [2]. By leveraging advanced techniques in automated compliance tracking, efficient parameter management, and centralized documentation, this approach bridges
Sammer, Gerald, Schuch, Nikolas, Kammerhofer, Markus
Examining Time Sensitive Networking in Military Ground Vehicle Architectures2025-01-046509/16/2025
Time-Sensitive Networking (TSN) is a modern networking technology that promises to combine the speed, performance, and scalability of traditional best-effort Ethernet with the resilience and assurance of a safety-critical communications bus, all in a single physical network infrastructure. Although TSN is over a decade old, the collection of standards and profiles of which it consists are still evolving at a fast pace. Significant work remains to converge on a set of standardization and implementation details that will lead to meaningful interoperability in military ground vehicle applications. This paper explores the current state of TSN and how DEVCOM-GVSC’s partnership with industry, through collaborative refinement of ground combat vehicle requirements, is accelerating the adoption of this foundational MOSA-enabling technology.
Sopel, Shane, Elliott, Leonard, Kinstler, Erik, Salama, Christina
SAE BOOKS: From ADAS to SDVs with Plato Pathrose25AUTP09_0409/01/2025
Author's third book delves deeper into SDVs. An experienced engineer with a history in software development and systems engineering, Plato Pathrose is turning from ADAS to SDVs with his latest work. Pathrose's third book, Software Defined Vehicles, will be published in September 2025 with SAE International. “This is both a technology and a business book,” Pathrose told SAE Media. “It aims to offer a comprehensive perspective on one of the most transformative trends in the automotive industry. Software Defined Vehicles explores how software is reshaping the design, function, and value of modern vehicles.” From concept, architecture, and connectivity to over-the-air updates and vehicle personalization, Pathrose's latest book dives deep into the technologies driving this shift. It also addresses the business implications, including new revenue models, ecosystem strategies, and the changing role of OEMs and suppliers.
Blanco, Sebastian
101st Combat Aviation Brigade Makes History with First MUOS Connectivity in a Helicopter25AERP08_0608/01/2025
In a groundbreaking achievement, the 101st Combat Aviation Brigade, 101st Airborne Division (Air Assault) earlier this year became the first unit to successfully use the Mobile User Objective System (MUOS) function of the Army/Navy Portable Radio Communications (AN/PRC) 158 and 162 radios for conventional rotary wing operations. The trailblazing accomplishment occurred as the brigade continued its mission of providing support to ground forces, April 9, 2025. The MUOS function, of the AN/PRC-158 and 162 radios, operates by transmitting ultra-high frequency radio waves through a constellation of satellites to create a steady communications network. MUOS is a component of a bigger Integrated Tactical Network (ITN).
Ferroelectric Material Adapts to Light Stimuli by Reorganizing Atomic ConnectivityTBMG-5354808/01/2025
“Today’s supercomputers and data centers demand many megawatts of power,” said Haidan Wen, a Physicist at the U.S. Department of Energy (DOE) Argonne National Laboratory. “One challenge is to find materials for more energy-efficient microelectronics. A promising candidate is a ferroelectric material that can be used for artificial neural networks as a component in energy-efficient microelectronics.”
101st Combat Aviation Brigade Makes History with First MUOS Connectivity in a HelicopterTBMG-5358808/01/2025
In a groundbreaking achievement, the 101st Combat Aviation Brigade, 101st Airborne Division (Air Assault) earlier this year became the first unit to successfully use the Mobile User Objective System (MUOS) function of the Army/Navy Portable Radio Communications (AN/PRC) 158 and 162 radios for conventional rotary wing operations. The trailblazing accomplishment occurred as the brigade continued its mission of providing support to ground forces, April 9, 2025.
Electronic Control Units for Enhanced Safety and Monitoring2025-01-504007/03/2025
The rapid evolution of electric vehicles (EVs) necessitates advanced electronic control units (ECUs) for enhanced safety, monitoring, and performance. This study introduces an innovative ECU system designed with a modular architecture, incorporating real-time monitoring, cloud connectivity, and crash sensing. The methodology includes cost-effective design strategies, integrating STM32 controllers, CAN bus systems, and widely available sensors for motor RPM and temperature monitoring. Key findings demonstrate that the proposed ECU system improves data reliability, enhances vehicle safety through crash response systems, and enables predictive maintenance via cloud connectivity. This scalable and affordable ECU is adaptable to a broad range of EV models.
Padma Priya, S.R., Santhipkumar, S., Sasipriya, S., Srivisweswara, M.S.
Automated Test Process for Highly Configurable Software-Defined Mobility Systems in CI/CD2025-01-029707/02/2025
In the pursuit of customizability and evolvability of vehicle functions, manufacturers shift towards software-defined vehicles to enable flexible customization and over-the-air updates. This results in multiple variants and versions of a vehicle model. While shifting to software-defined vehicles (SDVs) adds value and flexibility for customers, manufacturers struggle with homologating new and updated functionality because existing testing processes do not scale for high-frequency release cycles that limit available testing resources. Overcoming this challenge by using a coherent test process designed for testing continuously evolving variant-rich systems will be one of the key enablers. This paper presents an innovative end-to-end pipeline for efficient and comprehensive testing of variant-rich vehicle functionality tailored to an application in continuous development. Our transferable test pipeline employs sample-based variant selection, a software-in-the-loop environment for executing
Hettich, Lennard, Pett, Tobias, Nägele, Ann-Therese, Schindewolf, Marc, Eriş, Halit, Wagner, Stefan, Sax, Eric, Schaefer, Ina, Weyrich, Michael
Applying Real World Traffic Data on Machine Learning Methods for Graph Based Cooperation Strategies of Automated Vehicles2025-01-028607/02/2025
With the increasing distribution of smart mobility systems, automated & connected vehicles are more and more interacting with each other and with smart infrastructure using V2X-communication. Hereby, the vehicles’ position, driving dynamics data, or driving intention are exchanged. Previous research has explored graph-based cooperation strategies for automated vehicles in mixed traffic environments based on current V2X-communication standards. Thereby, the focus is set on cooperation optimization and maneuver negotiation. These strategies can be implemented through both centralized and decentralized computational approaches and are conflict-free by design. To enhance these previously established cooperation models, real-world traffic data is used to derive vehicle trajectories, providing a more accurate representation of actual traffic scenarios in order to enhance the practical application of the described methodology. Additionally, machine learning algorithms are employed to train
Flormann, Maximilian, Meyer, Felix, Henze, Roman
Assessment of Cooperative Navigation Algorithms for CAVs in Threat Scenarios12-09-01-000706/14/2025
This article introduces a comprehensive cooperative navigation algorithm to improve vehicular system safety and efficiency. The algorithm employs surrogate optimization to prevent collisions with cooperative cruise control and lane-keeping functionalities. These strategies address real-world traffic challenges. The dynamic model supports precise prediction and optimization within the MPC framework, enabling effective real-time decision-making for collision avoidance. The critical component of the algorithm incorporates multiple parameters such as relative vehicle positions, velocities, and safety margins to ensure optimal and safe navigation. In the cybersecurity evaluation, the four scenarios explore the system’s response to different types of cyberattacks, including data manipulation, signal interference, and spoofing. These scenarios test the algorithm’s ability to detect and mitigate the effects of malicious disruptions. Evaluate how well the system can maintain stability and avoid
Khan, Rahan Rasheed, Hanif, Athar, Ahmed, Qadeer
The Growing Connectivity Dimensions in Medical TechnologyTBMG-5328306/01/2025
Transforming Satellite Antenna Technology for the Next Era of Aerospace and Defense25AERP06_0306/01/2025
The global satellite communications (SATCOM) sector is undergoing profound transformation. Fueled by the rapid growth of low Earth-orbit (LEO) constellations, increased government investment, and heightened demand for secure, high-throughput connectivity, the market is projected to expand from $66.75 billion in 2025 to $103.78 billion by 20291, 2. This momentum reflects a broader realignment of priorities across commercial and defense markets: a shift from reliance on legacy geostationary systems toward agile, resilient networks capable of supporting next-generation missions and applications.
V2P-Based Speed Guidance Method for Avoiding Vehicle–Pedestrian Collisions at Intersections12-09-01-000605/14/2025
Conflicts between vehicles and pedestrians at unsignalized intersections occur frequently and often result in serious consequences. In order to alleviate traffic flow congestion at unsignalized intersections caused by accidents, reduce vehicle congestion time and waiting time, and improve intersection safety as well as intersection access efficiency, a speed guidance algorithm based on pedestrian-to-vehicle (P2V) and vehicle-to-pedestrian (V2P) communication technologies is proposed. The method considers the heading angle (direction of motion) of vehicles and pedestrians and combines the post encroachment time (PET) and time to collision (TTC) to determine whether there is a risk of collision, so as to guide the speed of vehicles. Network simulator NS3 and traffic flow simulation software SUMO are used to verify the effectiveness of the speed guidance strategy proposed in this article. The experimental findings demonstrate that the speed guidance strategy introduced in this article
Sun, Yuanyuan, Wang, Kan, Liu, Weizhen, Li, Wenli
New Method Makes Designing a Metamaterial Cell EasyTBMG-5303105/01/2025
Researchers from MIT and the Institute of Science and Technology Austria have developed a computational technique that makes it easier to quickly design a metamaterial cell from smaller building blocks like interconnected beams or thin plates, and then evaluate the resulting metamaterial’s properties.
Legal Issues and Policy: Vol. 3EPRCOMPV05202404/30/2025
Abdul Hamid, Umar Zakir, Eastman, Brittany
Infrastructure Enablers for Automation: Vol. 3EPRCOMPV04202404/30/2025
Coyner, Kelley, Bittner, Jason
Aerospace Developments: Vol. 3EPRCOMPV09202404/30/2025
Muelaner, Jody Emlyn, Moran, Matthew, Phillips, Paul
Predicting Real-time Crash Risks during Hurricane Evacuation Using Connected Vehicle Data09-13-01-000604/12/2025
Hurricane evacuations generate high traffic demand with increased crash risk. To mitigate such risk, transportation agencies can adopt high-resolution vehicle data to predict real-time crash risks. Previous crash risk prediction models mainly used limited infrastructure sensor data without covering many road segments. In this article, we present methods to determine potential crash risks during hurricane evacuation from an emerging alternative data source known as connected vehicle data that contain vehicle speed and acceleration information collected at a high frequency (mean = 14.32, standard deviation = 6.82 s). The dataset was extracted from a database of connected vehicle data for the evacuation period of Hurricane Ida on Interstate-10 in Louisiana. Five machine learning models were trained considering weather features and different traffic characteristics extracted from the connected vehicle data. The results indicate that the Gaussian process boosting and extreme gradient
Syed, Zaheen E Muktadi, Hasan, Samiul
A Time-Aware Shaper-Based Method for Addressing Traffic Bursts and Out-of-Order Induced by IEEE 802.1CB in In-Vehicle Networks2025-01-807904/01/2025
The trends of intelligence and connectivity are continuously driving innovation in automotive technology. With the deployment of more safety-critical applications, the demand for communication reliability in in-vehicle networks (IVNs) has increased significantly. As a result, Time-Sensitive Networking (TSN) standards have been adopted in the automotive domain to ensure highly reliable and real-time data transmission. IEEE 802.1CB is one of the TSN standards that proposes a Frame Replication and Elimination for Reliability (FRER) mechanism. With FRER, streams requiring reliable transmission are duplicated and sent over disjoint paths in the network. FRER enhances reliability without sacrificing real-time data transmission through redundancy in both temporal and spatial dimensions, in contrast to the acknowledgment and retransmission mechanisms used in traditional Ethernet. However, previous studies have demonstrated that, under specific conditions, FRER can lead to traffic bursts and
Luo, Feng, Ren, Yi, Zhu, Yian, Wang, Zitong, Guo, Yi, Yang, Zhenyu
Eco-Approach and Departure Algorithm for Connected and Automated PHEVs: Simulation and in-Vehicle Results2025-01-838404/01/2025
Plug-in Hybrid Electric Vehicles (PHEVs) combine the benefits of electric propulsion and storage with the extended range of conventional internal combustion engines to reduce fuel consumption and greenhouse gas emissions. However, optimizing the efficiency of PHEVs in real-world driving conditions remains a challenge due to the uncertainties of environmental and driving conditions. Connectivity and automation technologies can offer a unique opportunity to enhance the efficiency of PHEVs by enabling real-time interaction with surrounding vehicles and infrastructure. By leveraging these technologies, significant reductions in energy consumption for PHEVs can be achieved. However, most existing works primarily rely on simulation-based analyses to evaluate energy savings offered by connected and automated PHEVs. This study advances the understanding of the energy-saving potential of connected and automated PHEVs by incorporating experimental validation alongside simulation-based analyses
Kibalama, Dennis, Ozkan, Mehmet Fatih, Stockar, Stephanie, Canova, Marcello, Rizzoni, Giorgio
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