Browse Topic: Connectivity

Items (742)

Automated Test Process for Highly Configurable Software-Defined Mobility Systems in CI/CD

2025-01-0297To be published on 07/02/2025

In the pursuit of customizability and evolvability of vehicle functions, manufacturers shift towards software-defined vehicles (SDV) to enable flexible customization and over-the-air updates. This results in multiple variants and versions of a vehicle model. While shifting to 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 variant-rich systems in continuous evolution will be one of the key enablers for the future development of SDVs. 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

Hettich, Lennard, Pett, Tobias, Nägele, Ann-Therese, Schindewolf, Marc, Eris, 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 Vehicles

2025-01-0286To be published on 07/02/2025

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

Predicting Real-time Crash Risks during Hurricane Evacuation Using Connected Vehicle Data

09-13-01-0006

04/12/2025

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

Lessons and Challenges from Crowd-Sourced Data in Rural Michigan to Assess EV Suitability based on Analyzing Personal Driving

2025-01-8525

04/01/2025

Abstract Real-world driving data is an invaluable asset for several types of transportation research, including emissions estimation, vehicle control development, and public infrastructure planning. Traditional methods of real-world driving data collection use expensive GPS-based data logging equipment which provide advanced capabilities but may increase complexity, cost, and setup time. This paper focuses on using the Google Maps application available for smartphones due to the potential to scale-up real-world driving data logging. Samples of the potential data processing and information that can be gathered by such a logging methodology is presented. Specifically, two months of Google Maps driving data logged by a rural Michigan resident on their smartphone may provide insights on their driving range, duration, and geographic area of coverage (AOC) to guide them on future vehicle purchase decisions. Aggregating such statistics from crowd-sourcing real-world driving data via Google

Manoj, Ashwin, Yin, Sally, Ahmed, Omar, Vaishnav, Parth, Stefanopoulou, Anna, Tomkins, Sabina

Freedom from Interference Challenges for Adaptive Autosar Based Platform

2025-01-8074

04/01/2025

This paper examines the challenges and mechanisms for ensuring Freedom from Interference in Adaptive AUTOSAR-based platforms, with a focus on managing Memory, Timing, and Execution challenges. It explores the robust safety mechanisms in Classic AUTOSAR that ensure Freedom from Interference and the significant challenges in achieving interference-free operation in Adaptive AUTOSAR environments while adhering to ISO26262 standards. The study emphasizes strategies for managing complexities and outlines the multifaceted landscape of achieving interference-free operation. Additionally, it discusses ASIL-compliant Hypervisor, memory partitioning, and Platform Health Management as mechanisms for ensuring safety execution. The paper also raises open questions regarding real-time problems in live projects that are not solved with existing safety mechanisms. Adaptive AUTOSAR plays a crucial role in the development of autonomous and connected vehicles, where functional safety is of utmost

Jain, Yesha

A Time-Aware Shaper-Based Method for Addressing Traffic Bursts and out-of-Order Induced by IEEE 802.1CB in in-Vehicle Networks

2025-01-8079

04/01/2025

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 Results

2025-01-8384

04/01/2025

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

Modal Characteristics of Oil-Gas Interconnected Suspension Systems and their Influence on Vehicle Ride Quality

2025-01-8271

04/01/2025

This study focuses on the dynamic behavior and ride quality of three different modes of oil-gas interconnected suspension systems: fully interconnected mode, left-right interconnected mode, and independent mode. A multi-body dynamics model and a hydraulic model of the oil-gas suspension were established to evaluate the system's performance under various operating conditions. The research includes simulations of pitch and roll excitations, as well as ride comfort tests on different road surfaces, such as Class B roads and gravel roads. The analysis compares the effectiveness of the modes in suppressing pitch and roll movements and their impact on overall ride comfort. Results show that the independent mode outperforms the other two in minimizing roll, while the fully interconnected mode offers better pitch control but at the cost of reduced comfort. These findings provide valuable insights for the future design and optimization of oil-gas interconnected suspension systems, especially in

Xinrui, Wang, Chen, Zixuan, Zhang, Yunqing, Wu, Jinglai

An Adaptive Risk-Based Access Control with Trusted Execution Environment for Vehicles

2025-01-8089

04/01/2025

The rapid development of intelligent and connected vehicles is transforming them into data-rich information carriers, which generate and store vast amounts of sensitive information. However, the frequent sharing of resources within these vehicles poses substantial risks to user privacy and data security. Should sensitive resources be accessed maliciously, the consequences could be severe, leading to significant threats to the safety, property, and reputation of both drivers and passengers. To address these risks, this paper proposes an adaptive risk-based access control with Trusted Execution Environment (TEE) specifically designed for vehicles, aimed at managing and restricting access permissions based on risk assessments. Firstly, this paper designs an adaptive risk model in accordance with ISO/SAE 21434, taking into account factors such as the security levels of subjects and objects, context, and the risk history of subjects to separately quantify threats and impacts. By adjusting

Luo, Feng, Li, Zhihao, Wang, Jiajia, Luo, Cheng

Research on Segmented Latency Testing Method for in-Vehicle Real-Time Systems Based on DDS Middleware

2025-01-8083

04/01/2025

With the rapid development of intelligent connected vehicles, their open and interconnected communication characteristics necessitate the use of in-vehicle Ethernet with high bandwidth, real-time performance, and reliability. DDS is expected to become the middleware of choice for in-vehicle Ethernet communication. The Data Distribution Service (DDS), provided by the Object Management Group (OMG), is an efficient message middleware based on the publish/subscribe model. It offers high real-time performance, flexibility, reliability, and scalability, showing great potential in service-oriented in-vehicle Ethernet communication. The performance of DDS directly impacts the stable operation of vehicle systems, making accurate evaluation of DDS performance in automotive systems crucial for optimizing system design. This paper proposes a latency decomposition method based on DDS middleware, aiming to break down the overall end-to-end latency into specific delays at each processing stage

Yu, Yanhua, Luo, Feng, Ren, Yi, Hou, Yongping

Vehicle–Vehicle Collaborative Control Strategy for Dedicated Lanes of Connected Vehicles

12-08-02-0012

03/28/2025

To alleviate the problem of reduced traffic efficiency caused by the mixed flow of heterogeneous vehicles, including autonomous and human-driven vehicles, this article proposes a vehicle-to-vehicle collaborative control strategy for a dedicated lane in a connected and automated vehicle system. First, the dedicated lane’s operating efficiency and formation performance are described. Then, the characteristics of connected vehicle formations are determined, and a control strategy for heterogeneous vehicle formations was developed. Subsequently, an interactive strategy was established for queueing under the coordination of connected human-driven and autonomous vehicles, and the queue formation, merging, and splitting processes are divided according to the cooperative interaction strategy. Finally, the proposed lane management and formation strategies are verified using the SUMO+Veins simulation software. The simulation results show that the dedicated lane for connected vehicles can

Zhang, Xiqiao, Cui, Leqi, Yang, Longhai, Wang, Gang

How Will TSN Ethernet Impact the Future of Embedded Computing for Aerospace and Defense Applications?

25AERP03_06

03/01/2025

Time Sensitive Networking (TSN) Ethernet is a real-time networking capability that is being developed by a growing number of embedded computing companies for the earliest stages of adoption by aerospace and defense manufacturers and their suppliers. According to the Institute of Electrical and Electronics Engineers (IEEE) TSN working group, it is a set of standards that provides deterministic connectivity within IEEE 802-aligned networks. Nigel Forrester is the Director of Product Strategy for Concurrent Technologies, a UK-based provider of high performance embedded computing solutions for aerospace, defense and many other industries. Check out our interview with Forrester about the potential impact of TSN Ethernet on new and legacy aerospace and defense applications, and how it is being adopted by manufacturers and system integrators below.

Artificial Intelligence Use Cases for Ground Vehicle Applications

J3312_202502 (Current)

02/25/2025

This SAE Technical Information Report identifies use cases for AI technology applications to ground vehicles and transportation infrastructure. Whenever applicable, functional definitions and noted issues and concerns are provided in consistent with the current industry mobility practices and published peer-reviewed literature.

Artificial Intelligence

Toward a Methodology for Safety—Performance Trade-Off Analysis for Connected Automated Vehicles Supported by a Smart Infrastructure

12-08-02-0020

02/24/2025

Introducing connectivity and collaboration promises to address some of the safety challenges for automated vehicles (AVs), especially in scenarios where occlusions and rule-violating road users pose safety risks and challenges in reconciling performance and safety. This requires establishing new collaborative systems with connected vehicles, off-board perception systems, and a communication network. However, adding connectivity and information sharing not only requires infrastructure investments but also an improved understanding of the design space, the involved trade-offs and new failure modes. We set out to improve the understanding of the relationships between the constituents of a collaborative system to investigate design parameters influencing safety properties and their performance trade-offs. To this end we propose a methodology comprising models, analysis methods, and a software tool for design space exploration regarding the potential for safety enhancements and requirements

Fornaro, Gianfilippo, Törngren, Martin, Gaspar Sánchez, José Manuel

Research on Map Matching Method Based on Road Geometric Features

2025-01-7159

02/21/2025

For the mismatching defects of vertical projection method, this paper proposes an improved map matching algorithm based on road geometric features. For GNSS data, static repeated data is eliminated, dynamic high frequency data is compressed by light bar method. For network map data, extract motorized road segment, break road segment curve at the turning point, and establish network topology relationship. During map matching, determine the candidate road segment through the circular error area, and determine the matching path through the heading angle, connectivity and projection distance, and determine the projection points through the historical trajectory and driving speed. The effectiveness of the proposed algorithm is verified by case study.

Zhang, Hongbin, Zhang, Xu

Study on Variable Speed Limit Control Strategy of Highway under Intelligent Connected Environment

2025-01-7189

02/21/2025

This paper presents a novel variable speed limit control strategy based on an Improved METANET model aimed at addressing traffic congestion in the bottleneck areas of expressways while considering the impact of an intelligent connected environment. Traffic flow simulation software was employed to compare the outcomes of the traditional variable speed limit model with those derived from the proposed strategy. The results indicated that under three scenarios—main road, ramp, and lane closure—with a 100% penetration rate of intelligent connected vehicles, the average delay for vehicles utilizing the new model decreased by 9.37%, 11.11%, and 7.22%, respectively. This study offers an innovative approach to highway variable speed limits under an intelligent connected environment.

Qi, Tiancheng, Qu, Xinhui, Gu, Haiyan, Sang, Zheming, Ning, Fangyue

Traffic Flow Simulation Analysis of Mixed Traffic Flow Involving CAVs and Human-Driven Vehicles in Urban Work Zones

2025-01-7187

02/21/2025

With the acceleration of urbanization, developing public transportation is an important means to alleviate travel pressure and traffic congestion in cities. Work zones that occupy urban road resources affect normal vehicle operations, leading to reduced vehicle efficiency. Based on this, the paper conducts research on traffic flow modeling and simulation analysis for work zones in a vehicle-road coordination environment. Based on the Gipps model and the SCAT model, optimizations and improvements were made to the following and lane-changing rules for three types of vehicles: human-driven vehicles (HVs), autonomous and connected vehicles (CAVs), and buses. Using cellular automata theory, it constructs a running model suitable for mixed traffic flow vehicles in work zones. MATLAB software is utilized to simulate the operation process of vehicles under work zone scenarios, analyzing changes in traffic flow from two directions: road geometric conditions (speed limits) and traffic flow

Xie, Rongkai, Sun, Bo, Zheng, Yunchao, Liao, Meixian, Zhang, Wendi, Li, Rui

Testing Methods for Advanced Intelligent Driving Systems Based on Natural Driving Behavior Characteristics

2025-01-7147

02/21/2025

The technology of advanced intelligent driving systems equipped in intelligent and connected vehicles evolves rapidly, while the corresponding testing and evaluation standards lag behind. To propose new testing methods for advanced intelligent driving systems, this study first identifies typical intelligent driving functions through extensive research. Based on the distribution characteristics of natural driving scenarios, a series of test cases for these typical functions are developed. By employing simulation methods and the "logical scenario-critical scenario-experimental scenario" mechanism, the generalized test cases are filtered, enabling the rapid extraction of high-value test cases for real-world field testing and validation. Finally, the typical intelligent driving functions of advanced driving systems are analyzed and evaluated from the perspectives of perception and decision-making, as well as control operations. The experimental results demonstrate that the proposed testing

Mo, Jingyue, Wu, Biao, Ma, Zhixiong, Ren, Hongze, He, Jiacan

Identification and Quantitative Analysis Technique of Road Obstacle Safety Risks

2025-01-7201

02/21/2025

The transition from manual to autonomous driving introduces new safety challenges, with road obstacles emerging as a prominent threat to driving safety. However, existing research primarily focuses on vehicle-to-vehicle risk assessment, often overlooking the significant risks posed by static or dynamic road obstacles. In this context, developing a system capable of real-time monitoring of road conditions, accurately identifying obstacle positions and characteristics, and assessing their associated risk levels is crucial. To address these gaps, this study proposes a comprehensive process for rapid obstacle identification and risk quantification, composed of three main components: road obstacle event detection and feature extraction, risk quantification and level assessment, and output of warning information and countermeasures. First, a rapid detection method suited for highway scenarios is proposed based on the YOLOv5 model, enabling fast detection and classification of obstacles in

Chen, Tingting, Chen, Leilei, Yu, Wenlu, Chen, Daoxie

A Reinforcement Learning-Based Parameter Tuning Approach for a Secure Cooperative Adaptive Cruise Control System

12-08-04-0033

01/25/2025

Connected and autonomous vehicles (CAVs) rely on communication channels to improve safety and efficiency. However, this connectivity leaves them vulnerable to potential cyberattacks, such as false data injection (FDI) attacks. We can mitigate the effect of FDI attacks by designing secure control techniques. However, tuning control parameters is essential for the safety and security of such techniques, and there is no systematic approach to achieving that. In this article, our primary focus is on cooperative adaptive cruise control (CACC), a key component of CAVs. We develop a secure CACC by integrating model-based and learning-based approaches to detect and mitigate FDI attacks in real-time. We analyze the stability of the proposed resilient controller through Lyapunov stability analysis, identifying sufficient conditions for its effectiveness. We use these sufficient conditions and develop a reinforcement learning (RL)-based tuning algorithm to adjust the parameter gains of the

Javidi-Niroumand, Farahnaz, Sargolzaei, Arman

In-Vehicle Network Anomaly Detection Based on a Graph Attention Network

12-08-04-0034

01/10/2025

The increased connectivity of vehicles expands the attack surface of in-vehicle networks, enabling attackers to infiltrate through external interfaces and inject malicious traffic. These malicious flows often contain anomalous semantic information, potentially leading to misleading control instructions or erroneous decisions. While most semantic-based anomaly detection methods for in-vehicle networks focus on extracting semantic context, they often overlook interactions and associations between multiple semantics, resulting in a high false positive rate (FPR). To address these challenges, the Adaptive Structure Graph Attention Network Model (AS-GAT) is proposed for in-vehicle network anomaly detection. Our approach combines a semantic extractor with a continuously updated graph structure learning method based on attention weight similarity constraints. The semantic extractor identifies semantic features within messages, while the graph structure learning module adaptively updates the

Luo, Feng, Luo, Cheng, Wang, Jiajia, Li, Zhihao

SAE TOMORROW TODAY: Scaling Connected Vehicles with Over-The-Air Updates

1349212/18/2024

As the automotive world shifts toward fully software-defined vehicles (SDVs), many OEMs are hesitant to embrace a consumer-driven model for over-the-air (OTA) updates. Enter Sibros, a company offering holistic OTA software that enables automakers to achieve scalable, software-defined mobility. By providing AI-powered insights that deliver continuous product and service enhancements, OEMs can harness Sibros' single no-code platform to monitor, control and optimize SDVs, thus accelerating time-to-market, reducing code defects and enabling hundreds of connected vehicle use cases at global scale. This presents unique value for consumers, OEMs, commercial fleet operators, and even off-road sectors like agriculture and mining. To learn more, we sat down with Hemant Sikaria, CEO & Co-Founder, Sibros, to discuss the impact of his company's groundbreaking technology, how insurance and regulation come into play, and the importance of robust security measures to ensure the responsible growth of

Hineman, Marcie

Diagnostics of Automotive Service-Oriented Architectures with SOVD

2024-01-7036

12/13/2024

The term Software-Defined Vehicle (SDV) describes the vision of software-driven automotive development, where new features, such as improved autonomous driving, are added through software updates. Groups like SOAFEE advocate cloud-native approaches – i.e., service-oriented architectures and distributed workloads – in vehicles. However, monitoring and diagnosing such vehicle architectures remain largely unaddressed. ASAM’s SOVD API (ISO 17978) fills this gap by providing a foundation for diagnosing vehicles with service-oriented architectures and connected vehicles based on high-performance computing units (HPCs). For service-oriented architectures, aspects like the execution environment, service orchestration, functionalities, dependencies, and execution times must be diagnosable. Since SDVs depend on cloud services, diagnostic functionality must extend beyond the vehicle to include the cloud for identifying the root cause of a malfunction. Due to SDVs’ dynamic nature, vehicle systems

Boehlen, Boris, Fischer, Diana, Wang, Jue

Automotive Cybersecurity: Defend the Future of Connected Vehicles

2024-28-0123

12/05/2024

Cybersecurity, particularly in the automotive sector, is of paramount importance in today’s digital age. With the advent of connected commercial vehicles, which leverage telematics for efficient fleet management, the landscape of automotive cybersecurity is rapidly evolving. These vehicles, integral to logistics and transportation businesses, are becoming increasingly connected, thereby escalating the risks associated with cybersecurity threats. These commercial vehicles are becoming prime targets for cyber-attacks due to their connectivity and the valuable data they hold. The potential consequences of these cyber-attacks can range from data breaches to disruptions in fleet operations, and even safety risks. This paper analyses the unique challenges faced by the commercial vehicle sector, such as the need for robust telematics systems, secure communication channels, and stringent data protection measures. Case studies of notable cybersecurity incidents involving commercial vehicles are

Mahendrakar, Shrinidhi, Madarla, Manoj, Gangapuram, Siva, Dadoo, Vishal

Ethernet-Based IDS for Zonal Architecture

2024-28-0121

12/05/2024

In an era where automotive technology is rapidly advancing towards autonomy and connectivity, the significance of Ethernet in ensuring automotive cybersecurity cannot be overstated. As vehicles increasingly rely on high-speed communication networks like Ethernet, the seamless exchange of information between various vehicle components becomes paramount. This paper introduces a pioneering approach to fortifying automotive security through the development of an Ethernet-Based Intrusion Detection System (IDS) tailored for zonal architecture. Ethernet serves as the backbone for critical automotive applications such as advanced driver-assistance systems (ADAS), infotainment systems, and vehicle-to-everything (V2X) communication, necessitating high-bandwidth communication channels to support real-time data transmission. Additionally, the transition from traditional domain-based architectures to zonal architectures underscores Ethernet's role in facilitating efficient communication between

Appajosyula, kalyanSaiVitalVamsi

MAKING SOFTWARE-DEFINED VEHICLES CYBER-SECURE

24TOFHP12_03

12/01/2024

Virtualization features such as digital twins and virtual patching can accelerate development and make commercial vehicles more agile and secure. There is one sure-fire way to secure commercial vehicles from cyber-attacks. “You just remove the connectivity,” quipped Brandon Barry, CEO of Block Harbor Cybersecurity and the moderator of a panel session on “cybersecurity of virtual machines” at the SAE COMVEC 2024 conference in Schaumburg, Illinois. Obviously, that train has left the station - commercial vehicles of all types, including trains, are only becoming more automated and connected, which increases the risks for cyber-attacks. “We have very connected vehicles, so attacks can be posed not just through powertrain solutions but also through telemetry, infotainment systems connected to different applications and services, and also through cloud platforms,” said Trisha Chatterjee, current product support and data specialist for fuel cell and hydrogen technology at Accelera by Cummins.

Gehm, Ryan

Shedding Weight: Connectivity in Military-Aerospace Applications

TBMG-52211

12/01/2024

The Software-defined Vehicle: Its Current Trajectory and Execution Challenges

EPR2024027

11/25/2024

Original equipment manufacturers, Tier 1 suppliers, and the rest of the value chain, including the semiconductor industry, are reshaping their product portfolios, development processes, and business models to support this transformation to software-defined vehicles (SDVs). The focus on software is rippling out through the automotive sector, forcing the industry to rethink organization, leadership, processes, and future roadmaps. The Software-defined Vehicle: Its Current Trajectory and Execution Challenges assesses the state of SDVs and explores the potential hurdles to execution and examines the work being done in the industry. The goal is to evaluate whether the implementation of SDVs will encounter the same fate as electrification or autonomous technologies, which after some level of disillusionment, are expected to pick up momentum in a more mature way. Click here to access the full SAE EDGETM Research Report portfolio.

Goswami, Partha

Intelligent Electric Vehicles

R-58411/01/2024

Embark on a journey into the future of transportation with Intelligent Electric Vehicles. This comprehensive guide demystifies complex concepts, offering a roadmap to harness the monetization opportunities within the thriving IEV ecosystem. From management strategies to cutting-edge technology, this book provides a holistic perspective on the IEV industry. Explore real-world case studies, learn about emerging trends like cockpit intelligence and connected vehicles, and discover how to navigate the challenges and opportunities of this transformative space. Key Features: • Interdisciplinary approach: Bridges the gap between management and technology. • Real-world case studies: Grounds theoretical knowledge in practical applications. • Future-focused insights: Prepares readers for the next wave of innovations. • Monetization roadmap: Offers strategic advice for capitalizing on IEV advancements. Whether you're an automotive industry professional, technology enthusiast, or investor

Liu, Shaoshan

A Centralized Data Management Platform

TBMG-51940

11/01/2024

Many organizations have data stored in differing formats and various locations throughout the organization and often outside the organization. It is often difficult to access such data and to determine and access interconnected data and data derivatives. Developed at NASA Ames Research Center is a novel data management platform for managing interconnected data and its derivatives.

Cyber Security Challenges in V2C and in Vehicle Network

2024-28-0035

10/17/2024

Based on advanced Automotive functionality, Vehicle networks has enabled the exchange of data to multiple domains and to meet these demands, more complex software applications, some of which require service-based cloud are developed. Exposure of data creates multiple threats for attacker to tamper security and privacy. Automotive cybersecurity topic has gained momentum based on multiple gaps identified in Automotive In vehicle and around the vehicle networks. In this paper, we provide an extensive overview on V2C (Vehicle to Cloud) and In-vehicle data protection, we also highlight methods to identify threats on any vehicle network connected to V2C and identify methods to verify security functionality using Fuzz or Penetration test protocol, we have identified gaps in existing security solutions and outline possible open issues and probable solution.

Panda, Jyotiprakash, Jain, Rushabh Deepakchand

Contextual Study of Security and Privacy in V2X Communication for Architecture & Networking Products

2024-28-0038

10/17/2024

In recent times there has been an upward trend in “Connected Vehicles”, which has significantly improved not only the driving experience but also the “ownership of the car”. The use of state-of-the-art wireless technologies, such as vehicle-to-everything (V2X) connectivity, is crucial for its dependability and safety. V2X also effectively extends the information flow between the transportation ecosystem pedestrians, public infrastructure (traffic management system) and parking infrastructure, charging and fuel stations, Etc. V2X has a lot of potential to enhance traffic flow, boost traffic safety, and provide drivers and operators with new services. One of the fundamental issues is maintaining trustworthy and quick communication between cars and infrastructure. While establishing stable connectivity, reducing interference, and controlling the fluctuating quality of wireless transmissions, we have to ensure the Security and Privacy of V2I. Since there are multiple and diverse

Sundar, Shyam, Pundalik, Krantiveer, Unnikrishnan, Ushma

Enhancing Availability of Autonomous Shuttle Services: A Conceptual Approach toward Challenges and Opportunities

12-08-03-0023

10/09/2024

Autonomous vehicle technologies have become increasingly popular over the last few years. One of their most important application is autonomous shuttle buses that could radically change public transport systems. In order to enhance the availability of shuttle service, this article outlines a series of interconnected challenges and innovative solutions to optimize the operation of autonomous shuttles based on the experience within the Shuttle Modellregion Oberfranken (SMO) project. The shuttle shall be able to work in every weather condition, including the robustness of the perception algorithm. Besides, the shuttle shall react to environmental changes, interact with other traffic participants, and ensure comfortable travel for passengers and awareness of VRUs. These challenging situations shall be solved alone or with a teleoperator’s help. Our analysis considers the basic sense–plan–act architecture for autonomous driving. Critical components like object detection, pedestrian tracking

Dehghani, Ali, Salaar, Hamza, Srinivasan, Shanmuga Priya, Zhou, Lixian, Arbeiter, Georg, Lindner, Alisa, Patino-Studencki, Lucila

The Industrial Nervous System: IIoT and PLCs

TBMG-51718

10/01/2024

The industrial internet of things (IIoT) is the nervous system in manufacturing facilities worldwide, with programmable logic controllers (PLCs) serving as its vital synapses. This digital neural network is transforming isolated machines into interconnected ecosystems of unprecedented intelligence and efficiency. PLCs have evolved from simple control devices into sophisticated nodes in a vast, responsive network.

SAE TOMORROW TODAY: Scaling 2 Million Miles in Autonomous Trucking

1347709/16/2024

Get ready for COMVEC 2024 with a rewind of Episode 235! We're honored to have Continental as the Executive Leadership sponsor of COMVEC, the leading forum for global experts in the commercial vehicle industry taking place September 10-12 in Schaumburg, IL. Join us as we network, exchange ideas, and get up to date on CV research and technology. Learn more and register now. A traditional Class 8 truck is on the road for a million miles or more over its lifetime. For autonomous trucks, that number could double to two million or more -- and that requires a specialty focus on scalability and safety. Enter Continental Automotive, a multinational automotive parts manufacturer pioneering technologies and services for the sustainable and connected mobility of people and goods. Continental has partnered with Aurora to commercially scale autonomous trucking systems. Together, they recently finalized the completion of the blueprint and design of the future Aurora Driver hardware and fallback

Hineman, Marcie

Next-gen Urban Buses: Autonomy and Connectivity

EPR2024019

08/26/2024

The deployment of autonomous urban buses brings with it the hope of addressing concerns associated with safety and aging drivers. However, issues related autonomous vehicle (AV) positioning and interactions with road users pose challenges to realizing these benefits. This report covers unsettled issues and potential solutions related to the operation of autonomous urban buses, including the crucial need for all-weather localization capabilities to ensure reliable navigation in diverse environmental conditions. Additionally, minimizing the gap between AVs and platforms during designated parking requires precise localization. Next-gen Urban Buses: Autonomy and Connectivity addresses the challenge of predicting the intentions of pedestrians, vehicles, and obstacles for appropriate responses, the detection of traffic police gestures to ensure compliance with traffic signals, and the optimization of traffic performance through urban platooning—including the need for advanced communication

Hsu, Tsung-Ming

Electric Vehicles: Theory and Design

R-57007/25/2024

Dive into the future of automotive engineering with our latest book, Electric Vehicles: Theory and Design. As the world shifts towards sustainable mobility, this indispensable guide offers a deep dive into the cutting-edge world of electric vehicles (EVs). Authored by an industry expert with a background in combustion engineering, this book bridges the gap between traditional automotive knowledge and the electrified future. From the basics of EV theory to advanced design principles, this book covers every aspect of EV engineering. Whether you're an experienced EV engineer or just entering the field, you'll find invaluable insights, technical requirements, and practical recommendations to navigate the complex world of EV engineering. Forget outdated references – this book delivers up-to-date information on EVs and their essential components, including cutting-edge battery systems, propulsion technology, and intelligent subsystems. Plus, explore the latest trends in electrification

Yuan, Yiqing

SAE TOMORROW TODAY: Scaling 2 Million Miles in Autonomous Trucking

1346807/23/2024

A traditional Class 8 truck is on the road for a million miles or more over its lifetime. For autonomous trucks, that number could double to two million or more--and that requires a specialty focus on scalability and safety. Enter Continental Automotive, a multinational automotive parts manufacturer pioneering technologies and services for the sustainable and connected mobility of people and goods. Continental has partnered with Aurora to commercially scale autonomous trucking systems. Together, they recently finalized the completion of the blueprint and design of the future Aurora Driver hardware and fallback system. To learn more, we sat down with Phil McEwen, Vice President and General Manager, Commercial and Special Vehicles North America, Continental Automotive, to discuss the importance of safety in autonomous trucking technology, the partnership with Aurora, and the future of autonomy. We're also honored to have Continental as the Executive Leadership sponsor of COMVEC, the

Hineman, Marcie

Firefighting Vehicle Dispatch and Route Planning Model Based on Priority Passage Rights

12-08-02-0014

07/11/2024

Efficient fire rescue operations in urban environments are critical for saving lives and reducing property damage. By utilizing connected vehicle systems (CVS) for firefighting vehicles planning, we can reduce the response time to fires while lowering the operational costs of fire stations. This research presents an innovative nonlinear mixed-integer programming model to enhance fire rescue operations in urban settings. The model focuses on expediting the movement of firefighting vehicles within intricate traffic networks, effectively tackling the complexities associated with collaborative dispatch decisions and optimal path planning for multiple response units. This method is validated using a small-scale traffic network, providing foundational insights into parameter impacts. A case study in Sioux Falls shows its superiority over traditional “nearest dispatch” methods, optimizing both cost and response time significantly. Sensitivity analyses involving clearance speed, clearance time

Wei, Shibo, Gu, Yu, Liu, Han

Simulating Cloud Environments of Connected Vehicles for Anomaly Detection

2024-01-2996

07/02/2024

The emergence of connected vehicles is driven by increasing customer and regulatory demands. To meet these, more complex software applications, some of which require service-based cloud and edge backends, are developed. Due to the short lifespan of software, it becomes necessary to keep these cloud environments and their applications up to date with security updates and new features. However, as new behavior is introduced to the system, the high complexity and interdependencies between components can lead to unforeseen side effects in other system parts. As such, it becomes more challenging to recognize whether deviations to the intended system behavior are occurring, ultimately resulting in higher monitoring efforts and slower responses to errors. To overcome this problem, a simulation of the cloud environment running in parallel to the system is proposed. This approach enables the live comparison between simulated and real cloud behavior. Therefore, a concept is developed mirroring

Weiß, Matthias, Stümpfle, Johannes, Dettinger, Falk, Jazdi, Nasser, Weyrich, Michael

‘Attacker’ Device to Protect AVs from Cyberattacks

TBMG-50852

06/01/2024

Modern cars and autonomous vehicles (AVs) use millimeter wave (mmWave) radio frequencies to enable self-driving or assisted driving features that ensure the safety of passengers and pedestrians. This connectivity, however, can also expose them to potential cyberattacks.

Cybersecurity firm enlists AI in battle as threats increase

24AUTD05_06

05/01/2024

Following its annual report detailing the growing cybersecurity threats to vehicles, fleets, and the networks they rely on, Upstream Security announced the launch of a generative AI tool to enhance its ability to reduce the risk posted by global threats. Israel-based Upstream, which has a vehicle security operations center (VSOC) in Ann Arbor, Mich., monitors millions of connected vehicles and Internet of Things (IoT) devices and billions of API transactions monthly. Ocean AI is built into the company's detection and response platform, called M-XDR, enabling its analysts, as well as those from OEMs and IoT vendors, to efficiently detect threat patterns and automate investigations before prioritizing a response.

Clonts, Chris

Sensors — Powering the Future of Transportation

TBMG-50626

05/01/2024

The pace of innovation in automotive and heavy-duty transportation is rapidly accelerating. Manufacturers are harnessing advancements in electrification and electronification, ushering in new levels of safety, comfort, infotainment, connectivity, performance, and sustainability.

O-RAN Redefining the Future of Wireless Connectivity

TBMG-50633

05/01/2024

Research on Speed Guidance Strategy at Continuous Signal Intersection Based on Vehicle–Road Coordination Technology

12-07-04-0023

04/13/2024

With the rapid growth of automobile ownership, traffic congestion has become a major concern at intersections. In order to alleviate the blockage of intersection traffic flow caused by signals, reduce the length of vehicle congestion and waiting time, and for improving the intersection access efficiency, therefore, this article proposes a vehicle speed guidance strategy based on the intersection signal change by combining the vehicle–road cooperative technology. The randomness of vehicle traveling speed in the road is being considered. According to the vehicle traveling speed, a speed guidance model is established under different conditions. Finally, the effectiveness of the speed guidance strategy in this article is verified through experimental simulation, and the benefits of the intersection with intelligent control and traditional control are compared, and the experimental results show that the intelligent control method in this article can effectively reduce vehicle congestion and

Li, Wenli, Li, An, Ren, Yongpeng, Wang, Kan

The Design of Operational Design Condition for Automated Driving System

12-07-03-0021

04/10/2024

A new revolution has taken place in the automobile industry in recent years, intelligent and connected vehicle (ICV) [1] has achieved a higher market share in recent years and relevant technologies have been quickly developed and widely accepted, so the auto industry needs to make regulations for automated driving system (ADS) on ICVs, mainly to assure the safety of ICV. To meet the requirements above, the definition of operational design domain (ODD) [2, 3] was put forward by the Society of Automotive Engineers (SAE) and International Organization for Standardization (ISO) a few years ago. ODD defines necessary external environment conditions for the ADS to operate, but the internal status of the vehicle is also a key part of judging whether ADS can operate safely. Based on that, we propose a novel definition named operational design condition (ODC), which can supersede ODD to play a bigger role in improving regulations and standards, and promoting vehicle safety and technological

Sun, Hang, Wu, Jiajie, Zhang, Miao, Zhang, Hang

Multicast Transmission in DDS Based on the Client-Server Discovery Model

2024-01-2392

04/09/2024

The functions of modern intelligent connected vehicles are becoming increasingly complex and diverse, and software plays an important role in these advanced features. In order to decouple the software and the hardware and improve the portability and reusability of code, Service-Oriented Architecture (SOA) has been introduced into the automotive industry. Data Distribution Service (DDS) is a widely used communication middleware which provides APIs for service-oriented Remote Procedure Call (RPC) and Service-Oriented Communications (SOC). By using DDS, application developers can flexibly define the data format according to their needs and transfer them more conveniently by publishing and subscribing to the corresponding topic. However, current open source DDS protocols all use unicast communication during the transmission of user data. When there are multiple data readers subscribing to the same topic, the data writer needs to send a unicast message to each data reader individually

Li, Binqi, Zhu, Yuan, Lu, Ke, Zhong, Xu, Sun, Zhipeng

Dynamic Speed Limit for Self-Identifying Platoons of Mixed Vehicular Traffic on Freeways under Connected Environment

2024-01-1996

04/09/2024

About 200,000 miles (~8 times around the earth) comprise the National Highway System, which carries most of the highway freight and traffic in the U.S. The core of the nation’s highway system is the 48,254 miles of Interstate Highways, which comprise just over 1 percent of highway mileage but carry over 25% of all highway traffic. Americans traveled a total of 5.3 trillion miles by all transportation modes in 2016, an average of 16,400 miles per person. About 80 percent was by automobile, truck, or motorcycle. Due to a high contribution to mobility and energy consumption, freeways and highway have been attracting researchers to move more vehicles faster and in energy-efficient manner. The research interest in motorways and highways has been driven by their significant impact on transportation efficiency and energy consumption, as they facilitate the movement of vehicles at higher speeds while optimizing energy usage. This entails the development of enhanced control techniques capable

Mittal, Archak

Front Zone Control Unit for Propulsion and Chassis Domains in a Zonal E/E Architecture – System Engineering Approach to Architecture Design

2024-01-2500

04/09/2024

The modern automotive industry field is in the middle of a major transformation of the Electric/Electronics (E/E) system design, to meet the future mobility trends driven by Autonomy, Electrification and expanded Connectivity. For these reasons, the ongoing industry trend is to move to more centralized E/E architectures by combining and integrating sub-systems and controllers, from either a functional domain standpoint (horizontal integration, or “cross-domain controllers”) or a geographical zone standpoint (vertical integration, or “central brain with zones”), with the objective to optimize cost, weight, power distribution, provide enhanced security and versatility. This is because electrification, autonomy and connectivity features are significantly increasing the demand for data processing bandwidth, network throughput, intelligent power distribution and wiring harness capabilities for additional sensors/actuators. The evolution to a Centralized Architecture is made possible with

Tavella, Domenico, Muhialdin, Ali, Garante, Enrico, Peciarolo, Alessandro

Eco-Routing Algorithm for Energy Savings in Connected Vehicles Using Commercial Navigation Information

2024-01-2605

04/09/2024

Vehicle-to-everything (V2X) communication, primarily designed for communication between vehicles and other entities for safety applications, is now being studied for its potential to improve vehicle energy efficiency. In previous work, a 20% reduction in energy consumption was demonstrated on a 2017 Prius Prime using V2X-enabled algorithms. A subsequent phase of the work is targeting an ambitious 30% reduction in energy consumption compared to a baseline. In this paper, we present the Eco-routing algorithm, which is key to achieving these savings. The algorithm identifies the most energy-efficient route between an Origin-Destination (O-D) pair by leveraging information accessible through commercially available Application Programming Interfaces (APIs). This algorithm is evaluated both virtually and experimentally through simulations and dynamometer tests, respectively, and is shown to reduce vehicle energy consumption by 10-15% compared to the baseline over real-world routes. This

Rajakumar Deshpande, Shreshta, Bhagdikar, Piyush, Gankov, Stanislav, Rengarajan, Sankar, Sarlashkar, Jayant, Hotz, Scott, Bhattacharjya, Shuvodeep

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