Browse Topic: Vehicle to everything (V2X)

Items (881)
The SAE J3216 standard defines Cooperative Driving Automation (CDA), which has received increasing attention in recent years as an umbrella framework encompassing a wide range of automated vehicle applications enabled by Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) technologies. Despite this growing interest, limited research has investigated the impact of Cellular Vehicle-to-Everything (C-V2X) on CDA applications, particularly with respect to agreement-seeking operations. This work presents a hardware-in-the-loop (HIL) experimental study designed to evaluate an Argonne National Laboratory designed CDA controller under different message configurations and varying C-V2X PC5 radio transmission frequencies. A three-vehicle car-following scenario was implemented in the Argonne-developed Roadrunner simulator, incorporating CDA agreement-seeking logic, vehicle powertrain models, and V2V communication modules. CDA messages were exchanged through two physical C-V2X PC5 radios
Zhan, LuDi Russo, MiriamDas, DebashisStutenberg, KevinMisra, PriyashJeong, JongryeolHyeon, Eunjeong
The advancement of Cooperative Adaptive Cruise Control (CACC) technology enables vehicle platooning on public roads, offering significant potential to enhance urban mobility, driving safety, and energy efficiency. Among various applications, truck platooning has become a promising strategy to increase highway flow rates by reducing vehicle headways, improving coordination, and optimizing space utilization. This paper presents a quantitative assessment of a CACC-based truck platooning system, focusing on its effectiveness in enhancing highway mobility under varying traffic conditions. A statistical regression model is developed and calibrated using simulations of real-world highway networks to identify key influencing factors and evaluate the resulting improvements in traffic flow. The analysis considers five primary variables: desired platoon speed, platoon size, space headway, percentage of platooning trucks, and non-platoon traffic flow. The study systematically examines the impact
Karbasi, Amir HosseinWang, JinghuiYang, Hao
This paper presents the integration and validation of Adaptive Cruise Control (ACC) algorithms on a student-team-developed vehicle as part of the U.S. Department of Energy EcoCAR EV Challenge. The competition provided each team with a 2023 Cadillac Lyriq, which was modified to an all-wheel-drive configuration and re-architected to support the development of SAE Level 3 autonomous features including Adaptive Cruise Control (ACC), Automatic Intersection Navigation (AIN), Lane Centering Control (LCC), and Automatic Parking (AP). The scope of this paper, however, is limited to the development, implementation, and validation of a Level 2 longitudinal ADAS function. Higher-level automation requirements such as Operational Design Domain (ODD) definition and Driver Monitoring System (DMS) enforcement are addressed at the vehicle architecture and competition level but are not the focus of this work. The major contribution of this work is the development of ACC with Vehicle-to-Infrastructure
Gupta, IshikaEstrada, TylerTambolkar, PoojaMidlam-Mohler, Shawn
Cooperative Driving Automation (CDA) has emerged as an active research area in recent years, categorized into four classes of operations with varying levels of cooperation as defined in the SAE J3216 standard. Among these, Class C CDA, referred to as Agreement-Seeking Cooperation (ASC), has received limited attention in literature. Unlike Cooperative Adaptive Cruise Control (CACC), which typically engages when lead vehicles are identified as cooperative and disagree under manual override or safety-critical conditions, ASC requires agents to exchange messages interactively to reach consensus on a proposed plan and its implementation. This necessitates more sophisticated communication and control designs, which in turn influences customized ASC efficiency. Previous work has examined, through simulation, the impact of three key parameters on ASC system performance: CDA message transmission frequency, Packet Drop Ratio (PDR), and Cooperation Duration Length (CDL). In this paper, we extend
Zhan, LuDi Russo, MiriamDas, DebashisStutenberg, KevinMisra, PriyashJeong, JongryeolHyeon, Eunjeong
Modern vehicles require sophisticated, secure communication systems to handle the growing complexity of automotive technology. As in-vehicle networks become more integrated with external wireless services, they face increasing cybersecurity vulnerabilities. This paper introduces a specialized Proxy based security architecture designed specifically for Internet Protocol (IP) based communication within vehicles. The framework utilizes proxy servers as security gatekeepers that mediate data exchanges between Electronic Control Units (ECUs) and outside networks. At its foundation, this architecture implements comprehensive traffic management capabilities including filtering, validation, and encryption to ensure only legitimate data traverses the vehicle's internal systems. By embedding proxies within the automotive middleware layer, the framework enables advanced protective measures such as intrusion detection systems, granular access controls, and protected over-the-air (OTA) update
M, ArvindPraneetha, Appana DurgaRemalli, Ravi Teja
This document provides vehicle-level data collection, data analysis, and data verification procedures that may be used to verify that an instrument under test (IUT) satisfies the vehicle-level requirements specified in SAE J3161/1. For the purposes of this report, “vehicle-level requirements” primarily consist of those requirements which can be verified external to the vehicle. The IUT for these procedures is a configured LTE-V2X vehicle-to-vehicle (V2V) device as defined in SAE J3161/1 and is installed on a vehicle of class 2, 3, 4, or 5. While the IUT is conceptually separated from the vehicle it is installed on, the tests outlined in this document are primarily vehicle level, so the terms “vehicle” and “IUT” can generally be considered interchangeable. Additionally, non-vehicle-level complementary tests, not included in this document, are required to verify that the entire set of requirements specified in SAE J3161/1 is satisfied. This document also includes a Traceability Matrix to
C-V2X Technical Committee
This SAE Aerospace Recommended Practice (ARP) defines lightning strike zones and provides guidelines for locating them on particular aircraft, together with examples. The zone definitions and location guidelines described herein are applicable to Parts 23, 25, 27, and 29 aircraft. The zone location guidelines and examples are representative of in-flight lightning exposures.
AE-2 Lightning Committee
As vehicles transform into complex cyber-physical systems within Intelligent Transportation Systems (ITS), automotive cybersecurity has become a foundational pillar in securing safe, reliable, and trustworthy transportation. This paper examines cybersecurity challenges in connected and autonomous vehicles (CAVs), focusing on Vehicle-to-Everything (V2X) communications technologies, including Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), and Vehicle-to-Pedestrian (V2P), and critical systems like electronic control units (ECUs), battery management units (BMUs), and sensor fusion modules. Key vulnerabilities, such as remote hacking, denial-of-service (DoS) attacks, malware injection, and data breaches, threaten vehicle functionality, passenger safety, and privacy. Key protection mechanisms, including encryption, intrusion detection systems (IDS), cryptographic protocols, secure over-the-air (OTA) updates, and Advanced Artificial Intelligence (AI) and Machine Learning (ML
Kumar, OmKumar, RajivSankar M, GopiHaregaonkar, Rushikesh Sambhaji
State Transport Units (STUs) are increasingly using electric buses (EVs) as a result of India's quick shift to sustainable mobility. Although there are many operational and environmental benefits to this development, like lower fuel prices, fewer greenhouse gas emissions, and quieter urban transportation, there are also serious cybersecurity dangers. The attack surface for potential cyber threats is expanded by the integration of connected technologies, such as cloud-based fleet management, real-time monitoring, and vehicle telematics. Although these systems make fleet operations smarter and more efficient, they are intrinsically susceptible to remote manipulation, data breaches, and unwanted access. This study looks on cybersecurity flaws unique to connected passenger electric vehicles (EVs) that run on India's public transit system. Electric vehicle supply equipment (EVSE), telematics control units (TCUs), over-the-air (OTA) update systems, and in-car networks (such as the Controller
Mokhare, Devendra Ashok
This paper presents a comprehensive testing framework and safety evaluation for Vehicle-to-Vehicle (V2V) charging systems, incorporating advanced theoretical modeling and experimental validation of a modern, integrated 3-in-1 combo unit (PDU, DCDC, OBC). The proliferation of electric vehicles has necessitated the development of resilient and flexible charging solutions, with V2V technology emerging as a critical decentralized infrastructure component. This study establishes a rigorous mathematical framework for power flow analysis, develops novel safety protocols based on IEC 61508 and ISO 26262 functional safety standards, and presents comprehensive experimental validation across 47 test scenarios. The framework encompasses five primary test categories: functional performance validation, power conversion efficiency optimization, electromagnetic compatibility (EMC) assessment, thermal management evaluation, and comprehensive fault-injection testing including Byzantine fault scenarios
Uthaman, SreekumarMulay, Abhijit BNikam, Sandip B.
The automotive industry is rapidly extending the capabilities of automated systems by incorporating connectivity and cooperation features that enable real-time information exchange between vehicles and road infrastructure. Within the Connected, Cooperative, and Automated Mobility (CCAM) framework, Vehicle-to-Vehicle (V2V) communication is expected to play a key role in improving road safety, traffic efficiency, and driving comfort. This work addresses a practical implementation of the standardized Manoeuvre Coordination Messages (MCMs), as defined in the ongoing ETSI standard (ETSI TS 103 561). The proposed approach is demonstrated through a cooperative cut-in use case in which two vehicles negotiate a lane change manoeuvre. In the considered scenario, the ego vehicle, driven by a Highway Pilot (HWP) system, receives the intention to cut-in from a neighbouring cooperative vehicle through an MCM. In response, the ego vehicle adapts its behaviour by decelerating to generate a safe
Leiva Ricart, GiselaDomingo Mateu, Bernat
The modern vehicle is no longer a mechanical appliance—it has transformed into a software-defined cyber-physical system, integrating OTA updates, cloud-connected diagnostics, V2X services, and telematics-driven personalization. While this evolution promises unprecedented value in consumer experience and fleet operations, it also surfaces a dramatically expanded and evolving attack perimeter, especially across safety-critical ECUs and communication buses. Cyber vulnerabilities have shifted from isolated IT threats to real-time, embedded exploits. Controller area network (CAN), the backbone of vehicle bus systems, remains intrinsically insecure due to its lack of authentication and encryption, making it highly susceptible to message injection and denial-of-service by low-cost tools. Similarly, OEM implementations of BLE-based passive entry systems have proven vulnerable to replay and spoofing attacks with minimal hardware. In the Indian context, the transition to connected mobility is
Shah, RavindraAwasthi, Vibhu VaibhavKarle, Ujjwala
Highway Pilot (HWP) systems, classified as SAE Level 3 Automated Driving Systems (ADS), represent a potential advancement for safer and more efficient highway drives. In this work, the development of a connected HWP prototype is presented. The HWP system is deployed in a real test vehicle and designed to operate autonomously in highway environments. The implementation presented in this paper covers the complete setup of the vehicle platform, including sensor selection and placement, hardware integration and communication interfaces for both autonomous functionality and Vehicle-to-Everything (V2X) connectivity. The software architecture follows a modular design, composed of modules for perception, decision-making and motion control to operate in real-time. The prototype integrates Vehicle-to-Vehicle (V2V) communication, such as Cooperative Awareness Messages (CAM), to enhance situational awareness and improve the overall system behaviour. The modular structure allows new functionalities
Domingo Mateu, BernatLeiva Ricart, GiselaFacerias Pelegri, MarcPerez, Marc
The rapid development of science and technology has impacted on the human lifestyle. The automotive industry plays a crucial role as travel is an integral part of human lifestyle. This indeed has increased the need and demand for automotive domain to step ahead with technology and innovations. Especially, related to ADAS features and AI/ML based algorithms to provide comfort, safety, and many other factors for the consumers. The busy life of human beings has shown an increased rate of many health-related issues like stress, anxiety, heart attacks, blood pressure and so on. The existing system in vehicles detects health emergency and triggers SOS to the emergency service center. However, several catastrophic events occur due to delayed information, thus there is a need for a proactive solution that combines technology and human safety. In this work, we have investigated the different methods which detect the health issues of occupants in a vehicle by monitoring their stress level, heart
Eswarappa, AshaNagaraj, ChaitraMudassir, Syed
Effective communication is the key for bringing harmony - be it the communication between humans and humans, or communication between machine and machine. Today’s car is a sophisticated gadget, equipped with the best of technologies running using millions of lines of codes of software. The effective use of these technologies involve communication between car to car and car to infrastructure using Dedicated Short-Range Communication (DSRC), C-V2X (Cellular Vehicle-to-Everything). It is pertinent that any communication using the internet needs to be digitally secure and that the systems are designed to mitigate the perceived threats. The methods used for ensuring cyber safety of automobiles need to be verified before the end product is put to use. Automotive Industry Standards AIS-189 and AIS-190 have been formulated to provide a harmonized verification framework. Both the vehicle manufacturer and the test agency need to equip themselves with necessary skills and tools to ensure
Nayak, PratikTandon, VikramBadusha, AkbarDesai, ManojSathianesan, Rejin
This paper is a new approach to improve road safety and traffic flow by combining vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. The Study is focused on a system that connects vehicles with each other and with traffic light to share real-time data about speed and position. This work is aimed to discuss the methodology adopted for developing a system which predicts and advises the optimal speed for vehicles approaching an intersection. Inspired by the Green Light Optimized Speed Advisory (GLOSA) , the proposed system is designed to help drivers approach traffic signals at speeds that minimize unnecessary stops, reduce delays, and improve traffic efficiency. This paper contains the approach taken, the decision-making algorithm, and the simulation framework built in MATLAB/Simulink to validate the concept under real traffic conditions. Simulation results are presented to demonstrate how the system generates speed recommendations based on vehicle parameters
Pinto, Colin AubreyShah, RavindraKarle, Ujjwala
This paper presents a comprehensive technical review of the Software-Defined Vehicle (SDV), a paradigm that is fundamentally reshaping the automotive industry. We analyze the architectural evolution from distributed Electronic Control Units (ECUs) to centralized zonal compute platforms, examining the critical role of Service-Oriented Architectures (SOA), the AUTOSAR standard, and virtualization technologies in enabling this shift. A comparative analysis of leading High-Performance Computing (HPC) platforms, including NVIDIA DRIVE, Tesla FSD, and Qualcomm Snapdragon Ride, is conducted to evaluate the silicon foundation of the SDV. The paper further investigates key enabling technologies such as Over- the-Air (OTA) updates, Digital Twins, and the integration of Artificial Intelligence (AI) for applications ranging from predictive maintenance to software-defined battery management. We scrutinize the competing V2X communication standards (DSRC vs. C-V2X) and address the paramount
Ahmad, AqueelHemanth, KhimavathKumar, OmKumar, RajivHaregaonkar, Rushikesh Sambhaji
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 publickey 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
This paper presents a dynamic switching control strategy for vehicle platoons to address communication delays and packet dropouts in connected and autonomous vehicle systems. The proposed strategy combines adaptive cruise control (ACC), cooperative adaptive cruise control (CACC), and a Kalman filter to compensate for time-varying delays, while employing an equidistant spacing policy to support reliable information flow within the platoon. A switching mechanism based on an acceleration threshold enables seamless transition between ACC, which depends on onboard sensor data, and CACC, which relies on vehicle-to-vehicle (V2V) communication. This design reduces dependence on V2V communication, thereby lowering the risk of packet dropouts and improving platoon stability. The control architecture adopts a hierarchical structure: an upper-level sliding mode controller generates desired acceleration commands, and a lower-level PID controller converts them into throttle and brake actions. A
Pan, DengYao, ZhiyongWang, ChangJi, JieZhang, Bohan
With the rapid development of automobile industrialization, the traffic environment is becoming increasingly complex, traffic congestion and road accidents are becoming critical, and the importance of Intelligent Transportation System (ITS) is increasingly prominent. In our research, for the problem of cooperative control of heterogeneous intelligent connected vehicle platoons under ITS considering communication delay. The proposed method integrates the nonlinear Intelligent Driver Model (IDM) and a spacing compensation mechanism, aiming to ensure that the platoon maintains structural stability in the presence of communication disturbances, while also enhancing the comfort and safety of following vehicles. Firstly, construct heterogeneous vehicle platoon system based on the third-order vehicle dynamics model, Predecessor-Leader-Following (PLF) communication topology, and the fixed time-distance strategy, while a nonlinear distributed controller integrating the IDM following behavior
Ye, XinKang, Zhongping
The efficient tracking and management of goods within light commercial vehicles (LCVs) is crucial for various industries, particularly craftsmen and parcel delivery services. This article explores the integration of artificial intelligence (AI) and sensor technologies to enhance item tracking and optimize logistical operations in LCVs. Two technological approaches are examined: a Bluetooth-based tracking system and a camera-based parcel identification framework. The Bluetooth-based solution is designed primarily for craftsmen. It employs Bluetooth tags, vehicle connectivity gateways (VCGs), and a centralized server to provide real-time inventory monitoring and prevent tool misplacement. The camera-based system is aimed at parcel carriers. It utilizes AI-driven object detection and pose estimation to localize and identify parcels within the vehicle. Experimental evaluations show that Bluetooth tracking ensures reliability in tool management and the AI-based vision system holds promise
Aslandere, TurgayLens, MathijsKirchhof, Jörg ChristianRobberechts, PieterGrein, MarcelMeert, WannesVandewalle, PatrickDavis, JesseRumpe, BernhardGoedemé, Toon
Vehicle trajectories encapsulate critical spatial-temporal information essential for traffic state estimation, congestion analysis, and operational parameter optimization. In a Vehicle-to-Infrastructure (V2I) environment, connected automated vehicles (CAVs) not only continuously transmit their own real-time trajectory data but also utilize onboard sensors to perceive and estimate the motion states of surrounding regular vehicles (RVs) within a defined communication range. These multi-source data streams, when integrated with fixed infrastructure-based detectors such as speed cameras at intersections, create a robust foundation for reconstructing full-sample vehicle trajectories, thereby addressing data sparsity issues caused by incomplete CAV penetration. Building upon classical car-following (CF) theory, this study introduces a novel trajectory reconstruction framework that fuses CAV-generated trajectories and infrastructure-based speed detection data. The proposed method specifically
Bai, WeiFu, ChengxinYao, Zhihong
V2X technology enables vehicles to obtain a wider range of information and is less susceptible to environmental factors such as weather, which can to some extent compensate for the insufficient range of visibility of onboard sensors such as radar and cameras. Based on the advantages of V2X technology, some autonomous driving functions may be achieved by integrating V2X technology with vehicular intelligence technology or only by V2X technology. How to effectively test and evaluate autonomous driving functions based on V2X technology has attracted widespread attention. This paper studies the track test method of autonomous driving functions based on V2X technology from the perspective of safety. The research results of this paper can provide reference and guidance for automotive industry testing institutions to carry out test of autonomous driving functions based on V2X technology.
Li, ChunSun, HangZheng, ChangZhu, Pingqing
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, JiantongZhu, ChunhongRen, Xiaolong
This study investigates urban traffic congestion optimisation strategies based on V2X technology. V2X technology (Vehicles and Internet of Everything) aims to alleviate urban traffic congestion, improve access efficiency, and reduce tailpipe emissions through real-time collection and fusion of traffic data to optimise traffic signal control and path planning. The efficacy of the optimisation strategies under different V2X penetration rates is evaluated by conducting multi-factor orthogonal experiments in different typical congestion scenarios. The experimental results show that the V2X-based signal optimisation, path induction, and event response combination strategies exhibit significant optimisation effects in all three scenarios: node bottleneck, corridor congestion, and event induction. Under the condition of 100% penetration, the combined strategy reduces delay by 41.9% in the node bottleneck scenario, improves accessibility by 28.1% in the corridor congestion scenario, and
Xi, ChaohuLi, JiashengQu, FengzhenLiu, HongjunLiu, XiaoruiWang, Chunpeng
Ensuring secure and ultra-reliable low-latency communication (URLLC) is critical for Vehicle-to-Everything (V2X) systems, which form the backbone of autonomous transportation. This paper presents a theoretical framework for designing secure communication protocols tailored for V2X systems with stringent latency and reliability requirements. The proposed framework incorporates dynamic message prioritization, adaptive encryption, and lightweight authentication to address the unique challenges of V2X networks. The study provides mathematical models to predict latency and security performance under varying network conditions, with a focus on scalability and efficiency. This work aims to contribute a foundational approach for future advancements in URLLC protocols in autonomous vehicle ecosystems.
Imran, Shaik Moinuddin
A road simulator reproduction method was developed to reproduce the off-road conditions of utility vehicles in a laboratory setting. Off-road running behavior can be reproduced by considering the effects of inertial forces from jump landings owing to uneven terrain and slow-speed navigation. However, extremely low-frequency components and behaviors, including inertial forces from jumps, vehicle acceleration and deceleration, are difficult to reproduce with a normal road simulator in the limited test space of a laboratory. Therefore, it is common practice to intentionally remove input components below 1 Hz. Alternatively, inertial forces can be reproduced by adding a restraining device to the sprung mass of the vehicle along the wheel-axle inputs. Therefore, the former method excludes extremely low-frequency components, whereas the effects between actuators, which increase the test complexity and time required, should be canceled in the latter method. Furthermore, the restraining device
Miyasaka, TakahiroShimizu, Ryota
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, AdrianoBerzi, LorenzoFabbri, MarcoFranci, MichaelGulino, Michelangelo SantoPugi, LucaOrtenzi, FernandoVitiello, Francesco
This SAE Standard describes classes of Aftermarket V2X Devices (AVDs) intended to support particular services, provides their respective requirements (including RF performance requirements), and specifies their radio profiles. This document is targeted to enable near- and long-term deployments by supporting different classes of AVDs that could interact with other onboard units (OBUs) and roadside units (RSUs). Users of this document include manufacturers of vehicles and micro-mobility conveyances, developers of hardware and applications, as well as those interested in LTE-V2X system architecture, testing, and certification.
C-V2X Technical Committee
In the context of intelligent transportation systems and applications such as autonomous driving, it is essential to predict a vehicle’s immediate future states to enable precise and timely prediction of vehicles’ movements. This article proposes a hybrid short-term kinematic vehicle prediction framework that integrates a novel object detection model, You Only Look Once version 11 (YOLOv11), with an unscented Kalman filter (UKF), a reliable state estimation technique. This study provides a unique method for real-time detection of vehicles in traffic scenes, tracking and predicting their short-term kinematics. Locating the vehicle accurately and classifying it in a range of dynamic scenarios is achievable by the enhanced detection capabilities of YOLOv11. These detections are used as inputs by the UKF to estimate and predict the future positions of the vehicles while considering measurement noise and dynamic model errors. The focus of this work is on individual vehicle motion prediction
Pahal, SudeshNandal, Priyanka
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, TianfangZhang, XingHuiChen, LiangHuang, ZhichenNi, Dong
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, HongHou, De-Zao
Vehicle-to-whatever communication technologies continue to be put through their paces around the world. To point at just one example of the continued evolution of V2X technologies, let's take a quick visit to Japan and the 2025 JSAE Annual Spring Congress this May. That's where Toyota and Eye-Net Mobile Ltd., a subsidiary of Foresight Autonomous Holdings Ltd., presented a research paper on using vehicle-to-network technology to enhance ADAS systems by connecting to smartphones in the environment to address the inherent limitations of in-vehicle sensors. Titled, “Feasibility Study of a Hazard Avoidance Brake Control System Using V2N Technology,” the paper examined how smartphones could act as external sensors that could connect to an onboard ADAS system using vehicle-to-network (V2N) communications. The main purpose of these signals would be for enhanced hazard detection, Toyota said, adding that some of the top issues addressed in the paper were “communication latency, tracking
Blanco, Sebastian
Perception is a key component of automated vehicles (AVs). However, sensors mounted to the AVs often encounter blind spots due to obstructions from other vehicles, infrastructure, or objects in the surrounding area. While recent advancements in planning and control algorithms help AVs react to sudden object appearances from blind spots at low speeds and less complex scenarios, challenges remain at high speeds and complex intersections. Vehicle-to-infrastructure (V2I) technology promises to enhance scene representation for connected and automated vehicles (CAVs) in complex intersections, providing sufficient time and distance to react to adversary vehicles violating traffic rules. Most existing methods for infrastructure-based vehicle detection and tracking rely on LIDAR, RADAR, or sensor fusion methods, such as LIDAR–camera and RADAR–camera. Although LIDAR and RADAR provide accurate spatial information, the sparsity of point cloud data limits their ability to capture detailed object
Saravanan, Nithish KumarJammula, Varun ChandraYang, YezhouWishart, JeffreyZhao, Junfeng
Ongoing research and development in the field of electric vehicles (EVs) have resulted in a continuous expansion of their range. Additionally, advancements in vehicle connectivity have created new opportunities for intelligent driving assistance and energy optimization, particularly through the use of cloud data. However, the integration of eco-driving assistance with numerical optimization of speed trajectories remains challenging due to the high computational demands of these methods. To address this challenge and make such a system feasible for integration into vehicle systems, the computational effort required for an optimized driving trajectory must be minimized. This paper presents a method to accelerate speed trajectory optimization using pre-calculated energy and time consumption maps. For this purpose, a dynamic discretization of the anticipated driving profile is applied. Initial results show a substantial reduction in computation time, varying with different scenarios
Schilling Johnson, ReneHenke, Markus
The U-Shift IV represents the latest evolution in modular urban mobility solutions, offering significant advancements over its predecessors. This innovative vehicle concept introduces a distinct separation between the drive module, known as the driveboard, and the transport capsules. The driveboard contains all the necessary components for autonomous driving, allowing it to operate independently. This separation not only enables versatile applications - such as easily swapping capsules for passenger or goods transportation - but also significantly improves the utilization of the driveboard. By allowing a single driveboard to be paired with different capsules, operational efficiency is maximized, enabling continuous deployment of driveboards while the individual capsules are in use. The primary focus of U-Shift IV was to obtain a permit for operating at the Federal Garden Show 2023. To achieve this goal, we built the vehicle around the specific requirements for semi-public road
Pohl, EricScheibe, SebastianMünster, MarcoOsebek, ManuelKopp, GerhardSiefkes, Tjark
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, MaximilianMeyer, FelixHenze, Roman
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 RasheedHanif, AtharAhmed, Qadeer
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, YuanyuanWang, KanLiu, WeizhenLi, Wenli
Letter from the Guest Editors
Liang, CiTörngren, Martin
Coyner, KelleyBittner, Jason
This document describes machine-to-machine (M2M)1 communication to enable cooperation between two or more traffic participants or CDA devices hosted or controlled by said traffic participants. The cooperation supports or enables performance of the dynamic driving task (DDT) for a subject vehicle equipped with an engaged driving automation system feature and a CDA device. Other participants may include other vehicles with driving automation feature(s) engaged, shared road users (e.g., drivers of conventional vehicles or pedestrians or cyclists carrying compatible personal devices), or compatible road operator devices (e.g., those used by personnel who maintain or operate traffic signals or work zones). Cooperative driving automation (CDA) aims to improve the safety and flow of traffic and/or facilitate road operations by supporting the safer and more efficient movement of multiple vehicles in proximity to one another. This is accomplished, for example, by sharing information that can be
Cooperative Driving Automation(CDA) Committee
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 MuktadiHasan, Samiul
The proliferation of the electric vehicle (EVs) in the US market led to an increase in the average vehicle weight due to the assembly of the larger high-voltage (HV) batteries. To comply with this weight increase and to meet stringent US regulations and Consumer Ratings requirements, Vehicle front-end rigidity (stiffness) has increased substantially. This increased stiffness in the larger vehicles (Large EV pickups/SUVs) may have a significant impact during collision with smaller vehicles. To address this issue, it is necessary to consider adopting a vehicle compatibility test like Euro NCAP MPDB (European New Car Assessment Program Moving Progressive Deformable Barrier) for the North American market as well. This study examines the influence of mass across vehicle classes and compares the structural variations for each impact class. The Euro NCAP MPDB (European New Car Assessment Program Moving Progressive Deformable Barrier) protocol referenced for this analysis. Our evaluation
Kusnoorkar, HarshaKoraddi, BasavarajGuerrero, MichaelSripada, Venu VinodTangirala, Ravi
Platooning occurs when vehicles travel closely together to benefit from multi-vehicle movement, increased road capacity, and reduced fuel consumption. This study focused on reducing energy consumption under different driving scenarios and road conditions. To quantify the energy consumption, we first consider dynamic events that can affect driving, such as braking and sudden acceleration. In our experiments, we focused on modeling and analyzing the power consumption of autonomous platoons in a simulated environment, the main goal of which was to develop a clear understanding of the different driving and road factors influencing power consumption and to highlight key parameters. The key elements that influence the energy consumption can be identified by simulating multiple driving scenarios under different road conditions. The initial findings from the simulations suggest that by efficiently utilizing the inter-vehicle distances and keeping the vehicle movements concurrent, the power
Khalid, Muhammad ZaeemAzim, AkramulRahman, Taufiq
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, YanhuaLuo, FengRen, YiHou, Yongping
Vehicle-to-Infrastructure (V2I) cooperation has emerged as a fundamental technology to overcome the limitations of the individual ego-vehicle perception. Onboard perception is limited by the lack of information for understanding the environment, the lack of anticipation, the drop of performance due to occlusions and the physical limitations of embedded sensors. The perception of V2I in a cooperative manner improves the perception range of the ego vehicle by receiving information from the infrastructure that has another point of view, mounted with sensors, such as camera and LiDAR. This technical paper presents a perception pipeline developed for the infrastructure based on images with multiple viewpoints. It is designed to be scalable and has five main components: the image acquisition for the modification of camera settings and to get the pixel data, the object detection for fast and accurate detection of four wheels, two wheels and pedestrians, the data fusion module for robust
Picard, QuentinMorice, MaloFadili, MaryemPechberti, Steve
Driving safely through urban intersections is quite challenging for self-driving vehicles due to complicated road geometries and the highly dynamic maneuvers of oncoming traffic, which can cause a high risk of collisions. Traditional onboard sensors like cameras, radar, and lidar give limited visibility in this environment. To overcome these limitations, this paper explores implementing a collision avoidance system at urban intersections utilizing vehicle-to-everything (V2X) communication. The system leverages V2X map data to identify warning zones and uses vehicle-to-vehicle (V2V) communication to estimate the maneuver types and paths of approaching vehicles. The system assesses collision risk by calculating the intersection points of predicted paths for the ego vehicle and oncoming traffic. Depending on the level of collision risk, the system generates a collision warning signal to the driver or activates emergency braking when necessary to prevent accidents. We implement the system
Park, Seo-WookSuresh, RaynierAiluri, Anusha
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