Browse Topic: Data exchange

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Research on Urban Traffic Congestion Optimisation Strategies Based on V2X Technology2025-99-0117To be published on 11/11/2025
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, Chaohu, Li, Jiasheng, Qu, Fengzhen, Liu, Hongjun, Liu, Xiaorui, Wang, Chunpeng
Multi-Objective Optimization-Based Vehicle-Cargo Matching and Route Collaborative Decision Modeling2025-99-0119To be published on 11/11/2025
Aiming at the problem of efficiency loss caused by the independent optimization of traditional vehicle - cargo matching and route planning, this paper proposes a spatio - temporal collaborative optimization model. By constructing three - dimensional decision variables to describe the “vehicle - cargo - route” mapping relationship, a multi - objective mixed - integer programming model considering transportation costs, time - window constraints, and carbon emissions is established. An improved NSGA - II algorithm is designed to solve the Pareto optimal solution set, and the TOPSIS method is combined to achieve scheme optimization. Experiments show that the collaborative optimization model reduces the comprehensive cost by an average of 12.7% and the vehicle empty - running rate by 18.4% compared with the traditional two - stage method.
Yang, Meiru, Liu, Jian
Intelligent Decision-Making and Trajectory Planning of Semi-Trailer Trains Under Multi-Vehicle Interference2025-99-0125To be published on 11/11/2025
Semi-trailer trains are the main force of highway freight. In a complex environment with multiple vehicles, accidents are easily caused by complex structures and driver operation problems. Intelligent technology is urgently needed to improve safety. In view of the shortcomings of existing research on its dedicated models and algorithms, this paper studies the intelligent decision-making and trajectory planning of semi-trailer trains under multiple vehicles. A local trajectory planning method based on global path planning and Frenet coordinate decoupling based on the improved A* algorithm is proposed. The smooth weight transition function and B-spline curve are introduced to optimize the global path. The polynomial function is combined with the acceleration rate to optimize the local trajectory. TruckSim, Prescan and Simulink are used to build a joint simulation platform for multi-condition verification. The simulation results show that the search efficiency of the improved A* algorithm
Song, Zeyuan, Geng, Shuai
Research on Ship Network Security Situation Awareness and Defense Mechanism Based on Improved Spatiotemporal Attention and Deep Reinforcement Learning2025-99-0126To be published on 11/11/2025
With the development of ship intelligence, network security threats are increasing day by day. This paper proposes a ship network security situation awareness algorithm based on an improved spatiotemporal attention mechanism, and constructs a supporting defense mechanism. The algorithm accurately captures changes in network security situation through dynamic weight allocation and multi-scale feature extraction. In the experimental simulation, OMNeT++ is combined with SUMO to build a ship network simulation environment, and Maritime - CPS - Dataset and other data sets are used for testing. The algorithm in this paper is compared with ARIMA, LSTM, GRU and other algorithms. The results show that in terms of situation awareness accuracy, the algorithm in this paper reaches 95.6%, which is 27.8% higher than ARIMA, 12.3% higher than LSTM, and 10.1% higher than GRU respectively; the average response time of the defense mechanism is shortened to 2.3 seconds, which is 40% faster than the
Kong, Zeyu, Zhou, Bofei, Wan, Shiyao
Research on Irregular ITS-Assisted Covert Communication in High-Speed Railway Environments2025-99-0141To be published on 11/11/2025
To address the high security demands of HSR communication, this letter proposes a covert communication scheme using irregular intelligent transparent surfaces (ITSs) deployed on train windows. A joint optimization framework is developed to enhance covert rate under element constraints, involving ATS for topology design and NECE for beamforming and phase shift. Gradient descent is used to handle covert constraints. Simulations confirm that the proposed irregular ITS outperforms regular ITS in performance and robustness, offering a promising solution for future HSR covert communication.
Jia, Jingwen, Gao, Yunbo, Xie, Jianli
DriVE-Net: A Multi-Objective Framework for Generating Diverse, Realistic, and Hazard-Aware Driving Scenarios2025-99-0133To be published on 11/11/2025
The progress of the automatic driving system, namely ADS, requires rigorous testing in various safety-critical scenarios to ensure its reliability in a real environment. However, most of the existing scenario generation methods can’t balance multiple objectives, such as safety, reality, and diversity, and improve learning, namely RL utility, which limits their effectiveness in revealing system vulnerabilities. In order to deal with these problems, DriVE-Net is proposed, which is a brand-new multi-objective framework for generating diverse, realistic, and danger-aware driving. DriVE-Net integrates four core dimensions: one is safety, which is quantified by advanced risk indicators, such as ADI and TIS; the other is reality, which is guaranteed by aligning the data distribution of the scenario with the real world; the third is diversity, which is achieved by targeted parameter space sampling; and the fourth is learning effectiveness, which is optimized by the gradual difficulty level of
Xie, Dongxuan, Li, Dongyang, Zhang, Youkang, Zhao, Yingjie, Hong, Baofeng, Wang, Nan
Optimization System of E-commerce Logistics Distribution Path Based on Data Analysis2025-99-0108To be published on 11/11/2025
With the rapid development of e-commerce, the logistics industry also presents new features such as multi-level, integrated upstream-downstream operations, increasingly perfect service quality and low logistics costs. The exponential growth in online transactions and consumer expectations for faster, more reliable deliveries intensifies the pressure on logistics systems. The last-mile service network refers to the logistics nodes that have direct contact with consumers, and its geographical location and quantity will directly affect the service level, cost and customer service mode of the distribution network. However, with the rapid growth in the number of online shoppers and their imbalance on the Internet, these factors have gradually become an important basis for influencing the layout of terminal outlets. This imbalance, coupled with dynamic urban traffic conditions, renders traditional distribution planning methods inadequate. Therefore, in the e-commerce environment, how to
Tong, Tong, Gu, Xuefei, Li, Lingxiao
Big Data Trajectory Analysis and Traffic Flow Framework Construction for Ship Manipulation Decision-Making2025-99-0134To be published on 11/11/2025
We present a novel processing approach to extract a ship traffic flow framework in order to cope with problems such as large volume, high noise levels and complexity spatio-temporal nature of AIS data. We preprocess AIS data using covariance matrix-based abnormal data filtering, develop improved Douglas-Peucker (DP) algorithm for multi-granularity trajectory compression, identify navigation hotspots and intersections using density-based spatial clustering and visualize chart overlays using Mercator projection. In experiments with AIS data from the Laotieshan waters in the Bohai Bay, we achieve compression rate up to 97% while maintaining a key trajectory feature retention error less than 0.15 nautical miles. We identify critical areas such as waterway intersections and generate traffic flow heatmap for maritime management, route planning, etc.
Kong, Xiangyu, Shao, Guoyu
Analysis of Injected Mass Shot-To-Shot Dispersion and Injection Rate Profile for a PFI Injector in Actual Operating Conditions2025-32-001911/03/2025
In order to improve engine emission and limit combustion instabilities, in particular for low load and idle conditions, reducing the injected fuel mass shot-to-shot dispersion is mandatory. Unfortunately, the most diffused approach for the hydraulic analysis of low-pressure injectors such as PFIs or SCR dozers is restrained to the mean injected mass measurement in given operating conditions, since the use of conventional injection analyzers is unfeasible. In the present paper, an innovative injection analyzer is used to measure both the injection rate and the injected mass of each single injection event, enabling a proper dispersion investigation of the analysed low pressure injection system. The proposed instrument is an inverse application of the Zeuch’s method, which in this case is applied to a closed volume upstream the injector, with the injector being operated with the prescribed upstream-to-downstream pressure differential. Further, the injector can inject freely against air
Postrioti, Lucio, Maka, Cristian, Martino, Manuel
Automotive Battery Thermal Management by Federated Learning Methodology - Real Time Thermal Runaway Detection2025-28-040810/30/2025
Modern battery management systems, as part of Battery Digital Twin, include cloud-based predictive analytics algorithms. These algorithms predicts critical parameters like Thermal runaway events, state of health (SOH), state of charge (SOC), remaining useful life (RUL), etc. However, relying only on cloud-based computations adds significant latency to time-sensitive procedures such as thermal runaway monitoring. This is a very critical and safety function and delay is not acceptable, but automobiles operate in various areas throughout the intended path of travel, internet connectivity varies, resulting in a delay in data delivery to the cloud and similarly delay in return of the detected warning to the driver back in the vehicle. As a result, the inherent lag in data transfer between the cloud and vehicles challenges the present deployment of cloud-based real-time monitoring solutions. This study proposes application of Federated Learning and applying to a thermal runaway model in low
Sarkar, Prasanta
Dome Profile Optimization and Stress Analysis of Type IV Composite Cylinders Using a CLT-Based MATLAB Program and FEA Validation2025-28-037410/30/2025
Type IV composite pressure (CP) vessels composed of a plastic liner and composite layers require special design attention to the dome region. The cylindrical portion of the composite cylinder is wrapped with composite layers consisting of the 900 hoop layers and low-angle helical layers, whereas the dome surface carries helical layers only. The winding angle of the helical layers being a constant over the cylindrical portion starts to vary from the cylinder-dome junction toward the boss at the top continuously. Along with the winding angle, the composite thickness also varies continuously resulting in a maximum thickness at the top crown region. The complete analysis and layer-wise stress prediction of Type IV composite cylinders for service pressures up to 70 MPa was analyzed by the Classical Lamination theory (CLT)-based MATLAB program. The MATLAB program developed in this work for the dome initially performs the dome profile generation through the numerical integration of the dome
R. S., Nakandhrakumar, Tandi, Ronak, M, Ramakrishnan, Raja, Selvakumar, Elumalai, Sangeethkumar, Velmurugan, Ramanathan
3D CFD Analysis of Flow and Thermal Dynamics of PEM Water Electrolyzer2025-28-035010/30/2025
The proton exchange membrane (PEM) water electrolyzer is an emerging technology to produce green hydrogen due to its compactness and producing high purity hydrogen. This study presents a numerical investigation on multiphase flow dynamics and heat transfer within the anode flow field of a PEM water electrolyzer. Two different channel configurations, i.e., rectangular, semi-circular are considered having same cross-sectional area while keeping the porous transport layer (PTL) thickness constant (which is within the commercially available ranges). Simulations are conducted for various oxygen generation rates and heat fluxes (corresponding to different current densities) and different inlet water flow rates. The effects of channel configurations on pressure drop, flow uniformity, and temperature distribution are illustrated pictorially and graphically. The impact of water flow rates and oxygen generation rates on phase distribution, pressure drop, and temperature profiles, particularly
Dash, Manoj Kumar, Bansode PhD, Annasaheb
Development of Capacitive Pressure Sensor for Automotives2025-28-038710/30/2025
Measurement plays a crucial role in the precise and accurate management of automotive subsystems to enhance efficiency and performance. Sensors are essential for achieving high levels of accuracy and precision in control applications. Rapid technical advancements have transformed the automobile industry in recent years, and a wide range of novel sensor devices are being released to the market to speed up the development of autonomous vehicle technology. Nonetheless, stricter regulations for reliable pressure sensors in automobiles have resulted from growing legal pressures from regulatory bodies. This work proposes and investigates a tribo electric nano sensor that is affected by a changing parameter of the separation distance between the device's primary electrode and dielectric layers. The system is being modeled using the COMSOL multiphysics of electrostatics and the tribo-electric effect. Open circuit electric potential and short circuit surface charge density are two of the
P, Geetha, K, Neelima, Sudarmani, R, C, Venkataramanan, Satyam, Satyam, Nagarajan, Sudarson
Simulation of Hydraulic Retarder Using Particleworks2025-28-038210/30/2025
This study explores the application of Particleworks, a meshless CFD solver based on the Moving Particle Simulation (MPS) method, for simulating hydraulic retarders. Two distinct models were used: one for validating physical fidelity and another for conducting performance-focused design investigations. Validation results demonstrated that Particleworks closely aligns with experimental data from the reference literature, effectively capturing torque variations with rotor speed effect. A sensitivity study also emphasized the importance of particle resolution on accuracy and computational cost. Design studies using an in-house hydraulic retarder model assessed the influence of flow rate, rotor speed, working fluid, temperature, and cup geometry on braking torque. Notably, torque increased with rotor speed and steeper cup angles, while thermal effects and fluid properties significantly impacted performance trends. Comparative analysis with Star-CCM+ showed that Particleworks offers similar
Kumar, Kamal S., Chaudhari, Gunjan B.
Study on Fluctuation Rules of CCFI Main Routes Based on Empirical Mode Decomposition2025-99-003510/17/2025
The China Container Freight Index (CCFI) is an important barometer of the global container shipping market. It is very important for participants in the shipping market to understand its composition. This study takes six representative routes as the research objects and conducts a detailed analysis of the composition of CCFI. The freight rate indices of these routes are decomposed and reconstructed by using the Empirical Mode Decomposition (EMD) algorithm, aiming to clarify the economic significance of each route and the fluctuation law of the reconstructed components. The research results show that the freight rate fluctuations of the west Coast, Southeast Asia and Mediterranean routes exhibit a complex nonlinear interdependence, and the simple linear model cannot fully reflect this relationship. On the contrary, the trend components of the European and Mediterranean routes effectively identify and represent the main trends within the original freight rate index. Global major events
Yin, Sitian
The Morning Commute Problem with Carpool and Dynamic Toll Scheme2025-99-002210/17/2025
This study extends the bottleneck model to analyze dynamic user equilibrium (UE) in carpooling during the morning peak commute. It is assumed that the carpooling platform offers both traditional human-driven vehicles and novel shared autonomous vehicles. First, we analyze the traffic distribution on a two-lane road. We find that traffic distribution is influenced by the additional cost of carpooling behavior. A corresponding functional relationship is established and visualized. Second, we derive the critical fare threshold for carpooling. Carpooling occurs only when the fare is below this threshold. Third, we obtain the user equilibrium (UE) solution under a specified case, including flow distribution, equilibrium cost, and total number of vehicle. Furthermore, a system-optimal dynamic tolling scheme is proposed to minimize total system cost while maintaining commuter UE. By equating the system marginal cost to the equilibrium cost, we derive the analytical expression for the lane
Zheng, XiaoLong, Zhong, RenXin
Robust Object Tracking Method Based on Multi-Level Association Matching2025-99-002010/17/2025
Target tracking is an important component of intelligent vehicle perception systems, which has outstanding significance for the safety and efficiency of intelligent vehicle driving. With the continuous improvement of technologies such as computer vision and deep learning, detection based tracking has gradually become the mainstream target tracking framework in the field of intelligent vehicles, and target detection performance is the key factor determining its tracking performance. Although remarkable progress has been made in current 3D object detection networks, a single network still struggles to provide stable detection for distant and occluded targets. Besides, traditional tracking methods are based on single-stage association matching, which can easily lead to identity jumps and target loss in case of missed detections, resulting in poor overall stability of the tracking algorithm. To solve the above problem, a hierarchical association matching method using a dual object
Wu, Shaobin, Chu, Yunfeng, Li, Yixuan, Su, Shengjie, Liu, Zhaofeng, Li, Xiaoan, Si, Lingrui
Road Traffic State Classification Method Based on AutoEncoder and Clustering Algorithm2025-99-004810/17/2025
Urban road traffic state classification is essential for identifying early-stage deterioration and enabling proactive traffic management. This study presents a novel method to accurately assess the traffic state of urban roads while addressing the limitations of existing methods in spatial generalization performance. The approach consists of three key components. First, several indicators are designed to capture the spatial-temporal evolution mechanisms of traffic state, speed freedom, flow saturation, and their variations over time and space. Then, a feature learning module based on an AutoEncoder network is introduced to reduce the dimensionality of the constructed feature set. This enhances feature distinction while mitigating noise effects on classification results. Third, k-means clustering is applied to analyze significant features extracted from the AutoEncoder latent space, categorizing road traffic states into fluent, basic fluent, moderate congested and severe congested
Wang, Xiaocong, Huang, Min, Guo, Xinling, Xie, Jiemin, Zhang, Xiaolan
Architecture Analysis & Design Language (AADL) Annex F: AADL Annex for the FACE™ Technical Standard Edition 3.0AS5506/4 (Current)10/13/2025
AS-2C Architecture Analysis and Design Language
Health and Usage Monitoring System Data Interchange SpecificationAS5395A (Current)09/18/2025
This document establishes the Rotorcraft Industry Technology Association (RITA) Health and Usage Monitoring System Data Interchange Specification. The RITA HUMS Data Interchange Specification will provide information exchange within a rotorcraft HUMS and between a rotorcraft HUMS and external entities.
HM-1R Rotorcraft Integrated Vehicle Health Management
Common, Open Data Exchange Format for Rotorcraft Health and Usage Monitoring Systems (CODEX-HUMS)AS7140 (Current)09/16/2025
This SAE Aerospace Standard (AS) provides guidance on the development and implementation of a Common Open Data Exchange (CODEX) format for rotorcraft Health and Usage Monitoring Systems (HUMS). The standard is intended to apply to data generated on board rotorcraft and the transmission of that data, as well as the data ingested by ground stations to facilitate Integrated Vehicle Health Management (IVHM). The standard provides both a conceptual data model (or models) and logical data models for rotorcraft HUMS use cases. However, the intent of the standard is to allow for data schema evolution and does not define the physical data models. The standard provides functional requirements for HUMS data acquisition and HUMS data transfer interfaces. The initial standard is focused primarily on drive train systems but is designed to potentially accommodate other data (e.g., structural fatigue) in future revisions. It is acknowledged that current rotorcraft onboard systems do not generate data
HM-1R Rotorcraft Integrated Vehicle Health Management
Use of Model-Based Datasets and Neural-Networks to Support Real-Time Driving Suggestions System for Components Preservation in Battery Electric Vehicles2025-24-011509/07/2025
Nowadays, Battery Electric Vehicles (BEVs) are considered an attractive solution to support the transition towards more sustainable transportation systems. Although their well-known advantages in terms of overall propulsion efficiency and exhaust emissions, the diffusion of BEVs on the market is still reduced by some technical bottlenecks. Among those, the uncertainty about the expected durability of the vehicle's onboard battery packs plays a key role in affecting customer choice. In this context, this paper proposes the use of model-based datasets for training a driving support system based on machine learning techniques to be installed on board. The objective of this system is to acquire vehicle, environmental, and traffic information from sensor’ networks and provide real-time smart suggestions to the driver to preserve the remaining useful life of vehicle components, with particular reference to the battery pack and brakes. For the generation of the training dataset, first, a set
Bernardi, Mario Luca, Capasso, Clemente, Iannucci, Luigi, Sequino, Luigi
The Future of EMI Shielding Is Lightweight, Flexible, and Ready for Flight25AERP09_0509/01/2025
Modern military aircraft represent some of the most complex electronic environments ever engineered. These platforms integrate advanced avionics, radar systems, data links, and communication networks that must function seamlessly in hostile, high-frequency environments. In these mission-critical contexts, electromagnetic interference (EMI) poses a silent but serious threat that can degrade signal integrity, cause crosstalk between systems, or even lead to mission failure. The combination of increasing data rates, higher frequencies, and more complex electromagnetic environments demands shielding solutions that can deliver superior performance while contributing to overall system weight reduction. This challenge has driven innovation toward advanced materials that maintain electrical effectiveness while dramatically reducing mass.
Adaptive Path Planning and Control of Autonomous Sweeping Vehicle Considering the Error of Perception10-09-04-003508/19/2025
This article presents a path planning and control method for a cost-effective autonomous sweeping vehicle operating in enclosed campus. First, to address the challenges from perception, an effective obstacle filtering algorithm is proposed, considering the elimination of false detection and correction of object position. Based on it, the adaptive sampling–based path planner and pure pursuit controller are developed. Not only an adaptive cost-weighting mechanism is introduced by TOPSIS algorithm to determine the desired trajectory as a multi-objective optimization problem, but also the adaptive preview distance is designed according to the trajectory curvature and vehicle state. The real-vehicle tests are implemented in typical scenario. The results show that the 87.8% effective edge-following rate is achieved in curved paths, and 22.93% cleaning coverage is improved for cleaning coverage. Therefore, the proposed method is effective and reliable for cost-effective autonomous sweeping
Lei, WuKun, Yang, Bo, Pei, Xiaofei, Zhang, Yang, Zhou, HongLong
Agentic Generation of OpenX Files from Natural Language Descriptions2025-01-029907/02/2025
Usually, scenarios for testing of advanced driver assistance systems (ADAS) are generated utilizing certain scenario and road specification languages such as ASAM OpenSCENARIO and OpenDRIVE. Directly adopting these low-level languages limits the rate in which new scenarios are generated for virtual testing. Natural language (NL) would allow a much broader group of people and artificial intelligences to generate scenarios, increasing test coverage and safety. Instead of trying a direct translation from NL into OpenX, the existing intermediate domain specific language (DSL) stiEF is used. This not only facilitates testing and debugging but also generation, as its grammar can be used as a constraint for a large language model (LLM), which is then able to translate NL into stiEF. A parser is applied in an agentic way that interacts with the LLM until a syntactically correct file is generated, an optional second agent is then used to do basic semantic verification. Finally, the translation
Vargas Rivero, Jose Roberto, Bock, Florian, Menken, Stefan
Customized Signalized Intersection Control for Pedestrian Safety Enhancement through Computer Vision Technologies09-13-02-000806/26/2025
The escalating complexity at intersections challenges the safety of the interaction between vehicles and pedestrians, especially for those with mobility impairments. Traditional traffic control systems detect pedestrians through costly technologies such as LiDAR and radar, limiting their adoption due to high costs and static programming. Therefore, the article proposes a customized signalized intersection control (CSIC) algorithm for pedestrian safety enhancement. This algorithm integrates advanced computer vision (CV) algorithms to detect, track, and predict pedestrian movements in real time, enhancing safety at a signalized intersection while remaining economically viable and easily integrated into existing infrastructure. Implemented at a key intersection in Bellevue, the CSIC system achieves a 100% pedestrian passing rate while simultaneously minimizing the average remaining walk time after crossings. The algorithm used in this study demonstrates the potential of combining CV with
Xia, Rongjing, Fang, Hongchao, Zhang, Chenyang
Yaw Motion of Motor Vehicles2025-01-504306/20/2025
Vehicular accident reconstruction is intended to explain the stages of a collision. This also includes the description of the driving trajectories of vehicles. Stored driving data is now often available for accident reconstruction, increasingly including gyroscopic sensor readings. Driving dynamics parameters such as lateral acceleration in various driving situations are already well studied, but angular rates such as those around the yaw axis are little described in the literature. This study attempts to reduce this gap somewhat by evaluating high-frequency measurement data from real, daily driving operations in the field. 813 driving maneuvers, captured by accident data recorders, were analyzed in detail and statistically evaluated. These devices also make it possible to record events without an accident. The key findings show the average yaw rates as a function of driving speed as well as the ratio between mean and associated peak yaw rate. Beyond that, considerably lower yaw rates
Fuerbeth, Uwe
Increasing Wear Strength and Life Cycle of Tamping Machine Tool by Silicon Carbide Coating for Railway Maintenance05-19-02-001106/19/2025
When a train passes continuously over a section of the track, the track gradually moves away from the intended vertical and horizontal alignment with time and repeated use. Regular maintenance on the track, such as leveling, lifting, lining, and tamping, is necessary to maintain the optimal geometry of the track. Ballast is leveled and squeezed by hydraulic rams in tamping machines. The tamping is a process of ballast packing under railway tracks. In current system a set of tungsten carbide chips are attached either by welding or by coating on tamping tool tip made of EN24 steels. These tungsten carbide chips directly come in contact with the ballasts. After few tamping works, gradually these chips torn out and need to be replaced after certain period. Tungsten carbide is a costly material, therefore this research deals with replacement of tungsten carbide with silicon carbide (easily available cheaper) coating used for tamping tools tip. The study consists of microstructural
Mishra, Mamta, Pandey, Manas, Singh, Shruti, Srivastava, Sanjay, Kumar, Jitendra
SAE TOMORROW TODAY - Removing Roadblocks to Fleet Electrification1351806/09/2025
What does it really take to electrify America's fleets? From skyrocketing insurance rates to policy risks to reduced incentives, the market dynamics are complex. Enter Electrada, a Cincinnati-based EV infrastructure company revolutionizing how fleets transition to clean energy. As the developer, owner, and operator of electric fueling assets, Electrada offers a unique 360 Charging-as-a-Service (CaaS) model that delivers zero capital investment, 99%+ uptime, predictable pricing, and expert management. Serving all fleet types across multiple transportation sectors, Electrada designs fully tailored, long-term EV charging solutions that reduce cost per mile from day one with no operational disruptions or price risk. Listen in as we sit down with Kevin Kushman, CEO of Electrada, to discuss the challenges and opportunities in the North American fleet electrification market. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org
Hineman, Marcie
Analysis and Evaluation of Roll Safety Thresholds of Tractor Semi-Trailer Vehicles during Turning Maneuvers Based on the Yaw Rate of Vehicle Bodies and Roll Safety Factor02-18-04-002406/05/2025
Hung, Ta Tuan
Wearable Sensors Provide Real-Time Measurements of Sweat Rate and Electrolytes and Metabolites in SweatTBMG-5322206/01/2025
Researchers developed wearable skin sensors that can detect what’s in a person’s sweat. Using the sensors, monitoring perspiration could bypass the need for more invasive procedures like blood draws and provide real-time updates on health problems such as dehydration or fatigue. The sensor design can be rapidly manufactured using a roll-to-roll processing technique that essentially prints the sensors onto a sheet of plastic.
Development of an Intelligent Instrumented Tire for Real-Time Hydroplaning Risk Estimation10-09-03-002705/21/2025
This study introduces an innovative intelligent tire system capable of estimating the risk of total hydroplaning based on water pressure measurements within the tread grooves. Dynamic hydroplaning represents an important safety concern influenced by water depth, tread design, and vehicle longitudinal speed. Existing intelligent tire systems primarily assess hydroplaning risk using the water wedge effect, which occurs predominantly in deep water conditions. However, in shallow water, which is far more prevalent in real-world scenarios, the water wedge effect is absent at higher longitudinal speeds, which could make existing systems unable to reliably assess the total hydroplaning risk. Groove flow represents a key factor in hydroplaning dynamics, and it is governed by two mechanisms: water interception rate and water wedge pressure. In both the shallow water and deep water cases, the groove water flow will increase as a result of increasing the longitudinal speed of the vehicle for a
Vilsan, Alexandru, Sandu, Corina, Anghelache, Gabriel, Warfford, Jeffrey
Variable Speed Limit Control Based on Deep Deterministic Policy Gradient under Mixed Traffic Environment12-09-01-000405/06/2025
The existing variable speed limit (VSL) control strategies rely on variable message signs, leading to slow response times and sensitivity to driver compliance. These methods struggle to adapt to environments where both connected automated vehicles (CAVs) and manual vehicles coexist. This article proposes a VSL control strategy using the deep deterministic policy gradient (DDPG) algorithm to optimize travel time, reduce collision risks, and minimize energy consumption. The algorithm leverages real-time traffic data and prior speed limits to generate new control actions. A reward function is designed within a DDPG-based actor-critic framework to determine optimal speed limits. The proposed strategy was tested in two scenarios and compared against no-control, rule-based control, and DDQN-based control methods. The simulation results indicate that the proposed control strategy outperforms existing approaches in terms of improving TTS (total time spent), enhancing the throughput efficiency
Ding, Xibin, Zhang, Zhaolei, Liu, Zhizhen, Tang, Feng
Localisation of Ultra-Short Sound Emissions from Automotive Components by Using the Sound Field Scanning Method2025-01-009205/05/2025
Design verification and quality control of automotive components require the analysis of the source location of ultra-short sound events, for instance the engaging event of an electromechanical clutch or the clicking noise of the aluminium frame of a passenger car seat under vibration. State-of-the-art acoustic cameras allow for a frame rate of about 100 acoustic images per second. Considering that most of the sound events introduced above can be far less than 10ms, an acoustic image generated at this rate resembles an hard-to-interpret overlay of multiple sources on the structure under test along with reflections from the surrounding test environment. This contribution introduces a novel method for visualizing impulse-like sound emissions from automotive components at 10x the frame rate of traditional acoustic cameras. A time resolution of less than 1ms eventually allows for the true localization of the initial and subsequent sound events as well as a clear separation of direct from
Rittenschober, Thomas
Short-Time Current Rating of Aircraft Wire2025-01-014505/02/2025
This paper presents a comparative analysis of various short-time current rating formulas, focusing on applications in aircraft wiring. Examining historical formulas developed by pioneers such as W.H. Preece and I.M. Onderdonk alongside modern experimental data provide a comprehensive understanding of short-time current rating formulas. Also, exploring key challenges, such as environmental conditions and material variability in aviation with particular attention to adiabatic methods for current-carrying calculations. The findings of this paper offer practical insights into improving the safety and reliability of an aircraft electrical system with improving the accuracy of short-time current rating predictions.
Fifield, Jon
New Study Showcases 3D Photonics with Record Performance for AITBMG-5301305/01/2025
Artificial intelligence (AI) systems promise transformative advancements, yet their growth has been limited by energy inefficiencies and bottlenecks in data transfer. Researchers at Columbia Engineering have unveiled a groundbreaking solution: a 3D photonic-electronic platform that achieves unprecedented energy efficiency and bandwidth density, paving the way for next-generation AI hardware.
Ultrasonic Welding: Key Considerations for Designing Medical WearablesTBMG-5316505/01/2025
Not only the use, but also the wearing time of medical wearables continues to increase in modern healthcare. However, to ensure that wearable products do not cause skin irritation, product designers must consider the moisture vapor transmission rate (MVTR) during development. It plays an important role in skin compatibility and wearing comfort — and can be decisively influenced by the right joining technology.
JAUS Unmanned Ground Vehicle Service SetAS6091 (Historical)04/24/2025
This document defines a set of standard application layer interfaces called JAUS Unmanned Ground Vehicle Services. JAUS Services provide the means for software entities in an unmanned system or system of unmanned systems to communicate and coordinate their activities. The Unmanned Ground Vehicle Services represent the platform-specific capabilities commonly found in UGVs, and augment the Mobilty Service Set [AS6009] which is platform-agnostic. At present ten (10) services are defined in this document. These services are categorized as:
AS-4JAUS Joint Architecture for Unmanned Systems Committee
JAUS Autonomous Capabilities Service SetAS8024 (Current)04/24/2025
This document defines a set of standard application layer interfaces called JAUS Autonomous Capabilities Services. JAUS Services provide the means for software entities in an unmanned system or system of unmanned systems to communicate and coordinate their activities. The Autonomous Behaviors Services represent the platform-independent capabilities commonly found in platforms across domains, including air, maritime, and ground. At present five (5) services are defined in this document. These services are: Comms Lost Policy Manager: Detect and recover from loss of communications with a control station Retrotraverse: Return along a path previously traveled Self-Righting: Attempt to recover from a tip over condition Cost Map 2D: Provides information about the current operating environment of the platform Path Reporter: Provides information about the previous or future planned path of the platform
AS-4JAUS Joint Architecture for Unmanned Systems Committee
JAUS Manipulator Service SetAS6057A (Current)04/24/2025
This document defines a set of standard application layer interfaces called JAUS Manipulator Services. JAUS Services provide the means for software entities in an unmanned system or system of unmanned systems to communicate and coordinate their activities. The Manipulator Services represent platform-independent capabilities commonly found across domains and types of unmanned systems. At present, twenty-five (25) services are defined in this document. These services are categorized as: Low Level Manipulator Control Services – The one service in this category allows for low-level command of the manipulator joint actuation efforts. This is an open-loop command that could be used in a simple tele-operation scenario. The service in this category is listed as follows: Primitive Manipulator Service Manipulator Sensor Services – These services, when queried, return instantaneous sensor data. Three services are defined that return respectively joint positions, joint velocities, and joint
AS-4JAUS Joint Architecture for Unmanned Systems Committee
Virtual Encoder for Achieving Crank Angle Resolution Measurements of In-Cylinder Pressure in Small Engines by using Time Based Data Acquisition2024-32-010504/18/2025
Small size engines feature several peculiarities that render them a challenge with respect to implementing measurements required for characterizing specific phenomena such as combustion evolution. Measuring in-cylinder pressure is well established as standard procedure for determining combustion characteristics, but in the case of small size units actually applying it can require alternative approaches. Fitting a crank angle encoder may be extremely difficult, as a consequence of the actual size of the power unit. Cost is another essential driver for small engine development that also influences how measurements are implemented. Within this context, the present work describes the development and implementation of a method that employs an algorithm that practically generates a ‘virtual’ encoder. Only a basic phasing signal is required, such as an inductive crankshaft position sensor output or that of an ignition pulser. The software was developed on an experimental engine with a crank
Irimescu, Adrian, Cecere, Giovanni, Merola, Simona Silvia, Vaglieco, Bianca Maria
Experimental Study on Thermo-Catalytic Ammonia Decomposition into Hydrogen2024-32-011804/18/2025
In order to rapidly achieve the goal of global net-zero carbon emissions, ammonia (NH3) has been deemed as a potential alternative fuel, and reforming partial ammonia to hydrogen using engine exhaust waste heat is a promising technology which can improve the combustion performance and reduce the emission of ammonia-fueled engines. However, so far, comprehensive research on the correlation between the reforming characteristic for accessible engineering applications of ammonia catalytic decomposition is not abundant. Moreover, relevant experimental studies are far from sufficient. In this paper, we conducted the experiments of catalytic decomposition of ammonia into hydrogen based on a fixed-bed reactor with Ru-Al2O3 catalysts to study the effects of reaction temperature, gas hour space velocity (GHSV) and reaction pressure on the decomposition characteristics. At the same time, energy flow analysis was carried out to explore the effects of various reaction conditions on system
Li, Ze, Li, Tie, Chen, Run, Li, Shiyan, Zhou, Xinyi, Wang, Ning
Experimental Study on Pre-Chamber Hydrogen Flame Jet Ignition of Ammonia/Air Mixture in Constant Volume Combustion Chamber2024-32-011704/18/2025
To address the issues of difficult ignition and slow combustion when ammonia is used as engine fuel, a method of igniting ammonia/air mixture with hydrogen flame jet generated by a pre-chamber is proposed. The combustion characteristics of mixtures ignited by the hydrogen flame jet were studied in a constant volume combustion chamber with high-speed video camera and pressure acquisition in the main chamber. The characteristics were compared with those ignited by the ammonia flame jet. The introduction of the hydrogen flame jet notably improved mixture combustion and expanded the lean flammability limit. Combustion with hydrogen injection demonstrated reduced pressure rise delay and combustion duration, increased average heat release rate, and sustained combustion stability. This phenomenon was more pronounced under low equivalence ratio conditions in the main combustion chamber. The hydrogen flame jet was shuttle-shaped when touched the lower surface owing to the rapid combustion speed
Yin, Shuo, Tian, Jiangping, Cui, Zechuan, Zhang, Xiaolei, Nishida, Keiya, Dong, Pengbo
Changes of Shifting Rate of Metal V-Belt Type CVT during Speed Up/Down under Quasi-Idle Loading Condition2024-32-007804/18/2025
The objective of this experimental study was to investigate the change of shifting rate of metal V-belt type CVT during speed up/down under quasi-idle loading condition. Changes in the rotational speeds of the driving and driven pulleys were simultaneously measured by the rotational speed sensors installed on the driving and driven shafts during speed up/down shifting, respectively. In addition, the interaxial force applied to the driving and driven pulleys was measured by a load cell. The shifting rate was defined as the ratio of the calculated radial displacement to the tangential displacement of the belt in the pulley groove. This study found that the shifting rate was determined not only by the slippage between the pulley and the belt element, but also by the elastic deformation of the belt element in the pulley groove. The power transmission performance was improved when the elastic deformation was small even though radial slippage between the pulley and the belt element was
Mori, Yuichirou, Okubo, Kazuya, Obunai, Kiyotaka
T.R.I.C.K. 2.0: Enhanced Vehicle Dynamics Analysis and Estimation Harnessing Advanced Vehicle Sensors10-09-03-002504/09/2025
Automotive signal processing is dealt with in several contributions that propose various techniques to make the most out of the available data, typically for enhancing safety, comfort, or performance. Specifically, the accurate estimation of tire–road interaction forces is of high interest in the automotive world. A few years ago the T.R.I.C.K. tool was developed, featuring a vehicle model processing experimental data, collected through various vehicle sensors, to compute several relevant virtual telemetry channels, including interaction forces and slip indices. Following years of further development in collaboration with motorsport companies, this article presents T.R.I.C.K. 2.0, a thoroughly renewed version of the tool. Besides a number of important improvements of the original tool, including, e.g., the effect of the limited slip differential, T.R.I.C.K. 2.0 features the ability to exploit advanced sensors typically used in motorsport, including laser sensors, potentiometers, and
Napolitano Dell’Annunziata, Guido, Farroni, Flavio, Timpone, Francesco, Lenzo, Basilio
Verification of the Impact of Coefficient of Drag Variation Due to Natural Wind on Fuel Consumption Based on Actual Driving Data2025-01-877804/01/2025
The natural wind experienced on public roads can increase the yaw angle and therefore drag coefficient (CD), which may contribute to the discrepancy between catalog fuel economy and actual fuel economy. The impact of yaw characteristics alone on fuel economy during actual driving has not been verified or proven as it is difficult to obtain actual driving data under uniform conditions. For this reason, shape optimization is normally performed at zero-yaw through the aerodynamic development phases. In this paper, two vehicles with different yaw sensitivity characteristics are driven simultaneously, and fuel economy measurements are performed simultaneously with ambient airflow, environment, and vehicle conditions. The results where the conditions of the two vehicles match are extracted to clarify the impact of the differences of yaw characteristics on fuel economy. The obtained results matched the values predicted by theoretical calculations for the impact of yaw angle on fuel economy
Onishi, Yasuyuki, Nichols, Larry, Metka, Matt, masumitsu, Yasutaka, Inoue, Taisuke
Validation of SynthEyes for Use in Collision Reconstruction2025-01-868804/01/2025
Accurate reconstruction of vehicle collisions is essential for understanding incident dynamics and informing safety improvements. Traditionally, vehicle speed from dashcam footage has been approximated by estimating the time duration and distance traveled as the vehicle passes between reference objects. This method limits the resolution of the speed profile to an average speed over given intervals and reduces the ability to determine moments of acceleration or deceleration. A more detailed speed profile can be calculated by solving for the vehicle’s position in each video frame; however, this method is time-consuming and can introduce spatial and temporal error and is often constrained by the availability of external trackable features in the surrounding environment. Motion tracking software, widely used in the visual effects industry to track camera positions, has been adopted by some collision reconstructionists for determining vehicle speed from video. This study examines the
Perera, Nishan, Griffiths, Harrison, Prentice, Greg
Reducing Power Consumption through Effective Data Sharing in Platooning Scenarios2025-01-805104/01/2025
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 Zaeem, Azim, Akramul, Rahman, Taufiq
Research on Dangerous Driving Behavior Recognition Algorithm Based on LSTM2025-01-820404/01/2025
To address the issue of high accident rates in road traffic due to dangerous driving behaviors, this paper proposes a recognition algorithm for dangerous driving behaviors based on Long Short-Term Memory (LSTM) networks. Compared with traditional methods, this algorithm innovatively integrates high-frequency trajectory data, historical accident data, weather data, and features of the road network to accurately extract key temporal features that influence driving behavior. By modeling the behavioral data of high-accident-prone road sections, a comprehensive risk factor is consistent with historical accident-related driving conditions, and assess risks of current driving state. The study indicates that the model, in the conditions of movement track, weather, road network and conditions with other features, can accurately predict the consistent driving states in current and historical with accidents, to achieve an accuracy rate of 85% and F1 score of 0.82. It means the model can
Huang, Yinuo, Zhang, Miaomiao, Xue, Ming, Jin, Xin
3D Modeling of Thermal Runaway in Pouch Cells: Effects of Surface Heating and Heating Rates2025-01-855904/01/2025
Thermal runaway in battery cells presents a critical safety concern, emphasizing the need for a thorough understanding of thermal behavior to enhance battery safety and performance. This study introduces a newly developed AutoLion 3D thermal runaway model, which builds on the earlier AutoLion 1D framework and offers significantly faster computational performance compared to traditional CFD models. The model is validated through simulations of the heat-wait-search mode of the Accelerating Rate Calorimeter (ARC), accurately predicting thermal runaway by matching experimental temperature profiles from peer-reviewed studies. Once validated, the model is employed to investigate the thermal behavior of 3D LFPO cells under controlled heating conditions, applying heat to one or more surfaces at a time while modeling heat transfer from non-heated surfaces. The primary objective is to understand how these localized heating patterns impact temperature profiles, including average core temperatures
Hariharan, Deivanayagam, Gundlapally, Santhosh
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