Browse Topic: People and personalities

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Image Processing-Based Chip Detection by KIZKI Algorithm and Its Optimization2025-01-0168To be published on 04/25/2025
The process of producing aircraft parts involves the drilling of aluminum alloys. This creates a large amount of chips, which are removed using air, but sometimes they still remain within the holes. This is checked by inspectors through visual inspection. However, the quality of human inspection varies based on skill level and fatigue. Thus, image-based inspection should be used to stabilize and further improve inspection quality. This study aims to build a framework for chip detection based on image processing. Taking into account on-site implementation, the system must have low installation and running costs and be standalone. Therefore, we adopt the KIZKI algorithm, which satisfies these conditions. KIZKI means awareness in Japanese. This is a model of human peripheral vision and saccades. It does not require training like AI and can achieve high-speed and high-performance detection using a low-performance computer. In other words, there is no need for a computer with an expensive
Iinuma, Marin, Sato, Junya, Tsuji, Masahiko
Technical Paper
AI-Driven Design Optimization of Engineering Systems: A Case Study on Turboshaft Engines2025-01-0173To be published on 04/25/2025
In the pursuit of optimizing complex engineering systems, the exploration and thorough understanding of the design space become imperative, particularly when dealing with multi-objective systems characterized by an array of independent variables. This paper presents a comprehensive analysis on the design space mapping of such intricate systems, utilizing a turboshaft engine as a representative case study. The initial phase of our methodology involves the employment of a physics-based model to generate a synthetic dataset. This dataset reflects the intricate interplay of various system parameters that underpin the engine's operation. The synthesized data serves as a foundation for the subsequent development of a Machine Learning or Deep Learning-based surrogate model. This surrogate AI model is meticulously crafted to encapsulate the multiple inputs and outputs inherent in the turboshaft engine's functioning, thereby facilitating an efficient and accurate exploration of the design space
PANKAJ, PEEYUSH, Thokala, Satish
Technical Paper
Using CAN Electrical Signals for Cybersecurity and Harness Diagnostics2025-01-8080To be published on 04/01/2025
This paper describes a novel invention which is an Intrusion Detection System based on fingerprints of the CAN bus analogue features. Clusters of CAN message analogue fingerprints can be associated with each ECU on the network. During a learning mode of operation, fingerprints can be learnt with the prior knowledge of which CAN identifier should be transmitted by each ECU. During normal operation, if the fingerprint of analogue features of a particular CAN identifier does not match the one that was learnt then there is a strong possibility that this particular CAN identifier’s message is symptomatic of a problem. It could be that the message has been sent by either an intruder ECU or an existing ECU has been hacked to send the message. In this case an intruder can be defined as a device that has been added to the CAN bus OR a device that has been hacked/manipulated to send CAN messages that it was not designed to (i.e. could be originally transmitted by another device). It could also
Quigley, Christopher, Charles, David
Technical Paper
Testing Complex Circuits with Radio-frequency Reflectometry2025-01-8251To be published on 04/01/2025
Driving automation systems rely heavily on sophisticated electronics to function effectively, and economic pressure poses new challenges in manufacturing. Tightly integrated sensors, processors, and communication modules monitor and control the vehicle's operation at any time. Size, weight, power, and cost constraints put pressure on manufactures to reduce stack electronics, miniaturize boards, and innovate over the traditional sequential assemble/test cycle. Consequently, designers and manufacturers reduce access to boards, remove test points, co-locate RF with other components, and break the sequential SMT line. Radiofrequency (RF) reflectometry is a mature and reliable technology essential for characterizing materials, components, and analog circuits. It provides precise insights into electromagnetic properties like impedance and permittivity, crucial for optimizing RF and microwave designs. Widely used in fields from material science to quantum computing, RF reflectometry is key to
Moreno, Carlos, Sharma, Rakshit, Pabbi, Srijan, Fischmeister, Sebastian
Technical Paper
Market Research & Analysis of failures due to environmental gases in Automotive Electronics and integration of learnings in development testing2025-01-8255To be published on 04/01/2025
Automotive industry is growing rapidly with innovations leading to increase in new features and improving the Quality of vehicles. These new components are developed with the available design standards across global OEMs. This Quality research paper aims to address the need of revision of design standards due to environmental factors prevailing in India. With the increase towards autonomous mobility, the number of electronics is also increasing, and this involves hardware & software evaluation. The hardware testing is a point of concern due to increase in the failure rate from the markets. Environment changes are very much evident with the growing economies and OEMs are developing the components with innovation, but if the basic design standards are not revised in parallel with the changing environment, the issues will continue to trouble the end customers. The failed cases data received from across the country was analyzed and observed that the cases are majorly reported from urban
Marwah, Ramnik, Pyasi, Praveen, Bindra, Ritesh, Garg, Vipin
Technical Paper
Driving Under the Influence: A Review of Fitness to Drive, Drug-Induced Impairments, and Simulation Testing2025-01-8666To be published on 04/01/2025
This literature review examines the concept of fitness to drive and how it can be affected by drugs consumption. The Systematic Literature Review (SLR) methodology is used to analyse the Literature, exploiting Scopus, Consensus and Elicit databases. Firstly, the paper presents research across mechanical engineering and related fields to establish a comprehensive and multidisciplinary understanding of how fitness to drive is evaluated. This includes a definition of the term and the identification of the protocols used for its assessment. Secondly, the emphasis is on the impact of drug use on driving performance, excluding alcohol and cannabis. Driving simulators represent a valid possibility for analysing such effects in a safe, controlled and replicable environment. They are presented considering their most relevant characteristics and the measurements collected for the driver's state analysis. Key findings reveal a lack of a comprehensive taxonomy for fitness to drive, resulting in
Uccello, Lorenzo, Nobili, Alessandro, Pasina, Luca, Novella, Alessio, Elli, Chiara, Mastinu, Gianpiero
Technical Paper
Highly accurate Machine Learning models for Automotive Crash applications using CAE centric AI/ML Platform2025-01-8719To be published on 04/01/2025
In the automotive industry, there have been many efforts of late in using Machine Learning tools to aid virtual simulation and decrease product development time and cost. As the simulation world grapples with how best to incorporate ML techniques, two main challenges are evident. There is the risk of not knowing if the trained model is sound enough to drive the design. In addition, the complexity of porting simulation data back and forth to a ML software can make the process cumbersome. We would like to put forth a highly accurate and comprehensive one-stop ML workflow that has been implemented within a commercially available CAE driven platform called DEP MeshWorks. MeshWorks is used for rapid concept CAE and CAD model generation and parametrization. The AI platform within Meshworks leverages the inherent best-in-class parameterization capability to help rapidly generate data for training purposes. It is relatively quick to set up a fully parameterized CAE model and vary design
Krishnan, Radha
Technical Paper
Driver’s Pedal Control for Detecting Pedal Misapplication2025-01-8675To be published on 04/01/2025
Drivers sometimes operate the accelerator pedal instead of the brake pedal due to driver error, potentially resulting in serious accidents. Acceleration Control for Pedal Error (ACPE) has been developed, a system that detects such errors and controls vehicle acceleration to prevent these incidents. The United Nations is already considering regulations for this technology. If ACPE can detect errors based on the operations of the accelerator pedal at various driving speeds, the system will be even more effective in terms of safety. The purpose of this study is to investigate the operation characteristics of the accelerator pedal and brake pedal, focusing on the pedal operation characteristics of pedal stroke speed and pedal force speed used as thresholds for the operation of ACPE. We believe that if there is a significant difference in the operations of the accelerator pedal and brake pedals while driving, it can be used as a threshold for judging misstep. In this study, we utilized a
Natsume, Hayato, Shen, Shuncong, Hirose, Toshiya
Technical Paper
Modern Simulink DevOps Integration2025-01-8077To be published on 04/01/2025
Model-based developers are turning to DevOps principles and toolchains to increase engineering efficiency, improve model quality and to facilitate collaboration between large teams. Mature DevOps processes achieve these through automation. This paper demonstrates how integrating modern version control (git) with collaborative development practices and automated quality measures can streamline workflows for large teams using Simulink. The focus is on enhancing model consistency, enabling team collaboration, and development speed.
Mathews, Jon, Tamrawi, Ahmed, Ferrero, Sergio, Sauceda, Jeremias
Technical Paper
Freedom from Interference Challenges for Adaptive Autosar Based Platform2025-01-8074To be published on 04/01/2025
Keyword - Autonomous & Connected Vehicles, Functional Safety, ISO26262, Freedom from Interference, Adaptive Autosar, Operating System, Safety mechanisms, Hypervisor, MPU, MMU, PHM. Adaptive AUTOSAR is extensively utilized in the development of autonomous and connected vehicles, where functional safety is paramount. This framework ensures that critical safety requirements are met, providing a reliable and secure platform for advanced vehicular functionalities. The paper delves into challenges and mechanisms for ensuring Freedom from Interference in Adaptive AUTOSAR-based platform, emphasizing strategies for managing complexities and adhering to ISO 26262 standards. This study focuses on managing Memory, Timing, and Execution challenges within Adaptive AUTOSAR-based Platform. In Classic AUTOSAR, robust safety mechanisms ensure Freedom from Interference (FFI). Memory protection is achieved through Memory Protection Unit configuration and memory partitioning. Timing Protection mechanisms
Jain, Yesha
Technical Paper
Cost Analysis of Battery Electric and Fuel Cell Powertrains for Class 8 Heavy-Duty Trucks in Real-World Scenarios: A 2024, 2035 and 2050 Perspective2025-01-8592To be published on 04/01/2025
This study evaluates the performance of alternative powertrains for Class 8 heavy-duty trucks under a variety of real-world driving conditions, cargo loads, and operating ranges. Energy consumption, greenhouse gas emissions, and the Levelized Cost of Driving (LCOD) were assessed for different powertrain technologies in 2023, 2035, and 2050, considering anticipated technological advancements. The analysis was conducted using simulation models that accurately reflect vehicle dynamics, powertrain components, and energy storage systems, leveraging real-world driving data. The Argonne National Laboratory's POLARIS, SVTrip, Autonomie, and TechScape software were used in an integrated simulation workflow for this analysis. Additionally, a sensitivity analysis was conducted on fuel and battery costs to understand their impact on economic outcomes. The study considered a hydrogen cost of $4/kg in 2035 and 2050, three AEO2023 low, medium, high diesel cost scenarios, and electricity costs ranging
Mansour, Charbel, Bou Gebrael, Julien, Kancharla, Amarendra, Freyermuth, Vincent, Islam, Ehsan Sabri, Vijayagopal, Ram, Sahin, Olcay, Zuniga, Natalia, Nieto Prada, Daniela, Alhajjar, Michel, Rousseau, Aymeric, Borhan, Hoseinali, El Ganaoui-Mourlan, Ouafae
Technical Paper
A Novel Hybrid Approach for Segmenting Driver Based on their Driving Style2025-01-8205To be published on 04/01/2025
Drivers present a diverse landscape with their distinct personalities, preferences, and driving habits influenced by many factors. While drivers exhibit a wide range of behaviors, identifiable patterns in driving styles enable the classification of drivers into discrete segments. Discrete segmentation provides a practical and effective way to categorize and address the differences in driving style. The segmentation approach offers many benefits, including simplification, measurement, proven methodology, customization, and safety. Numerous studies have investigated driving style classification using real-world vehicle data. These studies employed various methods to identify and categorize distinct driving patterns, including naturalist differences in driving and field operational tests. This paper presents a novel hybrid approach for segmenting driver behavior based on their driving patterns. We leverage vehicle acceleration data to create granular driver segments by combining event
Chavan, Shakti Pradeep, Chinnam, Ratna Babu
Technical Paper
Regression Model based Method for Stiffness Design of Laminated Glasses2025-01-8320To be published on 04/01/2025
There has been a growing interest in laminated sidelites (or door glasses) in automotive for the benefits of both security and comfort. Current standard products are a 2.1/0.76/2.1 mm construction with soda-lime glass symmetrically distributed on each side of a PVB layer. Due to low shear stiffness of PVB, the standard laminate has a significantly reduced flexural rigidity in comparison to a monolith with the same total thickness. A novel lightweight laminate concept with ultrathin chemically strengthened glass was developed by Corning [1]. This concept considered asymmetrical designs with thinner (0.5 – 1.1 mm) chemically strengthened Corning® Gorilla® Glass laminated to relatively thick outer ply of conventional soda-lime glass and was found to provide enhanced stiffness over standard symmetrical laminate designs of same total thickness. It is known that flexural rigidity of laminated glass depends on multiple variables, such as shape, load distribution and boundary constraining
Yu, Chao, Cleary, Thomas, Joubaud, Laurent, kister, Evan, Fisher, W Keith
Technical Paper
Reproduction of Real-World Scenarios in CARLA: An Extension of CARLA Functionality2025-01-8059To be published on 04/01/2025
Reproducing driving scenarios involving near-collisions and collisions in a simulator can be useful in the development and testing of autonomous vehicles, as it provides a safe environment to explore detailed vehicular behavior during these critical events. CARLA, an open-source driving simulator, has been widely used for reproducing driving scenarios. CARLA allows for both manual control and traffic manager control (the module that controls vehicles in autopilot manner in the simulation). However, current versions of CARLA are limited to setting the start and destination points for vehicles that are controlled by traffic manager, and are unable to replay precise waypoint paths that are collected from real-world collision and near-collision scenarios, due to the fact that the collision-free pathfinding modules are built into the system. This paper presents an extension to CARLA’s source code, enabling the replay of exact vehicle trajectories, irrespective of safety implications
Ai, Yan, Adhikari, Bikram, Park, Chung-Kyu, Kan, Cing-Dao, Wijesekera, Duminda
Technical Paper
Use of Vehicle Cyber Engineering (VCE) testbeds to develop AI Safety enhancements based on ISO TR 5469.2025-01-8090To be published on 04/01/2025
The University of Detroit-Mercy (UD-M) has developed CLaaS (Cyber-Security Labs as a Service) to support teaching students how to understand and mitigate cyber security attacks. The UD-M Vehicle Cyber Engineering (VCE) laboratory has physical hardware testbeds to support education and research on actual vehicle systems. With the increased use of Machine Learning (ML) and Artificial Intelligence (AI) in on- and offroad vehicles, it is becoming critical to enhance the laboratory to help educate a new generation of engineers that understand the cyber security and functional implications of AI/ML. The ISO TR 5469 Technical Report provides a framework to classify the AI/ML technology based on usage level and the properties and requirements to mitigate cyber and functional safety risks for the technology. This paper provides an overview of the approach used by ISO TR 5469 as well as an example how one of the six ISO TR 5469 desirable properties (resilience to adversarial and intentional
Zachos, Mark, Seifert, Heinz
Technical Paper
Objective and subjective evaluation of the interaction of automated vehicles and human drivers in take-over scenarios2025-01-8048To be published on 04/01/2025
The research activity aims at defining specific Operational Design Domains (ODDs) representative of Italian traffic environments. The paper focuses on the human-machine interaction in Automated Driving (AD), with a focus on take-over scenarios. The study, part of the European/Italian project “Interaction of Humans with Level 4 AVs in an Italian Environment - HL4IT”, describes suitable methods to investigate the effect of the Take-Over Request (TOR) on the human driver’s psycho-physiological response. The DriSMI dynamic driving simulator at Politecnico di Milano has been used to analyse three different take-over situations. Participants are required to regain control of the vehicle, after a take-over request, and to navigate through a urban, suburban and highway scenario. The psycho-physiological characterization of the drivers, through psychological questionnaires and physiological measures, allows for analyzing human factors in automated vehicles interactions and for contributing to
Gobbi, Massimiliano, Boscaro, Linda, De Guglielmo, Veronica, Fossati, Andrea, Galbiati, Andrea, Mastinu, Leda, Ponti, Marco, Mastinu, Gianpiero, Previati, Giorgio, Sabbioni, Edoardo, Signorini, Maria Gabriella, Somma, Antonella, Subitoni, Luca, Uccello, Lorenzo
Technical Paper
Safe Cooperative Control Framework for Highway On-Ramp Merging2025-01-8024To be published on 04/01/2025
The development of connected and automated vehicles (CAVs) is rapidly increasing in the next generation and the automotive industry is dedicated to enhancing the safety and efficiency of CAVs. A cooperative control strategy helps CAVs to collaborate and share information among the neighboring CAVs, improving efficiency, optimizing traffic flow, and enhancing safety. This research proposes a safe cooperative control framework for CAVs designed for highway merging applications. In the urban transportation system, highway merging scenarios are high-risk collision zone, and the CAVs on the main and merging lanes should collaborate to avoid potential accidents. In the proposed framework, the on-ramp CAVs merge at 40 mph within the same and opposite directions to the main lane CAVs. The proposed framework includes the consensus controller, safety filter, and quadratic programming (QP) optimization method. The consensus controller incorporates the communication between CAVs and designs the
Chang, PeiYu, Bhatti, Sidra, Javed, Nur Uddin, Ahmed, Qadeer
Technical Paper
The Effect of Directional Tactile Guidance on Takeover Performance in Level 3 Automated Driving2025-01-8049To be published on 04/01/2025
Automated driving is an important development direction of the current automotive industry. Level 3 automated driving allows the driver to perform non-driving related tasks (NDRTs) during automated driving, however, once the operating conditions exceed the designed operating domain, the driver is still required to take over. Therefore, it is important to rationally design takeover requests (TORs) in Level 3 conditional automated driving. This paper investigates the effect of directional tactile guidance on driver takeover performance in emergency obstacle avoidance scenarios during the transfer of control from automated driving mode to manual driving.18 participants drove a Level 3 conditional automated driving vehicle in a driving simulator on a two-way four-lane urban road, performed a takeover, and avoided obstacles while performing non-driving related tasks. The driver's takeover performance during the takeover process was measured and subjective driver evaluation data was
Liang, Xinying, Liang, Yunhan, Ma, Xiaoyuan, Wang, Luyao, Chen, Guoying, Hu, Hongyu
Technical Paper
Combine HD map information to enhance road topology reasoning by offline supervised training and on-line ensemble learning2025-01-8021To be published on 04/01/2025
Topology reasoning plays a crucial role in understanding complex driving scenarios and facilitating downstream planning, yet the process of perception is inevitably affected by weather, traffic obstacles and worn lane markings on road surface. Combine pre-produced high-precision maps, and other type of map information to the perception network can effectively enhance perception robustness, but this on-line fused information often requires a real-time connection to website servers. We are exploring the possibility to compress the information of offline maps into a network model and integrate it with the existing perception model. We designed a topology prediction module based on graph attention neural network and an information fusion module based on ensemble learning. The module, which was pre-trained on offline high-precision map data, when used online, inputs the structured road element information output by the existing perception module to output the road topology, and the output
Kuang, Quanyu, Rui, Zhang, Zhang, Song, Yixuan, Gao
Technical Paper
Adding and Assessing Vehicle Sound and Steering Feedback: Application to an Unreal Engine Driving Simulator.2025-01-8668To be published on 04/01/2025
To provide an affordable and practical platform for evaluating driving safety, this project developed and assessed 2 enhancements to an Unreal-based driving simulator to improve realism. The current setup uses a 6x6 military truck from the Epic Games store, driving through a pre-designed virtual world. To improve auditory realism, sound cues such as engine RPM, braking, and collision sounds were implemented through Unreal Engine's Blueprint system. Engine sounds were dynamically created by blending 3 distinct RPM-based sound clips, which increased in volume and complexity as vehicle speed rose. For haptic feedback, the road surface beneath each tire was detected, and Unreal Engine Blueprints generated steering wheel feedback signals proportional to road roughness. These modifications were straightforward to implement. They are described in detail so that others can implement them readily. A pilot study was conducted with 3 subjects, each driving a specific route composed of a straight
Duan, Lingbo, Xu, Boyu, Green, Paul
Technical Paper
Viability Assessment of Wind and Solar Renewable Energy Generation In Support of Nationwide Vehicle Electrification2025-01-8121To be published on 04/01/2025
In 2022, the U.S. transportation sector was the largest source of greenhouse gas emissions in the country, with the combination of passenger and commercial vehicles contributing 80% of these emissions. As adoption of passenger electric vehicles continues to climb, sights are being set on the electrification of heavy-duty commercial vehicle (HDCV) fleets. The sustainability of these shifts relies in part on the addition of significant renewable energy generation resources to both bolster the grid in the face of increased demand, and to prevent a shift in the source of greenhouse gas (GHG) emissions to the grid, as opposed to a true net reduction. Additionally, it is necessary to quantify the variations in economic viability across the country for these technologies as it pertains to their productive capabilities. Doing so will encourage investment and ensure that the transition to electrified HDCV fleets is commercially viable, as well as sustainable. In an effort to meet these goals
Miller, Brandon, Sun, Ruixiao, Sujan, Vivek
Technical Paper
An incremental coordinated control method for distributed drive electric vehicle through the anti-squat/lift/dive suspension2025-01-8267To be published on 04/01/2025
In this paper, an incremental coordinated control method through anti-squat/lift/dive suspension is proposed based on and suited to a distributed drive electric vehicle with front and rear dual motors. The precise relationship between the suspension reaction force and the driving force of the wheel is derived as the control model through an in-depth analysis of the wheel motion and force. Through imposing the first-order dynamics, the proposed method not only provides the longitudinal speed control of the vehicle but also suppresses the longitudinal, vertical and pitch vibration of the vehicle Simulation results show that the suspension reaction force formula derived in this paper is more suitable for dynamic conditions, and compared with the control method based on the simplified suspension anti-squat/lift/dive control model, the proposed method using the accurate control model has superior comprehensive control performance.
Feng, Cong, Wu, Guangqiang, Yang, Yuchen
Technical Paper
Objective System Level Sustainability Evaluation of Competing Materials for Demanding Automotive Applications2025-01-8607To be published on 04/01/2025
In response to a mix of drivers, including new and emerging global regulatory requirements, consumer sentiment and scarcity of resources, Global Automotive OEMs are setting new sustainability targets for their organizations. Engineers are faced with these new sustainability goals and must develop effective strategies to meet them while concurrently maintaining safety, cost, performance and customer satisfaction. Global Warming Potential (GWP100) as measured in CO2e through a Life Cycle Assessment (LCA) is the leading metric for evaluating the environmental impact of a product throughout its lifecycle. From Raw Material Sourcing (Cradle), Manufacturing and Assembly, and Customer Use all the way through to End of Life and Resource Recovery (Cradle) represents a Cradle-to-Cradle analysis. LCA’s can be conducted for various portions of a product’s life, however, when selecting materials for a given application, comparing GWP100 values at only the material level can be misleading. A lack of
Halsband, Adam, Leinemann, Tomke, Beer, Markus, Haiss, Eric
Technical Paper
Estimation of Tire Longitudinal Force under Combined Slip Condition Using an Intelligent Tire System2025-01-8275To be published on 04/01/2025
Under extreme driving conditions, such as emergency braking, rapid acceleration, and high-speed cornering, the tire, as the vehicle's only direct connection to the road, plays a critical role in influencing dynamic performance and driving stability. Accurately predicting and tire longitudinal force under such combined slip conditions is key to improving vehicle control precision and ensuring driving safety. This study proposes a tire longitudinal force estimation strategy based on an intelligent tire system. The core of this system consists of three integrated PVDF (Polyvinylidene Fluoride) sensors embedded in the tire, which, due to their exceptional sensitivity, can precisely capture dynamic deformation information of the tire under varying conditions. This provides real-time, detailed data to better understand the complex interaction forces between the tire and the road. To study and validate the longitudinal force estimation model, the research team employed a high-precision indoor
Zhang, Zipeng, Xu, Nan, Tang, Zepeng, Chen, Hong
Technical Paper
Tunnel Lining Crack Intelligent Recognition Based on YOLOv11 Algorithm2025-01-713702/21/2025
Tunnel linings are an important safeguard for the integrity and stability of tunnels. However, cracks in the tunnel lining may have extremely unfavourable consequences. With the acceleration of urbanisation and the increasing construction of tunnels, the problem of cracks in the concrete lining is becoming more and more prominent. These cracks not only seriously affect the stability of the structure, but also pose a serious threat to the safety of tunnel operation. If left unchecked, the cracks may expand further and cause various safety hazards, such as water leakage and falling blocks. This in turn will undermine the normal function of the tunnel and endanger the lives of tunnel users. It has been proved that the traditional manual method of detecting cracks in tunnels has problems such as low accuracy and low efficiency. In order to solve this problem, it is very necessary for this study to pioneer an intelligent method for identifying tunnel lining cracks using the YOLOv11
Zhang, Yalin, Niu, Pei, Guo, Feng, Yan, Wei, Liu, Jian, Kou, Lei
Technical Paper
Uncertainty Quantification for Predicting Low-Temperature Crack Resistance of Asphalt Mixture Base on Bayesian Neural Network2025-01-714302/21/2025
Developing models for predicting the low-temperature cracking resistance of asphalt mixtures is a complex process with a wide variety and complex influence mechanisms of variables, leading to higher uncertainty in the prediction results. Several models have been developed in this regard. This study developed a Bayesian neural network (BNN) model for predicting the fracture energy of low-temperature semi-circular bending (SCB) tests based on pavement condition measurements, traffic, climate, and basic parameters of the material. The model was trained and evaluated using low-temperature SCB test data from in-situ pavement core samples, and the results showed that the coefficient of determination (R2) of the BNN model was greater than 0.8 for both the training and testing sets. The variable importance scores showed that the decrease of transverse crack rating index (TCEI) and gradation were the most important factor affecting low-temperature fracture energy and that the ambient
Song, Ziyu, Ni, Fujian, Huang, Jiaqi, Jiang, Jiwang
Technical Paper
Matching and Fusing Multi-Source Vehicle Information in Highway Gantry Scenarios Using Convolutional Neural Networks2025-01-713602/21/2025
The performance differences of multiple sensors lead to inconsistencies, incompleteness, and distortion in the perception data of multi-source vehicle information in highway scenarios. Optimizing data fusion methods is important for intelligent toll collection systems on highways. First, this paper constructs a dataset for matching and fusing multi-source vehicle information in highway gantry scenarios. Second, it develops convolutional neural network models, Match-Pyramid-MVIMF-EGS and CDSSM-MVIMF-EGS, for this purpose. Finally, comparative experiments are conducted based on the constructed dataset to assess the performance of the Match-Pyramid-MVIMF-EGS and CDSSM-MVIMF-EGS models. The experimental results indicate that the Match-Pyramid-MVIMF-EGS model performs better than the CDSSM-MVIMF-EGS model, achieving matching and fusion accuracy of 93.07%, precision of 95.71%, recall of 89.17%, F1 scores of 92.32%, and 186 of training throughput respectively.
Wang, Junjun, Zhao, Chihang
Technical Paper
Driver Cognitive Distraction Recognition Based on Multi-Source Data from Simulated Driving Experiments2025-01-714002/21/2025
Nowadays, cognitive distraction in the process of driving has become a frequent phenomenon, which has led to a certain proportion of traffic accidents, causing a lot of property losses and casualties. Since the fact that cognitive distraction is mostly reflected in the driver's reception and thinking of information unrelated to driving, it is difficult to recognize it from the driver's facial features. As a result, the accuracy of prediction is usually lower relying solely on facial performance to detect cognitive distraction. In this research, fifty participants took part in our simulated driving experiment. And each participant conducted the experiment in four different traffic scenarios using a high-fidelity driving simulator, including three cognitive distraction scenarios and one normal driving scenarios. Firstly, we identified the facial performance indicators and vehicle performance indicators that had a significant effect on cognitive distraction through one-way ANOVA. Then we
Qu, Chixiong, Bao, Qiong, Qu, Qikai, Shen, Yongjun
Technical Paper
Semantic Segmentation of Lane Lines for Pix2Pix Network Introducing Ghost Module2025-01-720802/21/2025
Technology for lane line semantic segmentation is crucial for ensuring the safe operation of intelligent cars. Intelligent cars can now comprehend the distribution and meaning of scenes in an image more precisely thanks to semantic segmentation, which calls for a certain degree of accuracy and real-time network performance. A lightweight module is selected, and two previous models are improved and fused to create the lane line detection model. Finally, experiments are conducted to confirm the model's efficacy. This paper proposes a lightweight replacement program with the aim of addressing the issue of large parameterization in the generative adversarial network (GAN) model and difficult training convergence. The overall network structure is selected from the Pix2Pix network in the conditional generative adversarial network, and the U-net network of the generator is cut and replaced by the Ghost Module, which consists of a modified downsampling module that enhances the global fusion
Yang, Kun, Wang, Jian
Technical Paper
Fleet Sizing and Relocation Strategies for Shared Autonomous Vehicles under Uncertainty: A Two-Stage Robust Optimization Approach2025-01-719202/21/2025
Shared autonomous vehicles systems (SAVS) are regarded as a promising mode of carsharing service with the potential for realization in the near future. However, the uncertainty in user demand complicates the system optimization decisions for SAVS, potentially interfering with the achievement of desired performance or objectives, and may even render decisions derived from deterministic solutions infeasible. Therefore, considering the uncertainty in demand, this study proposes a two-stage robust optimization approach to jointly optimize the fleet sizing and relocation strategies in a one-way SAVS. We use the budget polyhedral uncertainty set to describe the volatility, uncertainty, and correlation characteristics of user demand, and construct a two-stage robust optimization model to identify a compromise between the level of robustness and the economic viability of the solution. In the first stage, tactical decisions are made to determine autonomous vehicle (AV) fleet sizing and the
Li, Kangjiao, Cao, Yichi, Zhou, Bojian, Wang, Shuaiqi, Yu, Yaofeng
Technical Paper
Validating Human Factors-Based Classification Models for Safe and Efficient Mixed-Autonomy Interactions at Intersections Using a Virtual Simulator12-08-02-001902/12/2025
The introduction of autonomous vehicles (AVs) promises significant improvements to road safety and traffic congestion. However, mixed-autonomy traffic remains a major challenge as AVs are ill-suited to cooperate with human drivers in complex scenarios like intersection navigation. Specifically, human drivers use social cooperation and cues to navigate intersections while AVs rely on conservative driving behaviors that can lead to rear-end collisions, frustration from other road users, and inefficient travel. Using a virtual driving simulator, this study investigates the use of a human factors-informed cooperation model to reduce AV reliance on conservative driving behaviors. Four intersection scenarios, each involving a left-turning AV and a human driver proceeding straight, were designed to obfuscate the right-of-way. The classification models were trained to predict the future priority-taking behavior of the human driver. Results indicate that AVs employing the human factors-informed
Ziraldo, Erika, Oliver, Michele
Journal Article
A reduced-order beam modelling approach of BIW for torsional and bending stiffness optimization2025-28-018702/07/2025
Noise, Vibration, and Harshness (NVH) simulations of vehicle bodies are crucial for assessing performance during the design phase. However, these simulations typically require detailed computer-aided design (CAD) models and are time-consuming. In the early stages of vehicle development, when only high-level vehicle sections are available, designing the body-in-white (BIW) structure to meet target values for bending and torsional stiffness is challenging and often requires multiple iterations. To address these challenges, this study deploys a reduced-order beam modelling approach. This method involves identifying the beam-like sections and major joints within the BIW and calculating their sectional properties (area, area moments of inertia along the plane’s independent axes, and torsion constant). These components form a simplified skeleton model of the BIW. Load and boundary conditions are applied to the suspension mount locations at the front and rear of the vehicle, and torsional and
Khan, Mohd Zishan Ali, Thanapati, Alok, Deshmukh, Chandrakant
Technical Paper
Exploring Trapezoidal Salt Gradient Solar Pond Performance A Combined Numerical and Experimental Analysis with and without Reflective Covered Surface2025-28-020102/07/2025
This research explores the use of salt gradient solar ponds (SGSPs) as an environmentally friendly and efficient method for thermal energy storage. The study focuses on the design, construction, and performance evaluation of SGSP systems integrated with reflectors, comparing their effectiveness against conventional SGSP setups without reflectors. Both experimental and numerical methods are employed to thoroughly assess the thermal behavior and energy efficiency of these systems. The findings reveal that the SGSP with reflectors (SGSP-R) achieves significantly higher temperatures across all three zones—Upper Convective Zone (UCZ), Non-Convective Zone (NCZ), and Lower Convective Zone (LCZ)—with recorded temperatures of 40.56°C, 54.2°C, and 63.1°C, respectively. These values represent an increase of 6.33%, 11.12%, and 14.26% over the temperatures observed in the conventional SGSP (SGSP-C). Furthermore, the energy efficiency improvements in the UCZ, NCZ, and LCZ for the SGSP-R are
J, Vinoth Kumar
Technical Paper
Aerospace & Defense Technology: February 202525AERP0202/06/2025
The Art of Reverse Engineering Yesteryear for Aerospace and Defense Data Storage Drives Manufacturing Spotlight: Machining Complex Parts and Materials for Space Flight and Exploration Notre Dame's New Boundary Breaking Mach 10 Quiet Wind Tunnel Shape-Shifting Antenna Poised to Transform Communications British Army Completes First Test of Drone Killing Radio Frequency Weapon A Swarm of Sensors, Rovers and Astronauts Explore the 'Moon' Researchers at the German Aerospace Center have developed a new approach to networked communications that could theoretically occur on the Moon or in environments on Earth where conventional communications are unavailable. Army Researchers Examine Nanotechnology for Climate Solutions Army scientists are joining forces with experts from across the nation to tackle the climate crisis using the power of nanotechnology Airman Brings Fuel Sampling Innovation to Eglin, Possibly Air Force The U.S. Air Force is testing a new prototype single point nozzle adapter
Magazine Issue
A Comparative Durability Cost Analysis of Internal Combustion Engine, Electric and Fuel Cell Vehicles2025-01-707401/31/2025
This study introduces the Total Cost of Ownership per Unit Operating Time (TCOP) as a novel indicator to assess the economic impact of vehicle durability. A comprehensive analysis is conducted for fuel cell vehicles (FCVs), battery electric vehicles (BEVs), and internal combustion engine vehicles (ICEVs) in light- and heavy-duty scenarios. The results show that in HDVs, the advantages of low prices for hydrogen and electricity are fully demonstrated due to their high durability. In contrast, for LDVs, the purchase cost plays a much larger role, accounting for 68% of the total cost, indicating a significant difference between vehicles. Improving durability can significantly enhance the competitiveness of FCVs. For FCVs, increasing the durability from the current levels of 150,000 km for LDVs and 600,000 km for HDVs to 20,8500 km and 1,122,000 km, respectively, would align their TCOP with that of current ICEVs. A sensitivity analysis shows that for HDVs. The focus should be placed on
Qin, Zhikun, Yin, Yan, Zhang, Fan, Yao, Junqi, Guo, Ting, Wang, Bowen
Technical Paper
Research on Fuel Cell Vehicle Performance Based on PEMFC Stack Degradation2025-01-707201/31/2025
The degradation of vehicle performance resulting from powertrain degradation throughout the lifecycle of alternative energy vehicles (AEVs) has consistently been a focal issue among scholars and consumers. The purpose of this paper is to utilize a one-dimensional vehicle simulation model to analyze the changes in power performance and economy of fuel cell vehicles as the Proton Exchange Membrane Fuel Cell (PEMFC) stack degrades. In this study, a simulation model was developed based on the design parameters and vehicle architecture of a 45kW fuel cell vehicle. The 1D model was validated for accuracy using experimental data. The results indicate that as the stack performance degrades, the attenuation rate of the fuel cell engine is further amplified, with a degradation of up to 13.6% in the system's peak output power at the End of Life (EOL) state after 5000 hours. Furthermore, the level of economic performance degradation of the complete vehicle in the EOL state is dependent on the
Li, You, Du, Jing, Guo, Donglai, Wang, Kai, Wang, Yupeng
Technical Paper
Thermal Parameters Identification Method for Induction Machines Based on a Parallel Branches Network2025-01-705401/31/2025
Monitoring the rotor temperature of drive machines is crucial for the safety and performance of electric vehicles. However, due to the complex operating conditions of electric vehicles, the thermal parameters of vehicular induction machines (IMs) vary significantly and are difficult to identify accurately. This article first establishes a concise but effective thermal network for IMs and analyzes the influencing factors of thermal parameters. Then, a parameter identification network (PIN) with multiple parallel branches is constructed to learn the mapping relationship between electromechanical variables and thermal parameters. Afterward, temperature datasets for network training are built through bench testing. Finally, the effectiveness of identified parameters for rotor temperature estimation application is verified, demonstrating improved interpretability, generalization ability, and accuracy compared to an end-to-end neural network.
Jiang, Shang, Hu, Zhishuo
Technical Paper
Driving Cycle Simulation and Performance Comparison of Hydrogen Engine Hybrid Electric Vehicle2025-01-700101/31/2025
As a clean energy, low carbon and pollution-free, hydrogen is the preferred alternative fuel for traditional internal combustion engines. However, how to use hydrogen internal combustion engine to achieve satisfactory performance under vehicle conditions is still a challenge.In this paper, a vehicle simulation model is established based on a modified 25-ton hydrogen internal combustion engine truck, and the model is designed as a hybrid model by selecting a suitable motor. The two models are used to simulate the CHTC (China Heavy-duty Commercial Vehicle Test Cycle) cycle conditions. According to the simulation results, compared with the original vehicle's power performance and economy, the results show that the power performance is increased by 100%, and the economy is increased by 20%. Hybrid technology can effectively improve the performance of the vehicle.
Bai, Xueyan
Technical Paper
Research on Economic Energy Management Strategies for Range-Extended Energy Storage Microgrids2025-01-709301/31/2025
This paper presents the strategy design, development, and detailed simulation of an Energy Management System (EMS) for a range extender energy storage microgrid project. Initially, a microgrid system model including photovoltaic (PV) and energy storage devices was established. Secondly, the Latin Hypercube Sampling (LHS) method was employed to generate possible operational scenarios, and an improved K-means clustering algorithm was used for scenario classification. Subsequently, a series of constraints were constructed for the economic viability of the microgrid to minimize its annualized comprehensive cost, while satisfying power balance and equipment operation. Finally, the microgrid system was simulated and solved using the GUROBI solver, covering cost analyses of the energy storage system and diesel generators under different configurations, as well as the State of Charge (SOC) variations of the energy storage system. The simulation results indicate that, after considering the one
Hua, Yuwei, Jin, Zhenhua, Huang, Huilong, Wang, Zihao
Technical Paper
Multi-Criteria Evaluation and Operating Parameter Optimization of the SOFC-GT System under Variable Loads2025-01-707701/31/2025
At present, due to the complexity and nonlinearity, the thermal safety and economic feasibility assessment and optimization of the Solid Oxide Fuel Cell-Gas Turbine (SOFC-GT) system under variable loads is important to extend the service life and reduce the cost. To solve these problems, this paper proposes a top-level cyclic SOFC-GT system, which considers the design of two-stage preheaters, as well as the impact of material reaction kinetics and thermoelectric coupling characteristics on system performance. Furthermore, the multi-criteria evaluation of the SOFC-GT system under variable loads has been studied, with evaluation indicators primarily including thermodynamic and economic indicators. Afterwards, a Spearman-based parametric sensitivity analysis is used to explore the response trends of performance indicators within the SOFC-GT system. Additionally, an intelligent learning method based on convolutional neural network is designed to determine the dynamic behavior between
Fan, Liyun, Kui, Xu, Chen, Chen, Shen, Chongchong, Li, Bo, Wei, Yunpeng
Technical Paper
Numerical Study of Aerodynamic Flow and the Effects of Spoiler Wings on a Formula Student Race Car2024-01-524701/28/2025
Current work details the preliminary CFD analysis performed on custom-built race car by Team Sakthi Racing team as part of Formula SAE competition using OpenFOAM. The body of the race car is designed in compliance with FSAE regulations, OpenFOAM utilities and solvers are used to generate volumetric mesh and perform CFD analysis. Formula student tracks are typically designed with numerous sharp turns and a few long straights to maintain low speeds for safety. In order to enhance the cars’ performance in sharp turns, the race car should be equipped with aerodynamic devices like nose cone and wings on both the rear and front ends within the confines of the formula student racing rules. Thus, efficient aerodynamic design is highly critical to maximizing tire grip by ensuring consistent contact with the track, reducing the risk of skidding, and maintaining control, especially during high-speed maneuvers. In this work, the performance and behavior of the race car, both with and without the
Rangarajan, Kishore, Pushpananthan, Blesscin, Anumolu, Lakshman, Selvakumar, Kumaresh, Jayakumar, Shyam Sundar
Technical Paper
SAE TOMORROW TODAY: Launching Human Space Travel with a Luxury Balloon1349801/23/2025
Imagine a six-hour journey to outer space that includes a world-class meal, cocktail service, Wi-Fi, and unprecedented views of Earth. This experience could soon become reality. Space Perspective, the world's first carbon-neutral spaceflight experience company, is commercializing space travel with Spaceship Neptune, a pressurized capsule propelled by a giant SpaceBalloon(TM). The experience is designed to be gentle and accessible with no rockets, weightlessness, heavy g-forces, or training required. Alongside world-class meal and cocktail service, space travelers will also enjoy views through the largest windows ever flown to space, Wi-Fi, and a proper restroom. To learn more, we sat down with Taber MacCallum, Founder and Chief Technology Officer, Space Perspective, to discuss the technical development of the SpaceBalloon(TM) and how the company is unlocking the market for space travel in a new and innovative way. We'd love to hear from you. Share your comments, questions and ideas for
Hineman, Marcie
Podcast
2023–2024 Reviewers13-05-03-002212/31/2024
2023–2024 Reviewers
Pilla, Srikanth
Journal Article
A Study of India’s Transition to Electric Mobility and Its Impact on Associated Partners2024-01-511112/27/2024
The transition from internal combustion engine (ICE) industry to electric vehicle (EV) industry has significant financial implications for both the automotive industry, government, and associated partners. The shift to EVs could lead to savings in foreign exchange reserves, the creation of new jobs, and a reduction in greenhouse gas emissions. However, the transition could also result in job losses in the automobile and its associated manufacturing industry. This study aims to analyze the impact of this transition on different stakeholders in India. The study takes into account the different financial aspects that includes production, technology, government policy, skilling, employability, job creation, and other associated aspects on Indian economy. For the projected study different cases were considered with 2030 as the projected year with 30% EVs. A modest attempt is made to analyze the impact on associated partners. The findings of the study suggest that the transition to EVs could
Vashist, Devendra, Malik, Varun, Pandey, Sachchidanand
Technical Paper
Simulation Analysis of Multi-Objective Functions in Mobile Robot Navigation Based on Enhanced Deep Q-Network Algorithm2024-01-511012/24/2024
This research, path planning optimization of the deep Q-network (DQN) algorithm is enhanced through integration with the enhanced deep Q-network (EDQN) for mobile robot (MR) navigation in specific scenarios. This approach involves multiple objectives, such as minimizing path distance, energy consumption, and obstacle avoidance. The proposed algorithm has been adapted to operate MRs in both 10 × 10 and 15 × 15 grid-mapped environments, accommodating both static and dynamic settings. The main objective of the algorithm is to determine the most efficient, optimized path to the target destination. A learning-based MR was utilized to experimentally validate the EDQN methodology, confirming its effectiveness. For robot trajectory tasks, this research demonstrates that the EDQN approach enables collision avoidance, optimizes path efficiency, and achieves practical applicability. Training episodes were implemented over 3000 iterations. In comparison to traditional algorithms such as A*, GA
Arumugam, Vengatesan, Alagumalai, Vasudevan, Rajendran, Sundarakannan
Technical Paper
2023–2024 Reviewers03-17-08-006512/24/2024
2023–2024 Reviewers
Ryan, Tom
Journal Article
Augmenting Airworthiness Education via Concept Maps: An Exploratory Study among University Students01-18-01-000112/24/2024
Aerospace engineering programmes typically cover airworthiness philosophies, principles, structures, processes, and procedures. The industry has recently recognized the need to enhance the graduate engineers’ skills around airworthiness. This has led to introduction of standards acting as guides for developing curricula and content for university airworthiness courses. Concept maps, a visual mapping of concepts in a hierarchical way, enjoy wide use in engineering education (teaching and assessment). Airworthiness courses are both technical and legalistic, presenting challenges to students when it comes to understanding complex and intertwined regulations. Schematic representations of concepts can foster the cognitive processes of learning. Concept maps can assess efficiently and comprehensively a multitude of airworthiness topics. This study examines the feasibility of applying concept maps in airworthiness education. Fill-in-a-map concept maps were developed as assessment tools for an
Kourousis, Kyriakos, Chatzi, Anna
Journal Article
2023–2024 Reviewers02-17-04-002612/23/2024
2023–2024 Reviewers
Sandu, Corina
Journal Article
Challenges in Cost Reduction for Automotive Parts: A Comprehensive Analysis2024-36-017412/20/2024
The automotive industry is facing unprecedented pressure to reduce costs without compromising on quality and performance, particularly in the design and manufacturing. This paper provides a technical review of the multifaceted challenges involved in achieving cost efficiency while maintaining financial viability, functional integrity, and market competitiveness. Financial viability stands as a primary obstacle in cost reduction projects. The demand for innovative products needs to be balanced with the need for affordable materials while maintaining structural integrity. Suppliers’ cost structures, raw material fluctuations, and production volumes must be considered on the way to obtain optimal costs. Functional aspects lead to another layer of complexity, once changes in design or materials should not compromise safety, durability, or performance. Rigorous testing and simulation tools are indispensable to validate changes in the manufacturing process. Marketing considerations are also
Oliveira Neto, Raimundo Arrais, Souza, Camila Gomes Peçanha, Brito, Luis Roberto Bonfim, Guimarães, Georges Louis Nogueira
Technical Paper
Numerical Simulation of Drive Cycles for Formula Electric Vehicle Comparative Powerflow Analysis2024-36-009712/20/2024
This paper proposes a theoretical drive cycle for the competition, considering the battery pack project under design. The vehicle has a non-reversible, double-stage gear train, created without a dynamic investigation. To evaluate the effect on performance, several ratios were analyzed. Dynamic model uses Eksergian’s Equation of Motion to evaluate car equivalent mass (generalized inertia), and external forces acting on the vehicle. The circuit is divided into key locations where the driver is likely to accelerate or brake, based on a predicted behavior. MATLAB ODE Solver executed the numerical integration, evaluating time forward coordinates, creating the drive cycle. Linear gear train results provided data as boundary conditions for a second round of simulations performed with epicyclic gear trains. Model is updated to include their nonlinearity by differential algebraic equation employment with Lagrange multipliers. All data undergoes evaluation to ascertain the mechanical and
Rodrigues, Patrícia Mainardi Tortorelli, Silveira, Henrique Leandro
Technical Paper
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