Browse Topic: Human Factors and Ergonomics

Items (20,092)
Online road profiling capability is required for automotive active suspension systems to be realized in a consumer and commercial landscape. One challenge that impedes the realization of these systems is the need for the online road profiler to maintain an optimal spatial resolution of the oncoming road profile. Shifting of the road profiling sensor measurement frame of reference due to body motion experienced by the vehicle can negatively impact profiling accuracy. Prior work proposed a corrective look-ahead road profiling system (CLARPS) and demonstrated the CLARPS architecture and initial MATLAB/Simulink simulation environment. First, this work further develops the robust simulation environment. The simulation allows the look-ahead viewing angles to be optimized for the best road profile spatial resolution and facilitates a study on the impact of road profiler sensor location on the accuracy of the generated road profile. Second, this work introduces a lab-scale physical CLARPS
Morison, DaneMynderse, James
Technology development for enhancing passenger experience has gained attention in the field of autonomous vehicle (AV) development. A new possibility for occupants of AVs is performing productive tasks as they are relieved from the task of driving. However, passengers who execute non-driving-related tasks are more prone to experiencing motion sickness (MS). To understand the factors that cause MS, a tool that can predict the occurrence and intensity of MS can be advantageous. However, there is currently a lack of computational tools that predict passenger's MS state. Furthermore, the lack of real-time physiological data from vehicle occupants limits the types of sensory data that can be used for estimation under realistic implementations. To address this, a computational model was developed to predict the MS score for passengers in real time solely based on the vehicle's dynamic state. The model leverages self-reported MS scores and vehicle dynamics time series data from a previous
Kolachalama, SrikanthSousa Schulman, DanielKerr, BradleyYin, SiyuanWachsman, Michael BenPienkny, Jedidiah Ethan ShapiroJalgaonkar, Nishant M.Awtar, Shorya
Predictive performance simulation of a high-efficiency lightweight vehicle is performed through development of a multi-physics MATLAB Simulink model including advanced vehicle dynamics. The vehicle is put into a three-dimensional representation of the racetrack, including its dimensions, slope, banking, and adhesion coefficient along the model space, elaborated from the track GPS data points. The vehicle’s reference trajectory is not priorly provided to the model at the simulation start as, during run-time, a predictive Steering Angle Generation (SAG) algorithm based on Nonlinear Model Predictive Control (NMPC) computes the optimal steering angle input needed to drive the vehicle on the track within its limits. Computation is based on fast predictive simulations of a simplified version of dynamics modelling of the vehicle. Each single simulation exploits a different possible steering angle to be applied by the virtual driver, starting from the initial conditions given by the actual
De Carlo, MatteoManzone, Simonede Carvalho Pinheiro, HenriqueCarello, Massimiliana
This paper explores the application of a modeled torque converter in the real-time control of a hybrid electric powertrain. The study aims to determine the optimal gear selection and engine speed target required to meet driver demands. It also delves into the concept of torque converter input inertia compensation, particularly during open, open-to-close, and close-to-open states. The primary objective is to achieve the intended driver torque while minimizing torque sag and bumps during these transitions. This approach ensures improved powertrain response and maintains system integrity within the operational limits of the battery, motors, and engine.
Madireddy, Krishna ChaitanyaBanuso, AbdulquadriSha, HangxingPatel, NadirshKarogal, IndrasenKhanal, Shishir
Abstract Real-world driving data is an invaluable asset for several types of transportation research, including emissions estimation, vehicle control development, and public infrastructure planning. Traditional methods of real-world driving data collection use expensive GPS-based data logging equipment which provide advanced capabilities but may increase complexity, cost, and setup time. This paper focuses on using the Google Maps application available for smartphones due to the potential to scale-up real-world driving data logging. Samples of the potential data processing and information that can be gathered by such a logging methodology is presented. Specifically, two months of Google Maps driving data logged by a rural Michigan resident on their smartphone may provide insights on their driving range, duration, and geographic area of coverage (AOC) to guide them on future vehicle purchase decisions. Aggregating such statistics from crowd-sourcing real-world driving data via Google
Manoj, AshwinYin, SallyAhmed, OmarVaishnav, ParthStefanopoulou, AnnaTomkins, Sabina
Battery health status and driving rangeof electric vehicles (EVs) are critical factors in determining their market penetration. Choosing an optimal charging strategy—specifying how, when, and for how long to charge based on the driver’s travel behavior—can significantly mitigate battery degradation and extend battery life. This study introduces an EV powertrain system energy model designed to enhance the prediction accuracy of battery status under real-world driving conditions. By integrating with the Q-learning approach, this studyprovides tailored recommendations on charging behaviors, including charger type, start time, and charging duration. This study innovatively considers the rental costs caused by the battery capacity not being able to meet the daily driving range. Simulating a typical three-year usage scenario for an average driver in New England, the results indicate that thecharging strategy proposed by this study reduces battery degradation rates by 1.53‰, 3.57‰, and 7.68
Wang, JiayiJing, HaoOu, Shiqi (Shawn)Lin, Zhenhong
This paper introduces a novel approach to optimize battery power usage and optimal engine torque for Axle disconnect device engagement under power constrained scenarios for range extended hybrid vehicles. Range extended hybrid architecture provides benefits of BEV architecture and relief the range anxiety that BEV drivers often have. The Axle disconnect device helps improve the efficiency of the battery power usage when it is disconnected and provides better drivability and performance to fulfill driver demand when it is connected [1]. Under power constraint scenario, the disconnect device engagement could take too long or eventually fail to engage and result in degradation for drivability and vehicle level performance. This novel approach is utilizing the engine to either generate more power to spin up the disconnect motor faster under discharge limited case or generate less power to allow the disconnect motor to spin down under charge limited case. The effectiveness of this approach
Sha, HangxingMadireddy, Krishna ChaitanyaBanuso, AbdulquadriKhanal, ShishirRock, JoePatel, Nadirsh
As the electrification of chassis systems accelerates, the demand for fail-safety strategies is increasing. In the past, the steering system was mechanically connected, so the driver could respond directly to some extent. However, the Steer-by-Wire (SbW) system is composed of the column and rack bar as electrical signals, so the importance of response strategies for steering system failure is gradually increasing. When a steering system failure occurs, a differential braking control using the difference in braking force between the left and right wheels was studied. Recently, some studies have been conducted to model the wheel reaction force generated during a differential braking. Since actual tires and road surfaces are nonlinear and cause large model errors, model-based control methods have limited performance. Also, in previous studies assumed that the driver normally operates the steering wheel in a failure situation. However, if limited to a situation such as autonomous driving
Kim, SukwonKim, Young GwangKim, SungDoMoon, Sung Jin
Drivers sometimes operate the accelerator pedal instead of the brake pedal due to driver error, which can potentially result in serious accidents. To address this, the Acceleration Control for Pedal Error (ACPE) system has been developed. This system detects such errors and controls vehicle acceleration to prevent these incidents. The United Nations is already considering regulations for this technology. This ACPE system is designed to operate at low speeds, from vehicle standstill to creep driving. However, if the system can detect errors based on the driver's operation of the accelerator pedal at various driving speeds, the system will be even more effective in terms of safety. The activation threshold of ACPE is designed to detect operational errors, and it is necessary to prevent the system from being activated during operational operations other than operational errors, i.e., false activation. This study focuses on the pedal operation characteristics of pedal stroke speed and
Natsume, HayatoShen, ShuncongHirose, Toshiya
Steering feeling plays a critical role in the driving experience and is one of the most significant topics during a new vehicle development process. To reach a consensus for the customers’ satisfaction in both the subjective and objective characteristics in a particular market segment, there have been several studies to investigate the correlations between subjective and objective evaluations of on-center steering feeling. However, it is still not clear how to determine the steering characteristic based on the correlations. In this paper, a series of new correlations between subjective and objective evaluations are built, which focus on steering stiffness, on-center feel, torque symmetry, torque ripple etc. Firstly, a set of objective metrics which are followed by professional test drivers or tuning experts have been extracted from 12 vehicles’ on-center handling test based on ISO 13674-1 2023, these vehicles covering different motorcycle type, various brands and diverse tuning styles
Jin, AnkangLuo, KaijieYang, JianyuanZheng, Yue
E-mobility is revolutionizing the automotive industry by improving energy-efficiency, lowering CO2 and non-exhaust emissions, innovating driving and propulsion technologies, redefining the hardware-software-ratio in the vehicle development, facilitating new business models, and transforming the market circumstances for electric vehicles (EVs) in passenger mobility and freight transportation. Ongoing R&D action is leading to an uptake of affordable and more energy-efficient EVs for the public at large through the development of innovative and user-centric solutions, optimized system concepts and components sizing, and increased passenger safety. Moreover, technological EV optimizations and investigations on thermal and energy management systems as well as the modularization of multiple EV functionalities result in driving range maximization, driving comfort improvement, and greater user-centricity. This paper presents the latest advancements of multiple EU-funded research projects under
Ratz, FlorianBäuml, ThomasKompara, TomažKospach, AlexanderSimic, DraganJan, PetraMöller, SebastianFuse, HiroyukiParades Barros, EstebanArmengaud, EricAmati, NicolaSorniotti, AldoLukesch, Walter
In a three-phase voltage source inverter, in order to prevent the direct short circuit of the upper and lower tubes of the bridge arm and ensure the normal operation of the inverter, microsecond-level dead time needs to be added when the power devices are turned on and off. However, due to the dead-time effect, slight distortion may occur in the inverter within the modulation period, and this distortion will eventually lead to harmonic components in the output current after accumulation, thereby generating torque ripple. Against the above background, implementing dead-time compensation strategies is very important. To compensate for the voltage error caused by the dead-time effect, current polarity determination is required first. Then, the dead time is compensated, thereby indirectly compensating for the voltage error caused by the dead-time effect. Regarding the dead-time compensation time, without changing the hardware, this paper proposes a solution to turn off the dead-time
Jing, JunchaoZhang, JunzhiZuo, BotaoLiu, YiqiangYang, TianyuZhu, Lulong
Neck injury is one of the most common injuries in traffic accidents, and its severity is closely related to the posture of the occupant at the time of impact. In the current era of smart vehicle, the triggered AEB and the occupant's active muscle force will cause the head and neck to be out of position which has significant affections on the occurrence and severity of neck injury responses. Therefore, it is very important to study the influences of active muscle force on neck injury responses in in frontal impact with Automatic Emergency Braking conditions. Based on the geometric characteristics of human neck muscles in the Zygote Body database, the reasonable neck muscle physical parameters were obtained firstly. Then a neck finite element model (FEM) with active muscles was developed and verified its biofidelity under various impact conditions, such as frontal, side and rear-end impacts. Finally, using the neck FEM with or without active muscle force, a comparative study was
Junpeng, XuGan, QiuyuJiang, BinhuiZhu, Feng
This study investigates the influence of magnetorheological (MR) dampers in semi-active suspension systems (SASSs) on ride comfort, vehicle stability, and overall performance. Semi-active suspension systems achieve greater flexibility and efficacy by combining MR dampers with the advantages of active and passive suspension systems. The study aims to measure the benefits of MR dampers in improving ride comfort, vehicle stability, and overall system performance. The dynamic system model meets all required performance criteria. This study demonstrates that the proposed artificial intelligence approach, including a fuzzy neural networks proportional-integral-derivative (FNN-PID) controller, significantly enhances key performance criteria when tested under various road profiles. The control performance requirements in engineering systems are evaluated in the frequency and time domains. A quarter-car model with two degrees of freedom (2 DOF) was simulated using MATLAB/Simulink to assess the
M.Faragallah, MohamedMetered, HassanAbdelghany, M.A.Essam, Mahmoud A.
The rapid development of intelligent and connected vehicles is transforming them into data-rich information carriers, which generate and store vast amounts of sensitive information. However, the frequent sharing of resources within these vehicles poses substantial risks to user privacy and data security. Should sensitive resources be accessed maliciously, the consequences could be severe, leading to significant threats to the safety, property, and reputation of both drivers and passengers. To address these risks, this paper proposes an adaptive risk-based access control with Trusted Execution Environment (TEE) specifically designed for vehicles, aimed at managing and restricting access permissions based on risk assessments. Firstly, this paper designs an adaptive risk model in accordance with ISO/SAE 21434, taking into account factors such as the security levels of subjects and objects, context, and the risk history of subjects to separately quantify threats and impacts. By adjusting
Luo, FengLi, ZhihaoWang, JiajiaLuo, Cheng
Many methods have been proposed to accurately compute a vehicle’s dynamic response in real-time. The semi-recursive method, which models using relative coordinates rather than dependent coordinates, has been proven to be real-time capable and sufficiently accurate for kinematics. However, not only kinematics but also the compliance characteristics of the suspension significantly impact a vehicle’s dynamic response. These compliance characteristics are mainly caused by bushings, which are installed at joints to reduce vibration and wear. As a result, using relative or joint coordinates fails to account for the effects of bushings, leading to a lack of compliance characteristics in suspension and vehicle models developed with the semi-recursive method. In this research, we propose a data-driven approach to model the compliance characteristics of a double wishbone suspension using the semi-recursive method. First, we create a kinematic double wishbone suspension model using both the semi
Zhang, HanwenDuan, YupengZhang, YunqingWu, Jinglai
In the pre-crash emergency braking scenario, the occupant inside the vehicle will move forward due to inertia, deviating from the standard upright seating position for which conventional restraint systems are designed. Previous studies have mainly focused on the influence of out-of-position (OOP) displacement on occupant injuries in frontal collisions, and provided solutions such as active pretensioning seatbelts (APS). But little attention has been paid to the influence of OOP on whiplash injury during a subsequent rear-end collision. To investigate the forward OOP impact on whiplash injuries and the effectiveness of APS in this accident scenario, a vehicle interior model with an active human body model (AHBM) was setup in the MADYMO simulation platform. Different braking strengths (0.8g and 1.1g), APS triggering times (from 0.2s before to 0.2s after the braking initiation) and pretensioning forces (from 100N to 600N) were input to the simulation matrix. The occupant’s forward OOP
Fei, JingQiu, HangWang, PeifengLiu, YuCheng, James ChihZhou, QingTan, Puyuan
Comprehensive requirements generation is a critical stage of the design process. Requirements are used to bound the design space and to guide the selection and evaluation of various solutions. Requirements can be categorized as either functional, defining things that the solution must do (such as produce a certain amount of horsepower), or non-functional, defining desirable qualities of the solution (such as weigh less than a particular value). Functional requirements are relatively easy to define and are often associated with particular components or subsystems within the design. As such, they can be the main focus of academic design instruction and therefore the design projects undertaken by novice designers. However, non-functional requirements (NFRs) capture important characteristics of the design solution and should not be ignored. Because of their nature, they are also difficult to assign to a particular subset of components or subsystem within the system. In this study, a group
Sutton, MeredithAnbuvanan, AadithanCastanier, Matthew P.Turner, CameronKurz, Mary E.
Research on modeling head injury metrics and head acceleration waveforms from real-world collisions has been limited compared to vehicle crash pulses. Prior studies have used rectangular, triangular, polynomial, half-sine, and haversine pulse functions to model vehicle crash pulses and have employed more complex approximations for head injury metrics. This study aimed to develop a method to predict 15 ms Head Injury Criterion (HIC15) in frontal passenger vehicle impacts using these simple pulse functions, where only occupant peak head acceleration and head impact duration are known. Vehicle crash tests from the New Car Assessment Program (NCAP) were selected for frontal impacts that included driver occupants. Head acceleration and shoulder belt load channels of Hybrid III 50th percentile male anthropomorphic test devices were collected and separated for training a set of ratios and testing their performance. Rectangular, triangular, quadratic, half-sine, and haversine pulse functions
Westrom, ClydeTanczos, RachelAdanty, KevinShimada, Sean
The rapid adoption of electric vehicles (EVs), driven by stricter emissions norms, is transforming both urban and rural mobility. However, significant challenges remain, particularly concerning the charging infrastructure and battery technology. The limited availability of charging stations and the reliance on current high-energy-density cells restrict the overall effectiveness of the e-mobility ecosystem. These constraints lead to shorter vehicle ranges and longer charging times, contributing to range anxiety—one of the most critical barriers to widespread EV adoption. Adding to these challenges, auxiliary systems, especially air-conditioning (AC) systems, significantly impact energy consumption. Among all auxiliary systems, the AC system is the most energy-intensive, often exacerbating range anxiety by reducing the distance an EV can travel on a single charge. Hence, it is essential to focus on enhancing the efficiency of AC systems. This involves redefining and optimizing system
Sen, SomnathJadhav, YashSingh, KaramjeetSorte, SwapnilAnwar, Md Tahir
This study introduces an innovative torque vectoring control strategy designed to enhance ride comfort in autonomous electric vehicles. The approach seamlessly integrates steering and rear axle force control within a model predictive control (MPC) framework, enabling real-time optimization of comfort and handling performance. The proposed control method is applied to a two-rear-motor vehicle model, where the MPC algorithm adjusts steering angles and tire forces to minimize discomfort caused by yaw rate and lateral acceleration. Simulation results from a lane-change scenario demonstrate significant improvements in comfort metrics compared to conventional torque vectoring control strategies. The findings highlight the ability of the proposed method to significantly enhance ride comfort without compromising vehicle dynamics. This integrated and adaptive control strategy offers a promising solution for improving passenger satisfaction in autonomous electric vehicles, with potential
Zhao, BolinLou, BaichuanHe, XianqiXue, WanyingLv, Chen
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, LingboXu, BoyuGreen, Paul
Autonomous Vehicles (AVs) have transformed transportation by reducing human error and enhancing traffic efficiency, driven by deep neural network (DNN) models that power image classification and object detection. However, to maintain optimal performance, these models require periodic re-training; failure to do so can result in malfunctions that may lead to accidents. Recently, Vision-Language Models (VLMs), such as LLaVA-7B and MoE-LLaVA, have emerged as powerful alternatives, capable of correlating visual and textual data with a high degree of accuracy. These models’ robustness and ability to generalize across diverse environments make them especially suited to analyzing complex driving scenarios like crashes. To evaluate the decision-making capabilities of these models across common crash scenarios, a set of real-world crash incident videos was collected. By decomposing these videos into frame-by-frame images, we task the VLMs to determine the appropriate driving action at each frame
Fernandez, DavidMohajerAnsari, PedramSalarpour, AmirPesé, Mert D.
To effectively improve the performance of chassis control of a four in-wheel motor (IWM)-driven electric vehicles (EVs), especially in combing nonlinear observer and chassis control for improving road handling and ride comfort, is a challenging task for the IWM-driven EVs. Simultaneously, inaccurate state-based control and uncertainty with system input, are always existing, e.g., variable control boundary, varying road input or control parameters. Due to the higher fatality rate caused by variable factors, how to precisely chose and enforce the reasonable chassis prescribed performance control strategy of IWM-driven EVs become a hot topic in both academia and industry. To issue the above mentioned, the paper proposes a novel observer-based prescribed performance control to improve IWM-driven EVs chassis performance under the double lane change steering. Firstly, a nonlinear nine degree-of-freedom of full-car model is developed to describe vehicle chassis dynamics, and the proposed
Wang, ZhenfengLong, JiarongLi, ShengchongZhang, XiaoyangZhao, Binggen
In order to effectively predict the vehicle safety performance and reduce the cost of enterprise safety tests, a generalized simulation model for active and passive vehicle safety was proposed. The frontal driver-side collision model under the intervention of the Autonomous Emergency Braking (AEB) was created by using the MADYMO software. The collision acceleration obtained from the sled test was taken as the original input of the model to conduct simulation for the working conditions under different sitting postures of the human body. The injury values of various parts of the Hybrid III 50th dummy were read. Based on the correlation between the two, an active and passive simulation model was established through the Back Propagation (BP) neural network. The input of the model was the inclination angle centered on the dummy's waist, and the output was the acceleration of the dummy's head. The results showed that the comprehensive prediction accuracy rate exceeded 80%. Therefore, the
Ge, Wangfengyao, LV
The study analyzed data from on-road drives with a pre-production Level 2 (L2) partial automation system using a sample of 27 drivers ranging from 21 to 75 years of age. The system provides continuous automatic lateral and longitudinal control but requires the driver to remain attentive and intervene when necessary. The L2 system was equipped with a Driving Monitoring System (DMS) that issued escalating alerts to remind the driver to pay attention or take over when needed. During the 14-month study period, drivers completed 354,768 miles of travel with the L2 system engaged, totaling 5,913 trips. The results of the study showed that drivers were highly responsive to attention reminders and takeover alerts, with high compliance rates and quick response times. Importantly, there was no evidence of habituation to these alerts over time. These findings support the effectiveness of the system's DMS and alert HMI (Human-Machine Interface) strategy in promoting the proper use of the system
Llaneras, RobertGlaser, YiGreen, CharlesAugust, MaureenLandry, Steven
In this work, design optimization for the lightweight of the body frame of a commercial electric bus with the requirements of stiffness, strength and crashworthiness is presented. The technique for order preference by similarity to ideal solution (TOPSIS) is applied to calculate the components that have a great impact on the output response of the static modal model and the rear-end collision model. The thickness of the five components with the highest contribution in the two models is determined as the final design variable. Design of experiment (DOE) is carried out based on the Latin Hypercube sampling method, and then the surrogate models are fitted by the least squares regression (LSR) method based on the DOE sampling data. The error analysis of the surrogate model is carried out to determine whether it can replace the finite element (FE) model for optimization, then the optimization scheme for lightweight optimization of electric bus frame is implemented based on the algorithm of
Yang, XiujianTian, DekuanLiu, JiaqiCui, YanLin, Qiang
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, YinuoZhang, MiaomiaoXue, MingJin, Xin
Plasticized polyvinyl chloride (PVC) has many applications in automotive industry including electrical harnesses, door handles, seat and head rest covers, and instrument panel (IP) and other interior trim. In IP applications, the PVC skin plays a critical role in passenger airbag deployment (PAB) by tearing along the scored edge of the PAB door and allowing the door to open and the airbag to inflate to protect the occupant. As part of the IP, the PVC skin may be exposed to elevated temperatures and ultraviolet (UV) radiation during the years of the vehicle life cycle which can affect the PVC material properties over time and potentially influence the kinematics of the airbag deployment. Chemical and thermal aging of plasticized PVC materials have been studied in the past, yet no information is found on how the aging affects mechanical properties at high rates of loading typical for airbag deployment events. This paper compares mechanical properties of the virgin PVC-based IP skin
G, KarthiganSavic, VesnaRavichandran, Gowrishankar
Drivers present diverse landscapes with their distinct personalities, preferences, and driving habits influenced by many factors. Though drivers' behavior is highly variable, they can exhibit clear patterns that make sorting them into one category or another possible. Discrete segmentation provides an 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 and trip-based methodologies
Chavan, Shakti PradeepChinnam, Ratna Babu
Efficient and sustainable transportation in urban environments depends on understanding driving behaviors, and their implications. This study explores into the distinction between aggressive and non-aggressive driving patterns, leveraging an on-road driving dataset provided by an automotive company. By contrasting this data with established Fuel Economy cycles from United States Environmental Protection Agency (EPA) and employing curve-fitting techniques, the research not only reveals driving patterns but also predicts potential behaviors in unfamiliar scenarios. Results show significantly different acceleration profile patterns between different driving behaviors which has serious impact in fuel economy and environmental wellness. The findings highlights the environmental impact of driving behaviors, paving the way for environmentally responsible policy recommendations and sustainable driving practices.
Padmanaban, GandhimathiFeng, FredDai, EdwardSaini, AnkitHu, GuopengZhao, Yanan
This literature review examines the concept of Fitness to Drive (FTD) and its impairment due to drug consumption. Using a Systematic Literature Review (SLR) methodology, the paper analyzes literature from mechanical engineering and related fields to develop a multidisciplinary understanding of FTD. Firstly, the literature is analysed to provide a definition of FTD and collect methods to assess it. Secondly, the impact of drug use on driving performance is emphasized. Finally, driving simulators are presented as a valid possibility for analysing such effects in a safe, controlled and replicable environment. Key findings reveal a lack of a comprehensive taxonomy for FTD, with various assessment protocols in use. Only static simulators are employed for drug evaluation, limiting realism and result reliability. Standard Deviation of Lane Position (SDLP) emerges as a gold-standard measure for assessing driver performance. Future research should focus on developing standard definitions for
Uccello, LorenzoNobili, AlessandroPasina, LucaNovella, AlessioElli, ChiaraMastinu, Gianpiero
The suspension system could transmit and filter the forces between the body and road surface, which affects vehicle ride comfort and road maintenance capability. Compared to traditional passive and semi-active suspension, Active Suspension Systems (ASS) could automatically adjust the suspension stiffness, damping force, and body height according to changes in the vehicle's load distribution, travelling speed, and braking action through the addition of a power source such as a linear motor. Although the existing advanced control methods could help to effectively improve the driving quality of vehicles equipped with ASS, the conflict between ride comfort and road maintenance capacity is still a difficult problem to be solved. Therefore, an Active Suspension System optimal control strategy considering vehicle ride comfort and road maintenance capability is proposed in this paper. Firstly, a quarter ASS model and a road model are respectively developed based on the system dynamics
Zhu, BingZhang, ChaohuiSun, JihangWang, ShiweiDing, ShuweiLi, LunChen, Zhicheng
With the continuous development of automotive intelligence, there is an increasing demand for vehicle chassis systems to become more intelligent, electronically controlled, integrated, and lightweight. In this context, the steer-by-wire system, which is electronically controlled, offers high precision and fast response. It provides greater flexibility, stability, and comfort for the vehicle, thus meeting the above requirements and has garnered widespread attention. Unlike traditional systems, the steer-by-wire system eliminates mechanical components, meaning the road feel cannot be directly transmitted to the steering wheel. To address this, the road feel, which is derived from the vehicle's state or integrated with environmental driving data, must be simulated and transmitted to the steering wheel through a road feel motor. This motor generates feedback that mimics the road feel, similar to that experienced in a conventional steering system. This simulation enhances the driver's
Li, ShangKaku, ChuyoZheng, HongyuZhang, Yuzhou
Intelligent transportation systems and connected and automated vehicles (CAVs) are advancing rapidly, though not yet fully widespread. Consequently, traditional human-driven vehicles (HDVs), CAVs, and human-driven connected and automated vehicles (HD-CAVs) will coexist on roads for the foreseeable future. Simultaneously, car-following behaviors in equilibrium and discretionary lane-changing behaviors make up the most common highway operations, which seriously affect traffic stability, efficiency and safety. Therefore, it’s necessary to analyze the impact of CAV technologies on both longitudinal and lateral performance of heterogeneous traffic flow. This paper extends longitudinal car-following models based on the intelligent driver model and lateral lane-changing models using the quintic polynomial curve to account for different vehicle types, considering human factors and cooperative adaptive cruise control. Then, this paper incorporates CAV penetration rates, shared autonomy rates
Wang, TianyiGuo, QiyuanHe, ChongLi, HaoXu, YimingWang, YangyangJiao, Junfeng
With the widespread application of the Automatic Emergency Braking System (AEB) in vehicles, its impact on pedestrian safety has received increasing attention. However, after the intervention of AEB, the kinematic characteristics of pedestrian leg collisions and their corresponding biological injury responses also change. At the same time, in order to accurately evaluate the pedestrian protection performance of vehicles, the current assessment regulations generally use advanced pedestrian protection leg impactors (aPLI) and rigid leg impactors (TRL) to simulate the movement and injury conditions of pedestrian legs. Based on this, in order to explore the collision boundary conditions and changes in injury between vehicles and APLI and TRL leg impactors under the action of AEB, this paper first analyzes the current passive and active assessment conditions. Secondly, the simulation software LS-DYNA is used to build a finite element model of APLI and TRL impactor-vehicle collisions to
Ye, BinHong, ChengWan, XinmingLiu, YuCheng, JamesLong, YongchenHao, Haizhou
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 psychophysiological 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 psychophysiological characterization of the drivers, through psychological questionnaires and physiological measures, allows for analyzing human factors in automated vehicles interactions and for contributing to
Gobbi, MassimilianoBoscaro, LindaDe Guglielmo, VeronicaFossati, AndreaGalbiati, AndreaMastinu, LedaPonti, MarcoMastinu, GianpieroPreviati, GiorgioSabbioni, EdoardoSignorini, Maria GabriellaSomma, AntonellaSubitoni, LucaUccello, Lorenzo
There are numerous commercially available neck and back support/cushion/pillow devices which are commonly attached to seats by vehicle owners. To our knowledge, there has been no published research on the biomechanical effects of these devices in low-speed rear impacts. To address this, a series of 54 simulated low-speed rear impact tests were conducted using a validated remote-controlled crash sled system. All tests utilized an instrumented BioRID II rear impact anthropomorphic test device (ATD) restrained using a 3-point seatbelt system in a 2018 Toyota Camry LE driver’s seat. Two delta-V ranges were used: a lower range from 7.2 to 8.0 kph (4.5 to 5.0 mph) and a higher range from 10.5 to 11.3 kph (6.5 to 7.0 mph). Six neck only devices, one combination neck and back device, and three back only devices were assessed. Two tests per delta-V range for each device and each device adjustment position were conducted and compared against five reference tests without any devices at each delta
Phan, AndrewGross, JamieUmale, SagarCrowley, ShannonGlasser, GabrielFurbish, Christopher
In the Baja race, off-road vehicles need to run under a variety of real and complex off-road conditions such as pebble road, shell pit, stone bad road, hump, water puddle, etc. In the process of this high-intensity and high-concentration race, the unoptimized design of the cab in ergonomics will easily cause the driver's visual and handling fatigue, so that the driver's attention is not concentrated. Cause the occurrence of security accidents. Moreover, lower back pain, sciatic nerve discomfort, lumbar spine diseases and other occupational diseases are basically caused by uncomfortable driving posture and unreasonable control matching, and these have a lot to do with unreasonable ergonomic design. In order to solve these problems, firstly establish the human body model of the driver, and then build the BSC racing car model by using 3D modeling software Catia. Then use the ergonomics simulation software Jack to analyze the visibility, accessibility and comfort. Based on the simulation
Liu, YuzhouLiu, Silang
High-efficiency manufacturing involves the transmission of copious amounts of data, exemplified both by trends in the automotive industry and advances in technology. In the automotive industry, products have been growing increasingly complex, owing to multiple SKUs, global supply chains and the involvement of many tier 2 / Just-In Time (JIT) suppliers. On top of that, recalls and incidents in recent years have made it important for OEMs to be able to track down affected vehicles based on their components. All of this has increased the need for OEMs to be able to collect and analyze component data. The advent of Industry 4.0 and IoT has provided manufacturing with the ability to efficiently collect and store large amounts of data, lining up with the needs of manufacturing-based industries. However, while the needs to collect data have been met, corporations now find themselves facing the need to make sense of the data to provide the insights they need, and the data is often unstructured
Jan, JonathanPreston, JoshuaJuncker, John
As a kind of off-road racing car, the driving condition of Baja is extremely bad. In order to allow the driver to control the vehicle well in complex working conditions, it is particularly important to provide a comfortable and convenient driving space and handling space for the driver. In this paper, firstly, RAMSIS is used to carry out the ergonomics verification of the racing car from the comfort analysis, reachable area analysis and visual field analysis, and optimize the design of the cockpit layout of the Baja racing car. Then the NVH characteristics of the Baja racing car frame are studied, and the 12-order modal results are obtained by finite element analysis and simulation. Then the natural frequency of the frame is measured by experiments, and the experimental results are verified to match the theoretical values. The research shows that the above steps can design a comfortable driving posture and operating space for the racer and provide experience for the future layout of
Liu, Silang
FSAE is a competition designed to maximize car performance, in which the steering system is a key subsystem, and the steering system performance directly affects the cornering performance of the car. The driver relies on the steering system for effective handling, which is also crucial for cornering and achieving faster lap times. Therefore, while improving the performance of the steering system, it is crucial to match the vehicle design to the driver's habits. Traditionally, steering systems typically use an Ackermann rate between 0% and 100% to offset the slip angle caused by tire deformation, thus achieving the purpose of reducing tire wear. Calculations have shown that a 40-60% Ackermann rate provides a similar compensation effect with little difference in tire wear. The traditional steering design method also does not consider the driver's driving habits and feedback, which is not conducive to the improvement of the overall performance of the car. In FSAE's figure-of-eight loops
Wu, HailinLi, Mingyuan
Driver distraction remains a leading cause of traffic accidents, making its recognition critical for enhancing road safety. In this paper, we propose a novel method that combines the Information Bottleneck (IB) theory with Graph Convolutional Networks (GCNs) to address the challenge of driver distraction recognition. Our approach introduces a 2D pose estimation-based action recognition network that effectively enhances the retention of relevant information within neural networks, compensating for the limited data typically available in real-world driving scenarios. The network is further refined by integrating the CTR-GCN (Channel-wise Topology Refinement Graph Convolutional Network), which models the dynamic spatial-temporal relationships of human skeletal data. This enables precise detection of distraction behaviors, such as using a mobile phone, drinking water, or adjusting in-vehicle controls, even under constrained input conditions. The IB theory is applied to optimize the trade
Zhang, JiBai, Yakun
SAE J3230 provides Kinematic Performance Metrics for Powered Standing Scooters. These performance metrics include many tests which require specific conditions including flat pavement with a near zero slope, drivers of specific height and weights, and data acquisition equipment. In order to determine the efficacy of replicating SAE J3230 tests in a laboratory setting, a device called the Micromobility Device Thermo-Electric Dynamometer was used alongside outdoor tests to provide a comparison of scooter performance in these two testing applications. Based on the testing outcomes, it can be determined whether SAE J3230 and similar standards for other micromobility devices can be replicated in a lab-based setting, saving time, operator hazard, and providing more thorough data outputs.
Bartholomew, MeredithAndreatta, DaleZagorski, ScottHeydinger, Gary
Vehicle ADAS Systems majorly comprises of two functions: Driving and Parking. The most common form of damage to the vehicle which goes unnoticed with unidentified cause are parking damages. A vehicle once parked at a certain location may get damaged without knowledge of the user. In this work developed a solution that not only pre-warns the driver but also prepares the vehicle beforehand if it suspects a damage may occur. This eliminates the latency between damage and information capture, detects small damages such as scratches, classifies the type of damage and informs the user beforehand. This is solution is different from our competitors as the existing solutions informs the user about the scratches/damages, but these solutions are expensive, have high response time, and the damage information is captured after the damage has occurred. The solution consists of the following check blocks: Precondition, Sensor Control and Action Module. The Precondition Module observes the vehicle
Debnath, SarnabPatil, PrasadBelur Subramanya, SheshagiriGovinda, Shiva Prasad
In order to effectively improve the chassis handling stability and driving safety of intelligent electric vehicles (IEVs), especially in combing nonlinear observer and chassis control for improving road handling. Simultaneously, uncertainty with system input, are always existing, e.g., variable control boundary, varying road input or control parameters. Due to the higher fatality rate caused by variable factors, how to precisely chose and enforce the reasonable chassis prescribed performance control strategy of IEVs become a hot topic in both academia and industry. To issue the above mentioned, a fuzzy sliding mode control method based on phase plane stability domain is proposed to enhance the vehicle’s chassis performance during complex driving scenarios. Firstly, a two-degree-of-freedom vehicle dynamics model, accounting for tire non-linearity, was established. Secondly, combing with phase plane theory, the stability domain boundary of vehicle yaw rate and side-slip phase plane based
Liao, YinshengWang, ZhenfengGuo, FenghuanDeng, WeiliZhang, ZhijieZhao, BinggenZhao, Gaoming
In the post Covid era, risk of infection in conditioned space is getting attention and has generated a lot of interest for the design of the new systems and strategies for the management and operations of the existing HVAC systems. Risk management plays a key role where the amounts of outside air and recirculated airs can be used to mitigate the propagation of the virus within the conditioned space. In other words, ventilation plays a huge role within the conditioned space along with strategies based on UV irradiation, ionization and use of highly efficient filters. Different air purification systems have been created by the researchers based on the titanium oxide-based UV photocatalysis system, filters with MERV ratings higher than 11 (ASHRAE Standard 52.2) and HEPA filters. Recent ASHRAE standard 241 (2023) on infectious diseases recommends using high ventilation rates within the conditioned space to reduce virus concentration, and hence, to reduce the risk of infection. Determining
Mathur, Gursaran
With the increasing prevalence of Automatic Emergency Braking Systems (AEB) in vehicles, their performance in actual collision accidents has garnered increasing attention. In the context of AEB systems, the pitch angle of a vehicle can significantly alter the nature of collisions with pedestrians. Typically, during such collisions, the pedestrian's legs are the first to come into contact with the vehicle's front structure, leading to a noticeable change in the point of impact. Thus, to investigate the differences in leg injuries to pedestrians under various pitch angles of vehicles when AEB is activated, this study employs the Total Human Model for Safety (THUMS) pedestrian finite element model, sensors were established at the leg location based on the Advanced Pedestrian Legform Impactor (APLI), and a corresponding vehicle finite element model was used for simulation, analyzing the dynamic responses of the pedestrian finite element model at different pitch angles for sedan and Sport
Hong, ChengYe, BinZhan, ZhenfeiLiu, YuWan, XinmingHao, Haizhou
The proportion of pedestrian fatalities due to traffic accidents is higher at night than during the day. Drivers can more easily recognize pedestrians by setting their headlights to high beam, but use of high beam poses the issue of increasing glare for pedestrians. This study proposes a lighting technology that increases the noticeability of pedestrians for drivers and the noticeability of approaching vehicles for pedestrians while at the same time helping to reduce glare for pedestrians. The newly designed lighting enables geometric patterns projection lighting that makes use of projection technology. This geometric pattern projection lighting was compared with conventional low beam and high beam headlights to verify the effectiveness. Tests were conducted on a closed course with the participation of 20 drivers to evaluate the functionality of each headlight type. In these tests, subjects performed specific tasks such as evaluation of pedestrian visibility from the driver’s point of
Kawamura, KazuyukiOshida, Kei
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