Browse Topic: Vehicle occupants

Items (6,274)
ABSTRACT This study investigated the effect of an innovative chilling device that intends to make subjects more alert and less sleepy. Tests were conducted using a variety of methods including electric-encephalography (EEG) brain tomography. A series of behavioral tests showed an increase in alertness, changes of body temperatures, and performance indicators after usage of this device. The device chills specific areas of the body and disrupts the body’s ability to self-regulate core body temperature. The induced temperature shifts may reduce the body’s capability to go to sleep. Physiological changes and brain wave indicators of alertness were also reviewed in this paper. A full study of alertness indicators in expanded driver simulations is recommended. As for future application of this device to Human Factors aspects, this device may have the potential to enhance alertness in the human dimension of machine operation of manned and unmanned assets with further improvement
Hsieh, LiRanalli, RJ
ABSTRACT The need for up-armored vehicles has increased over the years. This has put a greater emphasis on suspensions that can provide improved ride and handling capabilities while facing the additional weight. One of the challenges with these vehicles traditionally has been increased likelihood of rollover. Increased rollover is due to high center of gravity, kinematics of the overloaded suspension, and the low damping that is needed to satisfy 6-Watt ride speed performance criteria. The Lord magneto-rheological (MR) suspension system addresses these issues by improving the ride quality and handling characteristics thereby increasing safety and mission effectiveness. During handling maneuvers, algorithms inside the controller unit apply corrective forces to minimize peak roll angle and peak roll rate. The benefit of this has been tested on a vehicle comparing the stock passive dampers to the MR dampers over NATO Lane change events. Furthermore, the controller has the capability to
Hildebrand, StephenMargolis, DonaldMathew, AbrahamMattson, Michael
ABSTRACT Through Army SBIR funding, NanoSonic has designed a next-generation multipurpose Spall Protective, Energy Absorbing (SPEA™) HybridSil® material that has the potential to provide vehicle occupants with pioneering combinatorial protection from 1) fragmentation behind-armor debris (BAD), 2) high velocity head / neck impact, and 3) fire during underbody blast, crash, and rollover events. This innovative multilayered ensemble consists of highly flame resistant, energy absorbing polyorganosiloxane foams, molded ultrahigh molecular weight polyethylene panels, and carbon fiber reinforced polymer derived ceramic composites. The technical foundation for this effort was provided through independent 1) MIL-STD-662 FSP ballistic testing with The Ballistics and Explosive Group at Southwest Research Institute (SwRI); 2) FMVSS 201U head impact testing with MGA Research Incorporation; and 3) ASTM E1354 fire resistance testing with the Fire Technology group at SwRI. Fragment simulating
Baranauskas, VinceKlima, Julie
ABSTRACT A promising approach to autonomous driving is machine learning. In machine learning systems, training datasets are created that capture the sensory input to a vehicle as well as the desired response. One disadvantage of using a learned navigation system is that the learning process itself may require both a huge number of training examples and a large amount of computing. To avoid the need to collect a large training set of driving examples, we describe a system that takes advantage of the immense number of training examples provided by ImageNet, but at the same time is able to adapt quickly using a small training set for the driving environment
Provodin, ArtemTorabi, LiilaMuller, UrsFlepp, BeatSergio, MichaelŽbontar, JureLeCun, YannJackel, L. D.
ABSTRACT While complex systems transform the landscape, the Systems Engineering discipline is also experiencing a transformation to a model-based discipline. In alignment with this, one of the International Council on Systems Engineering (INCOSE) strategic objectives is to accelerate this transformation. INCOSE is building a broad community that promotes and advances model based methods to manage the complexity of systems which seamlessly integrate computational algorithms and physical components across domains and traditional system boundaries. This paper covers contextual drivers for transformation as well as challenges, enablers, and INCOSE resources aligned with accelerating the transformation of Systems Engineering to a model-based discipline
Peterson, Troy
ABSTRACT Model based design techniques are being used increasingly to predict vehicle performance before building prototype hardware. Tools like ADAMS and Simulink enable very detailed models of suspension components to be developed so vehicle performance can be accurately predicted. In creating models of vehicle systems, often there is a question about how much component detail or model fidelity is required to accurately model system performance. This paper addresses this question for modeling shock absorber performance by comparing a low fidelity and high fidelity shock absorber model. A high fidelity and low fidelity mathematical model of a shock absorber was developed. The low fidelity shock absorber model was parameterized according to real shock absorber hardware dimensions. Shock absorber force vs. velocity curves were calculated in Simulink. The results from the low fidelity and high fidelity model were compared to shock absorber force vs. velocity test results. New vehicle
Masini, ChrisYang, Xiaobo
ABSTRACT This paper reviews the Army Generic Hull [1-5] as a vital developmental tool for underbody blast modeling and simulation applications. Since 2010, it has been used extensively to help calibrate and validate various numerical software codes and methodologies. These are being used extensively today in the development of underbody armor, as well as mine blast subsystems such as seats, to protect both military vehicles and their occupants. In the absence of easily shareable information in this domain due to data classification, this specially formulated product is a valuable part of any toolset for underbody blast development and product design. Citation: K. Kulkarni, S. Kankanalapalli, V. Babu, J. Ramalingam, R. Thyagarajan, “The Army Generic Hull As A Vital Developmental Tool For Underbody Blast Applications,” In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 16-18, 2022
Kulkarni, KumarKankanalapalli, SanjayBabu, VenkateshRamalingam, JaiThyagarajan, Ravi
ABSTRACT Military personnel involved in convoy operations are often required to complete multiple tasks within tightly constrained timeframes, based on limited or time-sensitive information. Current simulations are often lacking in fidelity with regard to team interaction and automated agent behavior; particularly problematic areas include responses to obstacles, threats, and other changes in conditions. More flexible simulations are needed to support decision making and train military personnel to adapt to the dynamic environments in which convoys regularly operate. A hierarchical task analysis approach is currently being used to identify and describe the many tasks required for effective convoy operations. The task decomposition resulting from the task analysis provides greater opportunity for determining decision points and potential errors. The results of the task analysis will provide guidance for the development of more targeted simulations for training and model evaluation from
Garrison, Teena M.Thomas, Mark D.Carruth, Daniel W.
ABSTRACT This paper focuses on the application of a novel Additive Molding™ process in the design optimization of a combat vehicle driver’s seat structure. Additive Molding™ is a novel manufacturing process that combines three-dimensional design flexibility of additive manufacturing with a high-volume production rate compression molding process. By combining the lightweighting benefits of topology optimization with the high strength and stiffness of tailored continuous carbon fiber reinforcements, the result is an optimized structure that is lighter than both topology-optimized metal additive manufacturing and traditional composites manufacturing. In this work, a combat vehicle driver’s seatback structure was optimized to evaluate the weight savings when converting the design from a baseline aluminum seat structure to a carbon fiber / polycarbonate structure. The design was optimized to account for mobility loads and a 95-percentile male soldier, and the result was a reduction in
Hart, Robert JPerkins, J. ScottBlinzler, BrinaMiller, PatrickShen, YangDeo, Ankit
ABSTRACT The AirLift is a novel device that enables rapid stabilized extraction of injured personnel from a ground vehicle. When deployed from its pre-installed position as a seat cover, the AirLift rigidizes for stabilizing the occupant’s spine by pressurizing an inflatable panel. After extraction from the vehicle with the occupant stabilized in the seated position, the AirLift can convert to a backboard so that the occupant can be safely transported in the supine position. The inflatable panel was designed and tested to provide stiffness while also being durable and manufacturable at volume. Pressure mapping tests were also performed to demonstrate that the AirLift did not change seat comfort compared to the standard seat. Citation: A. Purekar, G. Hiemenz, P. Gillis, “AirLift: Enabling Blast Protection and Rapid, Stabilized Vehicle Extraction”, In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 11-13, 2020
Purekar, AshishHiemenz, GregoryGillis, Paula
ABSTRACT With US military casualties mounting due to Improvised Explosive Devices (IEDs) and other roadside bombs, improving the protective capabilities of armored vehicles for service personnel is of paramount importance. Accurate numerical simulations of the blast event provide a means to quickly and economically evaluate the blast-protection performance of armored vehicles, and to develop improved blast countermeasures. This effort developed computational simulations of a system intended to mitigate blast accelerations to a level where the acceleration is no longer a lethal threat to the occupants of an armored vehicle. The hypothesis is that through the manipulation of the mass ratio, stiffness and damping properties of a dual-hull system, the capability of current Mine Resistant Ambush Protected (MRAP) vehicles can be greatly improved. The results show that, in comparison to the standard single-hull vehicle, the dual-hull vehicle reduces head injury criteria by 95.7%, neck
Schaffner, GrantMiller, Adam
Summary Combat vehicle designers have made great progress in improving crew survivability against large blast mines and improvised explosive devices. Current vehicles are very resistant to hull failure from large blasts, protecting the crew from overpressure and behind armor debris. However, the crew is still vulnerable to shock injuries arising from the blast and its after-effects. One of these injury modes is spinal compression resulting from the shock loading of the crew seat. This can be ameliorated by installing energy-absorbing seats which reduce the intensity of the spinal loading, while spreading it out over a longer time. The key question associated with energy-absorbing seats has to do with the effect of various factors associated with the design on spinal compression and injury. These include the stiffness and stroking distance of the seat’s energy absorption mechanism, the size of the blast, the vehicle shape and mass, and the weight of the seat occupant. All of these
Eridon, James
Abstract On the Mobile Detection Assessment Response System (MDARS) production program, General Dynamics Robotics Systems (GDRS) and International Logistics Systems (ILS), are working with the US Army’s Product Manager – Force Protection Systems (PM-FPS) to reduce system costs throughout the production lifecycle. Under this process, GDRS works through an Engineering Change Proposal (ECP) process to improve the reliability and maintainability of subsystem designs with the goal of making the entire system more producible at a lower cost. In addition, GDRS recommends substitutions of Government requirements that are cost drivers with those that reduce cost impact but do not result in reduced capability for the end user. This paper describes the production lifecycle process for the MDARS system and recommends future considerations for fielding of complex autonomous robotic systems
Frederick, BrianVirtz, PaulGrinnell, Michal
ABSTRACT Autonomous driving systems (ADS) in autonomous and semi-autonomous vehicles have the potential to improve driving safety and enable drivers to perform non-driving tasks concurrently. Drivers sometimes fail to fully leverage a vehicle’s autonomy because of a lack of trust. To address this issue, the present study examined the influence of risk on drivers’ trust. Subject tests were conducted to evaluate the effects of combined internal and external risk, where participants drove a simulated semi-autonomous vehicle and completed a secondary task at the same time. Results of this study are expected to provide new insights into promoting trust and acceptance of autonomy in both military and civilian settings
Petersen, LukeZhao, HuajingTilbury, Dawn M.Yang, X. JessieRobert, Lionel P.
ABSTRACT One of the main thrusts in current Army Science & Technology (S&T) activities is the development of occupant-centric vehicle structures that make the operation of the vehicle both comfortable and safe for the soldiers. Furthermore, a lighter weight vehicle structure is an enabling factor for faster transport, higher mobility, greater fuel conservation, higher payload, and a reduced ground footprint of supporting forces. Therefore, a key design challenge is to develop lightweight occupant-centric vehicle structures that can provide high levels of protection against explosive threats. In this paper, concepts for using materials, damping and other mechanisms to design structures with unique dynamic characteristics for mitigating blast loads are investigated. The Dynamic Response Index (DRI) metric [1] is employed as an occupant injury measure for determining the effectiveness of the each blast mitigation configuration that is considered. A model of the TARDEC Generic V-Hull
Jiang, WeiranVlahopoulos, NickolasCastanier, Matthew P.Thyagarajan, RaviMohammad, Syed
ABSTRACT Although autonomy has the potential to help military drivers travel safely while performing other tasks, many drivers refuse to rely on the technology. Military drivers sometimes fail to leverage a vehicle’s autonomy because of a lack of trust. To address this issue, the current study examines whether augmenting the driver’s situational awareness will promote their trust in the autonomy. Results of this study are expected to provide new insights into promoting trust and acceptance of autonomy in military settings
Petersen, LukeTilbury, DawnRobert, LionelYang, Xi Jessie
With increasing emphasis on sustainable mobility and efficient energy use, advanced driver assistance systems (ADAS) may potentially be utilized to improve vehicles’ energy efficiency by influencing driver behavior. Despite the growing adoption of such systems in passenger vehicles for active safety and driver comfort, systematic studies examining the effects of ADAS on human driving, in the context of vehicle energy use, remain scarce. This study investigates the impacts of a driver speed advisory system on energy use in a plug-in hybrid electric vehicle (PHEV) through a controlled experiment using a driving simulator. A mixed urban highway driving environment was reconstructed from digitalizing a real-world route to observe the human driver’s behavior with and without driving assistance. The advisory system provided drivers with an optimized speed profile, pre-calculated for the simulated route to achieve maximum energy efficiency. Participants were instructed to navigate the
Telloni, MarcelloFarrell, JamesMendez, LuisOzkan, Mehmet FatihChrstos, JeffreyCanova, MarcelloStockar, Stephanie
This study compared modern vehicle and booster geometries with relevant child anthropometries. Vehicle geometries (seat length, seat pan height, shoulder belt outlet height, and roof height) were obtained for 275 center and outboard rear seating positions of US vehicles (MY 2009–2022). Measurements of 85 US boosters (pan height and pan length) and anthropometries of 80 US children between 4–14yo (seated height, thigh length, leg length, and seated shoulder height) were also collected. Comparisons were made between vehicles, boosters, and child anthropometries. Average vehicle seat lengths exceeded child thigh lengths (+9.5cm). Only 16.4% of seating positions had seat lengths less than the child thigh length mean+1SD. Even for children at least 145cm, only 18.8% had thigh lengths greater than the average vehicle seat length. Child thigh lengths were more comparable with average booster seat pan lengths for all multi-mode and high-back designs (-2.0cm) and low-back boosters (+3.1cm). The
Baker, Gretchen H.Connell, Rosalie R.Rhodes, Carrie A.Mansfield, Julie A.
In recent years, battery electric vehicles (BEVs) have experienced significant sales growth, marked by advancements in features and market delivery. This evolution intersects with innovative software-defined vehicles, which have transformed automotive supply chains, introducing new BEV brands from both emerging and mature markets. The critical role of software in software-defined battery electric vehicles (SD-BEVs) is pivotal for enhancing user experience and ensuring adherence to rigorous safety, performance, and quality standards. Effective governance and management are crucial, as failures can mar corporate reputations and jeopardize safety-critical systems like advanced driver assistance systems. Product Governance and Management for Software-defined Battery Electric Vehicles addresses the complexities of SD-BEV product governance and management to facilitate safer vehicle deployments. By exploring these challenges, it aims to enhance internal processes and foster cross
Abdul Hamid, Umar Zakir
Road safety remains a critical concern globally, with millions of lives lost annually due to road accidents. In India alone, the year 2021 witnessed over 4,12,432 road accidents resulting in 1,53,972 fatalities and 3,84,448 injuries. The age group most affected by these accidents is 18-45 years, constituting approximately 67% of total deaths. Factors such as speeding, distracted driving, and neglect to use safety gear increases the severity of these incidents. This paper presents a novel approach to address these challenges by introducing a driver safety system aimed at promoting good driving etiquette and mitigating distractions and fatigue. Leveraging Raspberry Pi and computer vision techniques, the system monitors driver behavior in real-time, including head position, eye blinks, mouth opening and closing, hand position, and internal audio levels to detect signs of distraction and drowsiness. The system operates in both passive and active modes, providing alerts and alarms to the
Ganesh, KattaPrasad, Gvl
The integration of Vehicle-to-Everything (V2X) communication technologies holds immense potential to revolutionize the automotive industry by enabling vehicles to communicate with each other (V2V) and with infrastructure (V2I). This paper investigates the feasibility of V2X and V2I communication, exploring available communication methods for vehicles to communicate. Many a times people like to travel together and it involves more than one vehicle travelling together, in such cases they often get lost the information about fellow vehicles due to the traffic condition and different driving behaviors of the individual driver. In such cases they communicate over phones to get to know the location of fellow vehicle or keep sharing their live locations. In such cases they don’t just follow the destination in maps also they should be continuously monitoring their fellow vehicles position. It is important for vehicles travelling in group to have communication and be connected so that they know
Barre, Deva Harshitha
Forward-facing child restraint systems (FF CRS) and high-back boosters often contact the vehicle seat head restraint (HR) when installed, creating a gap between the back surface of the CRS and the vehicle seat. The effects of HR interference on dynamic CRS performance are not well documented. The objective of this study is to quantify the effects of HR interference for FF CRS and high-back boosters in frontal and far-side impacts. Production vehicle seats with prominent, removeable HRs were attached to a sled buck. One FF CRS and two booster models were tested with the HR in place (causing interference) and with the HR removed (no interference). A variety of installation methods were examined for the FF CRS. A total of twenty-four tests were run. In frontal impacts, HR interference produced small but consistent increases in frontal head excursion and HIC36. Head excursions were more directly related to the more forward initial position rather than kinematic differences caused by HR
Mansfield, Julie A.
American drivers have long been accustomed to quickly filling up at a gas station with plenty of fuel available, and electric vehicle drivers want their pit stops to mimic this experience. Driver uncertainty about access to charging during long trips remains a barrier to broader EV adoption, even as the U.S. strives to combat climate change by converting more drivers
Since signing the legally binding Paris agreement, fighting climate change has been an increasingly important task worldwide. One of the key energy sectors to emit greenhouse gases is transportation. Therefore, long term strategies all over the world have been set up to reduce on-road combustion emissions. One of the emerging alternative technologies to decarbonize the transportation sector is Mobile Carbon Capture (MCC). MCC refers to the on-board separation of CO2 from vehicle exhaust. To accurately assess this technology, a techno-economic analysis is essential to compare MCC abatement cost to alternative decarbonization technologies such as electric trucks. Adding to the system capital and operational costs, our study includes mass penalty costs, CO2 offloading and transport costs for different transport scenarios. To better relate to a single consumer (driver), the cost can be converted from euro per-tCO2 to euro per-trip or euro per-mile. A sensitivity analysis is then conducted
SAAFI, Mohamed AliHamad, Esam
Most military wheeled vehicles operate with a simplistic table-based transmission shift strategy. However, Allison Transmission Inc has created an innovative algorithm-based transmission shift strategy known as FuelSense®2.0 with DynActive® Shifting which optimizes gear selection by accounting for driver demand and vehicle load. This method of shifting has the potential to significantly improve fuel economy while only minimally degrading vehicle performance. In this study, FuelSense®2.0 with DynActive® Shifting was evaluated across three platforms which included the Family of Medium Tactical Vehicles (FMTV), and the Heavy Tactical Vehicles (HTV) Heavy Expanded Mobility Tactical Truck (HEMTT) and Palletized Loading System (PLS). The trucks were drive-cycle tested using both an environmentally controlled dynamometer laboratory and a real-world proving ground user trial
Zielinski, StevenBeiter, StevenMach, Newly
In order to meet the driving characteristics and needs of different types of drivers and to improve driving comfort and safety, this article designs personalized variable transmission ratio schemes based on the classification results of drivers’ steering characteristics and proposes a switching strategy for selecting variable transmission ratio schemes in response to changes in driver types. First, data collected from driving simulator experiments are used to classify drivers into three categories using the fuzzy C-means clustering algorithm, and the steering characteristics of each category are analyzed. Subsequently, based on the steering characteristics of each type of driver, suitable speed ranges, steering wheel travel, and yaw rate gain values are selected to design the variable transmission ratio, forming personalized variable transmission ratio schemes. Then, a switching strategy for variable transmission ratio schemes is designed, using a support vector machine to build a
Chen, ChenZheng, HongyuZong, Changfu
India is a diverse country in terms of road conditions, road maintenance, traffic conditions, traffic density, quality of traffic which implies presence of agricultural tractors, bullock carts, autos, motor bikes, oncoming traffic in same lane, vulnerable road users (VRU) walking in the same lanes as vehicles, VRU’s crossing roads without using zebra crossings etc. as additional traffic quality deterrents in comparison to developed countries. The braking capacity of such vivid road users may not be at par with global standards due to their maintenance, loading beyond specifications, driver behavior which includes the tendency to maintain a close gap between the preceding vehicle etc. which may lead to incidents specifically of rear collisions due to the front vehicle going through an emergency braking event. The following paper provides a comprehensive study of the special considerations or intricacies in implementation of Autonomous Emergency Braking (AEBS) feature into Indian traffic
Kartheek, NedunuriKhare, RashmitaSathyamurthy, SainathanManickam, PraveenkumarKuchipudi, Venkata Sai Pavan
Advanced driver assistance systems (ADAS) have become an integral part of today’s vehicle development. These systems are designed to provide secondary support to the driver, but the driver is primarily responsible for the driving task, e.g., lane-keeping assist (LKA). The driving setup and testing of these LKA systems is very time-consuming and usually applied in the car, based on experiences and subjective evaluation. This results in a cost-intensive calibration of the system. An objective-based calibration procedure can increase efficiency. For a targeted calibration of the system, it is necessary to define and identify key performance indicators (KPIs), which are able to describe the secondary support in sufficient detail. Usually, subjective feelings are used to derive KPIs. Vice versa, there are no results on how to design an LKA without any subjective assessment, before the calibration. With this in mind, this paper is focused on filling this unknown aspect by using virtual
Baumann, BenjaminIatropolous, JannesPanzer, AnnaHenze, Roman
In an influential essay in 2019, entitled ‘The Bitter Lesson’, machine learning researcher Richard Sutton observed that the main driver of progress in artificial intelligence (AI) is the continued scaling up of computational power1. This view predicts that while manual approaches that embed human knowledge and understanding in AI agents lead to satisfying advances in the short term, in the long run they only stand in the way of developing more general, scalable methods. This provocative conclusion has led to heated debates about the role of human ingenuity, but the ‘bitter lesson’ paradigm has more or less played out in the area of natural language processing. By using scaled-up neural networks and as many text examples from the internet as possible as training data, researchers could solve previously complex problems of producing human language without syntactical errors. Further scaling has produced general-purpose and multimodal models with billions of parameters such as GPT-4
This SAE Recommended Practice establishes uniform procedures for assuring the manufactured quality, installed utility, and service performance of manual automotive adaptive products, other than those provided by the OEM, intended to provide driving capability for persons with physical disabilities. These devices function as adaptive appliances to compensate for lost or reduced performance in the drivers’ arms or legs, or both. Some of the devices are designed to transfer foot functions to the hands, hand functions to the feet, or functions from one side of the body to the other. This document applies only to primary controls as defined in 3.4.1 and in the Foreword. In particular, this document is specifically concerned with those mechanical and hybrid products that are intended by the manufacturer of the adaptive product to: Be installed within the occupant space of the vehicle Be operated by a vehicle driver with a physical disability Be added to, or substituted for, the OEM vehicle
Adaptive Devices Standards Committee
This specification covers a titanium alloy in the form of sheet
AMS G Titanium and Refractory Metals Committee
Continental's Georg Fässler, executive chair of the 2024 SAE COMVEC, details efforts to future-proof forthcoming vehicles. Severe driver shortages, rising fuel and material costs, escalating demand for freight transport, higher sustainability requirements - there is no shortage of challenges facing the transport sector. Commercial vehicle manufacturers and industry suppliers are devoting significant resources to develop, test and bring to market the technological advances that will help alleviate these pressure points. “The digitalization of commercial vehicles and the whole logistics chain is a necessary response and one of the most important developments in the CV industry in my view,” said Continental Automotive's head of commercial and special vehicles, Georg Fässler, in a recent interview with SAE International
Gehm, RyanUhrinek, Gretchen
Occupant packaging is one of the key tasks involved in the early architectural phase of a vehicle. Accommodation, as a convention, is generally considered related to a car’s interior. Typical roominess metrics of the occupant like hip room, shoulder room, and elbow room are defined with the door in its closed condition. Several other roominess metrics like knee room, leg room, head room, and the like are also specified. While all the guidelines are defined with doors in their closed condition, it is also important to consider the dynamics that exist while the occupant is entering the vehicle. This article expands the traditional understanding of occupant accommodation beyond conventionally considering the vehicle interior’s ability to accommodate anthropometry. It broadens the scope to include dynamic conditions, such as when doors are opened, providing a more realistic and practical perspective. As a luxury car manufacturer, it is important to ensure the best overall customer
Rajakumaran, SriramSreenivas, Kalyan
This research aims at understanding how the driver interacts with the steering wheel, in order to detect driving strategies. Such driving strategies will allow in the future to derive accurate holistic driver models for enhancing both safety and comfort of vehicles. The use of an original instrumented steering wheel (ISW) allows to measure at each hand, three forces, three moments, and the grip force. Experiments have been performed with 10 nonprofessional drivers in a high-end dynamic driving simulator. Three aspects of driving strategy were analyzed, namely the amplitudes of the forces and moments applied to the steering wheel, the correlations among the different signals of forces and moments, and the order of activation of the forces and moments. The results obtained on a road test have been compared with the ones coming from a driving simulator, with satisfactory results. Two different strategies for actuating the steering wheel have been identified. In the first strategy, the
Previati, GiorgioMastinu, GianpieroGobbi, Massimiliano
Driving safety in the mixed traffic state of autonomous vehicles and conventional vehicles has always been an important research topic, especially on highways where autonomous driving technology is being more widely adopted. The merging scenario at highway ramps poses high risks with frequent vehicle conflicts, often stemming from misperceived intentions [1]. This study focuses on autonomous and conventional vehicles in merging scenarios, where timely recognition of lane-changing intentions can enhance merging efficiency and reduce accidents. First, trajectory data of merging vehicles and their conflicting vehicles were extracted from the NGSIM open-source database in the I-80 section. The segmented cubic polynomial interpolation method and Savitzky–Golay filtering are utilized for data outlier removal and noise reduction. Second, the processed trajectory data were used as input to a hybrid Gaussian hidden Markov (GMM-HMM) model for driving intention classification, specifically lane
Ren, YouWang, XiyaoSong, JiaqiLu, WenyangLi, PenglongLi, Shangke
This article aims to address the challenge of recognizing driving styles, a task that has become increasingly complex due to the high dimensionality of driving data. To tackle this problem, a novel method for driver style clustering, which leverages the principal component analysis (PCA) for dimensionality reduction and an improved GA-K-means algorithm for clustering, is proposed. In order to distill low-dimensional features from the original dataset, PCA algorithm is employed for feature extraction and dimensionality reduction. Subsequently, an enhanced GA-K-means algorithm is utilized to cluster the extracted driving features. The incorporation of the genetic algorithm circumvents the issue of the model falling into local optima, thereby facilitating effective driver style recognition. The clustering results are evaluated using the silhouette coefficient, Calinski–Harabasz (CH) index, and GAP value, demonstrating that this method yields more stable classification results compared to
Chen, YinghaoWu, GuangqiangWu, JianWang, Hao
Autonomous vehicles (AVs) provide an effective solution for enhancing traffic safety. In the last few years, there have been significant efforts and progress in the development of AVs. However, the public acceptance has not fully kept up with technological advancements. Public acceptance can restrict the growth of AVs. This study focuses on investigating the acceptance and takeover behavior of drivers when interacting with AVs of different styles in various scenarios. Manual and autonomous driving experiments were designed based on the driving simulation platform. To avoid subjective bias, principal component analysis (PCA) and the Gaussian mixture model (GMM) were used to classify driving styles. A total of 34 young participants (male-dominated) were recruited for this study. And they were classified into three driving styles (aggressive, moderate, and conservative). And AV styles were designed into three corresponding categories according to the different driving behavior
Li, GuanyuYu, WenlinChen, XizhengWang, WuhongGuo, HongweiJiang, Xiaobei
The optimization and further development of automated driving functions offers great potential to relieve the driver in various driving situations and increase road safety. Simulative testing in particular is an indispensable tool in this process, allowing conclusions to be drawn about the design of automated driving functions at a very early stage of development. In this context, the use of driving simulators provides support so that the driving functions of tomorrow can be experienced in a very safe and reproducible environment. The focus of the acceptance and optimization of automated driving functions is particularly on vehicle lateral control functions. As part of this paper, a test person study was carried out regarding manual vehicle lateral control on the dynamic vehicle road simulator at the Institute of Automotive Engineering. The basis for this is the route generation as a result of the evaluation of curve radii from several hundred thousand kilometers of real measurement
Iatropoulos, JannesPanzer, AnnaHenze, Roman
As part of the safety validation of advanced driver assistance systems (ADAS) and automated driving (AD) functions, it is necessary to demonstrate that the frequency at which the system exhibits hazardous behavior (HB) in the field is below an acceptable threshold. This is typically tested by observation of the system behavior in a field operational test (FOT). For situations in which the system under test (SUT) actively intervenes in the dynamic driving behavior of the vehicle, it is assessed whether the SUT exhibits HB. Since the accepted threshold values are generally small, the amount of data required for this strategy is usually very large. This publication proposes an approach to reduce the amount of data required for the evaluation of emergency intervention systems with a state machine based intervention logic by including the time periods between intervention events in the validation process. For this purpose, a proximity measure that indicates how close the system is to an
Schrimpf, MalteBetschinske, DanielPeters, Steven
Investigating human driver behavior enhances the acceptance of the autonomous driving and increases road safety in heterogeneous environments with human-operated and autonomous vehicles. The previously established driver fingerprint model, focuses on the classification of driving styles based on CAN bus signals. However, driving styles are inherently complex and influenced by multiple factors, including changing driving environments and driver states. To comprehensively create a driver profile, an in-car measurement system based on the Driver-Driven vehicle-Driving environment (3D) framework is developed. The measurement system records emotional and physiological signals from the driver, including the ECG signal and heart rate. A Raspberry Pi camera is utilized on the dashboard to capture the driver's facial expressions and a trained convolutional neural network (CNN) recognizes emotion. To conduct unobtrusive ECG measurements, an ECG sensor is integrated into the steering wheel
Ji, DejieFlormann, MaximilianWarnecke, Joana M.Henze, RomanDeserno, Thomas M.
In the realm of transportation science, the advent of deep learning has propelled advancements in predicting longitudinal driving behavior. This study explores the application of deep neural network architectures, specifically long–short-term memory (LSTM) and convolutional neural networks (CNNs), recognized for their effectiveness in handling sequential data. Using a 3-s temporal window that includes past vehicle progress, speed, and acceleration, the proposed model, a hybrid LSTM–CNN architecture, predicts the vehicle’s speed and progress for the next 6 s. The approach achieves state-of-the-art performance, particularly within a 4 s horizon, but remains competitive even for longer-term predictions. This is achieved despite the simplicity of its input space, which does not include information about vehicles other than the target vehicle. As a result, while its performance may decrease slightly for longer-term predictions due to the lack of environmental information, it still offers
Lucente, GiovanniMaarssoe, Mikkel SkovKahl, IrisSchindler, Julian
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