Relevant bibliographies by topics / Driving simulator

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Driving simulator'

Author: Grafiati
Published: 4 June 2021
Last updated: 8 June 2024

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Journal articles on the topic "Driving simulator"

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Nam, Su Man, Jieun Park, Chaeyeon Sagong, Yujin Lee, and Hyung-Jong Kim. "A Vehicle Crash Simulator Using Digital Twin Technology for Synthesizing Simulation and Graphical Models." Vehicles 5, no. 3 (August 28, 2023): 1046–59. http://dx.doi.org/10.3390/vehicles5030057.

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Computer vehicle simulators are used to model real-world situations to overcome time and cost limitations. The vehicle simulators provide virtual scenarios for real-world driving. Although the existing simulators precisely observe movement on the basis of good-quality graphics, they focus on a few driving vehicles instead of accident simulation. In addition, it is difficult to represent vehicle collisions. We propose a vehicle crash simulator with simulation and animation components. The proposed simulator synthesizes and simulates models of vehicles and environments. The simulator animates corresponding to the simulation through the execution results. The simulation results validate that the proposed simulator provides collision and non-collision results according to the speed of two vehicles at an intersection.
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Tiu, Jonathan, Annie C. Harmon, James D. Stowe, Amen Zwa, Marc Kinnear, Latch Dimitrov, Tina Nolte, and David B. Carr. "Feasibility and Validity of a Low-Cost Racing Simulator in Driving Assessment after Stroke." Geriatrics 5, no. 2 (May 29, 2020): 35. http://dx.doi.org/10.3390/geriatrics5020035.

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There is a myriad of methodologies to assess driving performance after a stroke. These include psychometric tests, driving simulation, questionnaires, and/or road tests. Research-based driving simulators have emerged as a safe, convenient way to assess driving performance after a stroke. Such traditional research simulators are useful in recreating street traffic scenarios, but are often expensive, with limited physics models and graphics rendering. In contrast, racing simulators developed for motorsport professionals and enthusiasts offer high levels of realism, run on consumer-grade hardware, and can provide rich telemetric data. However, most offer limited simulation of traffic scenarios. This pilot study compares the feasibility of research simulation and racing simulation in a sample with minor stroke. We determine that the racing simulator is tolerated well in subjects with a minor stroke. There were correlations between research and racing simulator outcomes with psychometric tests associated with driving performance, such as the Trails Making Test Part A, Snellgrove Maze Task, and the Motricity Index. We found correlations between measures of driving speed on a complex research simulator scenario and racing simulator lap time and maximum tires off track. Finally, we present two models, using outcomes from either the research or racing simulator, predicting road test failure as linked to a previously published fitness-to-drive calculator that uses psychometric screening.
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Yadav, Ambar, and Arti Singh. "Driving Simulator." IOSR Journal of Computer Engineering 16, no. 3 (2014): 33–38. http://dx.doi.org/10.9790/0661-16313338.

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YOSHIMOTO, Kenichi. "Driving Simulator." Journal of the Society of Mechanical Engineers 92, no. 842 (1989): 8–11. http://dx.doi.org/10.1299/jsmemag.92.842_8.

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Hu, Ding Jun, Ming Liu, and Lin Gong. "Study on Watercraft Driving Simulator." Advanced Materials Research 658 (January 2013): 395–98. http://dx.doi.org/10.4028/www.scientific.net/amr.658.395.

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This article describes the overall structure of the watercraft simulator. The simulator simulates the battle positions of a certain type of landing craft equipment operation, using state-of-the-art visual display and stereoscopic projection technology. Communicate with the computer simulation device through the data acquisition card (AM9110), visual 3D modeling software (3D MAX / Studio, MultiGen, etc.) to complete, three-dimensional projection system to the edge of fusion technology, and edge blending processor and projector with used to form the big-resolution three-dimensional visual field. The results show that the 225° annular three-dimensional visual field and visual field 135 ° 360 ° visual field watercrafts realistic driving simulator training and good features.
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Unsworth, Carolyn, Megan White, and Natasha Lannin. "Use of a Driving Simulator to Facilitate Older People to Return to Driving." Innovation in Aging 4, Supplement_1 (December 1, 2020): 730–31. http://dx.doi.org/10.1093/geroni/igaa057.2595.

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Abstract Driving simulators are a relatively underutilized therapy tool that provide an opportunity for older drivers with a range of health-related problems to participate in simulated driving scenarios in a low cost and safe environment. The aim of this paper is to (i) describe the use of a Forum 8 driving simulator prior to a driver assessment, (ii) detail the story-boarding technique used to develop and grade driving scenes to enable older drivers to increase confidence, practice using vehicle modifications such as a spinner knob (e.g. for one-handed driving following stroke), and train specific skills including visual scanning and attention, and (iii) present five case studies to identify the strengths and limitations of incorporating the simulator into therapy programs with older drivers. of simulator use. The establishment and use of a driving simulator in a rehabilitation unit highlights both the challenges and benefits of using this kind of technology in practice. Part of a symposium sponsored by Transportation and Aging Interest Group.
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Michel, Pauline, Samir Bouaziz, Flavien Delgehier, and Stéphane Espié. "Rider in the Loop Dynamic Motorcycle Simulator: An Instrumentation Strategy Focused on Human Acceptability." Electronics 11, no. 17 (August 27, 2022): 2690. http://dx.doi.org/10.3390/electronics11172690.

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Human-in-the-loop driving simulation aims to create the illusion of driving by stimulating the driver’s sensory systems in as realistic conditions as possible. However, driving simulators can only produce a subset of the sensory stimuli that would be available in a real driving situation, depending on the degree of refinement of their design. This subset must be carefully chosen because it is crucial for human acceptability. Our focus is the design of a physical dynamic (i.e., motion-based) motorcycle-riding simulator. For its instrumentation, we focused on the rider acceptability of all sub-systems and the simulator as a whole. The significance of our work lies in this particular approach; the acceptability of the riding illusion for the rider is critical for the validity of any results acquired using a simulator. In this article, we detail the design of the hardware/software architecture of our simulator under this constraint; sensors, actuators, and dataflows allow us to (1) capture the rider’s actions in real-time; (2) render the motorcycle’s behavior to the rider; and (3) measure and study rider/simulated motorcycle interactions. We believe our methodology could be adopted by future designers of motorcycle-riding simulators and other human-in-the-loop simulators to improve their rendering (including motion) quality and acceptability.
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Zhang, Yanning, Zhongyin Guo, and Zhi Sun. "Driving Simulator Validity of Driving Behavior in Work Zones." Journal of Advanced Transportation 2020 (June 9, 2020): 1–10. http://dx.doi.org/10.1155/2020/4629132.

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Driving simulation is an efficient, safe, and data-collection-friendly method to examine driving behavior in a controlled environment. However, the validity of a driving simulator is inconsistent when the type of the driving simulator or the driving scenario is different. The purpose of this research is to verify driving simulator validity in driving behavior research in work zones. A field experiment and a corresponding simulation experiment were conducted to collect behavioral data. Indicators such as speed, car-following distance, and reaction delay time were chosen to examine the absolute and relative validity of the driving simulator. In particular, a survival analysis method was proposed in this research to examine the validity of reaction delay time. The result indicates the following: (1) most indicators are valid in driving behavior research in the work zone. For example, spot speed, car-following distance, headway, and reaction delay time show absolute validity. (2) Standard deviation of the car-following distance shows relative validity. Consistent with previous researches, some driving behaviors appear to be more aggressive in the simulation environment.
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Nickkar, Amirreza, Mansoureh Jeihani, and Sina Sahebi. "Analysis of Driving Simulator Sickness Symptoms: Zero-Inflated Ordered Probit Approach." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 4 (April 2019): 988–1000. http://dx.doi.org/10.1177/0361198119841573.

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Driving simulators can provide safe real-world driving conditions that may help researchers study driving behavior; however, driving simulator sickness (DSS) has been recognized as one of the most frequent challenges associated with using driving simulators. The DSS issue may affect the validity and reliability of results obtained during the driving simulator experience. Therefore, it is necessary to understand the potential consequences of DSS in the virtual environment of a driving simulator. The goal of this study is to analyze DSS symptoms among participants of a driving simulator by their demographics. The samples of four simulator studies were combined, including a total of 259 participants who were recruited from different socio-demographic backgrounds and drove a fixed-base driving simulator. All these studies used the same proportion of mixed urban and suburban content in designing the simulation environments of the experiments. A DSS questionnaire based on the standard Simulator Sickness Questionnaire (SSQ) has been used to measure the severity of DSS symptoms—general discomfort, fatigue, headache, eyestrain, blurred vision, salivation, sweating, dizziness, and nausea—among participants. This study applies zero-inflated ordered probit and ordered probit models to evaluate the possible statistical relationships between demographic characteristics and experiment duration, and DSS symptoms. The results show that there is a positive direct statistical relationship between the duration of the experiment and DSS. Also, older participants have more general discomfort, fatigue, blurred vision, and headache symptoms with DSS than do younger ones. Similarly, female participants experience headache and nausea symptoms more than men do.
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Mourant, Ronald R., Prasanna Rengarajan, Daniel Cox, Yingzi Lin, and Beverly K. Jaeger. "The Effect of Driving Environments on Simulator Sickness." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 51, no. 18 (October 2007): 1232–36. http://dx.doi.org/10.1177/154193120705101838.

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In order to be an effective tool for driver evaluation and education, driving simulators need to be better designed to reduce simulator sickness. This study investigated driving in four environments (country, suburban, city, and curves) using a simulator. When driving on straight roads (city and suburban environments) subjects reported less simulator sickness then driving in the city environment (which included left and right turns) and on curves. A mini-SSQ was used to measure the accumulation of simulator sickness over trials. From trial 1 to trial 5, reported simulator sickness increased linearly. From trial 5 through 8, the rate of increase in simulator sickness decreased. We suggest that the rapid and distorted optic flow experienced while executing turns and driving on curves in driving simulators makes a substantial contribution to simulator sickness.
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Dissertations / Theses on the topic "Driving simulator"

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Juto, Erik. "Driving Simulator Development and Performance Study." Thesis, Linköping University, Vehicular Systems, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-56442.

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The driving simulator is a vital tool for much of the research performed at theSwedish National Road and Transport Institute (VTI). Currently VTI posses three driving simulators, two high fidelity simulators developed and constructed by VTI, and a medium fidelity simulator from the German company Dr.-Ing. Reiner Foerst GmbH. The two high fidelity simulators run the same simulation software, developed at VTI. The medium fidelity simulator runs a proprietary simulation software. At VTI there is a wish to integrate the medium fidelity Foerst Trainer simulator hardware into the VTI simulation software environment. This would increase research, development and maintanance flexibility and simulator availability since development and research could be performed on one additional simulator. Anintegration would lead to a homogenous software environment that also decreasesdevelopment, maintanance and training costs.To integrate the Foerst Trainer simulator and the VTI simulation software to communicate a program that translates and relays input and output between the two was developed. An assessment of the hardware-software integration was performed through an experiment where the high fidelity Simulator 3 and the medium fidelity Foerst Trainer simulator were compared. The experiment was designed to measure the participants driving performances and the perceived realism of the simulator. The results of the experiment shows that there is suprisingly small differences between the simulators, but more research is needed for more conclusive results.

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Brandtner, Annika, Magnus Liebherr, Stephan Schweig, Niko Maas, Dieter Schramm, and Matthias Brand. "Subjectively estimated vs. objectively measured adaptation to driving simulators – Effects of age, driving experience, and previous simulator adaptation." Elsevier, 2019. https://publish.fid-move.qucosa.de/id/qucosa%3A75923.

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Objective The present study aims to investigate whether drivers’ age and their experience with driving simulators could explain differences between a subjective estimation of system adaptation and a respective objective systematic measurement. Background Assessing valid measurements in driving simulators causes concern because driving simulators are not yet as realistic as real on-road driving scenarios. Common methods like pre-defined training sessions and self-appraisals of simulator adaptation might therefore be insufficient to ensure actual valid data. Hence, influential variables on this discrepancy are investigated. Method In total, N = 203 drivers participated in a training session and a subsequent testing session in a close-to-production driving simulator. Subjective adaptation was estimated by the drivers and an objective adaptation value was gathered on the basis of driving accuracy. The discrepancy between these two measures was calculated and related to age, self-reported driving experience and occurrence of previous adaptation. Results Subjective adaptation was significantly faster than objective adaptation but neither drivers’ age, experience, nor previous adaptation could explain this discrepancy. Discussion Results indicate that younger and older drivers likewise underestimate the time needed for adaptation. Measuring a subjective point of adaptation seems to be an insufficient measure to ensure simulator validity when assessing both older and younger drivers.
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Tudor, Sarah Marie. "The Development of an Adaptive Driving Simulator." Scholar Commons, 2015. https://scholarcommons.usf.edu/etd/5597.

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The ability to drive a car is an important skill for individuals with a spinal cord injury to maintain a high quality of life, particularly their freedom and independence. However, driving with a physical disability often requires the installation of an adaptive driving system to control steering, gas, and braking. The two main types of adaptive driving controls are mechanical and electrical, also known as drive by wire (DBW). DBW controls work by converting electric signals to mechanical actuators. Driving simulators are useful tools for adaptive driving systems because they allow users to test different control devices, to practice driving without the dangers of being on the road, and can be used as a safe way to evaluate disabled drivers. This study focused on the development of a dynamic driving simulator using DBW controls because many studies focus on mechanical controls and not DBW controls and often use static simulators. The simulator was developed using the Computer Assisted Rehabilitation Environment (CAREN) virtual reality system. The CAREN system (Motek Medical, Amsterdam, Netherlands) includes a six degree of freedom (DOF) motion base, an optical motion capture system, a sound system, and a 180-degree projection screen. The two DBW controls, a lever device to control the gas and brake and a small wheel device to control steering, sent an electric signal to a Phidget microcontroller board, which interfaced with the CAREN system. Several different driving scenarios were created and imported into CAREN's D-Flow software. A program was developed in D-Flow to control the scene and motion of the platform appropriately based on the DBW controls via the Phidget. The CAREN system dynamically controlled the motion platform based on the user's input. For example, if the user applied the brake suddenly, the user felt a deceleration from the motion platform moving backwards. Human testing was performed and through the use of a survey, feedback about the system was obtained. Changes were made to the simulator using the feedback obtained and further testing showed that those changes improved the simulator. The driving simulator showed the capability to provide dynamic feedback and, therefore, may be more realistic and beneficial than current static adaptive driving simulators. The dynamic adaptive driving simulator developed may improve driving training and performance of persons with spinal cord injuries. Future work will include more human testing. The dynamic feedback provided through the system's moving platform and virtual camera movement will be optimized in order to perform similarly to a real car. Testing will also be completed with and without the dynamics from the moving platform to see how this type of feedback affects the user's driving ability in the virtual environment.
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TSUCHIDA, Nuio, Shigeru OKUMA, Tatsuya SUZUKI, Soichiro HAYAKAWA, Yoshimichi MATSUI, and Jong-Hae KIM. "Acquisition and Modeling of Driving Skills by Using Three Dimensional Driving Simulator." Institute of Electronics, Information and Communication Engineers, 2005. http://hdl.handle.net/2237/14989.

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Vazquez, Perez Jose. "Personality Factors, Age, and Aggressive Driving: A Validation Using a Driving Simulator." Doctoral diss., University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/6029.

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Two studies were conducted to investigate the relationship between age, personality factors and aggressive driving behavior. In Study 1, 1122 volunteers completed an online survey that included questionnaires on demographic data, personality factors, and driving behavior. Personality factors were measured using the Revised Competitiveness Index, the Sensation Seeking Scale, the Big Five Inventory, and the Cook Medley Hostility Scale, whereas aggressive driving behavior was measured using the Aggressive Driving Behavior Scale (ADBS). The majority of the volunteers were female (786 versus 336), while ages ranged from 18 to 87. In Study 2, 98 volunteers from Study 1 were recruited to perform driving simulations on two scenarios. These volunteers consisted of 52 females and 46 males, with ages ranging from 18 to 83. Results from both studies produced positive correlations between aggressive driving behavior and competitiveness, sensation seeking, hostility, extraversion, and neuroticism, while negative correlations were obtained between aggressive driving behavior and age, agreeableness, conscientiousness, and openness. No significant correlation was obtained between gender and aggressive driving behavior. Most importantly, scores in the ADBS were positively correlated to a composite of scores measuring aggressive driving behavior in the simulator. This pattern of results not only validates the ADBS, but it also provides another mechanism to study aggressive driving behavior.
Ph.D.
Doctorate
Psychology
Sciences
Psychology; Human Factors Psychology
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Olstam, Johan. "Simulation of Surrounding Vehicles in Driving Simulators." Doctoral thesis, Linköpings universitet, Institutionen för teknik och naturvetenskap, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-17453.

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Driving simulators and microscopic traffic simulation are important tools for making evaluations of driving and traffic. A driving simulator is de-signed to imitate real driving and is used to conduct experiments on driver behavior. Traffic simulation is commonly used to evaluate the quality of service of different infrastructure designs. This thesis considers a different application of traffic simulation, namely the simulation of surrounding vehicles in driving simulators. The surrounding traffic is one of several factors that influence a driver's mental load and ability to drive a vehicle. The representation of the surrounding vehicles in a driving simulator plays an important role in the striving to create an illusion of real driving. If the illusion of real driving is not good enough, there is an risk that drivers will behave differently than in real world driving, implying that the results and conclusions reached from simulations may not be transferable to real driving. This thesis has two main objectives. The first objective is to develop a model for generating and simulating autonomous surrounding vehicles in a driving simulator. The approach used by the model developed is to only simulate the closest area of the driving simulator vehicle. This area is divided into one inner region and two outer regions. Vehicles in the inner region are simulated according to a microscopic model which includes sub-models for driving behavior, while vehicles in the outer regions are updated according to a less time-consuming mesoscopic model. The second objective is to develop an algorithm for combining autonomous vehicles and controlled events. Driving simulators are often used to study situations that rarely occur in the real traffic system. In order to create the same situations for each subject, the behavior of the surrounding vehicles has traditionally been strictly controlled. This often leads to less realistic surrounding traffic. The algorithm developed makes it possible to use autonomous traffic between the predefined controlled situations, and thereby get both realistic traffc and controlled events. The model and the algorithm developed have been implemented and tested in the VTI driving simulator with promising results.
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Blana, Eumorfia. "The behavioural validation of driving simulators as research tools : a case study based on the Leeds Driving Simulator." Thesis, University of Leeds, 2001. http://etheses.whiterose.ac.uk/11329/.

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The objectives of this thesis was to provide researchers with a scientitically-based guide for interpreting driver behaviour results obtained on a fixed-base driving simulator and to provide guidance on how the Leeds Advanced Driving Simulator (LADS) could be modified to overcome any deficiencies that were detected. However. objectives of any simulator validation study are directly related to the specitic driving task under investigation. our ability to perform a similar task in the field (for the comparison of the results between the two environments) and the existing configuration capabilities of the simulator. To achieve the objectives of this study, driver behaviour was investigated at the control level under different road geometry and oncoming traffic conditions using the LADS. Speed and lateral displacement in terms of mean and standard deviation were chosen to represent driver behaviour. They were measured under free-flowing conditions on a rural A road. The objectives of the study were fulfilled by comparing observational uncontrolled real road data with experimental simulator data and by evaluating the differences between the two environments using the absolute and relative validity criteria. It was found that LADS is relatively valid in terms of speed and lateral position. It was also found that higher speeds are developed in the simulator where speed in not confined by the road geometry and simulator subjects drive significantly closer to the edge of the road compared to their real road counterparts irrespective of the road geometry and the oncoming traffic conditions. The face validity of the simulator was examined using subjective data obtained from questionnaires relative to the realism and ease of controlling the simulator. Subjects commented that the least realistic features of the simulator were the braking and steering systems. Subjects were classiffied to "good" and "poor" according to their responses regarding the simulator face validity. It was found that "good" subjects behave slightly better compared to "poor" subjects when driving the simulator.
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Penhallegon, William James. "Effects of display type, age, and gender on driving performance and simulator-induced sickness in a medium-fidelity driving simulator." Thesis, Virginia Tech, 2003. http://hdl.handle.net/10919/43717.

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This study investigated the link between age and gender susceptibility to simulator-induced sickness in conjunction with display type. Simulator-induced sickness and ataxia were measured before and after exposure to a medium-fidelity driving simulator. Participants in four age and gender categories (older and younger males and females) operated the simulator with a consumer-grade head-mounted display (HMD), and then with a large screen, direct-view plasma display.

This study set out to recommend a particular display type that would be appropriate for use with particular age/gender groups in a general-purpose driving simulator. Unfortunately, practice effects affected the simulator-induced sickness and driving performance results for display type, which precludes making recommendations regarding the appropriate use of each display. Despite this, several important discoveries were made, including: 1) older participants did experience significantly increased simulator-induced sickness discomfort than the younger participants - regardless of display type; and 2) there was no significant difference found between genders in either simulator-induced sickness or driving performance; although females generally expressed a subjective preference for the direct-view display.

Display type was not found to affect the degree of ataxia experienced by participants; however, this study did find that although older participants exhibited significantly higher rates of simulator-induced sickness discomfort than the younger participants, they recovered their postural equilibrium significantly faster. This indicates that the older participants had greater difficulty adapting to the simulation environment than younger persons. It also suggests that younger persons are at greater risk during immediate post-simulation activities such as driving. Although it is likely that this effect would disappear over time, it has implications for agencies such as the Department of Motor Vehicles or drivers education schools that are considering the use of a driving simulator device before an on-road skills test.
Master of Science

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Skagerlund, Kenny. "Implications of dysphoria on driving ability : A study using a driving simulator paradigm." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-59055.

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The project of enhancing traffic safety is a continuous effort that will not cease in its aspirations. In fact, as technology evolves and additional digital artifacts are implemented into our cars, the attention to traffic safety becomes even more important. Driving a car through urban and rural environments is a cognitively challenging task that especially tax attentional resources, and as more artifacts compete for our attention during driving, the adherence to traffic safety is vital. Thus, factors that influence driving ability, such as sleep, nutrition and – perhaps - emotions are of great interest. An earlier study by Bulmash et al. (2006) hypothesized that individuals with Major Depressive Disorder would perform worse than controls in a study using a driving simulator; their hypothesis was confirmed. The purpose of this thesis is to investigate whether dysphoric individuals show reduced driving performance relative to controls. The notion of dysphoria refers to mild depression in a non-clinical sense. This was investigated using a driving simulator that measured Lateral Positioning (Standard Deviation of Lateral Position - SDLP) on the road, Brake Reaction Time (BRT) and performance on a secondary task (Peripheral Detection Task - PDT). Dysphoric individuals were identified using the Major Depression Inventory (MDI). The hypothesis was partly confirmed, as dysphoric individuals did indeed show more variable positioning on the road. However, performance differences on PDT and BRT were not significant. The results indicate that the negative influence of mood on driving ability is not a discrete phenomenon primarily manifested in individuals with clinical depression, but is rather a continuous phenomenon. The results should be of special interest to clinicians that evaluate individuals with depressive tendencies, as well as the academic community in general since the insights into the impact of emotions on cognitive performance are inconclusive and still not clearly understood. These results might also be of interest in other domains of high complexity, where human performance is of great importance, such as Command and Control, nuclear power plants and control rooms in general.
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Nyberg, Viktor. "Simulatorbaserad träning av Eco-driving." Thesis, Umeå universitet, Institutionen för psykologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-151096.

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Användandet av simulatorer i utbildningar ökar mer och mer. Simulatorer har använts inom pilotutbildningar och inom medicinsk utbildning länge och det finns mycket forskning som stödjer deras effektivitet. Nu har simulatorerna blivit mer tillgängliga i och med den tekniska utvecklingen och har börjat användas för förarutbildningar. Däremot saknas samma gedigna vetenskapliga stöd som finns för pilotutbildningar och medicinsk utbildning. Det finns visst underlag för utbildning i riskmedvetenhet men inte så många andra färdigheter. Syftet med studien var att undersöka hur effektiv en simulator är vid utbildning av förare i Eco-driving. Till studien rekryterades 20 elever från Yrkesakademin som utbildas för behörighet C, tung lastbil. Studien var av mellangruppsdesign där experimentgruppen tränade Eco-drivingfärdigheter och data över bränsleförbrukning och hastighet samlades in. Kontrollgruppen fick en teoretisk utbildning i Eco-driving i form av en inspelad video. Experimentgruppen hade en signifikant förbättring av bränsleförbrukning men inte kontrollgruppen. Detta stödjer effektiviteten av simulatorbaserad utbildning av Eco-driving. Resultaten är även uppmuntrande till träning av liknande färdigheter som bland annat är av betydelse för trafiksäkerhet. Dessutom finns det goda möjligheter att minska kostnaderna vid förarutbildningar samtidigt som eleverna lär sig bättre.
The use of of simulators in education is increasing. The aviation and medical education have a long history of implementing simulator training and education. With a strong body of scientific research that validates their use in education. As the technical development has increased, the availability of affordable simulators has increased their use in driver education. Unfortunately the research is not as strong as with the aviation or medical education. There are some support that simulator-based education can improve hazard perception but not so many other skills. Therefore I want to examine the effectiveness of a simulator in teaching Eco-driving skills to drivers. 20 students from Yrkesakademin were recruited as they were learning to drive trucks. The study is of between group design where the experimental group practiced Eco-driving skills in the simulator. Data were collected of the participants fuel consumption and speed. The control group were shown a video lecture on Eco-driving. The experimental group did significant improve while the control group did not. These results support the effectiveness of simulator-based education of Eco-driving skills. It also is encouraging for similar driving skills that can have a significant effect on traffic safety. While there is encouraging evidence for reducing the cost of driver education at the same time the students learning is enhanced.
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Books on the topic "Driving simulator"

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United States. National Highway Traffic Safety Administration. and University of Iowa, eds. NADS: National Advanced Driving Simulator, the most sophisticated research driving simulator in the world. [Washington, D.C.]: U.S. Dept. of Transportation, National Highway Traffic Safety Administration, 2003.

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United States. National Highway Traffic Safety Administration and University of Iowa, eds. NADS: National Advanced Driving Simulator, the most sophisticated research driving simulator in the world. [Washington, D.C.]: U.S. Dept. of Transportation, National Highway Traffic Safety Administration, 2003.

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United States. General Accounting Office. Accounting and Information Management Division, ed. National Advanced Driving Simulator. Washington, D.C: The Office, 1994.

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Iowa, University of, ed. NADS: National Advanced Driving Simulator. Washington, D.C.]: National Highway Traffic Safety Administration, 2003.

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Training, California Commission on Peace Officer Standards and. Driving simulator training: Development guidelines. [Sacramento? Calif.]: The Commission, 1999.

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United States. National Highway Traffic Safety Administration, ed. The National Advanced Driving Simulator. [Washington, D.C.]: U.S. Dept. of Transportation, National Highway Traffic Safety Administration, 1994.

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United States. National Highway Traffic Safety Administration. and University of Iowa, eds. NADS: National Advanced Driving Simulator, the most sophisticated research driving simulator in the world. [Washington, D.C.]: U.S. Dept. of Transportation, National Highway Traffic Safety Administration, 2003.

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Frank, Lawrence Henry. Effects of visual display and motion system delays on operator performance and uneasiness in a driving simulator. Blacksburg, Va: Virginia Polytechnic Institute and State University, 1986.

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Hartas, Leo. Gran Turismo 4: The real driving simulator : driving the game. Lewes, East Sussex: Ilex, 2005.

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Gran turismo 4: The real driving simulator. Roseville, CA: Prima Games, 2005.

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Book chapters on the topic "Driving simulator"

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Chen, Fang, and Jacques Terken. "Driving Simulator Applications." In Springer Tracts in Mechanical Engineering, 239–56. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3448-3_14.

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Ren, Jianfeng, and Dong Xia. "Autonomous Driving Simulator." In Autonomous driving algorithms and Its IC Design, 153–62. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2897-2_6.

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Tüschen, Thomas. "SIMULATORS – ‘auto.mobile-driving simulator’ – suspensions design of a wheel-based driving simulator." In Proceedings, 411–34. Wiesbaden: Springer Fachmedien Wiesbaden, 2016. http://dx.doi.org/10.1007/978-3-658-14219-3_29.

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Arioui, Hichem, and Lamri Nehaoua. "Two-Wheeled Riding Simulator: From Design to Control." In Driving Simulation, 85–124. Hoboken, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118648636.ch4.

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Merzouki, Rochdi, Arun Kumar Samantaray, Pushparaj Mani Pathak, and Belkacem Ould Bouamama. "Road Vehicle Driving Simulator." In Intelligent Mechatronic Systems, 909–33. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-4628-5_13.

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Lietsch, Stefan, Henning Zabel, Martin Eikermann, Veit Wittenberg, and Jan Berssenbrügge. "Light Simulation in a Distributed Driving Simulator." In Advances in Visual Computing, 343–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11919476_35.

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Biswas, Pradipta. "User Studies on Driving Simulator." In Exploring the Use of Eye Gaze Controlled Interfaces in Automotive Environments, 41–57. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40709-8_4.

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Sun, Chao, Feng Xie, Xiaocao Feng, Mingmin Zhang, and Zhigeng Pan. "A Training Oriented Driving Simulator." In Entertainment Computing – ICEC 2007, 1–9. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74873-1_1.

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Hisham, Amirah ‘Aisha Badrul, Marwan Nafea, Ahmad Bukhari Aujih, Mohamad Hafis Izran Ishak, and Mohamad Shukri Zainal Abidin. "Racer: A Simulated Environment Driving Simulator to Investigate Human Driving Skill." In Communications in Computer and Information Science, 534–47. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-6502-6_46.

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De Blasiis, Maria Rosaria, Chiara Ferrante, Antonella Santilli, and Valerio Veraldi. "Driving Behavior in Weaving Maneuver: A Driving Simulator Study." In Advances in Intelligent Systems and Computing, 313–25. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41682-3_27.

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Conference papers on the topic "Driving simulator"

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Teasdale, Normand, Martin Lavallière, Mathieu Tremblay, Denis Laurendeau, and Martin Simoneau. "Multiple Exposition to a Driving Simulator Reduces Simulator Symptoms for Elderly Drivers." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2009. http://dx.doi.org/10.17077/drivingassessment.1318.

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Neumeier, Stefan, Michael Hopp, and Christian Facchi. "Yet Another Driving Simulator OpenROUTS3D: The Driving Simulator for Teleoperated Driving." In 2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE). IEEE, 2019. http://dx.doi.org/10.1109/iccve45908.2019.8965037.

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Strayer, David L., and Frank A. Drews. "Simulator Training Improves Driver Efficiency: Transfer from the Simulator to the Real World." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2005. http://dx.doi.org/10.17077/drivingassessment.1120.

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Balk, Stacy A., Mary Anne Bertola, and Vaughan W. Inman. "Simulator Sickness Questionnaire: Twenty Years Later." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2013. http://dx.doi.org/10.17077/drivingassessment.1498.

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Cao, Hui, Chaozhong Wu, and Houjian Tong. "Driving Simulator Based Route Tracing Simulation for Automatic Driving." In First International Conference on Transportation Engineering. Reston, VA: American Society of Civil Engineers, 2007. http://dx.doi.org/10.1061/40932(246)31.

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Mourant, Ronald R., and Maria T. Schultheis. "A HMD-Based Virtual Reality Driving Simulator." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2001. http://dx.doi.org/10.17077/drivingassessment.1061.

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Reed-Jones, James G., Rebecca J. Reed-Jones, Lana M. Trick, Ryan Toxopeus, and Lori A. Vallis. "Comparing Techniques to Reduce Simulator Adaptation Syndrome and Improve Naturalistic Behaviour During Simulated Driving." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2009. http://dx.doi.org/10.17077/drivingassessment.1332.

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Reed-Jones, Rebecca J., James G. Reed-Jones, Lana M. Trick, and Lori A. Vallis. "Can Galvanic Vestibular Stimulation Reduce Simulator Adaptation Syndrome?" In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2007. http://dx.doi.org/10.17077/drivingassessment.1288.

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Morgan, Justin, Scott Tidwell, Myra Blanco, Alejandra Medina, Richard Hanowski, and Olu Ajayi. "Driver Opinions of Simulator-Based Commercial Driver Training." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2011. http://dx.doi.org/10.17077/drivingassessment.1388.

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Rucoba, Robert, Lee Carr, Robert Liebbe, and Amanda Duran. "An Analysis of Driver Reactions to Tire Failures Simulated with the National Advanced Driving Simulator (NADS)." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2011. http://dx.doi.org/10.17077/drivingassessment.1389.

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Reports on the topic "Driving simulator"

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Ringhand, Madlen, Maximilian Bäumler, Christian Siebke, Marcus Mai, and Felix Elrod. Report on validation of the stochastic traffic simulation (Part A). Technische Universität Dresden, 2021. http://dx.doi.org/10.26128/2021.242.

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This document is intended to give an overview of the human subject study in a driving simulator that was conducted by the Chair of Traffic and Transportation Psychology (Verkehrspsychologie – VPSY) of the Technische Universität Dresden (TUD) to provide the Chair of Automotive Engineering (Lehrstuhl Kraftfahrzeugtechnik – LKT) of TUD with the necessary input for the validation of a stochastic traffic simulation, especially for the parameterization, consolidation, and validation of driver behaviour models. VPSY planned, conducted, and analysed a driving simulator study. The main purpose of the study was to analyse driving behaviour and gaze data at intersections in urban areas. Based on relevant literature, a simulated driving environment was created, in which a sample of drivers passed a variety of intersections. Considering different driver states, driving tasks, and traffic situations, the collected data provide detailed information about human gaze and driving behaviour when approaching and crossing intersections. The collected data was transferred to LKT for the development of the stochastic traffic simulation.
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Debs, Luciana, Yanchao Zheng, Jesutoba Ademiloye, Yunfeng Chen, and Jiansong Zhang. Synthesis Study on Employing Snowplow Driving Simulators in Training. Purdue University, 2023. http://dx.doi.org/10.5703/1288284317614.

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Departments of Transportation (DOTs) need to mobilize workers under harsh weather conditions for winter operations.Traditional snowplow driver training at INDOT is usually conducted annually before the snow season; therefore, it does not replicate the conditions which drivers will be exposed to during winter operations. To this point, some state DOTs have incorporated simulators in their snowplow driver training. Despite this raised interest, few studies have (1) surveyed other state DOTs about the use of this equipment in winter operations driver training, or (2) provided a systematic consideration of all factors involved in the decision to use driving simulators in snowplow driver training. To fill these gaps, the present study synthesizes information from previous literature, revises current information from INDOT, and surveys other state DOTs to identify the benefits and challenges of driving simulators for snowplow driver training. A mixed methods approach was utilized including a review of current INDOT practices, interviews with stakeholders, a survey of other state DOTs, and results from a pilot training. Based on the findings, the researchers recommend that INDOT continues to explore the use of driving simulators for training purposes in addition to the yearly snowplow driver training, due the ability to reinforce learning in a safe environment. Moreover, the research team suggests the following areas for further research: evaluating optimal simulator “seat time,” peer learning in simulator training, and the impact of experience level and work assignment in the perception of driving simulator training effectiveness.
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Bäumler, Maximilian, Madlen Ringhand, Christian Siebke, Marcus Mai, Felix Elrod, and Günther Prokop. Report on validation of the stochastic traffic simulation (Part B). Technische Universität Dresden, 2021. http://dx.doi.org/10.26128/2021.243.

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This document is intended to give an overview of the validation of the human subject study, conducted in the driving simulator of the Chair of Traffic and Transportation Psychology (Verkehrspsychologie – VPSY) of the Technische Universität Dresden (TUD), as well of the validation of the stochastic traffic simulation developed in the AutoDrive project by the Chair of Automotive Engineering (Lehrstuhl Kraftfahrzeugtechnik – LKT) of TUD. Furthermore, the evaluation process of a C-AEB (Cooperative-Automatic Emergency Brake) system is demonstrated. The main purpose was to compare the driving behaviour of the study participants and the driving behaviour of the agents in the traffic simulation with real world data. Based on relevant literature, a validation concept was designed and real world data was collected using drones and stationary cameras. By means of qualitative and quantitative analysis it could be shown, that the driving simulator study shows realistic driving behaviour in terms of mean speed. Moreover, the stochastic traffic simulation already reflects reality in terms of mean and maximum speed of the agents. Finally, the performed evaluation proofed the suitability of the developed stochastic simulation for the assessment process. Furthermore, it could be shown, that a C-AEB system improves the traffic safety for the chosen test-scenarios.
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Yoshida, Masashi, Jun Tajima, and Naohiro Yuhara. Perspective Projection With Nonlinear Mapping for Scene Generation of Driving Simulator. Warrendale, PA: SAE International, September 2005. http://dx.doi.org/10.4271/2005-08-0552.

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Maruyama, Kohei, Jun Tajima, and Naohiro Yuhara. Frequency-Dependent Scaling Function in Motion-Cueing Algorithm for Driving Simulator. Warrendale, PA: SAE International, September 2005. http://dx.doi.org/10.4271/2005-08-0553.

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Anne, Viswa Sri Rupa, Einat Tenenboim, and Srinivas Peeta. Using Driving Simulator Environment to Determine Interactions Between User Behavior and Infrastructure Design Under Autonomous Vehicles. Purdue University, 2022. http://dx.doi.org/10.5703/1288284317647.

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McGehee, Daniel V., G. H. Scott Baldwin, Peter Grant, Carole J. Simmons, Jon Hankey, Garrick Forkenbrock, and Elizabeth N. Mazzae. Examination of Drivers' Collision Avoidance Behavior Using Conventional and Antilock Brake Systems on the Iowa Driving Simulator. Washington, D.C: U.S. Department of Transportation. National Highway Traffic Safety Administration, June 1999. http://dx.doi.org/10.17077/9ail-egi7.

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Razmpa, Ali. An Assessment of Post-Encroachment Times for Bicycle-Vehicle Interactions Observed in the Field, a Driving Simulator, and in Traffic Simulation Models. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.5270.

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Edwards, Harvey M., and Rachel Markwald. Design and Integration of a Driving Simulator With Eye-Tracking Capabilities in the Computer Assisted Rehabilitation Environment (CAREN). Fort Belvoir, VA: Defense Technical Information Center, July 2014. http://dx.doi.org/10.21236/ada612243.

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Pulugurtha, Srinivas S., and Raghuveer Gouribhatla. Drivers’ Response to Scenarios when Driving Connected and Automated Vehicles Compared to Vehicles with and without Driver Assist Technology. Mineta Transportation Institute, January 2022. http://dx.doi.org/10.31979/mti.2022.1944.

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Traffic related crashes cause more than 38,000 fatalities every year in the United States. They are the leading cause of death among drivers up to 54 years in age and incur $871 million in losses each year. Driver errors contribute to about 94% of these crashes. In response, automotive companies have been developing vehicles with advanced driver assistance systems (ADAS) that aid in various driving tasks. These features are aimed at enhancing safety by either warning drivers of a potential hazard or picking up certain driving maneuvers like maintaining the lane. These features are already part of vehicles with Driver Assistance Technology, and they are vital for successful deployment of connected and automated vehicles in the near future. However, drivers' responses to driving vehicles with advanced features have been meagerly explored. This research evaluates driver participants' response to scenarios when driving connected and automated vehicles compared to vehicles with and without Driver Assistance Technology. The research developed rural, urban, and freeway driving scenarios in a driver simulator and tested on participants sixteen years to sixty-five years old. The research team explored two types of advanced features by categorizing them into warnings and automated features. The results show that the advanced features affected driving behavior by making driver participants less aggressive and harmonizing the driving environment. This research also discovered that the type of driving scenario influences the effect of advanced features on driver behavior. Additionally, aggressive driving behavior was observed most in male participants and during nighttime conditions. Rainy conditions and female participants were associated with less aggressive driving behavior. The findings from this research help to assess driver behavior when driving vehicles with advanced features. They can be inputted into microsimulation software to model the effect of vehicles with advanced features on the performance of transportation systems, advancing technology that could eventually save millions of dollars and thousands of lives.
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