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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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Mohd Siam, M. F., N. Borhan, and A. Sukardi. "Driving Simulator Development with Two Degrees of Freedom Motion for Driver Behavior Study." Journal of the Society of Automotive Engineers Malaysia 1, no. 1 (January 8, 2017): 4–11. http://dx.doi.org/10.56381/jsaem.v1i1.2.
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This paper discusses about the development of a driving simulator with 2 Degree of Freedom (DOF) motion platform as a data collection tool for driver behavior research. The simulator was installed with motion platform, steering wheel, pedals, transmission, screens, computer, simulation software and sound system to record the driving behaviors in simulated traffic environment. Data containing information such as participants' response time, vehicle speed, acceleration, braking, turn signals use and vehicle positioning were collected. This paper also discusses the benefits of driving simulator development for driver behavior research while addressing its challenge and limitation for future improvement. The paper concludes that the driving simulator development can contribute significantly to road safety research specifically in driver behavior study.
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Kaptein, Nico A., Jan Theeuwes, and Richard van der Horst. "Driving Simulator Validity: Some Considerations." Transportation Research Record: Journal of the Transportation Research Board 1550, no. 1 (January 1996): 30–36. http://dx.doi.org/10.1177/0361198196155000105.
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The validity of driving simulators for behavioral research is discussed. The concept of validity is introduced and explained, and a survey of validation studies follows, in the TNO driving simulator and others, comparing field and simulator study results. Results for mid-level driving simulators show that generally absolute validity of route choice behavior is obtained and relative validity of speed and lateral control behavior is obtained. There is evidence suggesting that for a number of applications the presence of a moving base and possibly a higher image resolution might increase the validity of a driving simulator.
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Cao, Qing Hua. "The Presence Research on 6-DOF Tank Driving Simulator." Applied Mechanics and Materials 44-47 (December 2010): 1229–33. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.1229.
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with computer graphics technology continually improved, visual simulation system development of sports simulators has become the hotspot. The structure and work principle of 6-DOF tank virtual driving simulator are presented, motion simulation of driven equipment are done by developed based on advanced simulation software(MultiGen Creator and OpenGVS SDK), which is combined with the Object-Oriented method. Dynamics model of simulate system is established , object model is disposed and collision detection is briefly analyzed. The immersion of this visual simulation has been confirmed experimentally.
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Brooks, Johnell O., Richard R. Goodenough, Matthew C. Crisler, Nathan D. Klein, Rebecca L. Alley, Beatrice L. Koon, William C. Logan, Jennifer H. Ogle, Richard A. Tyrrell, and Rebekkah F. Wills. "Simulator sickness during driving simulation studies." Accident Analysis & Prevention 42, no. 3 (May 2010): 788–96. http://dx.doi.org/10.1016/j.aap.2009.04.013.
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Won, Jae-Kyung, and Sang-Heon Lee. "Effect of Driving Simulator Training on Patients' Driving Performance and Self-Efficacy with Paraplegia due to Spinal Cord Injury." Korean Society of Medicine & Therapy Science 15, no. 2 (November 30, 2023): 37–44. http://dx.doi.org/10.31321/kmts.2023.15.2.37.
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Objective: The purpose of this study was to investigate the effect of driving simulator training on the driving performance and self-efficacy of paraplegic patients with spinal cord injury.
Method: Driving simulator training was provided to 12 participants with within subjects design, three sessions of basic driving, seven sessions of driving on the driving simulator. After training, performance time and operational performance scores, self-efficacy were analyzed.
Results: This study found that the intervention by the driving simulator had statistically significant effects on driving time, performance error, ‘Sudden start’, ‘No neutral gear when stopping’, and ‘Speed violation’ and ‘Social self-efficacy’ of paraplegic spinal cord injury patients (p<.05).
Conclusion: Driving simulator training can be a strategy to improve driving performance and social self-efficacy of paraplegic patients with spinal cord injury. Also, patients need sufficient sessions more than 10 times of driving simulator training.
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Ko, Byungjin, Lian Cui, Saerona Choi, Byungkyu Brian Park, and Seunghan Ryu. "Field Evaluation of Vehicle to Infrastructure Communication-Based Eco-Driving Guidance and Eco-Signal System." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 25 (October 12, 2018): 123–38. http://dx.doi.org/10.1177/0361198118797456.
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In urban areas, the main factor causing excessive fuel consumption is stop-and-go, which is prevalent at urban intersections. To decrease fuel consumption at the intersections, various methods have been proposed and evaluated using simulation models and driving simulators. However, it is not known how reliable the driving simulator results would be when compared with those of the field test. In this paper, eco-driving guidance and eco-signal system based on vehicle-to-infrastructure communication are developed and tested in the field in a multi-vehicle environment. They were also tested using a driving simulator and the results were compared with those of the field test. This was intended to assess the reliability of driving simulator-based study. The field test results at an isolated intersection indicated that the eco-driving guidance could save the fuel consumption around 20%–40% and the eco-signal system could reduce the fuel consumption up to 45%. Although the absolute fuel consumptions between the driving simulator test and the field test did not match, the results from both tests confirmed better performance with eco-driving guidance and eco-signal system when compared with the base scenarios. This indicates that a driving simulator is an effective tool for assessing relative benefits of eco-driving guidance and eco-signal system.
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Popović, Nenad B., Nadica Miljković, Kristina Stojmenova, Grega Jakus, Milana Prodanov, and Jaka Sodnik. "Lessons Learned: Gastric Motility Assessment During Driving Simulation." Sensors 19, no. 14 (July 19, 2019): 3175. http://dx.doi.org/10.3390/s19143175.
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In the era of technological advances and innovations in transportation technologies, application of driving simulators for the investigation and assessment of the driving process provides a safe and suitable testing environment. Although driving simulators are crucial for further improvements in transportation, it is important to resolve one of their main disadvantages–simulator sickness. Therefore, suitable methods for the assessment of simulator sickness are required. The main aim of this paper was to present a non-invasive method for assessing simulator sickness by recording gastric myoelectrical activity–electrogastrography. Open-source hardware for electrogastrography together with recordings obtained in 13 healthy volunteers is presented, and the main aspects of signal processing for artifact cancellation and feature extraction were discussed. Based on the obtained results, it was concluded that slow-wave electrical gastric activity can be recorded during driving simulation by following adequate recommendations and that proposed features could be beneficial in describing non-ordinary electrogastrography signals.
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Pieroni, Alessio, Claudio Lantieri, Hocine Imine, and Andrea Simone. "LIGHT VEHICLE MODEL FOR DYNAMIC CAR SIMULATOR." TRANSPORT 31, no. 2 (June 28, 2016): 242–49. http://dx.doi.org/10.3846/16484142.2016.1193051.
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Driving simulators have been becoming little by little a suitable tool oriented to improve the knowledge about the domain of driving research. The investigations that can be conducted with this type of tool concern the driver’s behaviour, the design/control of vehicles, testing assistance systems for driving and the roadway infrastructure’s impact. The benefits of simulation studies are many: lack of any real risk to users, reproducible situations, time savings and reduced testing costs. In addition, their flexibility allows to test situations that do not exist in reality or at least they rarely and randomly exist. The topic of the present work concerns the development of a brand new dynamic model for an existing car simulator owned by LEPSIS laboratory (Laboratoire d’Expliotation, Perception, Simulateurs et Silulations – Laboratory for Road Operations, Perception, Simulators and Simulations) belonging to COSYS (COmposants et SYStems), which is a department of IFSTTAR institute (Institut Français des Sciences et Technologies des Transports, de l’Aménagement et des Réseaux – French Institute of Science and Technology for Transport, Spatial Planning, Development and Networks) site. Once uses and advantages of driving simulators are listed and described, imperfections and limitations of the existing driving vehicle model belonging to the two Degrees of Freedom (DoF) driving simulator of the laboratory are highlighted. Subsequently, structure of the brand new vehicle model, designed by means of Matlab Simulink software, are illustrated through the theoretical framework. Since the vehicle model must refer to a real one, an instrumented Peugeot 406 has been chosen because all its technical features are provided and inserted both on the present model and Prosper/Callas 4.9 by OKTAL software to create a highly sophisticated and accurate virtual version of the commercial car. The validation of this new vehicle model is performed, where the results returned by several different driving scenarios are compared with the ones provided by Prosper software. All the scenarios are simulated with both existing and new vehicle model uploaded in the driving simulator, and the outputs are subsequently compared with the ones returned by Prosper in order to demonstrate the improvements done. Finally, being the number of outputs provided by the new model definitively higher with respect to previous one, additional validations concerning the further results are accomplished.
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Akamatsu, Motoyuki, Masayuki Okuwa, and Masaaki Onuki. "Development of Hi-Fidelity Driving Simulator for Measuring Driving Behavior." Journal of Robotics and Mechatronics 13, no. 4 (August 20, 2001): 409–18. http://dx.doi.org/10.20965/jrm.2001.p0409.
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A hi-fidelity driving simulator has been developed to measure driving behavior. Since the driver is an important component of Intelligent System (i.e., human factor), it is necessary to measure and investigate the driving behavior either with ITS or without ITS. As the driving behavior is situation dependent behavior, there is a great advantage from using the driving simulator because various situational (e.g., traffic situation) and environmental factors can be controlled. The driving simulator is composed of a 290 degree screen and a hexapod motion platform with a fully instrumented vehicle cabin. The road environment for the simulator was a town area with a complex road network and various buildings. The traffic control system can control a traffic scenario with 81 vehicles and 72 pedestrians. Since simulator sickness was one of main concerns of using the hi-fidelity driving simulator, we developed the Simplified Simulator Sickness Questionnaire (SSSQ) to evaluate the subjective severity of simulator sickness. The SSSQ consisted of three subscores for nausea, oculomotor, and disorientation symptoms. A preliminary experiment was conducted to investigate the change in severity of the sickness and the mental workload using SSSQ and NASA-TLX when simulator driving was repeated twelve times. We found that the severity of simulator sickness and the workload decreased with repeated simulator drives. When focusing on the change among three simulator drives within one day, the Nausea subscore decreased but the Oculomotor subscore increased.
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Zeng, Ji Guo, Jing Yu Liu, and Qiang Yu. "Kinematic and Dynamics Modeling of Vehicle Driving Simulator with 6DOF Motion Platform." Applied Mechanics and Materials 543-547 (March 2014): 379–82. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.379.
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In recent years, electric motion platforms are more popularly adopted in high-level driving simulators. This paper describes the kinematic and dynamics modeling for a high-level driving simulator. Firstly, the structure and kinematic models of the platform are introduced. Then, a linear engine simulation model in regard to the accelerator pedal is proposed. Tractive force and the resistance of the vehicle are also studied. Finally, a handling stability model with three degree of freedom is illustrated. All these models are used in the driving simulator of Chang'an University, which has a 6DOF electric motion platform.
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Galante, Francesco, Fabrizio Bracco, Carlo Chiorri, Luigi Pariota, Luigi Biggero, and Gennaro N. Bifulco. "Validity of Mental Workload Measures in a Driving Simulation Environment." Journal of Advanced Transportation 2018 (August 19, 2018): 1–11. http://dx.doi.org/10.1155/2018/5679151.
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Automated in-vehicle systems and related human-machine interfaces can contribute to alleviating the workload of drivers. However, each new functionality can also introduce a new source of workload, due to the need to attend to new tasks and thus requires careful testing before being implemented in vehicles. Driving simulators have become a viable alternative to on-the-road tests, since they allow optimal experimental control and high safety. However, for each driving simulator to be a useful research tool, for each specific task an adequate correspondence must be established between the behavior in the simulator and the behavior on the road, namely, the simulator absolute and relative validity. In this study we investigated the validity of a driving-simulator-based experimental environment for research on mental workload measures by comparing behavioral and subjective measures of workload of the same large group of participants in a simulated and on-road driving task on the same route. Consistent with previous studies, mixed support was found for both types of validity, although results suggest that allowing more and/or longer familiarization sessions with the simulator may be needed to increase its validity. Simulator sickness also emerged as a critical issue for the generalizability of the results.
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Faust, Kayla, Carri Casteel, Daniel V. McGehee, Corinne Peek-Asa, Diane Rohlman, and Marizen R. Ramirez. "Examining the Association Between Age and Tractor Driving Performance Measures Using a High-Fidelity Tractor Driving Simulator." Journal of Agricultural Safety and Health 27, no. 3 (2021): 159–75. http://dx.doi.org/10.13031/jash.14403.
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Highlights This study uses a new tractor driving simulator to examine the impact of age on perception response time in an emergency braking situation. The results demonstrate increased risk for crash among older farm equipment operators. Abstract. Transportation-related incidents are the leading cause of occupational fatalities for all industries in the U.S. In the agriculture industry, where tractor-related incidents are the leading cause of occupational fatality, fatal crashes occur more frequently among senior farm equipment operators (FEOs) than younger FEOs. This study examined the association between age and driving performance among FEOs using a simulated driving environment. We demonstrated that older FEOs have longer perception response times when encountering an incurring semi-truck during a simulated drive than younger FEOs. These results persisted when adjusted for selected medical diagnoses and medications, tractor generation, and tractor horsepower. However, due to the small sample size and limitations of the tractor driving simulator, its use for event perception response time research is questionable. The tractor driving simulator used in this study may be better suited for distracted driving studies and studies comparing the ways in which FEOs drive passenger vehicles compared to tractors. Keywords: Driving simulation, Perception response time, Senior drivers, Tractor.
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Chen, Liang, Jiming Xie, Simin Wu, Fengxiang Guo, Zheng Chen, and Wenqi Tan. "Validation of Vehicle Driving Simulator from Perspective of Velocity and Trajectory Based Driving Behavior under Curve Conditions." Energies 14, no. 24 (December 14, 2021): 8429. http://dx.doi.org/10.3390/en14248429.
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With their advantages of high experimental safety, convenient setting of scenes, and easy extraction of control parameters, driving simulators play an increasingly important role in scientific research, such as in road traffic environment safety evaluation and driving behavior characteristics research. Meanwhile, the demand for the validation of driving simulators is increasing as its applications are promoted. In order to validate a driving simulator in a complex environment, curve road conditions with different radii are considered as experimental evaluation scenarios. To attain this, this paper analyzes the reliability and accuracy of the experimental vehicle speed of a driving simulator. Then, qualitative and quantitative analysis of the lateral deviation of the vehicle trajectory is carried out, applying the cosine similarity method. Furthermore, a data-driven method was adopted which takes the longitudinal displacement, lateral displacement, vehicle speed and steering wheel angle of the vehicle as inputs and the lateral offset as the output. Thus, a curve trajectory planning model, a more comprehensive and human-like operation, is established. Based on directional long short-term memory (Bi–LSTM) and a recurrent neural network (RNN), a multiple Bi–LSTM (Mul–Bi–LSTM) is proposed. The prediction performance of LSTM, MLP model and Mul–Bi–LSTM are compared in detail on the validation set and testing set. The results show that the Mul–Bi–LSTM model can generate a trajectory which is very similar to the driver’s curve driving and have a preferable generalization performance. Therefore, this method can solve problems which cannot be realized in real complex scenes in the simulator validation. Selecting the trajectory as the validation parameter can more comprehensively and intuitively reflect the simulator’s curve driving state. Using a speed model and trajectory model instead of a real car experiment can improve the efficiency of simulator validation and lay a foundation for the standardization of simulator validation.
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Riera, Jose V., Sergio Casas, Francisco Alonso, and Marcos Fernández. "A Case Study on Vestibular Sensations in Driving Simulators." Sensors 22, no. 15 (August 4, 2022): 5837. http://dx.doi.org/10.3390/s22155837.
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Motion platforms have been used in simulators of all types for several decades. Since it is impossible to reproduce the accelerations of a vehicle without limitations through a physically limited system (platform), it is common to use washout filters and motion cueing algorithms (MCA) to select which accelerations are reproduced and which are not. Despite the time that has passed since their development, most of these algorithms still use the classical washout algorithm. In the use of these MCAs, there is always information that is lost and, if that information is important for the purpose of the simulator (the training simulators), the result obtained by the users of that simulator will not be satisfactory. This paper shows a case study where a BMW 325Xi AUT fitted with a sensor, recorded the accelerations produced in all degrees of freedom (DOF) during several runs, and data have been introduced in mathematical simulation software (washout + kinematics + actuator simulation) of a 6DOF motion platform. The input to the system has been qualitatively compared with the output, observing that most of the simulation adequately reflects the input to the system. Still, there are three events where the accelerations are lost. These events are considered by experts to be of vital importance for the outcome of a learning process in the simulator to be adequate.
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Faust, Kayla, Carri Casteel, Daniel V. McGehee, Marizen Ramirez, Diane S. Rohlman, and Corinne Peek-Asa. "Examination of Realism in a High-Fidelity Tractor Driving Simulator." Journal of Agricultural Safety and Health 26, no. 4 (2020): 123–37. http://dx.doi.org/10.13031/jash.14043.
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HighlightsDescribes the creation of a new high-fidelity tractor driving simulator.Describes the perceived realism of a tractor driving simulator among 99 Midwestern farm equipment operators.Examines how farm equipment operator characteristics affect perceived realism of a tractor driving simulator.Discusses potential improvements for future generations of tractor driving simulators.Abstract. Transportation-related incidents are the leading cause of occupational fatalities for all industries in the U.S., including the agricultural industry, which suffers thousands of crashes involving farm equipment each year. Simulated driving studies offer a safe and cost-effective way to conduct driving research that would not be feasible in the real world. A tractor driving miniSim was developed and then evaluated for realism at the University of Iowa among 99 Midwestern farm equipment operators. It is important for driving simulators to have a high degree of realism for their results to be applicable to non-simulated driving operations. High-fidelity driving simulators facilitate extrapolations made by driving research but should be re-tested for realism when changes are made to the design of the simulator. The simulator used in this study emulated a tractor cab with realistic controls, three high-resolution screens, and high-fidelity sound. After completing a 10-minute drive, farm equipment operators completed a survey and scored four specific domains assessing specific characteristics (i.e., appearance, user interface, control, and sound) of the tractor simulator’s realism using a seven-point Likert scale (from 0 = not at all realistic to 6 = completely realistic). An overall realism score and domain scores were calculated. Farm equipment operators were also asked to provide recommendations for improving the tractor miniSim. Overall, farm equipment operators rated the simulator’s realism favorably (i.e., >3 on a scale from 0 to 6) for all individual items and domains. The appearance domain received the highest average realism score (mean = 4.58, SD = 1.03), and the sound domain received the lowest average realism score (mean = 3.86, SD = 1.57). We found no significant differences in realism scores across farm equipment operator characteristics. The most frequently suggested improvements were to tighten the steering wheel (27%), make the front tires visible (19%), and that no improvements were needed to improve the simulator realism (18%). This study demonstrates that the new tractor miniSim is a viable approach to studying farm equipment operations and events that can lead to tractor-related crashes. Future studies should incorporate the suggested improvements and seek to validate the simulator as a research and outreach instrument. Keywords: Driving simulator, Farm equipment operators, Realism, Tractors.
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Mühl, Kristin, Christoph Strauch, Christoph Grabmaier, Susanne Reithinger, Anke Huckauf, and Martin Baumann. "Get Ready for Being Chauffeured." Human Factors: The Journal of the Human Factors and Ergonomics Society 62, no. 8 (September 9, 2019): 1322–38. http://dx.doi.org/10.1177/0018720819872893.
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Objective We investigated passenger’s trust and preferences using subjective, qualitative, and psychophysiological measures while being driven either by human or automation in a field study and a driving simulator experiment. Background The passenger’s perspective has largely been neglected in autonomous driving research, although the change of roles from an active driver to a passive passenger is incontrovertible. Investigations of passenger’s appraisals on self-driving vehicles often seem convoluted with active manual driving experiences instead of comparisons with being driven by humans. Method We conducted an exploratory field study using an autonomous research vehicle ( N = 11) and a follow-up experimental driving simulation ( N = 24). Participants were driven on the same course by a human and an autonomous agent sitting on a passenger seat. Skin conductance, trust, and qualitative characteristics of the perceived driving situation were assessed. In addition, the effect of driving style (defensive vs. sporty) was evaluated in the simulator. Results Both investigations revealed a close relation between subjective trust ratings and skin conductance, with increased trust and by trend reduced arousal for human compared with automation in control. Even though driving behavior was equivalent in the simulator when being driven by human and automation, passengers most preferred and trusted the human-defensive driver. Conclusion Individual preferences for driving style and human or autonomous vehicle control influence trust and subjective driving characterizations. Application The findings are applicable in human-automation research, reminding to not neglect subjective attributions and psychophysiological reactions as a result of ascribed control duties in relation to specific execution characteristics.
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Bidlingmaier, Michael, Tobias Bonitz, and Michael Hoffmann. "Evaluating the Driving Behavior Using a Simulated Environment and Driving Simulator." ATZ worldwide 125, no. 4 (March 24, 2023): 44–49. http://dx.doi.org/10.1007/s38311-023-1462-6.
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Tu, Huizhao, Zhenfei Li, Hao Li, Ke Zhang, and Lijun Sun. "Driving Simulator Fidelity and Emergency Driving Behavior." Transportation Research Record: Journal of the Transportation Research Board 2518, no. 1 (January 2015): 113–21. http://dx.doi.org/10.3141/2518-15.
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Haraldsson, Per-Olle, Christer Carenfelt, Hans Laurell, and Jan Tornros. "Driving Vigilance Simulator Test." Acta Oto-Laryngologica 110, no. 1-2 (January 1990): 136–40. http://dx.doi.org/10.3109/00016489009122528.
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McWilliams, Thomas, Bruce Mehler, Bobbie Seppelt, and Bryan Reimer. "Driving Simulator Validation for In-Vehicle Human Machine Interface Assessment." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 63, no. 1 (November 2019): 2104–8. http://dx.doi.org/10.1177/1071181319631438.
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Driving simulator validation is an important and ongoing process. Advances in in-vehicle human machine interfaces (HMI) mean there is a continuing need to reevaluate the validity of use cases of driving simulators relative to real world driving. Along with this, our tools for evaluating driver demand are evolving, and these approaches and measures must also be considered in evaluating the validity of a driving simulator for particular purposes. We compare driver glance behavior during HMI interactions with a production level multi-modal infotainment system on-road and in a driving simulator. In glance behavior analysis using traditional glance metrics, as well as a contemporary modified AttenD measure, we see evidence for strong relative validity and instances of absolute validity of the simulator compared to on-road driving.
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Duyun, Tatiana, Ivan Duyun, Petr Kabalyants, and Larisa Rybak. "Optimization of a 6-DOF Platform for Simulators Based on an Analysis of Structural and Force Parameters." Machines 11, no. 8 (August 8, 2023): 814. http://dx.doi.org/10.3390/machines11080814.
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Automotive driving simulators are widely used in driving schools and training centers, where they help students acquire the necessary skills without risk to life and health. This paper presents modern research in the field of creating a model and a real prototype of an automotive driving simulator based on the Gough–Stewart platform. This investigation presents optimized geometric parameters using the PSO algorithm. Virtual prototypes of the robotic platform were created by MSC Adams. In turn, this made it possible to conduct the simulation of kinematic and dynamic parameters. They represent operating conditions when exposed to workloads. This paper shows a prototype of an automotive driving simulator and special equipment with an integrated system of virtual 3D models of real terrain.
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Koo, T.-Y., C.-H. Bae, B.-Y. Kim, Z. Rowland, and M.-W. Suh. "Development of a driving simulator for telematics human—machine interface studies." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 222, no. 11 (November 1, 2008): 2077–86. http://dx.doi.org/10.1243/09544070jauto863.
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Driving simulators are useful tools not only to test the components of future cars but also to evaluate the telematics service and human—machine interface (HMI). However, driving simulators available at present cannot be implemented to test and evaluate the telematics service system as the global positioning system (GPS), which contains basic functional support for the telematics module, does not work in the virtual reality environment. In this paper, a GPS simulator is developed which is able to emulate GPS satellite signals, consisting of the NMEA-0183 protocol and RS232C communication standards, and thereby presenting a method of implementing a telematics service for a driving simulator. It is expected that the driving simulator, together with the GPS simulator, can be used to study the HMI for evaluation of commercial telematics systems in order to realize the human-in-the-loop evaluation systems.
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MIKI, KAZUO. "Activties of Simulators. Latest Trends of Driving Simulator." Journal of the Institute of Electrical Engineers of Japan 117, no. 8 (1997): 516–19. http://dx.doi.org/10.1541/ieejjournal.117.516.
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MIYATA, KEISUKE. "Activties of Simulators. Driving Simulator for Crane Operation." Journal of the Institute of Electrical Engineers of Japan 117, no. 8 (1997): 524–27. http://dx.doi.org/10.1541/ieejjournal.117.524.
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JANSE VAN RENSBURG, T., M. A. VAN WYK, and W. H. STEEB. "THREE-DIMENSIONAL GEOMETRY WITHIN A DRIVING SIMULATOR." International Journal of Modern Physics C 16, no. 06 (June 2005): 909–20. http://dx.doi.org/10.1142/s0129183105007650.
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Three-dimensional coordinate transformations are an essential part of the realistic visual display within a driving simulator. They are also used in other simulators such as flight simulators and for robotics. In this paper, the mathematical framework for implementing three-dimensional coordinate transformations is presented, provided with more detail for implementing it in a programming language such as C++. The realistic positioning of an observer for the "behind and above" view in a driving simulator will be discussed as an application of coordinate system transformations.
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McWilliams, Thomas, Nathan Ward, Bruce Mehler, and Bryan Reimer. "Assessing Driving Simulator Validity: A Comparison of Multi-Modal Smartphone Interactions across Simulated and Field Environments." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 37 (September 28, 2018): 164–71. http://dx.doi.org/10.1177/0361198118798729.
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The use of a driving simulator as a tool to evaluate secondary task performance elicits the question of simulator validity. After upgrading an existing driving simulator from a medium-fidelity to a high-fidelity configuration with a new software environment, a study was run to benchmark this simulator against previously published highway-driving data. A primary goal was to assess relative and absolute validity in a simulated highway environment. Data from 72 participants who performed manual and voice-based contact dialing tasks with a center-stack-mounted smartphone in either the driving simulator or driving on the highway in one of two vehicles is considered. This analysis compared secondary task demand between the simulator and on-road vehicles by primarily considering driver off-road glance behavior. Mean total eyes-off-road time, mean single-glance duration, and the number of long off-road glances showed similar patterns relative to the manual versus voice-based tasks in the simulator and the two on-road vehicles. A driving performance metric, percentage change of standard deviation of velocity, showed differing results between the simulator and on-road vehicles. It is concluded that these data make a strong argument for relative validity, and in some cases absolute validity, for this simulator for studying glance behavior associated with in-vehicle devices under a highway-driving scenario.
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Ka, Eunhan, Do-Gyeong Kim, Jooneui Hong, and Chungwon Lee. "Implementing Surrogate Safety Measures in Driving Simulator and Evaluating the Safety Effects of Simulator-Based Training on Risky Driving Behaviors." Journal of Advanced Transportation 2020 (June 19, 2020): 1–12. http://dx.doi.org/10.1155/2020/7525721.
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Human errors cause approximately 90 percent of traffic accidents, and drivers with risky driving behaviors are involved in about 52 percent of severe traffic crashes. Driver education using driving simulators has been used extensively to obtain a quantitative evaluation of driving behaviors without causing drivers to be at risk for physical injuries. However, since many driver education programs that use simulators have limits on realistic interactions with surrounding vehicles, they are limited in reducing risky driving behaviors associated with surrounding vehicles. This study introduces surrogate safety measures (SSMs) into simulator-based training in order to evaluate the potential for crashes and to reduce risky driving behaviors in driving situations that include surrounding vehicles. A preliminary experiment was conducted with 31 drivers to analyze whether the SSMs could identify risky driving behaviors. The results showed that 15 SSMs were statistically significant measures to capture risky driving behaviors. This study used simulator-based training with 21 novice drivers, 16 elderly drivers, and 21 commercial drivers to determine whether a simulator-based training program using the SSMs is effective in reducing risky driving behaviors. The risky driving behaviors by novice drivers were reduced significantly with the exception of erratic lane-changing. In the case of elderly drivers, speeding was the only risky driving behavior that was reduced; the others were not reduced because of their difficulty with manipulating the pedals in the driving simulator and their defensive driving. Risky driving behaviors by commercial drivers were reduced overall. The results of this study indicated that the SSMs can be used to enhance drivers’ safety, to evaluate the safety of traffic management strategies as well as to reduce risky driving behaviors in simulator-based training.
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Al-Shihabi, Talal, and Ronald R. Mourant. "Toward More Realistic Driving Behavior Models for Autonomous Vehicles in Driving Simulators." Transportation Research Record: Journal of the Transportation Research Board 1843, no. 1 (January 2003): 41–49. http://dx.doi.org/10.3141/1843-06.
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Autonomous vehicles are perhaps the most encountered element in a driving simulator. Their effect on the realism of the simulator is critical. For autonomous vehicles to contribute positively to the realism of the hosting driving simulator, they need to have a realistic appearance and, possibly more importantly, realistic behavior. Addressed is the problem of modeling realistic and humanlike behaviors on simulated highway systems by developing an abstract framework that captures the details of human driving at the microscopic level. This framework consists of four units that together define and specify the elements needed for a concrete humanlike driving model to be implemented within a driving simulator. These units are the perception unit, the emotions unit, the decision-making unit, and the decision-implementation unit. Realistic models of humanlike driving behavior can be built by implementing the specifications set by the driving framework. Four humanlike driving models have been implemented on the basis of the driving framework: ( a) a generic normal driving model, ( b) an aggressive driving model, ( c) an alcoholic driving model, and ( d) an elderly driving model. These driving models provide experiment designers with a powerful tool for generating complex traffic scenarios in their experiments. These behavioral models were incorporated along with three-dimensional visual models and vehicle dynamics models into one entity, which is the autonomous vehicle. Subjects perceived the autonomous vehicles with the described behavioral models as having a positive effect on the realism of the driving simulator. The erratic driving models were identified correctly by the subjects in most cases.
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Gonzalez, Diego, Danielle Filio, Lynn Dony, and Michele Oliver. "Muscle Activation and Driving Performance Differences Between Static and Dynamic Driving Simulation Conditions." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 63, no. 1 (November 2019): 2298–302. http://dx.doi.org/10.1177/1071181319631017.
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The purpose of this work was to compare simulator and surface electromyography (sEMG) variables between fixed base (FBDS) and dynamic driving (DDS) simulation conditions using a hexapod robot based driving simulator during 90 degree turning manoeuvers. Nine males and nine females, who wore a light-weight head mounted display to provide the visual input, drove faster in the DDS leading to faster turn exit velocities and turn completion times. For sEMG variables, one of the most common findings was that when making left turns, higher muscle activity was observed in the DDS. This suggests that DDS driving does differ from FBDS driving. Information provided by this work shows that simulator movement affects muscle activation, therefore, care should be taken when interpreting results from FBDS to not assume that similar results would be found in DDS, and by extension naturalistic driving.
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Affandi, Aiman, M. Z. Hassan, and Nur Hazwani Mokhtar. "The Development of the Driving Simulator: Anthropometry and Occupant Packaging Evaluation in Ergonomic Study." Journal of Hunan University Natural Sciences 49, no. 10 (October 30, 2022): 53–69. http://dx.doi.org/10.55463/issn.1674-2974.49.10.7.
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The primary purpose of this study was to produce a driving simulator guided by ergonomics and anthropometry in the population of Malaysians. The data obtained from previous studies on the Malaysian population are minimal, so this study should be highlighted in the automotive research industry. Hence, this study also aimed to improve the existing study, where the driving simulator can investigate driving behavior systematically and in more detail. Furthermore, the simulator can produce the same scenario on the road without involving actual vehicles. Therefore, using a driving simulator can reduce the risk and cost of the study done on a real road. The used monitor will broadcast the setup road scenario on the display that will be observed and evaluated afterward. The research observed anthropometry data from 103 participants in 23 different measurements of 11 standing and 12 sitting positions. This analysis continues with the study of occupant packaging measurement in an actual vehicle's driving area, determining the driving simulator dimension. The driving simulator design is then obtained by analyzing three different vehicle models: BMW i3, Toyota Prius, and Proton Preve. This phase includes the standard and optimum driver seat adjustment according to the required ergonomics study, which is proportional to the Malaysian population measurement based on the selected previous study. The design proceeds with the material selection with aluminum extrusion as its design material. Finally, the design created is analyzed in a CATIA V5 simulation to examine the displacement magnitude and von Mises stress of the rig frame structure when some load is appointed. The final phase included a physical test to measure the driving simulator's abilities to avoid the stated obstacles in measuring its accuracy compared to an actual on-road experiment. This phase included 10 participants with two different scenarios. Participants had a compulsory questionnaire to conclude the analysis based on their experience. In conclusion, this study discriminated against on-road driving behavior with high safety factors and low cost without involving an actual vehicle or road. Hence, the simulation of the designed product proves that the subject weight is directly proportional to the displacement magnitude and its von Mises stress, and vice versa.
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Ekanayake, Hiran B., Per Backlund, Tom Ziemke, Robert Ramberg, Kamalanath P. Hewagamage, and Mikael Lebram. "Comparing Expert and Novice Driving Behavior in a Driving Simulator." Interaction Design and Architecture(s), no. 19 (December 20, 2013): 115–31. http://dx.doi.org/10.55612/s-5002-019-009.
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This paper presents a study focused on comparing driving behavior of expert and novice drivers in a mid-range driving simulator with the intention of evaluating the validity of driving simulators for driver training. For the investigation, measurements of performance, psychophysiological measurements, and self-reported user experience under different conditions of driving tracks and driving sessions were analyzed. We calculated correlations between quantitative and qualitative measures to enhance the reliability of the findings. The experiment was conducted involving 14 experienced drivers and 17 novice drivers. The results indicate that driving behaviors of expert and novice drivers differ from each other in several ways but it heavily depends on the characteristics of the task. Moreover, our belief is that the analytical framework proposed in this paper can be used as a tool for selecting appropriate driving tasks as well as for evaluating driving performance in driving simulators.
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Nesti, Alessandro, Michael Barnett-Cowan, Heinrich H. Bülthoff, and Paolo Pretto. "Roll rate thresholds in driving simulation." Seeing and Perceiving 25 (2012): 167. http://dx.doi.org/10.1163/187847612x647973.
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The restricted operational space of dynamic driving simulators requires the implementation of motion cueing algorithms that tilt the simulator cabin to reproduce sustained accelerations. In order to avoid conflicting inertial cues, the tilt rate is limited below drivers’ perceptual thresholds, which are typically derived from the results of classical vestibular research, where additional sensory cues to self-motion are removed. These limits might be too conservative for an ecological driving simulation, which provides a variety of complex visual and vestibular cues as well as demands of attention which vary with task difficulty. We measured roll rate detection threshold in active driving simulation, where visual and vestibular stimuli are provided as well as increased cognitive load from the driving task. Here thresholds during active driving are compared with tilt rate detection thresholds found in the literature (passive thresholds) to assess the effect of the driving task. In a second experiment, these thresholds (active versus passive) are related to driving preferences in a slalom driving course in order to determine which roll rate values are most appropriate for driving simulators so as to present the most realistic driving experience. The results show that detection threshold for roll in an active driving task is significantly higher than the limits currently used in motion cueing algorithms, suggesting that higher tilt limits can be successfully implemented to better optimize simulator operational space. Supra-threshold roll rates in the slalom task are also rated as more realistic. Overall, our findings indicate that increasing task complexity in driving simulation can decrease motion sensitivity allowing for further expansion of the virtual workspace environment.
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Lee, Geonil, Seongmin Ha, and Jae-il Jung. "Integrating Driving Hardware-in-the-Loop Simulator with Large-Scale VANET Simulator for Evaluation of Cooperative Eco-Driving System." Electronics 9, no. 10 (October 8, 2020): 1645. http://dx.doi.org/10.3390/electronics9101645.
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Recent advances in information and communication technology (ICT) have enabled interaction and cooperation between components of the transportation system, and cooperative eco-driving systems that apply ICT to eco-driving systems are receiving significant attention. A cooperative eco-driving system is a complex system that requires consideration of the electronic control unit (ECU) and vehicle-to-everything (V2X) communication. To evaluate these complex systems, it is needed to integrate simulators with expertise. Therefore, this study presents an integrated driving hardware-in-the-loop (IDHIL) simulator for the testing and evaluation of cooperative eco-driving systems. The IDHIL simulator is implemented by integrating the driving hardware-in-the-loop simulator and a vehicular ad hoc network simulator to develop and evaluate a hybrid control unit and cooperative eco-driving application for the connected hybrid electric vehicle (CHEV). A cooperative eco-driving speed guidance application is utilized to demonstrate the use of our simulator. The results of the evaluation show the improved fuel efficiency of the CHEV through a calculation of the optimal speed profile and the optimal distribution of power based on V2X communication. Finally, this paper concludes with a description of future directions for the testing and evaluation of cooperative eco-driving systems.
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Rodwell, David, Grégoire S. Larue, Lyndel Bates, and Narelle Haworth. "What, Who, and When? The Perceptions That Young Drivers and Parents Have of Driving Simulators for Use in Driver Education." Safety 6, no. 4 (October 15, 2020): 46. http://dx.doi.org/10.3390/safety6040046.
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Driver education providers may utilise technologies such as driving simulators to augment their existing courses. Understanding the perceptions that young drivers and parents have of simulators may help to make simulator-based driver education more accepted and more likely to be effective. Young drivers and parents completed an online questionnaire that included a “simulator invention” visualisation task. Items based on the Goals for Driver Education framework investigated perceptions of the most appropriate skill type, while others examined the most suitable target group for simulator training, and timing in relation to completing a formal driver education course for simulator training to occur. Both groups perceived that simulators were most appropriate for training a combination of physical, traffic, psychological, and social driving skills with learner drivers during attendance at a novice driver education program. Young drivers and parents had similar perceptions regarding the amount that each skill type should be trained using a simulator. Understanding the perceptions of young drivers and parents, and especially those who are somewhat naïve to the use of driving simulators, may aid in the introduction and administration of simulator training and may increase the effectiveness of driver education as a crash countermeasure.
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Stinton, Susan B., Evangelos Pappas, Dale W. Edgar, and Niamh A. Moloney. "Driving performance following a wrist fracture: A pilot study using a driving simulator." Hand Therapy 25, no. 1 (December 10, 2019): 26–36. http://dx.doi.org/10.1177/1758998319887526.
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Introduction Driving performance, as assessed using a driving simulator, after distal radius fracture has not been previously studied. Our aims were to undertake a pilot study to assess feasibility via: (i) acceptability of driving simulation for this assessment purpose, (ii) recruitment and retention, (iii) sample size calculation. Preliminary evaluations of differences in driving performance between individuals recovering from distal radius fracture and controls were conducted to confirm if the methodology provided meaningful results to aid in justification for future studies. Methods Driving performance of 22 current drivers (aged 21–81 years), recruited by convenience sampling, was assessed using a driving simulator. The fracture group included those recovering from distal radius fracture managed with open reduction and internal fixation using a volar plate. The control group were uninjured individuals. Assessment was performed approximately five weeks post-surgery and follow-up assessment two weeks later. Acceptability outcome measures included pain and simulator sickness scores, feasibility measures included retention rates and measures of driving performance included time spent speeding, time spent out of the lane, standard deviation of lateral position and hazard reactions. Results The assessment was completed by 91% of participants; two participants dropped out secondary to simulator sickness. Retention rates were 83%. Preliminary results suggest those with distal radius fracture spent more time out of the lane and less time speeding. Conclusion This method was sensitive, acceptable and feasible according to the parameters of this pilot study. The results from this small sample suggest that between-group differences in driving performance are measurable using driving simulation five weeks following distal radius fracture.
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Wen, Mingyun, Jisun Park, Yunsick Sung, Yong Woon Park, and Kyungeun Cho. "Virtual Scenario Simulation and Modeling Framework in Autonomous Driving Simulators." Electronics 10, no. 6 (March 16, 2021): 694. http://dx.doi.org/10.3390/electronics10060694.
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Recently, virtual environment-based techniques to train sensor-based autonomous driving models have been widely employed due to their efficiency. However, a simulated virtual environment is required to be highly similar to its real-world counterpart to ensure the applicability of such models to actual autonomous vehicles. Though advances in hardware and three-dimensional graphics engine technology have enabled the creation of realistic virtual driving environments, the myriad of scenarios occurring in the real world can only be simulated up to a limited extent. In this study, a scenario simulation and modeling framework that simulates the behavior of objects that may be encountered while driving is proposed to address this problem. This framework maximizes the number of scenarios, their types, and the driving experience in a virtual environment. Furthermore, a simulator was implemented and employed to evaluate the performance of the proposed framework.
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Mourant, Ronald R., and Thara R. Thattacherry. "Simulator Sickness in a Virtual Environments Driving Simulator." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 44, no. 5 (July 2000): 534–37. http://dx.doi.org/10.1177/154193120004400513.
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Milleville-Pennel, Isabelle, and Camilo Charron. "Driving for Real or on a Fixed-Base Simulator: Is It so Different? An Explorative Study." Presence: Teleoperators and Virtual Environments 24, no. 1 (February 1, 2015): 74–91. http://dx.doi.org/10.1162/pres_a_00216.
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The use of driving simulators to assess driving abilities is often controversial because of their artificiality. Our aim is thus to tackle this question by estimating and comparing new indicators such as the mental workload, the psychological feeling (e.g., stress, anxiety, pleasure, and mastery), and feeling of presence when driving a simulator and a real vehicle (either one's own or one that belongs to a driving school). We are most interested in a particular sort of real-world driving: the driving school. This situation has two advantages: It matches our own particular interest in the evaluation of driving abilities and, to some extent, it is as artificial as driving in a simulator. Fourteen expert drivers participated in this study. Each driver was invited to complete two questionnaires (i.e., the NASA-TLX and Questionnaire of Psychological Feeling) that relate to the various driving conditions (i.e., simulator, driving school vehicle, and personal vehicle). The heart rate of drivers was also recorded at rest and during some of the driving conditions. Our results indicate that the feeling of presence was, for some of its component parts, identical in both the simulator and in a real car. Moreover, in both the simulator and real car, none of the assessments of presence revealed values that were close to 100%; indeed, sometimes they were considerably lower. This result leads us to believe that presence may often be underestimated in virtual environments because of the lack of an objective value of reference in the real world. Moreover, results obtained for mental workload and affective feeling indicate that a simulator can be a useful tool for the initial resumption of driving after a period off the road. In particular, a simulator can help to avoid the sort of stress that can lead to task failure or a deterioration in performance.
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Schwab, Benedikt, Christof Beil, and Thomas H. Kolbe. "Spatio-Semantic Road Space Modeling for Vehicle–Pedestrian Simulation to Test Automated Driving Systems." Sustainability 12, no. 9 (May 7, 2020): 3799. http://dx.doi.org/10.3390/su12093799.
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Automated driving technologies offer the opportunity to substantially reduce the number of road accidents and fatalities. This requires the development of systems that can handle traffic scenarios more reliable than the human driver. The extreme number of traffic scenarios, though, causes enormous challenges in testing and proving the correct system functioning. Due to its efficiency and reproducibility, the test procedure will involve environment simulations to which the system under test is exposed. A combination of traffic, driving and Vulnerable Road User (VRU) simulation is therefore required for a holistic environment simulation. Since these simulators have different requirements and support various formats, a concept for integrated spatio-semantic road space modeling is proposed in this paper. For this purpose, the established standard OpenDRIVE, which describes road networks with their topology for submicroscopic driving simulation and HD maps, is combined with the internationally used semantic 3D city model standard CityGML. Both standards complement each other, and their combination opens the potentials of both application domains—automotive and 3D GIS. As a result, existing HD maps can now be used by model processing tools, enabling their transformation to the target formats of the respective simulators. Based on this, we demonstrate a distributed environment simulation with the submicroscopic driving simulator Virtual Test Drive and the pedestrian simulator MomenTUM at a sensitive crossing in the city of Ingolstadt. Both simulators are coupled at runtime and the architecture supports the integration of automated driving functions.
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Tang, Fang, Yan Ding Wei, Xiao Jun Zhou, Zhu Hui Luo, Ming Xiang Xie, and Pei Xin Li. "Research on Vehicle Dynamics Simulation for Driving Simulator." Advanced Materials Research 308-310 (August 2011): 1946–50. http://dx.doi.org/10.4028/www.scientific.net/amr.308-310.1946.
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In order to fulfill the requirement of vehicle dynamics performance and real-time capability in driving simulator, modeling and simulation method of a four-wheeled vehicle model based on multi body dynamics software Vortex was studied. Fundamental construction and dynamics properties of the model such as body, chassis, wheels, power train, suspension and tyre model were described. The model was tested to simulate on the C grade of road. The results indicate that the model and simulation method can well represent vehicle dynamics performance and high real-time capability of simulation, and is worthy to apply to driving simulator in the future.