Academic literature on the topic 'Vehicle-driver interaction'
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Journal articles on the topic "Vehicle-driver interaction"
Dargahi Nobari, Khazar, Franz Albers, Katharina Bartsch, Jan Braun, and Torsten Bertram. "Modeling driver-vehicle interaction in automated driving." Forschung im Ingenieurwesen 86, no. 1 (January 24, 2022): 65–79. http://dx.doi.org/10.1007/s10010-021-00576-6.
Full textKrupenia, Stas. "Book Review: Automotive Ergonomics: Driver–Vehicle Interaction." Ergonomics in Design: The Quarterly of Human Factors Applications 23, no. 4 (October 2015): 29. http://dx.doi.org/10.1177/1064804615613314.
Full textPerterer, Nicole, Susanne Stadler, Alexander Meschtscherjakov, and Manfred Tscheligi. "Driving Together Across Vehicle." International Journal of Mobile Human Computer Interaction 11, no. 2 (April 2019): 58–74. http://dx.doi.org/10.4018/ijmhci.2019040104.
Full textPODOPRIGORA, N. V., and P. A. PEGIN. "SYSTEM APPROACH IN INFORMATION SUPPORT OF THE «ROAD USER-VEHICLE-ROAD-EXTERNAL ENVIRONMENT»." World of transport and technological machines 78, no. 3-5 (2022): 73–77. http://dx.doi.org/10.33979/2073-7432-2022-5(78)-3-73-77.
Full textOzsoy, Burak, Xuewu Ji, James Yang, Jared Gragg, and Bradley Howard. "Simulated effect of driver and vehicle interaction on vehicle interior layout." International Journal of Industrial Ergonomics 49 (September 2015): 11–20. http://dx.doi.org/10.1016/j.ergon.2015.05.004.
Full textPODOPRIGORA, N. V. "SYSTEM APPROACH IN INFORMATION SUPPORT OF THE «ROAD USER-VEHICLE-ROAD-EXTERNAL ENVIRONMENT»." World of transport and technological machines 77, no. 2 (2022): 70–75. http://dx.doi.org/10.33979/2073-7432-2022-76-1-70-75.
Full textGraichen, Lisa, Matthias Graichen, and Josef F. Krems. "Evaluation of Gesture-Based In-Vehicle Interaction: User Experience and the Potential to Reduce Driver Distraction." Human Factors: The Journal of the Human Factors and Ergonomics Society 61, no. 5 (January 29, 2019): 774–92. http://dx.doi.org/10.1177/0018720818824253.
Full textHanowski, Richard J., Robert J. Carroll, Walter W. Wierwille, and Rebecca L. Olson. "Light Vehicle-Heavy Vehicle Interactions: A Preliminary Assessment Using Critical Incident Analysis." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 46, no. 22 (September 2002): 1844–47. http://dx.doi.org/10.1177/154193120204602214.
Full textStevens, A. "Safety of driver interaction with in-vehicle information systems." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 214, no. 6 (June 2000): 639–44. http://dx.doi.org/10.1243/0954407001527501.
Full textDamiani, Sergio, Enrica Deregibus, and Luisa Andreone. "Driver-vehicle interfaces and interaction: where are they going?" European Transport Research Review 1, no. 2 (May 13, 2009): 87–96. http://dx.doi.org/10.1007/s12544-009-0009-2.
Full textDissertations / Theses on the topic "Vehicle-driver interaction"
Park, Shinsuk 1966. "Driver-vehicle interaction in braking." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/9421.
Full textIncludes bibliographical references (leaves 81-86).
While antilock brake systems (ABS) have become more and more popular with the public, statistics reports imply that ABS-equipped cars have no advantage over non-ABS-equipped cars in reducing fatal accidents. While the brake pedal needs to be pushed down (full-brake) to activate the ABS, many drivers on ABS-equipped cars fail to do this simple maneuver, reducing the effectiveness of ABS and even contributing to some accidents. Because of such behavior on the driver's part, the major feature of this brake assistance system is often ineffective. The goal of this thesis is to design brake systems that provide intuitive brake control and proper braking performance information for the driver. As a preliminary study in brake system design, the characteristics of human leg motion and its underlying motor control scheme were studied through experiments and simulations. Automotive brake systems were modeled as a type of master-slave tele-manipulator. Human force-displacement interaction at the master end (the brake pedal) has a strong effect on the system's ability to control the operations at the slave end (the braking performance). By providing drivers with "force feel" at the brake pedal, they can obtain information about braking conditions or performance. This thesis developed novel brake systems based on two new aspects. First, the mechanical impedance characteristics of the leg action of the driver were taken into consideration in designing the brake systems. Second, the brake systems provide the driver with kinesthetic feedback of braking conditions or performance. Since the effectiveness of brake systems needs to be examined as a combined driver-vehicle system, driving simulations were used to investigate the performance of the proposed designs.
by Shinsuk Park.
Ph.D.
Löfgren, Pär. "Identification of Driver Unawareness based on User Interaction." Thesis, Linköping University, Department of Electrical Engineering, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8761.
Full textIn new cars of today there are several electronically controlled systems that seek to aid the driver and make the journey as safe as possible. This include not only systems that directly control the vehicle such as ABS and ESP, but also systems that might make driving easier such as navigation systems, cruise control and even seat adjustments.
It is important that the effects on the driver from the use of such systems do not lead to an environment that diverts the attention of the driver from the main task, i.e. driving safely.
In this thesis a possible way of modeling the driver distractedness level due to the operation of these systems is discussed. This is done in Simulink with vehicle CAN data as inputs. An expert field test is done with 6 drivers over 18 trial runs with 31 secondary tasks on a highway. Two criteria are used to measure the distractedness, one objective based on the attributes of an element and one subjective, based on the use of the elements while driving during the trials. A lane monitoring system is evaluated and the offset from the lane center over time is used as an external criteria to the distractedness level. There is however no significant correlation between the external criteria and the subjective distractedness level.
The results of the subjective distractedness level are used in the model and possible future extensions to it are discussed.
Nash, Christopher James. "Measurement and modelling of human sensory feedback in car driving." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/270641.
Full textErséus, Andreas. "Driver-Vehicle Interaction : Identification, Characterization and Modelling of Path Tracking Skill." Doctoral thesis, KTH, Fordonsdynamik, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-13209.
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Lundin, Maria, and Lena Kanstrup. "Method for detection of sleepiness : - measurement of interaction between driver and vehicle." Thesis, Linköping University, Department of Mechanical Engineering, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-7714.
Full textAs more and more people conduct vigilance-based activities at times other than the traditional daytime work hours, the time utilization will continue to escalate in the next century and will further increase the risks of sleepiness-related accidents.
This project, which is commissioned by Scania CV AB, is to nvestigate the potential of a method for sleepiness detection belonging to esium AB. Our objective is to examine whether Scania CV AB should continue with the investigation of the patent method, and in that case, which patent parameters, that indicate sleepiness, should be more closely inquired. The purpose with the method of patent is to discover a sleepy driving behaviour. This method is based on the interaction that appears between the driver and the vehicle. The interaction consists of small spontaneous corrections with the steering wheel that in this report is called micro communication. How well the interaction is functioning can be measured in degree of interaction, which shows how well the driver and the truck interact with each other. The interaction between the driver and the vehicle is in this report looked upon as answers and questions with a certain reaction time, which appears with a certain answered question frequency. The differences in the signal’s amplitudes are measured in variation in amplitudes.
Experiments to collect relevant signals have to be conducted in order to investigate the potential with the method of the patent. It is eligible to collect data from a person falling asleep, which implies experiments conducted in a simulator. The experiments are executed in
a simulator, one test when they are alert and one when they are sleep deprived. Tests are also executed in a Scania truck. The purpose with these experiments is to collect data of the subject’s normal driving pattern in a truck and to investigate if it is possible to obtain
acceptable data in a truck.
The sleepiness experiments have indicated that the micro communication takes place in a frequency range of 0.25 to 6.0 Hz. The variables that have been found to detect sleepiness with high reliability are the reaction time and the degree of interaction presented in spectra.
The validation experiments have shown it is possible to collect exact and accurate data from the lateral acceleration and the steering wheel torque. But, there is more noise in the signals from truck then there is in the signals from the simulator.
This method for sleepiness detection has, according to the authors, a great potential. However, more experiments have to be conducted. The authors suggest further sleepiness experiments only conducted during night time. The subjects are sufficiently alert in the beginning of the test to receive data from normal driving behaviour. Physiological measurement could be interesting to have by the side of the subjective assessments as an additional base for comparison.
Stoltz-Sundnes, Max. "STPA-Inspired Safety Analysis of Driver-Vehicle Interaction in Cooperative Driving Automation." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-263933.
Full textAutonoma fordon på allmänna vägar blir verklighet och genom kooperativ funktionalitet öppnas nya möjligheter för att hitta säkrare och effektivare trafiklösningar än dagens förare har möjlighet till men för att tillåta dessa system måste de kunna bevisas säkra. Denna avhandling fokuserar på säkerhetsanalys av kooperativ körning och människa/maskininteraktion i autonoma fordon. Forskningen bygger på en fallstudie av KTH:s deltagande i en tävling där autonoma kooperativa fordon kör i tre verklighetsinspirerade trafiksituationer (GCDC 2016). Funktionssäkerheten hos den kooperativa körnings-funktionaliteten bedöms med hjälp av den nya metoden Systems Theoretic Process Analysis (STPA) vilket resulterade i ett antal säkerhetsbegränsningar på systemnivå. Analysen visade att utveckling i HMI-relaterade aspekter saknades och modulen som analyserats krävde fortsatt arbete. Under denna utveckling införs visuella aspekter, nya förarcentrerade risker i form av förvirring kring föraransvar och orättvisa övergångar samt en strategi för säker övergång mellan autonoma och manuella tillstånd. Den vidareutvecklade modulen, som resulterade i nya interaktions-möjligheter mellan förare och fordon, analyserades och STPA jämfördes med en ny metod utvecklad för säker läges-växling i autonoma fordon för att identifiera och kvantifiera HMI-relaterade risker. Resultaten visade att oavsiktlig inmatning eller felaktiga inmatningar från föraren innebar störst hot för förvirring, dvs risken för att antingen både fordon och förare eller ingen av dem tror sig ha ansvar för framfarten av fordonet.
Schnelle, Scott C. "Development of Personalized Lateral and Longitudinal Driver Behavior Models for Optimal Human-Vehicle Interactive Control." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1480362246357462.
Full textCocron, Peter. "Regenerative braking and low vehicle noise of electric vehicles – implications for the driver." Doctoral thesis, Universitätsbibliothek Chemnitz, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-155303.
Full textPagliarecci, Nico. "On the understanding of the vehicle-driver interaction using the objectification of subjective assessment : application to the tire development process." Thesis, Mulhouse, 2020. http://www.theses.fr/2020MULH4104.
Full textThe tire is heavily involved in the performance of a vehicle. Vehicle's fuel consumption (rolling resistance, aerodynamics), noise, comfort, handling and safety are related to the tire chosen. By using objective measurements, it is possible to predict some of those features but for some others like handling we cannot really predict the subjective evaluation made by experienced test drivers. Trial/error methodology is sometimes applied to identify tire potential and to gauge the tire performance related to specific designs and mechanical characteristics.Today, in the automotive industry, the evaluation of vehicle and tire handling performance is still largely performed on a subjective basis by experienced test drivers. This is justified by the fact that customer perception of vehicle performance is also made subjectively and, no reliable relationship has been found to relate objective performance measures to the human perception of performance.An extensive literature review on the objectification of subjective assessment, the vehicle-driver interaction, the vehicle dynamics simulation and the explorative multivariate data analysis as well as statistical hypothesis testing is the first research step aimed to investigate the methodologies, the data analytics and statistical tools used by other researchers.Based on the literature review, the thesis proposes a methodology that allows to translate subjective evaluations into objective metrics (vehicle environment as well as vehicle-tire environment) enabling the prediction of the outcome of a subjective test by using objective measurements leading to a reduction of the iterations during the tire development process. The choice of the most relevant vehicle dynamics model’s complexity depicts the main tire mechanical features affecting the handling performance and their effect on the objective metrics of interest. Specific experimental vehicle dynamics maneuvers have been selected for this study with the aim of unpacking the complexity of the subjective handling assessment without being simplistic and paying attention to interconnectedness of the different variables and their interplay with contextual factors.In the frame of the above-mentioned correlation study, the role of the driver in the driver-vehicle system is investigated. The results presented show that, with the chosen methodology, it is possible to gain insights on the driver’s testing strategy identifying the main vehicle responses affecting all the stages of the subjective evaluation. To deepen and strengthen the understanding of the driver’s role, two panel studies involving professional and non-professional drivers have been carried out. Those allowed the study and analysis of the vehicle-driver interaction in terms of proprioception and vision, audio-visual influences and aftereffects in motion
Wanner, Daniel. "Controlling over-actuated road vehicles during failure conditions." Doctoral thesis, KTH, Fordonsdynamik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-166819.
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Books on the topic "Vehicle-driver interaction"
Automotive ergonomics: Driver-vehicle interaction. Boca Raton: CRC Press, 2013.
Find full textC, Cacciabue Pietro, ed. Modelling driver behaviour in automotive environments: Critical issues in driver interactions with intelligent transport systems. London: Springer, 2007.
Find full textGkikas, Nikolaos. Automotive Ergonomics: Driver-Vehicle Interaction. Taylor & Francis Group, 2017.
Find full textGkikas, Nikolaos. Automotive Ergonomics: Driver-Vehicle Interaction. Taylor & Francis Group, 2016.
Find full textGkikas, Nikolaos. Automotive Ergonomics: Driver-Vehicle Interaction. Taylor & Francis Group, 2016.
Find full textGkikas, Nikolaos. Automotive Ergonomics: Driver-Vehicle Interaction. Taylor & Francis Group, 2012.
Find full textEnhanced Social Interaction in Traffic. Not Avail, 2005.
Find full textCacciabue, P. Carlo. Modelling Driver Behaviour in Automotive Environments: Critical Issues in Driver Interactions with Intelligent Transport Systems. Springer, 2007.
Find full textBook chapters on the topic "Vehicle-driver interaction"
Green, Paul A. "Motor Vehicle Driver Interfaces." In The Wiley Handbook of Human Computer Interaction, 843–88. Chichester, UK: John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781118976005.ch40.
Full textVerma, Indresh, Susmita Nath, and Sougata Karmakar. "Research in Driver–Vehicle Interaction: Indian Scenario." In Ergonomics in Caring for People, 353–61. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4980-4_43.
Full textGrimm, Petra, and Julia Maria Mönig. "Ethical Recommendations for Cooperative Driver-Vehicle Interaction—Guidelines for Highly Automated Driving." In Human–Computer Interaction Series, 213–29. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45131-8_4.
Full textStanton, Neville A., James W. H. Brown, Kirsten M. A. Revell, Jediah R. Clark, Joy Richardson, Patrick Langdon, Michael Bradley, Nermin Caber, Lee Skrypchuk, and Simon Thompson. "Modelling Automation–Human Driver Interactions in Vehicle Takeovers Using OESDs." In Designing Interaction and Interfaces for Automated Vehicles, 299–320. First edition. | Boca Raton, FL : CRC Press/Taylor & Francis Group, LLC, 2021. |: CRC Press, 2021. http://dx.doi.org/10.1201/9781003050841-19.
Full textDargahi Nobari, Khazar, Franz Albers, Katharina Bartsch, and Torsten Bertram. "Online Feedback Control for Driver-Vehicle Interaction in Automated Driving." In Advances in Intelligent Systems and Computing, 159–65. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-50943-9_21.
Full textWalch, Marcel, Kristin Mühl, Johannes Kraus, Tanja Stoll, Martin Baumann, and Michael Weber. "From Car-Driver-Handovers to Cooperative Interfaces: Visions for Driver–Vehicle Interaction in Automated Driving." In Automotive User Interfaces, 273–94. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-49448-7_10.
Full textWawage, Pawan, and Yogesh Deshpande. "Pilot Implementation for Driver Behaviour Classification Using Smartphone Sensor Data for Driver-Vehicle Interaction Analysis." In Lecture Notes in Computer Science, 412–20. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98388-8_37.
Full textKashevnik, Alexey, Igor Lashkov, Dmitry Ryumin, and Alexey Karpov. "Smartphone-Based Driver Support in Vehicle Cabin: Human-Computer Interaction Interface." In Lecture Notes in Computer Science, 129–38. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-26118-4_13.
Full textBrown, James W. H., Kirsten M. A. Revell, Joy Richardson, Jisun Kim, Nermin Caber, Patrick Langdon, Michael Bradley, Simon Thompson, Lee Skrypchuk, and Neville A. Stanton. "Can Allowing Interface Customisation Increase Driver Confidence and Safety Levels in Automated Vehicle TORs?" In Designing Interaction and Interfaces for Automated Vehicles, 345–82. First edition. | Boca Raton, FL : CRC Press/Taylor & Francis Group, LLC, 2021. |: CRC Press, 2021. http://dx.doi.org/10.1201/9781003050841-22.
Full textLashkov, Igor, and Alexey Kashevnik. "Human–Computer Interaction Interface for Driver Suspicious Action Analysis in Vehicle Cabin." In Advances in Data Science and Information Engineering, 787–97. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71704-9_57.
Full textConference papers on the topic "Vehicle-driver interaction"
Sezgin, Tevfik Metin, Ian Davies, and Peter Robinson. "Multimodal inference for driver-vehicle interaction." In the 2009 international conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1647314.1647348.
Full textAllen, R. Wade, Theodore J. Rosenthal, and Jeffrey R. Hogue. "Modeling and Simulation of Driver/Vehicle Interaction." In International Congress & Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1996. http://dx.doi.org/10.4271/960177.
Full textKim, Kyongho, HyunKyun Choi, and Byungtae Jang. "Design of the Driver-Adaptive Vehicle Interaction System." In 2018 International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2018. http://dx.doi.org/10.1109/ictc.2018.8539526.
Full textAllen, R. Wade, Henry T. Szostak, and Theodore J. Rosenthal. "Analysis and Computer Simulation of Driver/Vehicle Interaction." In SAE Government Industry Meeting and Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1987. http://dx.doi.org/10.4271/871086.
Full textSidhu, Anmol, Dennis A. Guenther, Ron A. Bixel, and Gary J. Heydinger. "Vehicle to Vehicle Interaction Maneuvers Choreographed with an Automated Test Driver." In SAE World Congress & Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2009. http://dx.doi.org/10.4271/2009-01-0440.
Full textBordegoni, Monica, Marina Carulli, and Yuan Shi. "Investigating the Use of Smell in Vehicle-Driver Interaction." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-60541.
Full textChampoux, B. "A mode of interaction for driver vehicle interface (DVI)." In IEEE Proceedings. Intelligent Vehicles Symposium, 2005. IEEE, 2005. http://dx.doi.org/10.1109/ivs.2005.1505202.
Full textChen, Liang-kuang, and Sheng-yung Hsu. "Investigation of Driver-Controller Interaction in Vehicle Rollover Prevention." In 2006 IEEE International Conference on Systems, Man and Cybernetics. IEEE, 2006. http://dx.doi.org/10.1109/icsmc.2006.384530.
Full textChoi, Jongwoo, Hye Sun Park, Yoonsook Hwang, and Kyong-Ho Kim. "Exhibition Speaker: Driver-Oriented Intelligent Human-Vehicle Interaction System." In 2012 3rd International Conference on Intelligent Systems, Modelling and Simulation (ISMS). IEEE, 2012. http://dx.doi.org/10.1109/isms.2012.149.
Full textDong, Yichen, Sakura Akahoshi, Jieun Lee, Yuchi Saito, and Itoh Makoto. "Modeling user requirements for driver-vehicle interaction system in China." In 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022). AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1001917.
Full textReports on the topic "Vehicle-driver interaction"
Fang, Chen. Unsettled Issues in Vehicle Autonomy, Artificial Intelligence, and Human-Machine Interaction. SAE International, April 2021. http://dx.doi.org/10.4271/epr2021010.
Full textDahal, Sachindra, and Jeffery Roesler. Passive Sensing of Electromagnetic Signature of Roadway Material for Lateral Positioning of Vehicle. Illinois Center for Transportation, November 2021. http://dx.doi.org/10.36501/0197-9191/21-039.
Full textRazdan, Rahul. Unsettled Topics Concerning Human and Autonomous Vehicle Interaction. SAE International, December 2020. http://dx.doi.org/10.4271/epr2020025.
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