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2024 | Vol. 27 | 309--320
Tytuł artykułu

Drivers' confidence in advanced drivers assistance systems (ADAS)

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Języki publikacji
EN
Abstrakty
EN
Road accidents are a serious social problem, both in terms of public health and the costs associated with it, and as individual tragedies. Efforts to reduce the role of human factors in road accidents include partial or full automation of tasks performed by drivers through various types of advanced driver assistance systems. The question arises as to what characteristics of a technology user determine the degree of their trust in it in the context of the functionality and reliability of this technology. Two research questions related to the assessment of technology users (ADAS) of its reliability and effectiveness of operation and the differentiation of these assessments in individual groups of respondents were adopted. Data were obtained through survey research using the CATI (Computer Aided Interaction) technique Assisted Web Interview. 155 respondents participated in the study. As a result of the conducted research, it was found that the oldest systems, used for many years – ABS, airbags, inspire the greatest trust among drivers, while the least popular, used relatively recently – line assistance system. The respondent’s metrics (gender, age, experience) do not affect the perception of the effectiveness and reliability of ADAS; this may be surprising, because it is commonly believed that young people are more willing to use various types of technological innovations. Many respondents have no opinion on the effectiveness and efficiency of ADAS systems – most often these are people who do not have such systems installed in their cars or have not had contact with them. The most “educated” group in terms of knowledge of ADAS are – which is not surprising – professional drivers, although the number of such respondents whose knowledge is negligible (17%) may be surprising.
Wydawca

Rocznik
Tom
Strony
309--320
Opis fizyczny
Bibliogr. 23 poz., tab., wykr.
Twórcy
  • Katedra Budowy, Eksploatacji Pojazdów i Maszyn, Wydział Nauk Technicznych, Uniwersytet Warmińsko-Mazurski, ul. Oczapowskiego 11, 10-736 Olsztyn, przemyslaw.drozyner@uwm.edu.pl
  • University of Warmia and Mazury in Olsztyn
Bibliografia
  • ARVIN R., KAMRANI M., KHATTAK A.J. 2019. How instantaneous driving behavior contributes to crashes at intersections: Extracting useful information from connected vehicle message data. Accident Analysis & Prevention, 127: 118-133. https://doi.org/10.1016/j.aap.2019.01.014
  • BIONDI F., STRAYER D.L., ROSSI R., GASTALDI M., MULATTI C. 2017. Advanced driver assistance systems: Using multimodal redundant warnings to enhance road safety. Applied Ergonomics, 58: 238-244. https://doi.org/10.1016/j.apergo.2016.06.016
  • CICCHINO J.B. 2017. Effectiveness of forward collision warning and autonomous emergency braking systems in reducing front-to-rear crash rates. Accident Analysis & Prevention, 99: 142-152. https://doi.org/10.1016/j.aap.2016.11.009
  • DEGUZMAN C.A., DONMEZ B. 2021. Knowledge of and trust in advanced driver assistance systems. Accident Analysis & Prevention, 156: 106121. https://doi.org/10.1016/j.aap.2021.106121
  • DEGUZMAN C.A., DONMEZ B. 2023. Factors influencing trust in advanced driver assistance systems for current users. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 67(1): 1403-1404. https://doi.org/10.1177/21695067231192903
  • DINGUS T.A., GUO F., LEE S., ANTIN J.F., PEREZ M., BUCHANAN-KING M., HANKEY J. 2016. Driver crash risk factors and prevalence evaluation using naturalistic driving data. Proceedings of the National Academy of Sciences, 113(10): 2636-2641.
  • EJDYS J. 2018. Zaufanie do technologii w e-administracji. Oficyna Wydawnicza Politechniki Białostockiej, Białystok.
  • ELVIK R., HØYE A., VAA T., SØRENSEN M. 2009. Factors contributing to road accidents. The Handbook of Road Safety Measures. Emerald Group Publishing Limited, Leeds, p. 35-80. https://doi.org/10.1108/9781848552517-003
  • FAGNANT D.J., KOCKELMAN K. 2015. Preparing a for autonomous vehicles: opportunities, nation barriers and policy recommendations. Transportation Research Part A: Policy and Practice, 77: 167-181. https://doi.org/10.1016/j.tra.2015.04.003
  • HAMID A.A., ISHAK N.S., ROSLAN M.F., ABDULLAH K.H. 2023. Tackling human error in road crashes: An evidence-based review of causes and effective mitigation strategies. Journal of Metrics Studies and Social Science, 2(1): 1-9. https://doi.org/10.56916/jmsss.v2i1.398
  • HELLMAN I.I., LINDMAN M. 2023. Estimating the crash reducing effect of advanced driver assistance systems (ADAS) for vulnerable road users. Traffic Safety Research, 4: 000036-000036. https://doi.org/10.55329/blzz2682
  • HUANG C., WANG J., YAN S., HE D. 2024. Exploring factors related to drivers’ mental model of and trust in advanced driver assistance systems using an ABN-based mixed approach. IEEE Transactions on Human-Machine Systems, 54(6): 646-657. https://doi.org/10.1109/THMS.2024.3436876
  • IYER L.S. 2021. AI enabled applications towards intelligent transportation. Transportation Engineering, 5: 100083. https://doi.org/10.1016/j.treng.2021.100083
  • JERMAKIAN J.S. 2011. Crash avoidance potential of four passenger vehicle technologies. Accident Analysis & Prevention, 43(3): 732-740. https://doi.org/10.1016/j.aap.2010.10.020
  • JIMÉNEZ F., NARANJO J.E., ANAYA J.J., GARCÍA F., PONZ A., ARMINGOL J.M. 2016. Advanced driver assistance system for road environments to improve safety and efficiency. Transportation Research Procedia, 14: 2245-2254. https://doi.org/10.1016/j.trpro.2016.05.240
  • KHAROUFAH H., MURRAY J., BAXTER G., WILD G. 2018. A review of human factors causes in commercial air transport accidents and incidents: From to 2000-2016. Progress in Aerospace Sciences, 99: 1-13. https://doi.org/10.1016/j.paerosci.2018.03.002
  • LANKTON N.K., MCKNIGHT D.H., THATCHER J.B. 2014. Incorporating trust-in-technology into Expectation Disconfirmation Theory. Journal of Strategic Information Systems, 23(2): 128-145. https://doi.org/10.1016/j.jsis.2013.09.001
  • LIAN Y., ZHANG G., LEE J., HUANG H. 2020. Review on big data applications in safety research of intelligent transportation systems and connected/automated vehicles. Accident Analysis & Prevention, 146: 105711. https://doi.org/10.1016/j.aap.2020.105711
  • MASELLO L., CASTIGNANI G., SHEEHAN B., MURPHY F., MCDONNELL K. 2022. On the road safety benefits of advanced driver assistance systems in different driving contexts. Transportation Research Interdisciplinary Perspectives, 15: 100670. https://doi.org/10.1016/j.trip.2022.100670
  • SAM D., VELANGANNI C., EVANGELIN T.E. 2016. A vehicle control system using a time synchronized Hybrid VANET to reduce road accidents caused by human error. Vehicular Communications, 6: 17-28. https://doi.org/10.1016/j.vehcom.2016.11.001
  • STERNLUND S., STRANDROTH J., RIZZI M., LIE A., TINGVALL C. 2017. The effectiveness of lane departure warning systems – A reduction in real-world passenger car injury crashes. Traffic Injury Prevention, 18(2): 225-229. https://doi.org/10.1080/15389588.2016.1230672
  • WADUD Z., MACKENZIE D., LEIBY P. 2016. Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles. Transportation Research Part A: Policy and Practice, 86: 1-18. https://doi.org/10.1016/j.tra.2015.12.001
  • ZHANG J., WANG F.Y., WANG K., LIN W.H., XU X., CHEN C. 2011. Data-driven intelligent transportation systems: A survey. IEEE Transactions on Intelligent Transportation Systems, 12(4): 1624-1639. https://doi.org/10.1109/TITS.2011.2158001.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
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