Drivers' confidence in advanced drivers assistance systems (ADAS)
Przemysław Drożyner
UWM w OlsztyniePaweł Mikołajczak
Abstrakt
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.
Słowa kluczowe:
advanced driver assistance systems, trust, technologyBibliografia
Arvin, Ramin, Mohsen Kamrani, and Asad J. Khattak. "How instantaneous driving behavior contributes to crashes at intersections: Extracting useful information from connected vehicle message data." Accident Analysis & Prevention 127 (2019): 118-133. Google Scholar
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. Google Scholar
Cicchino, Jessica B. "Effectiveness of forward collision warning and autonomous emergency braking systems in reducing front-to-rear crash rates." Accident Analysis & Prevention 99 (2017): 142-152. Google Scholar
DeGuzman , C.A., Donmez , B. 2021. Knowledge of and trust in advanced driver assistance systems. Accident Analysis & Prevention , 156 , 106121. Google Scholar
DeGuzman , CA, Donmez , B. 2023. Factors influencing trust in advanced driver assistance systems for current users. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting (Vol. 67, No. 1, pp. 1403-1404). Sage CA: Los Angeles, CA: SAGE Publications. Google Scholar
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. Google Scholar
Ejdys J. 2018., Trust in technology in e- administration , Białystok . Google Scholar
Elvik, R., Høye, A., Vaa , T.,Sørensen , M. 2009. Factors contributing to road accidents. In The handbook of road safety measures (pp. 35-80). Emerald Group Publishing Limited. Google Scholar
Fagnant, DJ, Kockelman , K. 2015. Preparing a for autonomous vehicles: opportunities, nation barriers and policy recommendations. Transportation Research Part A: Policy and Practice , 77 , 167-181. Google Scholar
Hamid, Ashyfah Abdul, et al. 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 (2023): 1-9. Google Scholar
Hellman, II, Lindman, M.(2023. Estimating the crash reducing effect of advanced driver assistance systems (ADAS) for vulnerable road users. Traffic Safety Research , 4 , 000036-000036. Google Scholar
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 . Google Scholar
Iyer, LS 2021. AI enabled applications towards intelligent transportation. Transportation Engineering , 5 , 100083. Google Scholar
Jermakian, Jessica S. "Crash avoidance potential of four passenger vehicle technologies." Accident Analysis & Prevention 43.3 (2011): 732-740. Google Scholar
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. Google Scholar
Jiménez, Felipe, et al. "Advanced driver assistance system for road environments to improve safety and efficiency." Transportation research procedia 14 (2016): 2245-2254 Google Scholar
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. Google Scholar
Lankton NK, McKnight DH, Thatcher JB 2014. , Incorporating trust-in-technology into Expectation Disconfirmation Theory, Journal of Strategic Information Systems, vol. 23(2), pp. 128-145. Google Scholar
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. Google Scholar
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. Google Scholar
Sam, Dahlia, Cyrilraj Velanganni , and T. Esther Evangelin. 2016. "A vehicle control system using a time synchronized Hybrid VANET to reduce road accidents caused by human error." Vehicular communications 6 (2016): 17-28. Google Scholar
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. Google Scholar
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. Google Scholar
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. Google Scholar
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