Analysis of the attention distraction of inexperienced drivers using a fuzzy model - research results

Kruszewski, Mikołaj; Nader, Mirosław

Artykuł - szczegóły

Tytuł artykułu

Analysis of the attention distraction of inexperienced drivers using a fuzzy model - research results

Autorzy

Kruszewski Mikołaj , Nader Mirosław

Wybrane pełne teksty z tego czasopisma

http://pnpw-transport.publisherspanel.com/resources/html/cms/MAINPAGE

Identyfikatory

Warianty tytułu

Analiza rozproszenia uwagi niedoświadczonych kierowców przy użyciu modelu rozmytego - wyniki badań

Języki publikacji

Abstrakty

Limiting the number and consequences of the traffic accidents is one of the most important goals of the EU policy for the road transport. Despite significant efforts in this area, the targets set for the 2010-2020 decade are unlikely to be achieved. This may be due to, inter alia, the increasing importance of the driver attention distraction as a factor contributing to their occurrence. In order to limit the effects of distraction, attempts are made to develop a method to detect such a state of a driver. The distraction of the driver affects the way he drives the vehicle. The authors in their earlier work conducted a research aimed at developing model for detecting states of distraction of the driver's attention, based on a change in the method of vehicle steering. The developed model uses fuzzy logic to detect distraction. This paper presents the results of this model's operation on a sample of 72 drivers, including 36 inexperienced drivers who were the main object of the tests.

Ograniczenie liczby i skutków wypadków w ruchu drogowym jest jednym z najważniejszych celów polityki UE. Pomimo znaczących wysiłków w tej dziedzinie, cele założone na dekadę 2010-2020 prawdopodobnie nie zostaną osiągnięte. Może być to spowodowane m.in. przez wzrost znaczenia rozproszenia uwagi kierowcy, jako czynnika przyczyniającego się do ich powstawania. W celu ograniczenia skutków rozproszenia uwagi podejmowane są próby opracowania metody wykrywania takiego stanu kierowcy. Rozproszenie uwagi kierowcy wpływa bowiem na sposób sterowania przez niego pojazdem. Autorzy we wcześniejszych pracach przeprowadzili badania mające na celu opracowanie modelu wykrywania stanów rozproszenia uwagi kierowcy, bazujący na zmianach w sposobie sterowania pojazdem. Model opracowano ze szczególnym uwzględnieniem kierowców niedoświadczonych i wykorzystuje on logikę rozmytą do wykrywania tych stanów. W artykule przedstawiono wyniki działania modelu, dla próby 72 uczestników badań, spośród których 36 osób było kierowcami niedoświadczonymi.

Słowa kluczowe

cognitive load driving simulators fuzzy logic

obciążenie poznawcze symulator jazdy logika rozmyta

Wydawca

Oficyna Wydawnicza Politechniki Warszawskiej

Czasopismo

Prace Naukowe Politechniki Warszawskiej. Transport

Rocznik

2019

Tom

z. 125

Strony

53--62

Opis fizyczny

Bibliogr. 43 poz., rys., wykr.

Twórcy

autor

Kruszewski Mikołaj

Motor Transport Institute

autor

Nader Mirosław

Warsaw University of Technology

Bibliografia

1. Al-Darrab I.A., Khan Z. A., Ishrat S.I.: An experimental study on the effect of mobile phone conversation on drivers’ reaction time in braking response. Journal of Safety Research, 40 (2009), pp. 185-189, 2009.
2. Ahlstrom C., Kircher K., Kircher A.: A gaze-based driver distraction warning system and its effect on visual behaviour. IEEE Transactions on Intelligent Transportation Systems 14, no. 2, pp. 965-973, 2013.
3. Ameyoe A., Chevrel P., Le-Carpentier E., Mars F., Illy H.: Identification of a linear parameter varying driver model for the detection of distraction. IFAC-PapersOnLine 48-26, pp. 037-042, 2015.
4. Angell L., Auflick J., Austria P.A., Kochhar D., Tijerina L., Biever W., Diptiman T., Hogsett J., Kiger S.: Driver Workload Metrics Task 2 Final Report, NHTSA, 2006.
5. Antin J.F., Dingus T.A., Hulse M.C., & Wierwille W.W.: An evaluation of the effectiveness of an automobile moving-mapnavigation display. International Journal of Man-Machine Studies, 33, 581-594, 1990.
6. Atcheley P., Atwood S., Boulton A.: The choice to text and drive in younger drivers: Behavior may shape attitude. Accident Analysis and Prevention, 43, 134-142, 2011.
7. Atchley P., & Dressel J.: Conversation limits the functional field of view. Human Factors, 46(4), 664- 673, 2004.
8. Beede K.E., Kass S.J.: Engrossed in conversation: The impact of cell phones on simulated driving performance. Accident Analysis and Prevention, 38,415-421, 2006.
9. Burns P.C., Parkes A., Burton S., Smith R.K., Burch D.: How dangerous is driving with a mobile phone? Benchmarking the impairment to alcohol. TRL report TRL547. Berkshire, United Kingdom: TRL Limited, 2002.
10. Caird J., Rizzo M., & Hancock P.: Critical issues in driving simulation methods and measures. Proceedings of the human factors and ergonomics society 48th annual meeting, surface transportation, Ed. Human Factors and Ergonomics Society, New Orleans, Louisiana, USA, pp. 2252-2255, 2004.
11. Choudhary P., Velaga N.R.: Modelling driver distraction effects due to mobile phone use on reaction time. Transportation Research part C 77, pp. 351-365, 2017.
12. Consiglio W., Driscoll P., Witte M., Berg W.P.: Effect of cellular telephone conversations and other potential interference on reaction time in a braking response. Accident Analysis & Prevention, 35(4), 495-500, 2003.
13. Curry G.A., Hieatt D.J., Wilde, G.J.S.: Task load in the motor vehicle operator: A comparative study of assessment procedures. Ottawa, Ontario: Ministry of Transport, Road and Motor Vehicle Traffic Safety Branch, 1975.
14. Drews F.A., Yazdani H., Godfrey C.N., Cooper J.M., Strayer D.L.: Text messaging during simulated driving. Human Factors: The Journal of the Human Factors and Ergonomics Society, 51, 762-770, 2009.
15. Edquist J., Rudin-Brown C.M., Lenne M.G.: The effects of on-street parking and road environment visual complexity on travel speed and reaction time Accident Analysis and Prevention, 45 (2012), pp. 759-765,2012.
16. Engstrom J., Johansson A., Ostlund J.: Effects of visual and cognitive load in real and simulated motorway driving, Transportation Research Part F, 8, 2005.
17. Engstrom J., Markkula G.: Effects of visual and cognitive distraction on lane change test performance. In Proceedings of the 4th international driving symposium on human factors in driver assessment, training, and vehicle design, Stevenson, WA, pp. 199-205, 2007.
18. Fletcher, Zelinsky A.: Driver inattention detection based on eye gaze-road event correlation. The international journal of robotics research 28, no. 6, pp. 774-801, 2009.
19. Funkhouser D., Sayer J.: Naturalistic census of cell phone use. Paper presented at the Proceedings of the 91st Annual Meeting of the Transportation Research Board, Washington, D.C., 2012. http://dx.doi.org/10.3141/2321-01.
20. Green P., Lin B., Bagian T.: Driver Workload as a Function of Road Geometry: A Pilot Experiment. Technical Report UMTRI-93-39/GLCTTR 22-91/01, Ann Arbor, MI: University of Michigan Transportation Research Institute, 1994.
21. Hart S.G., Staveland L.E.: Development of NASA-TLX (Task Load Index): results of empirical and theoretical research. In: Hancock, P.A., Meshkati, N. (Eds.), Human Mental Workload. Elsevier Science, Amsterdam, pp. 139-183, 1988.
22. Horrey W.J., Wickens C.D.: Driving and side task performance: The effects of display clutter, separation, and modality. Tech. Report AHFD-02-13/GM-02-2. Savoy: University of Illinois, Aviation Human Factors Division, 2002.
23. Jamson A.H., Merat N.: Surrogate in-vehicle information systems and driver behavior: Effects of visual and cognitive load in simulated rural driving. Transportation Research Part F (8), 79-96, (2005).
24. Jancke L., Musial F., Vogt J., Kalveram K.T.: Monitoring radio programs and time of day affect simulated car driving performance. Perceptual and Motor Skills, 79, 484-486, 1994.
25. Ji Q., Yang X.: Real-time eye, gaze, and face pose tracking for monitoring driver vigilance. Real-Time Imaging 8, no. 5, pp. 357-377, 2002.
26. Klauer S.G., Dingus T.A., Neale V.L., Sudweeks J.D., Ramsey D.J., 2006. The impact of driver inattention on near-crash/crash risk: an analysis using the 100-car naturalistic driving study data. Report No. DOT HS 810 594, National Highway Traffic Safety Administration, Washington, D.C.
27. Komenda Główna Policji: Wypadki drogowe w Polsce w 2018 roku, Warszawa, 2019. Dostęp URL: http://statystyka.policja.pl/st/ruch-drogowy/76562, Wypadki-drogowe-raporty-roczne.html
28. Kruszewski M., Nader M.: Projekt badań wpływu obciążenia poznawczego zadaniami dodatkowymi na prowadzenie pojazdu przez kierowcę, Logistyka 4/2015, str. 519-526.
29. Kruszewski M., Niezgoda M., Kamiński T., Matysiak A., Nader M.: Pilot study over secondary task cognitive workload induced on drivers in AS 1200-6 simulator, Logistics and Transport, 4(36)/2017, str. 69-78, 2017.
30. Kruszewski M., Razin P., Niezgoda M., Nader M.: Model oceny dodatkowego obciążenia poznawczego u kierowcy na podstawie badań z wykorzystaniem symulatora jazdy, Prace Naukowe Politechniki Warszawskiej - Transport, z. 118, 2017, str. 155-166, 2017.
31. Lee J. D.: Technology and teen drivers. Journal of Safety Research, 38(2), 203-213, 2007.
32. Liang Y., Lee J.: Combining cognitive and visual distraction: Less than the sum of its parts. Accident Analysis and Prevention, 42, 881-890, 2010.
33. Makishita H., Matsunaga K.: Differences of Drivers' Reaction Times According to Age and Mental workload. Accident Analysis and Prevention, 40 (2), pp. 567-575, 2008.
34. Masood S., Rai A., Aggarwal A., Doja M.N., Ahmad M.: Detecting distraction of drivers using Convolutional Neural Network. Pattern Recognition Letters (in press), 2018.
35. Patten Ch.J.D., Kircher A., Östlund J., Nilsson L.: Using mobile telephones: cognitive workload and attention resource allocation. Accident Analysis and Prevention 36 (2004) pp. 341-350, 2004.
36. Pöysti L., Rajalin S., Summala H.: Factors influencing the use of cellular (mobile) phone during driving and hazards while using it. Accident Analysis and Prevention, 37(1), 47-51, 2005. Dostęp URL: http://dx.doi.org /10.1016/j.aap.2004.06.003.
37. Rakauskas M.E., Gugerty L.J., Ward N.J.: Effects of naturalistic cell phone conversations on driving performance. Journal of Safety Research, 35, 453-464, 2004.
38. Recarte M.A., Nunes L.M.: Mental workload while driving: Effects on visual search, discrimination and decision making. Journal of Experimental Psychology: Applied, 9(2), 2003.
39. Reynaud M., Le Breton P., Gilot B., Vervialle F., Falissard B.: Alcohol is the main factor in excess traffic accident fatalities in France. Alcoholism: Clinical and Experimental Research, 26, 1833-1839, 2002.
40. Strayer D.L., Drews F.A., Johnston W.A.: Cell-phone induced failures of visual attention during simulated driving. Journal of Experimental Psychology: Applied, 9, 23-32, 2003.
41. Tömros J.E.B., Bolling A.K.: Mobile phone use - Effects of handheld and handsfree phones on driving performance. Accident Analysis and Prevention, 37(5), 902-909, 2005. http://dx.doi.org/10.1016/j.aap.2005.04.007.
42. U.S. Department of Transportation: Traffic safety facts, distracted driving in fatal crashes, 2017. DOT HS 812 700, Washington, 2019.
43. Zheng X.S., Tai Y.-C., & McConkie G.W.: Effects of cognitive tasks on driver’s eye behavior and performance. Paper presented at the 3rd international symposium on human factors in driver assessment, training & vehicle design, 2003.

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).

Typ dokumentu

Bibliografia

Identyfikator YADDA

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