Chapter
Aug 31, 2020
International Conference on Transportation and Development 2020

The Effects of Extra Cognitive Workload on Drivers’ Driving Performance under Smooth Car-Following Drive and Critical Situations

Publication: International Conference on Transportation and Development 2020

ABSTRACT

A large percentage of drivers like listening to music, radio, or talking to passengers while driving, especially phoning in recent days, even if they use bluetooth earphones or car phone instead of holding the phones by hand. However, such extra cognitive workload will have an impact on drivers’ driving performance. In this study, a driving simulator based experiment was designed to find out drivers’ performance under smooth car-following drive and critical situations. In this experiment, 24 participants (male = 13, female = 11) were required to drive the same city road route twice, with and without extra cognitive workload. Driving performance is measured in driving safety and stability with several indicators. While smooth following the lead vehicle, drivers’ operations are probably not change, however, their risk perception have been increased. Once critical situations happen, extra workload put drivers into a more dangerous and higher risk to collision circumstances. Most of the stability metrics show significant difference between drives with and without extra workload. It is hypothesized that extra workload makes drivers distracted so that they need to adjust velocity and position more frequently.

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REFERENCES

Alrefaie, M. T., S. Summerskill and T. W. Jackon (2019). “In a heart beat: Using driver’s physiological changes to determine the quality of a takeover in highly automated vehicles.” Accident Analysis & Prevention 131: 180-190.
Baldauf, D., E. Burgard and M. Wittmann (2009). “Time perception as a workload measure in simulated car driving.” Appl Ergon 40(5): 929-935.
Beggiato, M. and J. F. Krems (2013). “The evolution of mental model, trust and acceptance of adaptive cruise control in relation to initial information.” Transportation Research Part F Psychology & Behaviour 18(1-2): 47-57.
Bruyas, M.-P. and L. Dumont (2013). “Sensitivity of Detection Response Task (DRT) to the driving demand and task difficulty.”
Coughlin J F, R. B., Mehler B (2009). “Driver wellness, safety & the development of an awarecar.” AgeLab, Mass Inst. Technol., Cambridge, MA.
Deng, T.-M., J.-h. Fu, Y.-M. Shao, J.-s. Peng and J. Xu (2018). “Pedal operation characteristics and driving workload on slopes of mountainous road based on naturalistic driving tests.” Safety Science.
Dogan, E., V. Honnêt, S. Masfrand and A. Guillaume (2019). “Effects of non-driving-related tasks on takeover performance in different takeover situations in conditionally automated driving.” Transportation Research Part F: Traffic Psychology and Behaviour 62: 494-504.
Faure, V., R. Lobjois and N. Benguigui (2016). “The effects of driving environment complexity and dual tasking on drivers’ mental workload and eye blink behavior.” Transportation Research Part F Traffic Psychology & Behaviour 40: 78-90.
Foy, H. J. and C. Peter “Mental workload is reflected in driver behaviour, physiology, eye movements and prefrontal cortex activation.” Applied Ergonomics.
Frederik N, S. H., Christian P, et al. (2018). “From partial and high automation to manual driving: Relationship between non-driving related tasks, drowsiness and take-over performance.” Accident Analysis & Prevention 121: 28-42.
Gold, C., D. Dambock, L. Lorenz and K. Bengler (2013). “"Take over!” How long does it take to get the driver back into the loop?” Proceedings of the Human Factors & Ergonomics Society Annual Meeting 57(1): 1938-1942.
Gold, C., M. Körber, D. Lechner and K. Bengler (2016). “Taking over control from highly automated vehicles in complex traffic situations: the role of traffic density.” Human factors 58(4): 642-652.
Gold, C., L. Lorenz and K. Bengler (2014). Influence of automated brake application on take-over situations in highly automated driving scenarios. Proceedings of the FISITA 2014 World Automotive Congress.
Happee, R., C. Gold, J. Radlmayr, S. Hergeth and K. Bengler (2017). “Take-over performance in evasive manoeuvres.” Accid Anal Prev 106: 211-222.
J., F. H. and C. Peter (2018). “Mental workload is reflected in driver behaviour, physiology, eye movements and prefrontal cortex activation.” Applied Ergonomics.
Jeong, H. and Y. Liu “Effects of non-driving-related-task modality and road geometry on eye movements, lane-keeping performance, and workload while driving.” Transportation Research Part F: Traffic Psychology and Behaviour.
L., A. J. (2015). “Resurrecting driver workload metrics: a multivariate approach.” Procedia Manufacturing 3: 3160-3167.
Li, P., G. Markkula, Y. Li and N. Merat (2018). “Is improved lane keeping during cognitive load caused by increased physical arousal or gaze concentration toward the road center?” Accident Analysis & Prevention 117: 65-74.
Louw, T., R. Madigan, O. Carsten and N. Merat (2017). “Were they in the loop during automated driving? Links between visual attention and crash potential.” Injury prevention 23(4): 281-286.
Louw, T., G. Markkula, E. Boer, R. Madigan, O. Carsten and N. Merat (2017). “Coming back into the loop: Drivers’ perceptual-motor performance in critical events after automated driving.” Accid Anal Prev 108: 9-18.
Lu, G., B. Cheng, Q. Lin and Y. Wang (2012). “Quantitative indicator of homeostatic risk perception in car following.” Safety Science 50(9).
Lu, G., B. Cheng, Y. Wang and Q. Lin (2013). “A Car-Following Model Based on Quantified Homeostatic Risk Perception.” Mathematical Problems in Engineering 2013: 1-13.
Martens, M. and W. Van Winsum (2000). “Measuring distraction: the peripheral detection task.” TNO Human Factors, Soesterberg, Netherlands.
Mehler, B., B. Reimer, J. Coughlin and J. Dusek (2009). “Impact of Incremental Increases in Cognitive Workload on Physiological Arousal and Performance in Young Adult Drivers.” Transportation Research Record: Journal of the Transportation Research Board 2138: 6-12.
Mehler, B., B. Reimer, J. F. Coughlin and J. A. Dusek (2009). “Impact of Incremental Increases in Cognitive Workload on Physiological Arousal and Performance in Young Adult Drivers.” Transportation Research Record Journal of the Transportation Research Board 2138(2138): 6-12.
Merat, N., A. H. Jamson, F. C. H. Lai, M. Daly and O. M. J. Carsten (2014). “Transition to manual: Driver behaviour when resuming control from a highly automated vehicle.” Transportation Research Part F: Traffic Psychology and Behaviour 27: 274-282.
Natasha, M., J. A Hamish, F. C. H. Lai and C. Oliver (2012). “Highly automated driving, secondary task performance, and driver state.” Human Factors 54(5): 762.
Oliver, C., F. C. H. Lai, B. Yvonne, J. A Hamish and M. Natasha (2012). “Control task substitution in semiautomated driving: does it matter what aspects are automated?” Human Factors 54(5): 747.
Olsson, S. and P. Burns (2000). “Measuring driver visual distraction with a peripheral detection task.” Obtained from August.
Pecchini, D., R. Roncella, G. Forlani and F. Giuliani (2017). “Measuring driving workload of heavy vehicles at roundabouts.” Transportation Research Part F Traffic Psychology & Behaviour 45: 27-42.
Perlman, D., A. Samost, A. G. Domel, B. Mehler, J. Dobres and B. Reimer (2019). “The relative impact of smartwatch and smartphone use while driving on workload, attention, and driving performance.” Applied ergonomics 75: 8-16.
Radlmayr, J., C. Gold, L. Lorenz, M. Farid and K. Bengler (2014). How traffic situations and non-driving related tasks affect the take-over quality in highly automated driving. Proceedings of the human factors and ergonomics society annual meeting, Sage Publications Sage CA: Los Angeles, CA.
Ranney, T. A., G. Baldwin, L. A. Smith, E. N. Mazzae and R. S. Pierce (2014). Detection response task (DRT) evaluation for driver distraction measurement application.
Shakouri M, Ikuma L H and A. F (2018). “Analysis of the sensitivity of heart rate variability and subjective workload measures in a driving simulator: the case of highway work zones.” International journal of industrial ergonomics 66: 136-145.
Standardization, I. O. f. (2016). Road Vehicles—Transport Information and Control Systems—Detection–Response Task (DRT) for Assessing Attentional Effects of Cognitive Load in Driving, Author Geneva, Switzerland.
Strayer, D. L. and F. A. Drews (2007). “Cell-phone–induced driver distraction.” Current Directions in Psychological Science 16(3): 128-131.
Strayer, D. L., F. A. Drews and W. A. Johnston (2003). “Cell phone-induced failures of visual attention during simulated driving.” Journal of experimental psychology: Applied 9(1): 23.
Wickens, C. D. (2002). “Multiple resources and performance prediction.” Theoretical issues in ergonomics science 3(2): 159-177.
Wickens, C. D. and B. Goettle (1984). Multiple resources and display formatting: The implications of task integration. Proceedings of the Human Factors Society Annual Meeting, SAGE Publications Sage CA: Los Angeles, CA.
Yeung, J. S. and Y. D. Wong (2014). “The effect of road tunnel environment on car following behaviour.” Accident Analysis & Prevention 70: 100-109.
Yoon S H, K. Y. W., Ji Y G. (2019). “The effects of takeover request modalities on highly automated car control transitions.” Accident Analysis & Prevention 123: 150-158.
Zeeb, K., A. Buchner and M. Schrauf (2015). “What determines the take-over time? An integrated model approach of driver take-over after automated driving.” Accident Analysis and Prevention 78: 212-221.
Zeeb, K., A. Buchner and M. Schrauf (2016). “Is take-over time all that matters? The impact of visual-cognitive load on driver take-over quality after conditionally automated driving.” Accid Anal Prev 92: 230-239.

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Go to International Conference on Transportation and Development 2020
International Conference on Transportation and Development 2020
Pages: 289 - 300
Editor: Guohui Zhang, Ph.D., University of Hawaii
ISBN (Online): 978-0-7844-8314-5

History

Published online: Aug 31, 2020
Published in print: Aug 31, 2020

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1Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control, School of Transportation Science and Engineering, Beihang Univ., Beijing, China. Email: [email protected]
Guangquan Lu [email protected]
2Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control, School of Transportation Science and Engineering, Beihang Univ., Beijing, China; Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast Univ., Nanjing, China; Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang Univ., Beijing, China. Email: [email protected]
Facheng Chen [email protected]
3Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control, School of Transportation Science and Engineering, Beihang Univ., Beijing, China. Email: [email protected]

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