The influence of non-driving related tasks on driver availability in the context of conditionally automated driving

Advances in Intelligent Systems and Computing

Volumn 823, Issue , 2019, Pages 295-304

  Radlmayr, Jonas ^a   Fischer, Fabian Marco ^a   Bengler, Klaus ^a  

^a TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

Automated driving; NDRT; Non driving related tasks; Take over performance

Indexed keywords

AUTOMATION; HUMAN REACTION TIME; STATISTICS;

AUTOMATED DRIVING; CENTER OF PRESSURE; DEPENDENT VARIABLES; LATERAL ACCELERATION; NDRT; NON-DRIVING RELATED TASKS; STANDARD DEVIATION; TAKE-OVER PERFORMANCE;

ERGONOMICS;

EID: 85051763916     PISSN: 21945357     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-319-96074-6_32     Document Type: Conference Paper

References (12)

1. SAE Standard J3016 (2016) Taxonomy and definitions for terms related to on-road motor vehicle automated driving systems, Surface vehicle recommended practice
2. Marberger C, Mielenz H, Naujoks F, Radlmayr J, Bengler K, Wandtner B (2017) Understanding and applying the concept of “Driver Availability” in automated driving. In: Stanton NA (ed) Advances in Human Aspects of Transportation. Proceedings of the AHFE 2017 International Conference on Human Factors in Transportation, 17−21 July 2017, The Westin Bonaventure Hotel, Los Angeles, California. Springer, Cham, pp 595–605
3. Radlmayr J, Gold C, Lorenz L, Farid M, Bengler K (2014) How traffic situations and non-driving related tasks affect the take-over quality in highly automated driving. In: Proceedings of the human factors and ergonomics society annual meeting, vol 58, pp 2063–2067
4. Stanton NA, Young MS (1997) Automotive automation: investigating the impact on drivers’ mental workload. Int J Cogn Ergon 1:325–336
5. Neubauer C, Matthews G, Langheim L, Saxby D (2012) Fatigue and voluntary utilization of automation in simulated driving. Hum Factors 54:734–746
6. Victor TW, Harbluk JL, Engström JA (2005) Sensitivity of eye-movement measures to in-vehicle task difficulty. Transp Res Part F Traffic Psychol Behav 8:167–190
7. Recarte MÁ, Pérez E, Conchillo Á, Nunes LM (2008) Mental workload and visual impairment: differences between pupil, blink, and subjective rating. Span J Psychol 11: 374–385
8. Gold CG (2016) Modeling of take-over performance in highly automated vehicle guidance. Dissertation, Technische Universität München, München
9. Gold C, Naujoks F, Radlmayr J, Bellem H, Jarosch O (2017) Testing scenarios for human factors research in level 3 automated vehicles. In: Stanton NA (ed) Advances in human aspects of transportation. Proceedings of the AHFE 2017 International Conference on Human Factors in Transportation, 17 − 21 July 2017, The Westin Bonaventure Hotel, Los Angeles. Springer, Cham, pp 551–559
10. ISO14198:2012 (2012) Road vehicles-ergonomic aspects of transport information and control systems. Calibration tasks for methods which assess driver demand due to the use of in-vehicle systems, vol ISO/TS 14198:2012. International Organization for Standardization, Switzerland, p 16
11. Kirchner WK (1958) Age differences in short-term retention of rapidly changing information. J Exp Psychol 55:352
12. Gold C, Berisha I, Bengler K (2015) Utilization of drivetime–performing non-driving related tasks while driving highly automated. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting. SAGE Publications, Los Angeles, pp 1666–1670