journal article·2022-04-07Open access

Analysis of the Motion Sickness and the Lack of Comfort in Car Passengers

Estibaliz Asua, Jon Gutiérrez-Zaballa, Oscar Mata-Carballeira, Jon Ander Ruiz, Inés del Campo

Applied Sciences· Volume 12· Issue 8

Abstract

Advanced driving assistance systems (ADAS) are primarily designed to increase driving safety and reduce traffic congestion without paying too much attention to passenger comfort or motion sickness. However, in view of autonomous cars, and taking into account that the lack of comfort and motion sickness increase in passengers, analysis from a comfort perspective is essential in the future car investigation. The aim of this work is to study in detail how passenger’s comfort evaluation parameters vary depending on the driving style, car or road. The database used has been developed by compiling the accelerations suffered by passengers when three drivers cruise two different vehicles on different types of routes. In order to evaluate both comfort and motion sickness, first, the numerical values of the main comfort evaluation variables reported in the literature have been analyzed. Moreover, a complementary statistical analysis of probability density and a power spectral analysis are performed. Finally, quantitative results are compared with passenger qualitative feedback. The results show the high dependence of comfort evaluation variables’ value with the road type. In addition, it has been demonstrated that the driving style and vehicle dynamics amplify or attenuate those values. Additionally, it has been demonstrated that contributions from longitudinal and lateral accelerations have a much greater effect in the lack of comfort than vertical ones. Finally, based on the concrete results obtained, a new experimental campaign is proposed.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Ergonomics and Musculoskeletal Disorders · Virtual Reality Applications and Impacts · Sleep and Work-Related Fatigue

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Electricity and Electronics, Faculty of Science and Technology, University of the Basque Country UPV/EHU, 48940 Leioa, Spain

Ikerlan, S. Coop, Jose Maria Arizmendarrieta Pasealekua, 2, 20500 Arrasate-Mondragon, Spain

Funding

Basque Government · University of the Basque Country

References (58)

Show source-provided references
1. Three Decades of Driver Assistance Systems: Review and Future Perspectives10.1109/MITS.2014.2336271 ↗
2. Fafoutellis, P., Mantouka, E.G., and Vlahogianni, E.I. (2021). Eco-Driving and Its Impacts on Fuel Efficiency: An Overview of Technologies and Data-Driven Methods. Sustainability, 13.10.3390/su13010226 ↗
3. Inside the future cars [Technology Driverless Cars]10.1049/et.2017.1007 ↗
4. Velocity Control Strategies to Improve Automated Vehicle Driving Comfort10.1109/MITS.2017.2776148 ↗
5. Woolridge, E., and Chan-Pensley, J. (2020, July 20). Measuring User’s Comfort in Autonomous Vehicles. Available online: https://humandrive.co.uk/wp-content/uploads/2020/07/HumanDrive-HF-Comfort-White-Paper-v1.1.pdf.
6. Forstberg, J. (2000). Ride Comfort and Motion Sickness in Tilting Trains. [Ph.D. Thesis, Department of Vehicle Engineering, Royal Institute of Technology (KTH)].
7. Heibing, B., and Ersoy, M. (2011). Chassis Handbook: Fundamentals, Driving Dynamics, Components, Mechatronics, Perspectives, Viewg + Teubner Verlag.10.1007/978-3-8348-9789-3_2 ↗
8. Heinz (1999). Criteria for Ride Comfort in Buses and Coaches, Transportation Research Board.
9. Svensson, L., and Eriksson, J. (2015). Tuning for Ride Quality in Autonomous Vehicle: Application to Linear Quadratic Path Planning Algorithm. [Ph.D. Thesis, Uppsala University].
10. Javier, G.S. (2014). Generation of Ride Comfort Index. [Ph.D. Thesis, Universidad Politécnica de Barcelona].
11. Discomfort from feeling vehicle vibration, Vehicle System Dynamics10.1080/00423110701422426 ↗
12. Measuring the perception of comfort in acceleration variation using Eletro-Cardiogram and self-rating measurement for the passengers of the automated vehicle
13. Passenger comfort and trust on first-time use of a shared autonomous shuttle vehicle10.1016/j.trc.2020.02.026 ↗
14. Mühlbacher, D., Tomzig, M., Reinmüller, K., and Rittger, L. (2020). Methodological Considerations Concerning Motion Sickness Investigations during Automated Driving. Information, 11.10.3390/info11050265 ↗
15. Wang, C., Zhao, X., Fu, R., and Li, Z. (2020). Research on the Comfort of Vehicle Passengers Considering the Vehicle Motion State and Passenger Physiological Characteristics: Improving the Passenger Comfort of Autonomous Vehicles. Int. J. Environ. Res. Public Health, 17.10.3390/ijerph17186821 ↗
16. Evaluation of Whole-Body Vibration and Ride Comfort in a Passenger Car
17. Marzbani, H., and Jazar, R.N. (2014). Smart flat ride tuning. Nonlinear Approaches in Engineering Applications 2, Springer.10.1007/978-1-4614-6877-6_1 ↗
18. Structural dynamic characterization of a vehicle seat coupled with human occupant10.1016/j.jsv.2012.10.010 ↗
19. Vibration dose value in passenger car and road roughness10.1061/JPEODX.0000200 ↗
20. Driving Style Recognition for Intelligent Vehicle Control and Advanced Driver Assitance: A survey10.1109/TITS.2017.2706978 ↗
21. Naito, A., Miyajima, C., Nishino, T., Kitaoka, N., and Takeda, K. (2009, January 1–12). Driver evaluation based on classification of rapid decelerating patterns. Proceedings of the 2009 IEEE International Conference on Vehicular Electronics and Safety (ICVES), Pune, India.10.1109/ICVES.2009.5400239 ↗
22. Sathyanarayana, A., Boyraz, P., and Hansen, J.H. (2008, January 22–24). Driver behavior analysis and route recognition by hidden Markov models. Proceedings of the 2008 IEEE International Conference on Vehicular Electronics and Safety, Columbus, OH, USA.10.1109/ICVES.2008.4640874 ↗
23. Investigation of Route-Independent Aggressive and Safe Driving Features Obtained from Accelerometer Signals10.1109/MITS.2017.2666583 ↗
24. In the Passenger Seat: Investigating Ride Comfort Measures in Autonomous Cars10.1109/MITS.2015.2405571 ↗
25. An eco-driving approach for ride comfort improvement10.1049/itr2.12137 ↗
26. Driving Comfort, Enjoyment, and Acceptance of Automated Driving—Effects of Drivers’ Age and Driving Style Familiarity10.1080/00140139.2018.1441448 ↗
27. Objective metrics of comfort: Developing a driving style for highly automated vehicles10.1016/j.trf.2016.05.005 ↗
28. Qiao, X., Ling, Z., Li, Y., Ren, Y., Zhang, Z., Ziwei, Z., and Qiu, L. (2021). Characterization of the Driving Style by State–Action Semantic Plane Based on the Bayesian Nonparametric Approach. Appl. Sci., 11.10.3390/app11177857 ↗
29. Development and evaluation of the automotive seating discomfort questionnaire (ASDQ)10.1016/j.ergon.2005.09.005 ↗
30. Kolich, M. (1999). Reliability and Validity of an Automobile Seat Comfort Survey, SAE Technical Paper. Technical Report.10.4271/1999-01-3232 ↗
31. Driving comfort evaluation of passenger vehicles with natural language processing and improved AHP
32. Schoettle, B., and Sivak, M. (2014). Public Opinion about Self-Driving Vehicles in China, India, Japan, the US, the UK and Australia, UMTRI.
33. Kumara, V., Saranb, V., and Guruguntla, V. (2013, January 18–20). Study of vibration dose value and discomfort due to whole body vibration exposure for a two wheeler drive. Proceedings of the 1st International and 16th National Conference on Machines and Mechanisms (iNaCoMM2013), Roorkee, India.
34. Motion sickness in public road transport: The effect of driver, route and vehicle10.1080/001401399184730 ↗
35. An experimental study of low-frequency motion in cars10.1243/0954407042580093 ↗
36. Imaz, F.J., Hurani, R.A., and Jaurena, J.F. (2015). Estudio Del Índice de Confort del Servicio del Transporte Público de Pasajeros a Través de la Medición de Aceleraciones, Repositorio de la Universidad Tecnologica Nacional.
37. (2020, July 20). Mechanical Vibration and Shock—Evaluation of Human Exposure to Whole-Body Vibration—Part 1: General Requirements. ISO 2631-1 International Organisation for Standarisation. Available online: https://www.iso.org/standard/7612.html.
38. (2020, July 20). Guide to Measurement and Evaluation Of human Exposure to Whole-Body Mechanical Vibration and Repeated Shock. BS 6841. Available online: https://standards.globalspec.com/std/978372/BS%206841.
39. Visual field effects on motion sickness in cars
40. Effect of frequency and direction of horizontal oscillation on motion sickness
41. Motion sickness: Effect of the frequency of lateral oscillation
42. (2008). Vibraciones y Choques Mecánicos. Evaluación de la Exposición Humana a Vibraciones de Cuerpo Entero. Parte 1: Requisitos Generales, International Organization for Standardization. Standard.
43. Embedded system to evaluate the passenger comfort in public transportation based on dynamical vehicle behavior with user’s feedback10.1016/j.measurement.2013.08.068 ↗
44. Kilinc, A., and Baybura, A. (2012, January 6–10). Determination of minimum horizontal curve radius usedin the design of transportation structures, depending on the limit value of comfortcriterion lateral jerk. Proceedings of the Knowing to Manage the Territory, Protect Theenvironment, Evaluate the Cultural Heritage, Rome, Italy.
45. Frequency-domain method for evaluating the ride comfort of a motorcycle10.1080/00423110500420712 ↗
46. Parametric analysis of rail vehicle parameters influencing ride behavior10.4314/ijest.v3i8.5 ↗
47. Study on ride comfort of tractor with tandem suspension based on multi-body system dynamics10.1016/j.apm.2007.10.011 ↗
48. Stoica, P., and Moses, R.L. (2005). Spectral Analysis of Signals, Pearson Prentice Hall.
49. PSD computations using Welch’s method
50. Cohen, L. (1995). Time-Frequency Analysis, Prentice Hall PTR.
51. The Potential Benefits of Naturalistic Driving for Road Safety Research: Theoretical and Empirical Considerations and Challenges for the Future10.1016/j.sbspro.2012.06.1047 ↗
52. Blatt, A., Pierowicz, J., Flanigan, M., Lin, P.S., Kourtellis, A., Lee, C., Jovanis, P., Jenness, J., Wilaby, M., and Campbell, J. (2015). Naturalistic Driving Study: Field Data Collection, Transportation Research Board. Technical Report.10.17226/22367 ↗
53. (2020, July 20). Phyphox. Available online: https://phyphox.org/.
54. Kernel density estimation and its application10.1051/itmconf/20182300037 ↗
55. Quantification of Human Discomfort in a Vehicle Using a Four-Post Rig Excitation10.1260/0263-0923.31.1.29 ↗
56. In Situ Measurement of Discomfort Curves for Seated Subjects in a Car on the Four-Post Rig
57. Various vehicle speeds and road profiles effects on transmitted accelerations analysis to human body segments using vehicle and biomechanical models
58. (2021, October 14). Automotive Intelligence Center Virtual Development Center. Available online: https://www.aicenter.eu/services/vdc.