From car sickness to autonomous car sickness: A review

Iskander, Julie; Attia, Mohamed; Saleh, Khaled J.; Nahavandi, Darius; Abobakr, Ahmed; Mohamed, Shady; Asadi, Houshyar; Hossny, Mohammed; Lim, Chee Peng; Hossny, Mohammed

doi:10.1016/j.trf.2019.02.020

Cited by 95 publications

(31 citation statements)

References 49 publications

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“…With the vehicle taking complete control of the driving process, the drivers’ role is expected to change completely, enabling them to work or entertain themselves throughout the journey. However, it has been shown that engaging in tasks such as reading [ 1 ] or performing visual search tasks [ 2 ] that deprive passengers of a clear view of the external moving environment, can lead to increased motion sickness (MS), introducing a new challenge for autonomous vehicles’ infotainment designs [ 3 , 4 , 5 , 6 ]. Iskander et al have written an extensive review on the new “autonomous car sickness” (i.e., motion sickness, perceived in autonomous vehicles) in comparison to classic “car sickness” [ 4 ], expressing the need to separately study MS in AVs.…”

Section: Introductionmentioning

confidence: 99%

“…However, it has been shown that engaging in tasks such as reading [ 1 ] or performing visual search tasks [ 2 ] that deprive passengers of a clear view of the external moving environment, can lead to increased motion sickness (MS), introducing a new challenge for autonomous vehicles’ infotainment designs [ 3 , 4 , 5 , 6 ]. Iskander et al have written an extensive review on the new “autonomous car sickness” (i.e., motion sickness, perceived in autonomous vehicles) in comparison to classic “car sickness” [ 4 ], expressing the need to separately study MS in AVs. Since the occurrence and severity of MS in AVs are expected to increase [ 3 , 7 ], the general acceptance of AVs could be questionable without proper countermeasures [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

“…It is therefore important to investigate methods for real time and continuous assessment of MS, which can be time and event correlated. As subjective measurements could sometimes be biased, there is also an ongoing need in the research community for the development of objective measurement methods [ 4 , 5 ]. Despite low overall success, correlations of drivers’ physiological signals with the symptoms of MS have been established through heart rate variability [ 22 , 23 , 24 ], body temperature [ 25 ], skin conductance [ 25 , 26 , 27 ] and electrogastrogram [ 27 , 28 ].…”

Section: Introductionmentioning

confidence: 99%

“…Despite low overall success, correlations of drivers’ physiological signals with the symptoms of MS have been established through heart rate variability [ 22 , 23 , 24 ], body temperature [ 25 ], skin conductance [ 25 , 26 , 27 ] and electrogastrogram [ 27 , 28 ]. Among the research, the most often reported and widely studied MS symptom is nausea [ 4 , 5 , 11 , 25 , 29 , 30 ]. Since nausea and vomiting come from gastrointestinal distress [ 12 , 18 ], there is a reasonably high probability for successful detection of MS with techniques that are primarily used to monitor the gastrointestinal tract [ 31 , 32 ].…”

Section: Introductionmentioning

confidence: 99%

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Electrogastrography in Autonomous Vehicles—An Objective Method for Assessment of Motion Sickness in Simulated Driving Environments

Gruden

Popović

Stojmenova

et al. 2021

Sensors

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Autonomous vehicles are expected to take complete control of the driving process, enabling the former drivers to act as passengers only. This could lead to increased sickness as they can be engaged in tasks other than driving. Adopting different sickness mitigation techniques gives us unique types of motion sickness in autonomous vehicles to be studied. In this paper, we report on a study where we explored the possibilities of assessing motion sickness with electrogastrography (EGG), a non-invasive method used to measure the myoelectric activity of the stomach, and its potential usage in autonomous vehicles (AVs). The study was conducted in a high-fidelity driving simulator with a virtual reality (VR) headset. There separate EGG measurements were performed: before, during and after the driving AV simulation video in VR. During the driving, the participants encountered two driving environments: a straight and less dynamic highway road and a highly dynamic and curvy countryside road. The EGG signal was recorded with a proprietary 3-channel recording device and Ag/AgCl cutaneous electrodes. In addition, participants were asked to signalize whenever they felt uncomfortable and nauseated by pressing a special button. After the drive they completed also the Simulator Sickness Questionnaire (SSQ) and reported on their overall subjective perception of sickness symptoms. The EGG results showed a significant increase of the dominant frequency (DF) and the percentage of the high power spectrum density (FSD) as well as a significant decrease of the power spectrum density Crest factor (CF) during the AV simulation. The vast majority of participants reported nausea during more dynamic conditions, accompanied by an increase in the amplitude and the RMS value of EGG. Reported nausea occurred simultaneously with the increase in EGG amplitude. Based on the results, we conclude that EGG could be used for assessment of motion sickness in autonomous vehicles. DF, CF and FSD can be used as overall sickness indicators, while the relative increase in amplitude of EGG signal and duration of that increase can be used as short-term sickness indicators where the driving environment may affect the driver.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Electrogastrography in Autonomous Vehicles—An Objective Method for Assessment of Motion Sickness in Simulated Driving Environments

Gruden

Popović

Stojmenova

et al. 2021

Sensors

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“…Also, classical WFs suffer from other drawbacks including fixed WF parameters, absence of a human vestibular model and lack of consideration for MSP's limitations. These drawbacks lead to motion sickness as the most important drawback of the MCA [16]. The concept of the adaptive WF was introduced by Parrish et al [17] to change cut-off frequencies of the classical WF.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Washout Filter Based on Fuzzy Logic for a Motion Simulation Platform With Consideration of Joints’ Limitations

Qazani

Asadi

Bellmann

et al. 2020

IEEE Trans. Veh. Technol.

Self Cite

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Motion simulation platforms (MSPs) are widely used to generate driving/flying motion sensations for the users. The MSPs have a restricted workspace area due to the dynamical and physical restrictions of the Motion Platforms active joints as well as the physical limitations of its passive joints. The motion cueing algorithm (MCA) is the reproduction of the motion signal including linear accelerations and angular velocities. It aims to simultaneously respect the MSP's workspace limitations and make the same motion feeling for the user as a real vehicle. The Classical washout filter (WF) is a wellknown type of MCA. The classical WF is easy to set-up, offers a low computational burden and high functionality but has some major drawbacks such as fixed WF parameters tuned according to worstcase scenarios and no consideration of the human vestibular system. As a result, adaptive WFs were developed to consider the human vestibular system and enhance the efficiency of the method using time-varying filters. The existing adaptive WFs only cogitate the boundaries of the end-effector in the Cartesian coordinate space as a substitute for the active and passive joints limitations, which is MSP's main limiting factor. This conservative assumption reduces the available workspace area of the MSP and increases the motion sensation error for the MSPs user. In this study, a fuzzy logic-based WF is developed, to consider the dynamical and physical boundaries of the active joints as well as the physical boundaries of the passive joints. A genetic algorithm is used to select the membership functions' values of the active and passive joints' boundaries. The model is designed using MATLAB /Simulink and the outcomes demonstrate the efficiency of the proposed method versus existing adaptive WFs.

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Fluid Interface Concept for Automated Driving

Pretto

Mörtl

Neuhuber

2020

Lecture Notes in Computer Science

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The biggest challenge for a human-machine interface in highly automated vehicles is to provide enough information to the potentially unaware human operator to induce an appropriate response avoiding cognitive overload. Current interface design struggles to provide timely and relevant information tailored for future driver's needs. Therefore, a new human-centered approach is required to connect drivers, vehicles and infrastructures and account for non-driving related activities in the forthcoming automated vehicles. A viable solution derives from a holistic approach that merges technological tools with human factors knowledge, to enable the understanding and resolution of potential usability, trust and acceptance issues. In this paper, the human factors challenges introduced by automated driving provide the starting point for the conceptualization of a new Fluid interface. The requirements for the new concept are derived from a systematic analysis of the necessary interactions among driver, vehicle and environment. Therefore, the characteristics, components and functions of the interface are described at a theoretical level and compared to alternative solutions.

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From car sickness to autonomous car sickness: A review

Cited by 95 publications

References 49 publications

Electrogastrography in Autonomous Vehicles—An Objective Method for Assessment of Motion Sickness in Simulated Driving Environments

Electrogastrography in Autonomous Vehicles—An Objective Method for Assessment of Motion Sickness in Simulated Driving Environments

Adaptive Washout Filter Based on Fuzzy Logic for a Motion Simulation Platform With Consideration of Joints’ Limitations

Fluid Interface Concept for Automated Driving

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