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Will autonomous vehicles make us sick?



Autonomous vehicles have the potential to radically change the way we use and interact with our cars. Current thinking assumes that drivers will engage in non-driving tasks and, accordingly, future vehicle design may look dramatically different. However, the use cases envisaged are also known to exacerbate the incidence and severity of carsickness. This paper will discuss these scenarios with reference to the aetiology of carsickness and suggest design constraints to facilitate acceptable future autonomous vehicle design.
Diels, C. (2014). Will autonomous vehicles make us sick? In S. Sharples & S. Shorrock (Eds.),
Contemporary Ergonomics and Human Factors (pp. 301-307). Boca Raton, FL: CRC Press.
Cyriel Diels
Coventry School of Art & Design, Department of Industrial Design, Coventry
University, Priory Street
Coventry CV15FB, UK
Autonomous vehicles have the potential to radically change the
way we use and interact with our cars. Current thinking assumes
that drivers will engage in non-driving tasks and, accordingly,
future vehicle design may look dramatically different. However,
the use cases envisaged are also known to exacerbate the incidence
and severity of carsickness. This paper will discuss these scenarios
with reference to the aetiology of carsickness and suggest design
constraints to facilitate acceptable future autonomous vehicle
Maturation, integration and affordability of enabling technologies have turned
automated driving into a reality. We have seen Google’s driverless car clocking
up thousands of accident-free miles and now several US states, the UK and Japan
have passed laws permitting (human-supervised) autonomous cars on their roads
for R&D purposes. Several car manufacturers including GM, Mercedes, and
Nissan, also recently announced their intention to offer semi-autonomous
vehicles by 2020. These vehicles provide dual-mode operation whereby, on
demand, longitudinal and lateral vehicle control can be handed over to the
vehicle. The system essentially combines full range adaptive cruise control with
automated lane keeping applying steering actions using electrical power steering.
On-road trials are currently also underway to evaluate so-called platoon driving,
i.e. the grouping of vehicles maintaining a short time headway achieved by using
a combination of wireless communications, lateral and longitudinal control units,
and sensor technology. Current concepts under consideration assume a system
whereby the platoon is led by a trained, professional driver whilst the following
vehicles are driven fully automatically by the system (for an overview of vehicle
automation see SMART 2011).
By taking the driver out of the loop, automated personal mobility has the
potential to be more efficient, safer, and greener (e.g. Robinson et al. 2010). At
the same time, it allows drivers to engage in non-driving tasks. With vehicle
control in the hands of the automated system, the driver, now passenger, can sit
back and relax, have a coffee, check emails, read the morning paper, or swivel
his or her chair and have a face to face conversation with other passengers.
Diels, C. (2014). Will autonomous vehicles make us sick? In S. Sharples & S. Shorrock (Eds.),
Contemporary Ergonomics and Human Factors (pp. 301-307). Boca Raton, FL: CRC Press.
Vehicle interiors will be designed to become more like social, work, and
entertainment spaces.
Besides the critical aspect of liability, there are several human factors issues that
require a better understanding to ensure the successful introduction of vehicle
automation. Current research activities focus around the topics of transfer of
control, situational awareness, HMI design, mixed traffic conditions, system
trust, reliability, and user acceptance. There is one aspect, however, that thus far
has appeared to have gone unnoticed: carsickness.
Susceptibility to carsickness varies widely but it has been found that around 60%
of the population has experienced some nausea from car travel, whereas about a
third has vomited in cars before the age of 12 (Griffin, 1990). Although the
ultimate manifestation of motions sickness is vomiting, it is typically preceded
by signs and symptoms such as nausea, headache, fatigue, and drowsiness which
may linger on for hours (Griffin, 1990).
Coincidentally, the use cases that are being envisaged for automated driving are
also those we know to lead to increased levels of carsickness. First, automation
alters the driver’s function from an active to a passive, monitoring one.
Secondly, occupants are assumed to engage in non-driving tasks taking the eyes
off the road ahead. Finally, flexible seating arrangements may involve rearward
facing seats. In the context of carsickness, the common denominator across
above scenarios or use cases is the occupantsinability to sufficiently accurately
predict the future path of the vehicle which is known to be a main determinant of
sickness (e.g. Golding & Gresty, 2013). Following a brief introduction to the
aetiology of carsickness, the different use cases and their exacerbating effect on
carsickness will be discussed below.
Aetiology of carsickness
Motion is primarily sensed by the organs of balance located in the inner ear and
our eyes. Motion sickness can occur when these motion signals are in conflict
with one another or when we are exposed to motion that we are not accustomed
to (Reason, 1975; Oman, 1982). It can be caused by a wide variety of motions of
the body and the visual scene and is a common problem in travellers by car,
train, air, and particularly sea. Seasickness may happen whilst being below deck
where a clear view of the visual scene outside the ship is lacking. Under these
conditions, motion sickness occurs because the movements of the ship, as
perceived by the organs of balance, are in conflict with the motion perceived by
the eyes, which indicate a static visual surround.
Sickness can however also occur when we are exposed to motion that, from an
evolutionary perspective, we are not used to. Our bodies are not accustomed to
low frequency oscillating motion. Sea and airsickness, for example, are mainly
caused by slowly oscillating vertical motion. Carsickness, on the other hand, is
Diels, C. (2014). Will autonomous vehicles make us sick? In S. Sharples & S. Shorrock (Eds.),
Contemporary Ergonomics and Human Factors (pp. 301-307). Boca Raton, FL: CRC Press.
associated with horizontal accelerations (sway) caused by acceleration, braking,
and cornering (Guignard & McCauley, 1990; Turner & Griffin, 1999).
With regard to carsickness, it is linear accelerations (sway) in the low frequency
bands (0.1-0.5 Hz) that are most relevant and their effects increase as a function
of duration of exposure and the intensity of acceleration (Turner & Griffin,
1999). Apart from the route itself, carsickness heavily depends on the way the
car is driven. An aggressive driving style involving plenty of accelerating and
braking is therefore more likely to result in carsickness. A study on suburban car
journeys reported that the fore-and-aft and lateral acceleration motion patterns
were similar over the lower frequency range and were provocative in inducing
motion sickness. These low frequency fore-and aft and lateral oscillations are
more dependent on the driving behaviour of the driver than the characteristics of
the vehicle (Griffin & Newman, 2004).
Characteristics of the vehicle mainly affect higher frequency motion. Similarly,
road surface quality also affects the high frequency motion vibrations. From this
it follows that road surface quality and suspension affect riding comfort, but do
not induce carsickness. Exceptions to this rule are cars with particular soft
suspensions. In general, when the suspension frequency is below 1 Hz, the
likelihood of carsickness significantly increases (Turner & Griffin, 1999). Cars
with stiffer suspensions are therefore less likely to lead to cars sickness. Larger
amplitudes of lateral (sway) are particularly provocative. As the amplitude of
sway tends to increase towards the rear of vehicles (cars and buses), rear seat
passengers are particularly prone to car sickness, especially under conditions
where external visual views are limited (Turner & Griffin, 1999).
Carsickness and Autonomous Vehicles
The novel use cases that are being envisaged for autonomous driving are also
those we know to significantly increase the incidence and severity of carsickness.
First, automation alters the driver’s function from an active to a passive,
monitoring one. Secondly, occupants are assumed to engage in non-driving tasks
taking the eyes off the road ahead. Finally, flexible seating arrangements may
involve rearward facing seats. In the context of carsickness, the common
denominator across above scenarios is the occupants’ inability to sufficiently
accurate predict the future path of the vehicle which is known to be a main
determinant of sickness (e.g. Golding & Gresty, 2013).
Changing roles: From driver to passenger
With longitudinal and lateral vehicle control automated, the driver is no longer
required to actively engage in the driving task. In dual-mode systems where the
driver has the choice to drive the vehicle manually or hand over control to the
automated system, the driver may still be required to monitor vehicle status to
allow for manual override in case of emergencies. In effect, however, the driver
becomes a passive passenger.
Diels, C. (2014). Will autonomous vehicles make us sick? In S. Sharples & S. Shorrock (Eds.),
Contemporary Ergonomics and Human Factors (pp. 301-307). Boca Raton, FL: CRC Press.
It is commonly reported that drivers of cars, pilots of aircraft, or Virtual Reality
users in control of their own movements are usually not susceptible to motion
sickness despite the fact that they experience the same motion as their passengers
(Geeze & Pierson, 1986; Reason & Brand, 1975; Stanney & Hash, 1998). This
moderating effect of control on the generation of motion sickness symptoms has
typically been attributed to the presence of muscular activity. When we initiate a
movement, a copy of the movement command sent out by our central nervous
system (CNS), referred to as an “efference copy”, is used to perform a simulation
of the expected results (output or “reafference”) of the command. The expected
reafference is then compared with the actual sensed reafference within an
internal model in our CNS. If there is a discrepancy, for example, a movement
command normally used to move our finger to our nose does not produce the
intended arm movement due to additional exercise weights added to the wrists,
the internal model is updated. In this case, the efferent signal is increased to
account for the increased resistance. Taking the weights off subsequently results
in arm overshoot and thus requires a further recalibration of the internal model.
The presence of an efference copy to activate an internal model is thought to
facilitate this habituation process. With reference to motion sickness, those in
control can benefit from this mechanism to a larger extent and are generally
found to desensitise or habituate much faster (Oman, 1982; Reason, 1978;
Reason & Benson, 1978; Reason & Brand, 1975; Rolnick & Lubow, 1991; Stott,
1990). Oman (1991) argued that motion stimuli are relatively benign when
individuals are able to motorically anticipate incoming sensory cues. However, a
fundamental question is whether this anticipatory mechanism is only activated
when the perturbation is self-produced or whether this mechanism is also set in
motion in case the perturbation is made predictable by sensory information.
An anticipatory mechanism has been explicitly incorporated in the Subjective
Vertical-conflict model or SV-conflict model developed by Bles and colleagues
(Bles et al., 1998). As in the classical sensory conflict theory (Oman, 1982;
Reason, 1978), self-initiated movement results in an efference copy of the
command signal sent to the internal model which subsequently predicts how the
body will react, what the sensor responses will be, and which motion and body
attitude is to be expected. In the SV-conflict model, however, an anticipatory
mechanism is incorporated so that even during imposed passive motion, the
internal model is also activated as long as this motion can be anticipated based
on sensory information. Therefore, the SV-conflict model predicts that not only
drivers but also passengers sitting next to the driver to be less prone to motion
sickness, provided passengers have a clear view and looking at the road ahead
(Bles et al., 1998; Bles et al., 2000). Note, however, that this does not preclude
particularly sensitive passengers from getting sick.
Engagement in non-driving activities
Automated vehicles allow the driver to engage in non-driving activities. It is
highly probable that popular activities may include reading, checking one’s
emails, or engaging otherwise with nomadic or integrated infotainment systems
such as in-vehicle displays, laptops, video games, or tablets. On the basis of the
Diels, C. (2014). Will autonomous vehicles make us sick? In S. Sharples & S. Shorrock (Eds.),
Contemporary Ergonomics and Human Factors (pp. 301-307). Boca Raton, FL: CRC Press.
sensory conflict theory of motion sickness, one would expect to see an increase
in carsickness under these conditions. Similar to reading a map or book whilst
driving, the (static or dynamic) image displayed on displays will not correspond
to the motion of the vehicle which ultimately may lead to carsickness. This will
be particularly true for downward viewing angles or displays that prevent a clear
view from the road ahead or horizon. Note therefore that see-through displays
may provide one possible solution to minimise the impact of incongruent motion
Research indicates that in-vehicle entertainment systems indeed increase the
likelihood of carsickness. Cowings et al. (1999) reported a negative impact on
crew performance and health when subjects attended to visual computer screens
while the vehicle was moving. More recently, in a study by Kato and Kitazaki
(2008), 20 people were driven around for 30 minutes whilst sitting in the
backseat either watching the road ahead, or a rear-seat display showing written
text. During each of the two drives, the participants were asked to verbally rate
their motion sickness on a motion sickness scale that ranged from 0 (No
symptoms, I feel fine”) to 6 (“moderate nausea, I want to stop”). As expected
based on the conflict between the motion sensed by the visual and vestibular
system, results confirmed that watching the in-car screen led to significantly
higher levels of carsickness.
Flexible seating arrangements
An idea that can be traced back to at least the 50’s, autonomous vehicles are
considered to provide an opportunity to facilitate social interaction. Numerous
concepts for autonomous vehicles suggest flexible interior layouts which
frequently involve swivelling chairs allowing the driver and front passenger to
turn to the rear passengers. In the light of the previous sections, it becomes
apparent that facing rearwards may not only lead to conflicting sensory
information provided by the visual and vestibular system, it also reduces the
ability to anticipate the future motion path. Consequently, alternative layouts
with rearward facing seats will almost certainly lead to increased levels of
Surprisingly, there appears to be no published data to support this contention
however. This is even more surprising given the fact that rearward facing seats
are standard in trains. UK train operators offer customers the option to choose
the preferred direction of travel when purchasing pre-booked tickets. This would
imply a significant proportion of the customer base to have a preference to travel
forward facing. This is in agreement with the anecdotal evidence which suggests
that passengers prefer not to face rearwards in order to avoid motion sickness.
Facing forwards allows the passenger to anticipate the train’s motion to a large
extent than facing backwards even though the available visual information in
trains will be limited. Unlike drivers, train passenger will not be able to see the
Focus Of Expansion (FOE) which refers to the most informative part of the
observers’ visual field with regard to the direction of travel.
Diels, C. (2014). Will autonomous vehicles make us sick? In S. Sharples & S. Shorrock (Eds.),
Contemporary Ergonomics and Human Factors (pp. 301-307). Boca Raton, FL: CRC Press.
Design Implications for Autonomous Vehicles
The above discussion points towards 2 fundamental principles that need to be
taken into account to prevent carsickness: (1) avoid sensory conflict where
possible, and (2) maximise the ability to anticipate the future motion path. When
applied to the design of autonomous vehicles and its anticipated use cases, the
following design guidelines are suggested.
Forward and sideway visibility should be maximised. Ideally occupants have a
clear view of the road ahead. However, under conditions that this view is
compromised, any visual information (i.e. optic flow) that correctly indicates the
direction of travel will reduce the amount of sensory conflict and enhance the
ability to anticipate the motion path. The design should therefore aim for
maximum window surface areas or Day Light Openings (DLO), minimal
obstruction by A-, B-, and C-pillars, and low belt lines or seats of sufficient
height to ensure passengers ability to look out of the vehicle. New lighting
technologies such as OLED (Organic Light Emitting Diodes) may provide the
possibility to provide simulated optic flow patterns inside the vehicle. See-
through displays, such as head up displays will reduce the impact of incongruent
motion cues. Future research may also explore the effectiveness of using visual,
auditory, and/or tactile cues to provide an artificial horizon and signal the future
motion path. With regards to seasickness and airsickness, artificial spatial or
motion cues have already been shown to alleviate sickness (e.g. Rolnick & Bles,
1989; Tal et al. 2012). The extent to which these techniques can be extrapolated
to the automotive field has yet to be determined.
Finally, the occurrence of carsickness in autonomous vehicles will be dependent
on the driving scenario. Our organs of balance are in essence biological
accelerometers and this means that they are sensitive to accelerations only
(Howard, 1982). As a corollary, sensory conflict and hence the likelihood
carsickness from occurring, is significantly reduced when traveling at constant
speed. The organs of balance signal the body to be stationary and therefore any
stationary scene as sensed by our eyes will be perceived as congruent. Under
conditions of constant motion, i.e. no lateral or longitudinal accelerations,
carsickness is less likely to occur. With respect to the implementation of
autonomous systems this would suggest that future levels of carsickness may be
manageable provided the automation is not applied under traffic conditions that
involve high levels of accelerations as typically observed in urban or rush hour
motorway traffic.
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... This increases the likelihood of experiencing Motion Sickness (MS) symptoms (Guedry 1991;Isu et al. 2014;Jones et al. 2019). Since devoting travel time to NDRAs is a promise of HAVs, this issue poses a challenge to the widespread adoption of such vehicles (Diels 2014;Diels and Bos 2016). ...
... The common denominator in all cases of road transportation where MS occurs is poor capacity to anticipate future motion forces (Diels 2014;Golding and Gresty 2013). According to Oman (1991), individuals who are able to well anticipate incoming sensory cues are less affected by motion stimuli, as they generate an accurate expected afference that limits the intensity of the sensory mismatch. ...
This paper examines the feasibility of incorporating visual cueing systems within vehicles to mitigate the risk of experiencing motion sickness. The objective is to enhance passenger awareness and the ability to anticipate the forces associated with car travel motion. Through a comprehensive literature review, the findings demonstrate that visual cues can mitigate motion sickness for particular in-vehicle configurations, whereas their influence on situational awareness is not clear yet. Each type of visual cue proved more effective when presented in the peripheral field of view rather than solely in the central vision. Promising applications can be found within interactive screens and ambient lighting, while the use of extended reality shows potential for future investigations. In addition, integrating such systems into highly automated vehicles shows potential to improve their overall user acceptance.
... The longitudinal and lateral jerk values are related to the comfort component in driving Turner and Griffin (1999); Svensson and Eriksson (2015); Diels (2014). Fewer abrupt accelerations/decelerations and smooth lane-changing with well adjusted speed, result in lower jerk values and more comfortable driving experience. ...
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Achieving feasible, smooth and efficient trajectories for autonomous vehicles which appropriately take into account the long-term future while planning, has been a long-standing challenge. Several approaches have been considered, roughly falling under two categories: rule-based and learning-based approaches. The rule-based approaches, while guaranteeing safety and feasibility, fall short when it comes to long-term planning and generalization. The learning-based approaches are able to account for long-term planning and generalization to unseen situations, but may fail to achieve smoothness, safety and the feasibility which rule-based approaches ensure. Hence, combining the two approaches is an evident step towards yielding the best compromise out of both. We propose a Reinforcement Learning-based approach, which learns target trajectory parameters for fully autonomous driving on highways. The trained agent outputs continuous trajectory parameters based on which a feasible polynomial-based trajectory is generated and executed. We compare the performance of our agent against four other highway driving agents. The experiments are conducted in the Sumo simulator, taking into consideration various realistic, dynamically changing highway scenarios, including surrounding vehicles with different driver behaviors. We demonstrate that our offline trained agent, with randomly collected data, learns to drive smoothly, achieving velocities as close as possible to the desired velocity, while outperforming the other agents.
... Motion sickness is a key limiting factor when using immersive (and other) media when travelling. This problem is expected to grow with the arrival of automated vehicles [19,23,25,26,28,43,101]. This automation will turn drivers into passengers who may then use their time for non-driving related tasks (working, reading, watching movies, etc.). ...
... Although carsickness has been an issue since the invention of the automobile, it started to receive increasing attention since the early 2000s with the introduction of vehicle automation, which is expected to increase the incidence of carsickness. The reason for this is the fact that vehicle automation renders all occupants into passengers, who, compared to drivers, are known to be more susceptible to carsickness [23][24][25][26]. In addition, vehicle automation enables passengers to engage in a wide variety of in-vehicle activities, such as reading or screen use, which are also known to increase the likelihood of carsickness [25,26] (see further below). ...
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Motion sickness is known under several names in different domains, such as seasickness, carsickness, cybersickness, and simulator sickness. As we will argue, these can all be considered manifestations of one common underlying mechanism. In recent years, it has received renewed interest, largely due to the advent of automated vehicles and developments in virtual reality, in particular using head-mounted displays. Currently, the most widely accepted standard to predict motion sickness is ISO 2631-1 (1997), which is based on studies on seasickness and has limited applicability to these newer domains. Therefore, this paper argues for extending the ISO standard to cover all forms of motion sickness, to incorporate factors affecting motion sickness, and to consider various degrees of severity of motion sickness rather than just emesis. This requires a dedicated standard, separate from other effects of whole-body vibration as described in the current ISO 2631-1. To that end, we first provide a sketch of the historical origins of the ISO 2631-1 standard regarding motion sickness and discuss the evidence for a common mechanism underlying various forms of motion sickness. After discussing some methodological issues concerning the measurement of motion sickness, we outline the main knowledge gaps that require further research.
... Unfortunately, engaging in the NDRT as mentioned above will make the users of an AV become unaware of the vehicle's intention concerning its navigation and therefore unable to anticipate upcoming events [3], [4]. Most, if not all, of the attention will be channelled to performing the NDRT. ...
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... Researchers suggested a flexible interior with a rotatable seat concept in autonomous vehicles, whereby this arrangement allows the seats of the driver and front passenger to rotate and face backward. However, facing backward will lead to the inability to anticipate the future path direction (Diels, 2014). Furthermore, windows are not required by the passengers to look at the outside view because they do not control the vehicle (Kuiper et al., 2018). ...
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An autonomous vehicle is a rapidly evolving technology that received attention from researchers due to its potential benefits. Besides the advantages, there are also non-negligible issues that need to be overcome in the middle of the autonomous vehicle development process. Among all the challenges, one of the important topics that have not gained adequate consideration is motion sickness (MS). This paper reviews the benefit and challenges of autonomous vehicles, MS factors, the quantifying methods of MS, and the mitigation strategies of MS. Considering the importance of minimizing MS, it is concluded that the number of strategies to lessen MS's severity is still lacking; hence, requiring more attention from automotive researchers.
... Fully autonomous driving is expected to offer human drivers/users the opportunity to spend more of their travelling time by relaxing, working, or simply enjoying the in-car entertainment system [1]. Hence, future autonomous vehicle (AV) users will likely expect a comfortable riding experience. ...
Rapid advancements in automated vehicle (AV) technology have raised the question of how the AV will drive on the road. The first step to answering that question is identifying the human drivers' driving style (DS) and then projecting the AV's DS in the future. The Multidimensional Driving Style Inventory (MDSI) is a frequently used method to identify human DS in various cultural situations. This study aims to adapt the MDSI to Malaysian drivers and the local driving practices and then determine the Malaysian driving profiles. A total of 737 drivers aged from 17 years to 49 years completed the questionnaire. Exploratory Factor Analysis (EFA) revealed a 5-factor structure of the MDSI. Confirmatory Factor Analysis (CFA) confirmed that the model fit of the MDSI was acceptable. Next, the association of DS with several personality traits and demographic data will be examined to further understand human DS characteristics. Further analysis found 15 driving profiles with one or two DS each. The MDSI factors were medium correlated with desire for control but weakly associated with trust and sensation seeking. Significant demographic data on driving styles were acquired. The Malaysian version of the MDSI has proven reliable and a valuable tool for formulating DS of AV in the future.
Motion sickness (MS) is an unpleasant sensation such as headache and nausea which occurs during travelling by vehicle. Extensive studies had been carried out regarding the factor and the mitigation methods of MS, especially for the vehicle’s passengers. Nowadays, a revolution from the automotive industry resulting from the development of the autonomous vehicles. One of the key concerns in autonomous vehicle research is that its possibility to have a higher chance to contribute to MS among the occupants compared to the conventional vehicle. Hence, this paper presents reviews on the MS reduction methods, focusing on the application towards the autonomous vehicle. Considering the importance of MS reduction in improving the occupant’s comfort level, it is concluded that this issue requires more attention among autonomous vehicle researchers.KeywordsMotion sicknessAutonomous vehicleComfortUser acceptance
The electrification of suspension systems in vehicles and especially in hybrid and electric vehicles is ubiquitous. With the striving for higher performance and the simultaneous increase in weight, mechanical, electromechanical and (semi-)active suspension systems based on 12 V or 48 V low voltage (LV) power trains are reaching their dynamic limits. One approach to improve performance is to use suspension systems and components that can be applied to the high voltage (HV) vehicle power train that is being used more and more frequently. The use of HV suspension components results in many advantages such as punctual available power without having to set the voltages higher by means of so called DC/DC converters. However, there are also many challenges in this field that do not allow a simple exchange of the hardware from LV to HV without further considerations. During development, for example, the question of functional safety and the behavior of the HV suspension components in case of a crash arises. It is also necessary to take a closer look at what the main cost drivers in development are, whether a component has to be actively cooled due to the generation of heat or how it affects the overall range of an electric vehicle. Silver Atena GmbH has specialized in the development of LV and HV electronic components for decades. This includes also development and production of HV suspension components. This paper is intended to give a brief overview of the current challenges and the uncertainties in the complex HV suspension components development process. In the main part, after the motivation for using HV in suspension systems, it is shown which problems can arise from the replacement of LV by HV suspension components. Since their development can quickly reach a high degree of complexity, a good overview of key requirements will be pointed out here. The conclusion gives an outlook on the still open questions and challenges to be solved.
Whereas autonomous vehicles are expected to provide several advantages, the current scenarios envisioned for self-driving vehicles are expected to increase the incidence of motion sickness. This study investigates the effects of dynamic visual stimuli on the development of carsickness under two different view conditions. A prototypical light-emitting diode (LED) feedback system visualizing longitudinal driving dynamics in the passenger's peripheral visual field was installed in the rear of a modified serial vehicle. A real driving experiment was conducted on the test track of a major car manufacturer. Subjective motion sickness ratings were recorded. It was hypothesized that carsickness can be mitigated with the information from the visual feedback system. Subjective motion sickness scores tended to be lower with the LED feedback system while there was no substantial interaction effect with the view condition. Although the results indicate potential benefits of the LED feedback system for the mitigation of motion sickness, further development of the system and its functionalities and the inclusion of psychophysiological measures to objectively quantify motion sickness is necessary to confirm these findings.
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A method has been developed for improving the ease of viewing images on an in-vehicle display while a vehicle is moving and reducing carsickness. An attempt was made to mitigate carsickness by reducing sensory conflict by controlling the position of displayed images in synchronization with vehicle motions and passenger head motions produced by vehicle acceleration/deceleration forces. In the case of moving images, experimental results showed that, in addition to image position control, providing visual clues for distinguishing between the motions of the images themselves and the control motions can effectively reduce carsickness. The results further indicated that this method of controlling the position of displayed images is also effective in improving the ease of viewing images in a moving vehicle.
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To investigate whether the projection of Earth-referenced scenes during provocative motion can alleviate motion sickness severity and prevent motion sickness-induced degradation of performance. Exposure to unfamiliar motion patterns commonly results in motion sickness and decreased performance. Thirty subjects with moderate-to-severe motion sickness susceptibility were exposed to the recorded motion profile of a missile boat under moderate sea conditions in a 3-degrees-of-freedom ship motion simulator. During a 120-minute simulated voyage, the study participants were repeatedly put through a performance test battery and completed a motion sickness susceptibility questionnaire, while self-referenced and Earth-referenced visual scenes were projected inside the closed simulator cabin. A significant decrease was found in the maximal motion sickness severity score, from 9.83 ± 9.77 (mean ± standard deviation) to 7.23 ± 7.14 (p < 0.03), when the visual display better approximated the full scale of the roll, pitch, and heave movements of the simulator. Although there was a significant decrease in sickness severity, substantial symptoms still persisted. Decision making, vision, concentration, memory, simple reasoning, and psychomotor skills all deteriorated under the motion conditions. However, no significant differences between the projection conditions could be found in the scores of any of the performance tests. Visual information regarding the vessel's movement provided by an artificial horizon device might decrease motion sickness symptoms. However, although this device might be suitable for passive transportation, the continued deterioration in performance measures indicates that it provides no significant advantage for personnel engaged in the active operation of modern vessels.
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The purpose of this project was to use NASA technology to assist the US Army in the assessment of motion sickness and performance of soldiers in the Command and Control Vehicle (C2V). Three different vehicle configurations were tested: oblique, (3 seats at a 20-degree angle from the direction of travel); perpendicular, (3 seats at a 90 degree angle); and 4-forward, (all seats faced forward). In all vehicles, the front seat faced forward. Sixteen men and eight women participated for 15 days: 2 days of classroom instruction; 12 days of field tests in the C2V, and 15 minutes of post-field test performance measures. Conditions for field tests were: an initial Park; four Moves (i.e., travel over a mixed terrain); and four Short-halts following movement. NASA task batteries, mood and symptom scales, and physiological data were collected during field tests. Motion sickness symptoms ranging from slight to severe were reported for all subjects. Conclusions were: (1) there was no difference between vehicle configurations; (2) there was a negative impact on crew performance and health when subjects attended to visual screens during vehicle movement; and (3) symptoms and performance degradation were not mitigated by intermittent short-halts.
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This book provides a detailed review of the visual mechanisms involved in spatial orientation.
Offers a conceptual framework for the research thus far done on motion sickness. The "sensory rearrangement theory" attempts to identify the commonest characteristics of situations producing motion sickness, to describe the mechanisms underlying the acquisition of adaptation, and to determine why some individuals are consistently more susceptible than others. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
In reviewing the various forms of motion sickness, the classic sensory rearrangement theory has been redefined by demonstrating that only one type of conflict is necessary and sufficient to explain all different kinds of motion sickness. A mathematical description is provided from the summarizing statement that “All situations which provoke motion sickness are characterised by a condition in which the sensed vertical as determined on the basis of integrated information from the eyes, the vestibular system and the nonvestibular proprioceptors is at variance with the subjective vertical as expected from previous experience.”
Cybersickness is a pervasive and deleterious effect of human-virtual environment interaction. This paper applies motion-sickness adaptation theory to cybersickness in virtual environments to determine if the degree of user-initiated control can suppress sickness. It is suggested that if users are allowed some level of control over their movement within a virtual environment, cybersickness will not be as severe as that resulting from an enviornment in which users must follow a predetermined (i.e., scripted) path of movement. While past motion-sickness studies have examined control versus no control, the present study focuses on modifying the level of user-initiated control such that it matches the needs of the task characteristics while minimizing sickness. The degree of user sickness was tested under passive, active, and active-passive control scenarios. As measured by the Simulator Sickness Questionnaire, the active (i.e., complete control) condition reduced the severity of the symptoms experienced as compared to the passive (i.e., no control) condition, but did not do so as completely as the active-passive (i.e., coupled control) condition. The implication is that the level of user-initiated control can be manipulated to modify the deleterious effects of human-virtual environment interaction.
The rates at which protective adaptation was acquired to an incremental cross-coupled stimulus were compared under three conditions of movement control: 1) a passive condition in which the 45 degree lateral tilts of the subject's chair were controlled entirely by the experimenter (N = 12); 2) an active condition in which the same movements were achieved directly through the subject's own muscular effort (N = 12); and 3) an active-passive condition in which control was exercised indirectly through microswitches located on the chair arms (N = 12). Adaptation was measured by the rate of neutralization of the oculogyral illusion, as estimated from the apparent motion of a small, dimly illuminated target. The results supported the prediction that the passive condition would be the least effective mode for acquiring adaptation. An unexpected finding was that the active-passive condition proved to be the most efficient for the development of adaptation.