# Vibration-induced discomfort in automated driving:
OWHEEL case study

Cor-Jacques Kat, Viktor Skrickij, Barys Shyrokau, Paulius Kojis, Miguel Dhaens, Sara Mantovani, Francesco Gherardini, Salvatore Strano, Mario Terzo, Hiroshi Fujimoto, et al.

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► To cite this version:

Cor-Jacques Kat, Viktor Skrickij, Barys Shyrokau, Paulius Kojis, Miguel Dhaens, et al. Vibration-induced discomfort in automated driving: OWHEEL case study. SAE International Journal of Vehicle Dynamics, Stability, and NVH, 2024, 8 (2), pp.139-153. 10.4271/10-08-02-0009. hal-04930569

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Submitted on 5 Feb 2025

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# Vibration-induced discomfort in automated driving: OWHEEL case study

Cor-Jacques Kat<fnref n="1" />, Barys Shyrokau<fnref n="2" />, Viktor Skrickij<fnref n="3" />*, Paulius Kjis<fnref n="3" />, Miguel Dhaens<fnref n="4" />, Sara Mantovani<fnref n="5" />, Francesco Gherardini<fnref n="5" />, Salvatore Strano<fnref n="6" />, Mario Terzo<fnref n="6" />, Hiroshi Fujimoto<fnref n="7" />, Aldo Sorniotti<fnref n="8" />, Pablo Camocardi<fnref n="9" />, Alessandro Corrêa Victorino<fnref n="10" />, and Valentin Ivanov<fnref n="11" />

## Abstract

The paper aims to present the procedure of vibration-induced discomfort analysis in automated driving. In this regard, the presented research focuses on the key components related to driving comfort in automated driving, such as evaluation criteria, corresponding scenarios and the necessary equipment to perform the driving comfort analysis. Finally, as a case study, the ongoing European Commission project OWHEEL is presented, providing an example of the testing procedure of automotive wheel corner concepts to design new vehicle architecture, ensuring optimal comfort by automated driving.

**Keywords:** benchmarking criteria; comfort; vehicle corner; automated vehicle.

## 1. Introduction

Automated driving (AD) is a promising but also challenging innovation area in the automotive industry. AD technology is tightly linked to societal and economic challenges: minimization of traffic accidents, fuel consumption, traffic congestion, parking demand, and providing mobility for an ageing population, as well as addressing customer needs toward more personalized services [1]. Mainly three factors are considered to choose between conventional and AD vehicles [2]. Those factors include driving enjoyment, environmental concern and sentiments toward a conventional vehicle.

In conventional vehicles, the act of driving makes drivers practically insensitive to motion sickness and vibration-induced discomfort, while passive passengers typically suffer most, especially when deprived of visual information about self-motion [3, 4]. A similar issue is observed when the vehicle can drive autonomously without active human involvement.

Since a human is no longer required to be actively involved in driving, this allows the use of travel time for work or leisure; however, this requires high comfort levels to prevent vibration-induced discomfort and motion sickness. Visual and vestibular cue incongruence, especially during abrupt automatic driving manoeuvres, may also result in acceleration discomfort and excessive body motion.

Therefore, considering the abovementioned issues, the AD driving style must be carefully designed and evaluated. This requires determining the applicability of current ride quality criteria and driving comfort criteria currently used in the industry and research community to AD. This paper aims to present a procedure of vibration-induced discomfort analysis in automated driving, focusing on:

* Evaluation criteria of vibration-induced discomfort;

* Target scenarios for assessment;

* Testing equipment;

* An example of the procedure application.

<footnote n="1">¹ Vehicle Dynamics Group, Department of Mechanical and Aeronautical Engineering, University of Pretoria, South Africa; cor-jacques.kat@up.ac.za</footnote>

<footnote n="2">² Department of Cognitive Robotics, Delft University of Technology, Mekelweg 2, 2628CD Delft, The Netherlands; b.shyrokau@tudelft.nl</footnote>

<footnote n="3">³ Transport and Logistics Competence Centre, Transport Engineering Faculty, Vilnius Gediminas Technical University, Saulėtekio al. 11, 10223 Vilnius, Lithuania; viktor.skrickij@vilniustech.lt; eldar.sabanovic@vilniustech.lt</footnote>

<footnote n="4">⁴ DRIV, 3800 Sint-Truiden, Belgium; MDhaens@driv.com</footnote>

<footnote n="5">⁵ DIEF - Dipartimento di Ingegneria Enzo Ferrari, Università di Modena e Reggio Emilia, Via Vivarelli, 10, 41124, Modena, Italy; sara.mantovani@unimore.it; francesco.gherardini@unimore.it</footnote>

<footnote n="6">⁶ Department of Industrial Engineering, University of Naples Federico II, via Claudio 21, Naples, 80125, Italy; salvatore.strano@unina.it; mario.terzo@unina.it</footnote>

<footnote n="7">⁷ The University of Tokyo, Department of Advanced Energy, Graduate School of Frontier Sciences, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8561 Japan; fujimoto@k.u-tokyo.ac.jp</footnote>

<footnote n="8">⁸ Advanced Vehicle Engineering, University of Surrey, Guildford, Surrey GU2 7XH, UK; a.sorniotti@surrey.ac.uk</footnote>

<footnote n="9">⁹ Arrival Germany GmbH, Irma-Feldweg-Straße 8, 75179 Pforzheim, Germany; pablo.camocardi@arrival.com</footnote>

<footnote n="10">¹⁰ Université de technologie de Compiègne, CNRS, Heudiasyc (Heuristics and Diagnosis of Complex Systems), CS 60 319 - 60 203 Compiègne Cedex - France; acorreav@hds.utc.fr</footnote>

<footnote n="11">¹¹ Automotive Engineering Group, TU Ilmenau, 98693 Ilmenau, Germany; valentin.ivanov@tu-ilmenau.de</footnote>

<footnote>* Correspondence: viktor.skrickij@vilniustech.lt</footnote>
The paper's contribution is a comprehensive overview of the main components for vibration-induced discomfort analysis in automated driving, which is partially presented and discussed in the research studies.

In Sections 2 and 3, evaluation criteria and target scenarios are overviewed and summarised. Section 4 presents commonly used equipment and a discussion of its limitations. In Section 5, as a case study, we present our approach to evaluate comfort for AD within the OWHEEL project approach and describe all aspects that need to be taken into consideration.

## 2. Evaluation Criteria

Manufacturers are continually exploring new ways to improve the occupants' comfort in the vehicle. In general, the primary sources of discomfort are undesired motions and vibrations. Ride quality is related to the exposure to the vehicle's vibrations, and it can be improved by properly designing the suspension system. The occupant directly perceives not all vibrations and motions. The occupant will only perceive the motion and vibrations of the vehicle's body, i.e. the sprung mass. The main characteristic to examine is the sprung mass vibrations to analyze the perceived comfort. Therefore, ride quality can be addressed by investigating the sprung mass accelerations, which are a primary indicator of vibrations. These accelerations will give an insight into how the sprung mass behaves under different road inputs. As vibrations cause discomfort, smaller sprung mass vibrations indicate better ride quality. Therefore, the aim of improving the vehicle ride quality can be determined as the minimization of the body accelerations.

### 2.1. Objective evaluation criteria

The objective metrics for comfort evaluation need to be discussed to assess ride quality and driving comfort. The expected response to the overall vibration total values in public transport is standardized in ISO 2631-1 and BS 6841 [5, 6]. However, more objective metrics have been proposed. The overview of standardized research and industrial metrics are presented in Table 1 for vertical direction and can also be used to similarly assess longitudinal and lateral motion.

<table><caption>Table 1. Objective metrics for comfort evaluation</caption><thead><tr><th></th><th>Metrix</th><th>Formula</th><th>Threshold value/ Application</th></tr></thead><tbody><tr><td>1</td><td>Root mean square (r.m.s.) acceleration</td><td>a<sub>z,w</sub> = &radic;<span style="text-decoration: overline;">(1/T) &int;<sub>0</sub><sup>T</sup> a<sup>2</sup><sub>z,w</sub>(t) dt;</span><br>where T – the duration of measurement;<br>a<sub>z,w</sub>(t) – the weighted acceleration as a function of time for the vertical direction.</td><td>The frequency-weighted r.m.s acceleration is based on calculations of r.m.s values of vertical acceleration typically measured at the driver's or passengers' seat locations [5].</td></tr><tr><td>2</td><td>Crest factor</td><td>c.f. = max(|a<sub>z</sub>|) / r.m.s.(a<sub>z</sub>)<br>where max(|a<sub>z</sub>|) – the maximal value of acceleration for the vertical direction;<br>r.m.s. (a<sub>z</sub>) – the r.m.s. value of acceleration for the vertical direction.</td><td>The Crest factor is defined as the modulus of the ratio of the maximum instantaneous peak value of the frequency-weighted acceleration signal to its r.m.s value [5].</td></tr><tr><td>3</td><td>Maximum transient vibration value (MTVV)</td><td>MTVV = max(a<sub>z,w</sub>(t<sub>0</sub>))<br>where a<sub>z,w</sub>(t<sub>0</sub>) – the weighted acceleration as a function of time for the vertical direction.</td><td>An example of additional evaluation used to correct the calculation is the running r.m.s method which integrates the acceleration in a short time period t over the measurement period T. The MTVV gives the evaluation magnitude [5].</td></tr><tr><td>4</td><td>Vibration dose value (VDV)</td><td>VDV = &radic;<span style="text-decoration: overline;">&int;<sub>0</sub><sup>T</sup> a<sup>4</sup><sub>z</sub>(t) dt;</span></td><td>The VDV is an easy and robust method which is not affected by averaging [7].</td></tr><tr><td>5</td><td>Comfort index (CI) [m/s<sup>2</sup>]</td><td>1) not uncomfortable, CI &lt; 0.315<br>2) little uncomfortable, 0.315 ≤ CI &lt; 0.63<br>3) fairly uncomfortable, 0.5 &lt; CI &lt; 1<br>4) uncomfortable, 0.8 &lt; CI &lt; 1.6<br>5) very uncomfortable, 1.25 &lt; CI &lt; 2.5<br>6) extremely uncomfortable, CI &gt; 2</td><td>Many other factors influence ride comfort. The likely reaction of comfort to the vibration magnitude for urban public transports can be indicated by CI refers to the approximate indication of discomfort on a six-grade scale [8].</td></tr><tr><td>6</td><td>Root mean quad (r.m.q.)</td><td>r.m.q. = &radic;<span style="text-decoration: overline;">(1/T) &int;<sub>0</sub><sup>T</sup> a<sup>4</sup><sub>z</sub>(t) dt;</span></td><td>r.m.q. results in a time-averaged value that is more appropriate than r.m.s. when the motion is non-stationary and characterized by concentrated shocks, experimental findings demonstrate a better correlation with human experience applying the r.m.q method to transient events as opposed to r.m.s [5].</td></tr><tr><td>7</td><td>ISO index</td><td>ISO = &radic;<span style="text-decoration: overline;">k<sub>x</sub> &middot; r.m.s. (a<sub>x</sub>)<sup>2</sup> +<br>+k<sub>y</sub> &middot; r.m.s. (a<sub>y</sub>)<sup>2</sup> +<br>+k<sub>z</sub> &middot; r.m.s. (a<sub>z</sub>)<sup>2</sup></span><br>where k<sub>x</sub>, k<sub>y</sub>, and k<sub>z</sub> – multiplying factors used to correlate the objective metrics to the subjective evaluations for the longitudinal, lateral and vertical directions correspondingly.</td><td>The weighted r.m.s accelerations can be added into an overall acceleration level using the ISO index. ISO 2631 provides the guideline to calculate a global discomfort index that is able to consider the r.m.s acceleration in the three spatial directions. The multiplication factors are included to account for different effects on different body parts [5].</td></tr></tbody></table>
<table><tr><td>8</td><td>Vibration total value (VTV)</td><td>VTV = &radic; &sum;<sub>j=1</sub><sup>6</sup> k<sub>j</sub> &middot; r.m.s<sup>2</sup>(a<sub>w,j</sub>);<br/>where a<sub>w,j</sub> - the frequency weighted accelerations (j = 1 - x direction, j = 2 - y direction, j = 3 - z direction, j = 4 - angular acceleration around x axis, j = 5 - angular acceleration around y axis, j = 6 - angular acceleration around z axis, k<sub>j</sub> - the frequency weighting factors defined according to ISO 2631.</td><td>For the evaluation of vibrations in all 6 DoF, the VTV is used. For the assessment of ride quality based on the whole-body accelerations, the approximations of the ISO 2631-1 can be used [5].</td></tr><tr><td>9</td><td>NASA model</td><td>D<sub>vertical</sub> = {0.241 + 44.672a<sub>w,z</sub>, a<sub>w,z</sub> &gt; 0.1<br/>68.772 a<sub>w,z</sub>, a<sub>w,z</sub> &lt; 0.1<br/>D<sub>lat</sub> = {0.393 + 47.494a<sub>w,y</sub>, a<sub>w,y</sub> &gt; 0.1<br/>87.794 a<sub>w,y</sub>, a<sub>w,y</sub> &lt; 0.1<br/>D<sub>long</sub> = -0.02 + 42.24a<sub>w,x</sub>;</td><td>The NASA model applies the human comfort sensitivity weighting factors for vibration to spectral data in the five axes of measurement. After applying the filters to experimental data, the weighted acceleration spectra are converted to discomfort units in each axis using empirical relationships [9].</td></tr><tr><td>10</td><td>Peak-to-peak index (p-p)</td><td>p - p = max(a<sub>w</sub>(t)) - min(a<sub>w</sub>(t));</td><td>p-p is used to assess the acceleration magnitude [10].</td></tr><tr><td>11</td><td>Janeway's comfort criterion</td><td>1) Frequency range 1 - 6 Hz: peak jerk &lt; 12.6 m/s3<br/>2) 6 - 20 Hz: peak acceleration &lt; 0.33 m/s2<br/>3) 20 - 60 Hz: peak velocity &lt; 2.7 mm/s</td><td>Janeway's comfort criterion defines the acceptable amplitude of vertical vibration as a function of frequency and is divided into three parts [11]. This criterion does not consider the resonant effects of vibration combined with pitch and roll motion. The jerk is the derivative of the longitudinal acceleration during braking and can deteriorate the ride comfort if there are heavy pulsations during ABS mode [12]. All of the data used to establish the comfort boundaries were obtained with test subjects standing or sitting on a hard seat.</td></tr><tr><td>12</td><td>Virtual ride (VR)</td><td>VR = <sup>5</sup>&frasl;<sub>3 max(a<sub>z</sub>) + 2r.m.s(a<sub>z</sub>)</sub>;</td><td>VR has been proposed to assess ride quality. For the evaluation of the capability to filter medium and high frequencies due to pavement unevenness from 4 Hz to 30 Hz, the calculation of the virtual ride is based on measured vertical acceleration at the driver position (CG vertical Acceleration + pitch vertical component) [13].</td></tr></table>

Objective assessments of ride quality and driving comfort are mainly based on ISO metrics such as r.m.s acceleration, crest factor, MTVV, etc., and established industrial criteria, e.g. Ford Ride Comfort Metrics.

Besides the abovementioned criteria, there are attempts to develop metrics to quantify discomfort correlated with physical stimuli. Ideally, such metrics would be calculated directly from the measurement without any subjective evaluation, thus comparing discomfort caused by different vibrations or predicting the discomfort from measurements or simulations [7]. Psychophysical studies revealed a general relationship between physical stimuli and human sensations. The perceived discomfort depends not only on the physical magnitude or intensity but also on other physical properties of vibration stimuli, such as frequency and direction. For example, humans were most sensitive (causing most discomfort) to whole-body vertical vibration at about 5 Hz and less sensitive to vibration with higher frequencies [14]. Therefore, these physical properties also need to be taken into consideration.

It can be achieved through the usage of the difference thresholds (DTs), also known as Just Noticeable Difference (JND), is defined by Mansfield and Griffin [15] for vehicle vibration on a seat as "...the minimum change in the magnitude of the whole-body vibration required for the seat occupant to perceive the change in magnitude." The difference thresholds could therefore be used to predict whether the occupant would notice a difference between vehicle vibrations due to different vehicles or changes to subsystems/components on the same vehicle.

Studies have estimated difference thresholds for vertical whole-body vibration of participants on a rigid surface exposed to sinusoidal vibration [16, 17, 18] and to account for the effect of seating posture on an automobile seat exposed to sinusoidal [19] and random vibration [15, 20]. To account for the multi-axis vibration in the vehicle, Gräbe et al. [21] estimated DTs for participants in a vehicle on a 4-poster test rig. The relative difference thresholds from the literature are summarized according to stimuli type, i.e. sinusoidal (Table 2) and random (Table 3).
<table><caption>Table 2. Summary of median relative difference thresholds to sinusoidal stimuli</caption><thead><tr><th rowspan="2">Magnitude<br>[m.s.<sup>-2</sup>, m.s]</th><th colspan="8">Frequency [Hz]</th></tr><tr><th>1.3</th><th>2.5</th><th>5</th><th>6</th><th>10</th><th>20</th><th>40</th><th>80</th></tr></thead><tbody><tr><td>1.20</td><td></td><td></td><td></td><td>7.3<sup>2</sup></td><td></td><td></td><td></td><td></td></tr><tr><td>0.80</td><td></td><td>9.48</td><td>12.88</td><td></td><td>14.30</td><td>13.11</td><td>16.38</td><td>14.35</td></tr><tr><td>0.50</td><td>6.4<sup>2</sup></td><td></td><td>10.32<sup>1</sup></td><td>7.9<sup>2</sup></td><td></td><td>8.13<sup>1</sup></td><td></td><td></td></tr><tr><td>0.20</td><td>11.0<sup>2</sup></td><td>14.37</td><td>14.04</td><td>8.4<sup>2</sup></td><td>15.45</td><td>12.41</td><td>15.74</td><td>17.61</td></tr><tr><td>0.10</td><td></td><td></td><td>12.26<sup>1</sup></td><td></td><td></td><td>10.99<sup>1</sup></td><td></td><td></td></tr><tr><td>0.05</td><td></td><td>14.01</td><td>12.64</td><td></td><td>13.19</td><td>12.24</td><td>13.84</td><td>17.36</td></tr></tbody></table>

Median RDT from [18]; ¹[16]; ²[19]

<table><caption>Table 3. Summary of median relative difference thresholds to random stimuli</caption><thead><tr><th rowspan="2">Stimuli direction</th><th colspan="2">Magnitude</th><th colspan="3">Spectral shape</th></tr><tr><th>[m.s.<sup>-2</sup>, r.m.s]*</th><th>0.80</th><th>Tarmac<sup>1</sup></th><th>Pave<sup>1</sup></th><th>Ride road<sup>2</sup></th></tr></thead><tbody><tr><td rowspan="3">Vertical</td><td></td><td>0.40</td><td>11.85</td><td rowspan="3">14.1</td><td></td></tr><tr><td></td><td>0.20</td><td>13.85</td><td></td></tr><tr><td></td><td></td><td>12.85</td><td></td></tr><tr><td rowspan="3">Multi</td><td>CRVz</td><td>1.01</td><td></td><td></td><td>8.58</td></tr><tr><td>[m.s.<sup>-2</sup>, r.m.s]**</td><td>0.58</td><td></td><td></td><td>10.13</td></tr><tr><td>PRV</td><td>1.22</td><td></td><td></td><td>9.24</td></tr><tr><td></td><td>[m.s.<sup>-2</sup>, r.m.s]***</td><td>0.65</td><td></td><td></td><td>10.99</td></tr></tbody></table>

Median RDT for stimuli spectrum in ¹[15]; ²[21].

*Weighted r.m.s ; **Median r.m.s. of vertical component ride value ; ***Median r.s.s. of combined point ride value [6].

However, it is beneficial to conduct an additional test to determine the effect of test conditions on the DT. **_Erreur !_**
**Source du renvoi introuvable.** indicates the test condition spectrum. The left side corresponds to the laboratory conditions with high repeatability at the expense of realism. The right side reflects real driving conditions, with high realism at the expense of repeatability.

<figure><img src="image_3.png" /><figcaption>Figure 1. Effect of test conditions on difference thresholds</figcaption></figure>

## 2.2. Subjective evaluation criteria

In the experimental studies related to comfort, assessments there are often based on subjective measures. Test subjects are required to fill in a questionnaire at the end of the experiment, ranging from performing tasks in simple test rigs, prototype seats or real-life driving tests and asking them to (qualitatively) rate certain stimuli to be comfortable or not.

A well-known and widely used questionnaire targeting motion sickness and its individual differences is the Motion Sickness Susceptibility Questionnaire (MSSQ) for subjective evaluation. This questionnaire aims to predict individual susceptibility to motion sickness caused by various stimuli, and later an improved MSSQ was proposed [22]. The redesigned MSSQ provides new (and only) adult reference norms and was validated with data of motion and non-motion-induced nausea stimuli. Following its predecessor study, the MSSQ has been shortened even more (MSSQ-Short) [23]. Another common supporting questionnaire that is also seen in some comfort studies, usually related to drowsiness and fatigue, is the Karolinska Sleepiness Scale (KSS) [24]. Extra question is added to measure the subjective sleepiness level at a particular subject time. KSS might be helpful in certain studies that need to assess the subjects' changes in sleepiness, attention and performance under certain influences, for example, vibrations or prolonged exposure, during driving tasks.
### 3. Target Scenarios

Different manoeuvres corresponding to various speeds, road bumps, and road profiles corresponding to various pathways will be used to mimic and translate pavement situations (like cobblestone medium, large; asphalt, etc.) to evaluate comfort criteria. The specification of tests commonly used by industrial companies is summarised in Table 4.

<table><caption>Table 4. Ride comfort test specification</caption><thead><tr><th>Description</th><th>Constant speed specification, km/h</th></tr></thead><tbody><tr><td>Driving with constant speed and constant steering wheel angle in a bend on Belgian block</td><td>i) 50, medium speed on a dry surface;<br/>ii) 65, highest speed on a dry surface</td></tr><tr><td>Driving with constant speed over a special section on comfort road, track with different bends and gradients</td><td>60;<br/>50</td></tr><tr><td>Driving with constant speed over a special section on comfort road in severe surface condition</td><td>45; 35</td></tr><tr><td>Driving with constant speed over a gravel section</td><td>45; 35</td></tr><tr><td>Driving with constant speed over a special section on comfort road in very bad surface condition</td><td>60; 30</td></tr><tr><td>Driving with constant speed over a special section on comfort road with some transversal edges and potholes</td><td>70; 50</td></tr><tr><td>Driving with constant speed over a special section on a road with different speed bumps</td><td>25</td></tr><tr><td>Driving with constant speed over a special section on ride road</td><td>60</td></tr><tr><td>Driving with constant speed over a special surface with changing sinus stimulations</td><td>40</td></tr></tbody></table>

Ride comfort tests can be performed on proving grounds specially designed for these purposes; and in a virtual environment, replicating road profiles and driving conditions. Proving ground has specified comfort roads where the road surface is degraded (with potholes and corrugations).

The ride comfort test specification in Table 4 is presented in a concise form. Figure 2 presents different speed bumps used for one of the Comfort Tests. These pavement elements' geometry and shapes may also vary (Figure 3).

<figure><img src="image_4.png" /><figcaption>Figure 2. Artificial pavement element for reducing vehicle speed: a) speed bump; b) speed hump; c) cushion speed bump long-wavelength; d) cushion speed bump short wavelength</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>Figure 3. Crosssections of speed bumps (circular; trapezoidal; sinusoidal)</figcaption></figure>

Implementing the research, driving comfort quality should be analyzed concerning vehicle safety, stability, energy efficiency and reliability. Additional manoeuvres that are commonly used to evaluate vehicle handling, safety, stability, and steering feel (in the case of a semi-automated vehicle) should be performed. Such tests are presented in Table 5.

<table><caption>Table 5. Additional test procedures</caption><thead><tr><th></th><th>Standard</th><th>Test manoeuvre</th></tr></thead><tbody><tr><td rowspan="3">Vehicle handling</td><td>ISO 4138:2004</td><td>Constant Radius Cornering (open-loop)</td></tr><tr><td rowspan="2">ISO 7401:2003</td><td>Step Input (open-loop)</td></tr><tr><td>Frequency Sweep Response</td></tr><tr><td rowspan="4">Vehicle safety and stability</td><td>ISO 3888-1:1999</td><td>Double Lane Change (closed-loop)</td></tr><tr><td>ISO 19365:2016 & FMVSS 126</td><td>Sine with Dwell (open-loop)</td></tr><tr><td>ISO 17288-2:20</td><td>Steering-pulse (open-loop)</td></tr><tr><td>ISO 7975:2006</td><td>Braking in a Turn (open-loop)</td></tr><tr><td rowspan="2">Steering feel</td><td>ISO 13674-1:2010</td><td>Weave test for on-centre handling</td></tr><tr><td>ISO 13674-2:2006</td><td>Transition test</td></tr></tbody></table>

# 4. Testing Equipment

Laboratory testing is typically conducted using a motion simulator and/or a 4-poster test rig. They allow evaluating driving comfort in a safe, reliable, and controllable environment. The on-road experiments using a proving ground have always been performed as the final assessment stage. They may be conducted subject to the results from the laboratory tests and aspects related to the limitations of laboratory equipment discussed as follows.

## 4.1. Motion-based driving simulator

Usually, the 6 DoF motion system is used to generate acceleration up to 1 g in all directions and can effectively cover the frequency range of 0.1 Hz – 10 Hz with a limited amplitude. The stroke lengths and, as a result, utilized the workspace envelope are the physical constraints of the replayed signals related to driving comfort studies. An example of the simulator, TU Delft Advanced Vehicle Simulator [25], is shown in Figure 4. Its dynamic threshold values for platform motion latency range are from 10 to 20 ms, depending on motion direction. In addition, the curved rigid projection screen is used, covering horizontal and vertical fields of view for 210° and 45°, correspondingly. The generated images are projected by three Barco F50 WQXGA – VizSim Bright projectors. The simulator is operated in hard real-time using the dSPACE Scalexio system. HIL CarMaker software is extended for vehicle simulation by validated vehicle models and subsystems.
<figure><img src="image_6.png" /><figcaption>Figure 4. Driving simulator</figcaption></figure>

## 4.2. 4-poster test rig

As described above, the driving simulator has some limitations due to a limited workspace envelope; therefore, a 4-poster test rig is used. The actuators can excite a frequency range of 0 Hz – 40 Hz at the required displacements. However, the tests are limited to vertical, roll and pitch directions. Accelerations are measured on the driver/passenger seat surface and three-seat rail locations (or seat guide). A tri-axial accelerometer is used at the front left point of the seat rail, two accelerometers at the front right point and a single accelerometer to measure acceleration in the z-axis at the rear left point. Acceleration (x-, y- and z-axis) is measured on the seat surface below the driver's ischial tuberosities using a seat pad accelerometer. Stimulus refers primarily to vibrations to the occupant. Stimuli used in laboratory tests are based on vehicle vibrations over the road(s) of interest measured during on-road tests. The motion-based driving simulator allows testing to be done without or with visual inputs. Aural inputs to participants from sounds generated by the actuators can be reduced using earplugs. The semi-anechoic chamber in which the 4-poster test rig is situated creates an environment with limited aural and visual inputs.

For example, the 4-poster test rig at Tenneco is shown in Figure 5, consisting of four actuators that actuate in the vertical direction. Actuators under the front wheels generate 40 kN force and under the rear wheels 25 kN, respectively. The rig is controlled by an Instron 8800ml controller using Instron RS Studio ml as part of the Instron RS LabSite Modulogic 2.0 software suite.

<figure><img src="image_7.png" /><figcaption>Figure 5. 4-poster test rig</figcaption></figure>

## 4.3. On-road tests

Due to the limitations of laboratory equipment, the tests on the proving ground should be performed. The ride roads in the proving ground typically contain three sections, each corresponding to a comfort (relative) index that can be further analyzed:

* symmetric and asymmetric impact strips;

* asphalt road in disrepair with large primary ride inputs, body control, head toss;

* asphalt road with choppy secondary ride inputs, shake, harshness.
In addition, an outer durability road is used, which is a smooth road (almost no primary ride inputs) and consists partly of a smooth asphalt surface and an older, coarser asphalt surface. It can be categorized as a good quality secondary road to evaluate mainly harshness and shake and engine shake on some parts.

The experiments are performed using a vehicle demonstrator intended for studies in vehicle dynamics, ride quality and driving comfort. The example of the instrumented demonstrator is given as follows. Additional measurement systems are installed to enable a reliable assessment and control if needed: dSPACE rapid prototyping system; Kistler wheel force sensor RoaDyn S635; Racelogic VBOX dual antenna (VB3i SL) 100 Hz GPS Data Logger. The rapid prototyping system consists of the processor board DS1007, multi-channel A/D board DS2004 digitalizes signals from the analogue input. For CAN communication, the interface board DS4302 is used. The control of the brake actuators is realized through the digital input/output board DS4004. The control on actuators of the tire pressure control system and the semi-active suspension requires a multi-channel D/A board DS2103 having 32 outputs with 14-bit resolution and 10.0 µs of sample time.

# 5. Case study: The OWHEEL Project

Sections 2-4 provided an overview of the ride comfort test and evaluation criteria, target scenarios and testing procedures. Further, it will be implemented for automated vehicle components testing.

## 5.1. Project goals

The core of the OWHEEL project is the development of vehicle corners. This technology promises improved performance regarding comfort, efficiency, safety and stability. Four corner concepts are considered for optimal comfort by AD: i) Passive corner with specific wheel positioning; ii) Passive corner with composite elements; iii) Active corner with ordinary ride dynamics control; iv) Active corner with integrated wheel positioning control.

The new passive corner design includes a selection of in-wheel motors, suspension components design, structural analysis, multibody simulation and whole vehicle virtual testing. The initial idea for the passive vehicle corner with lightweight solutions is to keep the reference vehicle's suspension original kinematics and replace the material of components with minimal modifications in the original design. The main target is a weight reduction of vehicle corners, taking into account handling, safety, NVH behaviour, stiffness, etc.

Active corner control strategies to improve vehicle dynamics and ride comfort aspects are founded on model-based vehicle dynamics control (e.g. based on [26],[27]) and ride comfort control (e.g. based on [28, 29]). From the viewpoint of vehicle dynamics, this task covers the integration of active suspension actuation (which allows front-to-total anti-roll moment distribution control [30]) with direct yaw moment actuation. Moreover, from the viewpoint of ride comfort, we are developing nonlinear model predictive controllers to compensate for the longitudinal and vertical oscillations of the sprung mass caused by road irregularities. In-wheel motors are used to compensate for the longitudinal component of the disturbance, and semi-active suspension actuators compensate for the vertical component. Nonlinear model predictive and sliding mode controllers allow the integrated implementation of active body control and yaw rate control through the optimal distribution of suspension tyre forces, i.e., the so-called tyre force-vectoring.

In an active corner with integrated wheel positioning control, the focus of innovation is on the wheel positioning covering the design of robust, fast and precise observers for highly dynamic systems based on sliding modes techniques. Optimal and sub-optimal Kalman-based estimation approaches are needed to reconstruct the tire-road interaction forces at the level of each vehicle corner [31]. The ongoing preliminary activity is dealing with extensive simulation campaigns to define the level of power loss reduction (considering longitudinal and lateral tyre slip power losses as well as powertrain power losses) achievable through the optimal actuation of direct yaw moment control (torque-vectoring), active and semi-active suspension control, and wheel positioning control (e.g., active toe control).

## 5.2. The procedure application

This subsection proposes a testing procedure to compare wheel corner concepts towards optimal comfort by AD (Figure 6). The driving comfort criteria can assess wheel corner concepts in simulation, laboratory, and vehicle evaluations at the full vehicle level. Assessment of wheel corner concepts should be done at the full vehicle level rather than using simplified versions (i.e. quarter car or pitch-bounce models). It has been shown that the simplified versions may not accurately predict ride comfort [32].

During the initial stage, new corner designs were developed for front and rear axles (Figure 7), and the impact of increased unsprung mass on vehicle comfort has been investigated using multibody dynamics simulation software MSC Adams. Initial results for corners installed on the rear and front axles are presented in Table 6.
<figure><img src="image_8.png" /><figcaption>Figure 6. Outline of benchmarking procedure</figcaption></figure>

<figure><img src="image_9.png" /><figcaption>Figure 7. Vehicle corners with in-wheel motors</figcaption></figure>

The IPG CarMaker simulation platform was utilized to create a mathematical vehicle model. Field test data from the proving ground was obtained from online sources to parameterize and validate the model. For tire dynamics simulation, the Delft Tire model was employed. A sinusoidal road profile was chosen as the input for the simulation, with a road roughness period of 2.5, 5, 10, and 20 Hz and a vehicle velocity of 20 km/h during initial testing. The frequencies for wheel excitation were selected based on previous studies that analyzed subjective human sensation to artificial vibration sources. The sinusoid amplitude was varied to achieve 0.2 m/s² and 0.8 m/s² RMS at different frequencies. Following this, modifications were made to the vehicle's mathematical model, and kinematics and compliance analysis were conducted to evaluate the performance of new corner designs. Additionally, the unsprung mass and inertia were modified in accordance with the new design. The simulation was repeated under the same road and driving conditions as in the first case; the results are presented in the Table below.
<table><caption>Table 6. Median relative difference thresholds to sinusoidal stimuli after implementation of new corner design with inwheel motors</caption><thead><tr><th rowspan="2">Magnitude [m.s<sup>-2</sup>, m.s]</th><th colspan="4">Frequency [Hz]</th></tr><tr><th>2.5</th><th>5</th><th>10</th><th>20</th></tr></thead><tbody><tr><td rowspan="2">0.80</td><td>Relative difference thresholds</td><td>9.48</td><td>12.88</td><td>14.30</td><td>13.11</td></tr><tr><td>Simulation results</td><td><strong>16.67</strong></td><td><strong>29.64</strong></td><td><strong>32.32</strong></td><td><strong>14.88</strong></td></tr><tr><td rowspan="2">0.20</td><td>Relative difference thresholds</td><td>14.37</td><td>14.04</td><td>15.45</td><td>12.41</td></tr><tr><td>Simulation results</td><td>3.13</td><td>11.80</td><td><strong>20.35</strong></td><td><strong>40.65</strong></td></tr></tbody></table>

Increased unsprung mass negatively impacts vehicle dynamics; however, it is possible to eliminate this impact by using lightweight solutions and active suspension components.

After mathematical simulation, the general test procedure can be applied directly in the simulator's test; this procedure will let to determine the best corner concept. For the investigation using a 4-poster, a physical vehicle corner needs to be developed and installed on the vehicle platform. Slight changes are needed for the on-road test, specifically concerning the duration of stimulus and time between stimuli and the entire procedure's duration. On-road tests should be conducted subject to the results from the laboratory tests and whether sensible stimuli can be obtained using the reference vehicle and suitable proving ground. The environment of the proving ground will govern visual and aural inputs during on-road tests. Participants will engage in cognitive tasks associated with an occupant in an automated driving situation in both laboratory and on-road tests.

Driving comfort quality needs to be analyzed regarding vehicle safety and stability. This will be ensured by performing vehicle handling, safety, stability and steering feel (for the case of semi-automated vehicles) tests. Energy efficiency is another important aspect that needs to be taken into account. The energy consumption of actuators can be calculated as requested energy to overcome inertia and road resistance, plus additional energy to compensate for internal power loss. The reliability of redesigned components implementing lightweight materials will be ensured by factors of safety, NVH behavior, stiffness of components, and weight reduction.

Subjective assessment will be performed based on the different thresholds and questionnaires using a 4-poster test rig, a moving-based driving simulator and an instrumented vehicle. The considered wheel corner concept will be compared across each other.

## 6. Conclusions

Currently, the driving task makes drivers practically insensitive to motion sickness and vibration-induced discomfort, while passive passengers typically suffer the most, especially when deprived of visual information about self-motion. Automated driving will change the driver's role to the passive passenger. As a result, a new comfort level needs to be achieved in automated vehicles. Driving comfort quality needs to be analyzed regarding vehicle safety and stability, energy efficiency and reliability. The shift toward new vehicle powertrain and chassis design via corner solutions enabled by advanced control strategies presents relevant electrification opportunities, bringing us to environmentally neutral mobility.

In this research, comfort evaluation criteria that can be used for automated vehicle testing were systematically reviewed. Evaluation conditions for comfort, vehicle handling, safety, stability and steering feel are presented. Such an approach allows for solving the task complexly, considering safety, energy efficiency and reliability issues.

The OWHEEL project idea is presented, and corner concepts are described. Initial research showed that increased unsprung mass due to the installation of an inwheel motor negatively impacts comfort level. However, the impact is not drastic and could be resolved using lightweight solutions and active suspension components with wheel positioning. Future research will cover theoretical investigation using a simulation platform and experimental tests using a driving simulator, 4-poster test rig, and vehicle demonstrator.

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## Contact Information

Viktor Skrickij, Transport and Logistics Competence Centre, Saulėtekio al. 11, office SRC-309, LT-10223 Vilnius, Lithuania
+370 5 2744981, viktor.skrickij@vilniustech.lt, www.vilniustech.lt

## Acknowledgments
This research was funded from the European Union Horizon 2020 Framework Program, Marie Skłodowska-Curie actions, under grant agreement no. 872907.

**Definitions/Abbreviations**

Automated driving - AD

Root mean square - r.m.s.

Root mean quad - r.m.q.

- r.s.s.

Vibration total value - VTV

Peak-to-peak index - p-p

Virtual ride - VR

Maximum transient vibration value - MTVV

Difference thresholds - DTs

Just Noticeable Difference - JND

Motion Sickness Susceptibility Questionnaire - MSSQ

Karolinska Sleepiness Scale - KSS

Degree of freedom - DoF

Noise, vibration, and harshness - NVH