Usability Study to Improve Interaction Design for Drivers in Car-Sharing Systems

by Byungsoo Kim, Sharon Joines, Russell Flinchum, Jing Feng

Peer-reviewed Article

pp. 220-247

No PDF available for download.

Abstract

Car-sharing system users generally rent a vehicle for a brief amount of time, and they often do not take enough time to learn the controls and functions of a car that they are unfamiliar with.

The purpose of this study is to understand the difficulty of controlling a car’s functions while driving an unfamiliar car and to redesign controls to improve safety and usability. This study focuses on the secondary controls, such as those for the audio system and temperature system.

Fifteen participants were asked to perform simple tasks while driving two different cars: one was their own car and another was a car rented from Zipcar. The participants tended to glance at the controls more often (we counted how many times the participants’ glanced at a control) and spent more time completing the tasks in a car rented from Zipcar compared to their own car.

Two sets of prototypes (one set was for the center fascia and the other was for the steering wheel) were developed, and a usability study was conducted in a driving simulator to evaluate the usability of the prototypes. We used an eye-tracking device and conducted semi-structured interviews for both studies.

The results of the usability study indicate that the participants tended to have less difficulty completing tasks using the prototypes in their own personal car when compared to performing the same tasks using a rented Zipcar. Also, the location of controls on the steering wheel and center fascia is recommended for consideration when designing sharing-friendly vehicles. Recommendations regarding the location of controls, such as volume control on the steering wheel, are included in this paper. Pros and cons of using eye tracking and driving simulators are also discussed in this paper.

Keywords

car sharing, eye tracking, car interaction design, usability test, user preference, car interior, design research, industrial design, interface design

Introduction

The sharing economy, accessing goods and services that people need and paying short-term fees for that access, is growing rapidly and expected to outpace the traditional rental sector as shown in Figure 1 (Chen, 2009). Car sharing has become a worldwide phenomenon (Bardhi & Eckhardt, 2012). For more than 20 years, Switzerland and Germany have embraced car sharing, making it a popular alternative to car ownership (Bardhi & Eckhardt, 2012). According to the Transportation Sustainability Research Center at the University of California at Berkeley, there are approximately 4.8 million individuals sharing more than 104,000 vehicles across the globe (Lane, Zeng, Dhingra, & Carrigan, 2015). According to Navigant Consulting, global car sharing was predicted to be a $1 billion industry in 2013 and expected to grow to $6.2 billion by 2020.

Figure 1. Importance of sharing economy and car sharing. Note: Data visualizations in Figure 1 were generated by Byungsoo Kim (2016) from data provided by original sources[1].

Previous Studies

There are a number of previous studies regarding interaction design for drivers. A recent trend in automotive in-vehicle design is the inclusion of touch screens. As the display in a vehicle becomes larger, it includes an “increasing amount of functionality” (Rümelin & Butz, 2013, p. 48). Touch screens were initially installed for navigations systems and were expanded to include in-vehicle information systems and now are being extended to integrate connected car information (Rümelin & Butz, 2013). Screens in cars have been effectively providing information and entertainment (infotainment systems; Demers, 2005). However, due to the nature of a screen instead of a tangible interaction method, the touch screen does not provide enough haptic feedback for the driver to easily find them by touch and control them without looking. The lack of tactile feedback associated with touch screens can have a negative effect on “mental load and interrupt ability” (Rümelin & Butz, 2013, p. 48).

Because of the distraction of controlling a touchscreen while driving, the car industry is now searching for alternative interaction designs. There are some studies related to improving usability of interaction designs for drivers. An experiment to minimize the visual attention during interactions to maintain the driver’s focus on the road found that physical elements around the screen space were useful in helping drivers control the associated functions (Rümelin & Butz, 2013). When assessing how older people and younger people performed several tasks in actual driving conditions, some design factors improved visibility and controllability by older drivers. As a result, several design guidelines were proposed including cluster color and font, display location, and HVAC control type (Ryu et al., 2009). There is a study examining how drivers experience haptic feedback in a car while they are engaged in different communication situations (Väänänen-vainio-mattila et al., 2014). The results indicated that vibration was the most pleasant and familiar type of feedback. Pneumatic feedback was perceived as “novel, interesting, and even fun, but not always interpretable” (p. 251) Because the participants in the study did not drive a car while performing tasks, future studies examining participants driving while performing tasks will be necessary. For participant’s safety and to prevent potential accidents, conducting a study in an empty parking lot or using a driving simulator would be the most appropriate method for future studies. Regarding driver distraction, reducing the number of steps for driver assistance systems and in-vehicle information systems by providing “preconfigured functions” based on personal preferences was found to be beneficial (Siegmund, Altmüller, Bengler, & Gmbh, 2013). It was summarized as a structure for “personalized situation-adaptive user interaction” which would be one of the most important emerging trends for car interaction design.

These reviews illustrate that various interaction design methods for drivers have been applied and studied in cars to help improve the usability of the secondary controls while driving. However, there has not been a study investigating interaction design focusing on the needs of the user/driver within the car sharing context.

Distraction While Driving a Car

There are many distractions for drivers while driving (Strayer, Watson, & Drews, 2011). The distractions can be categorized in the following three areas:

visual distraction—tasks that require drivers’ attention to leave the road to visually obtain information
manual distraction—tasks that require drivers to take their hands off the steering wheel in order to control a device or function
cognitive distraction—tasks that include thinking about something other than driving (NHTSA, 2010)

Typically, distractions for drivers included talking to passengers, eating, drinking, lighting a cigarette, shaving, applying makeup, and listening to the radio (Strayer et al., 2011). Because car-sharing system users check out cars only when they need to drive, there is a chance that they will rent different cars each time. Also, because they check out a car for a short period of time, users may not take the time to familiarize themselves with the controls. Thus, they might start driving and figure out how to use the controls while driving; this may result in a combination of visual, manual, and cognitive distractions. These distractions for the drivers using car-sharing systems are in addition to traditional distractions.

This project consisted of two studies and a control design development. The first study assessed current conditions associated with driving cars from a car-sharing system and was conducted on the road. Based on the findings of the first study (Study 1), secondary car controls were redesigned and tested in a second lab-based study using a driving simulator (Study 2). The studies and redesigned controls are described in the following sections.

Purpose of Study 1

The purpose of Study 1 is to understand how drivers control the most frequently-used secondary functions while driving a car using a car-sharing system (that they are not familiar with). The secondary functions, such as those for the audio system and heating and cooling systems (HVAC), are located in different areas and have different types of controls; use of these controls are expected to cause distractions for car sharing users. For this reason, this study focuses on secondary controls.

Methods

This study adopted a 2 x 4 within-subject design. There were two factors: car type (two levels: own car and Zipcar) and in-vehicle task (four levels: turning on the radio/audio, selecting a radio station/music, controlling the audio volume, and controlling the HVAC). Both factors were varied by participant, meaning that each participant drove both types of cars and completed the four tasks in each car.

Study 1 involved completing two 5-minute driving tasks followed by a 10- to 15-minute interview. For each car type, the participant’s car and a car rented from Zipcar, there were 10 minutes of setup time (5 minutes to adjust mirrors, seat, etc. and 5 minutes for eye tracking device calibration). Two data collection methods were used in Study 1: direct observations and semi-structured interviews. Direct observations, also referred to as observational studies, allow the researcher to observe participants in an environment and collect data about their behaviors, actions, and activities (Holmes, 2013). Direct observations were conducted twice for each participant: in the participant’s car and in a vehicle rented by the experimenter. The purpose of the direct observation was to understand the difficulty the participants might have in controlling the secondary functions during an actual driving situation when in a car with which they were unfamiliar as compared to their own (familiar) car.

Eye tracking has been widely used to analyze eye movement—especially related to driving safety (Kapitaniak, Walczak, Kosobudzki, Jóźwiak, & Bortkiewicz, 2015). An EyeGuide eye tracking device, similar to a large set of headphones with a sensor located on the side of the participant’s face to record the driving situation, was used during Study 1. Eye tracking data was collected during the direct observations to record the participants’ eye movements.

After the participant had driven both cars, a semi-structured interview was conducted in the second car immediately after completing the final driving task so that the participants could vividly describe their experience. The interviewer generally followed an interview guide; however, when appropriate, the interviewer adapted questions to respond to the participant’s experience and description (Cohen & Crabtree, 2006).

Measurements

Two measurements were calculated from the eye tracking data: number of glances (NUMGLANCES) and task completion time (TASKTIME). These measurements were used to compare the result of direct observation. NUMGLANCES was defined as the number of times a participant moved his/her gaze away from the road and took a glance at the in-vehicle controls to complete a task. For instance, when the participant glanced three times at the interface to control the volume while driving, the NUMGLANCES for completing the controlling volume task was three.

TASKTIME was defined as the amount of time that a participant spent completing each task. More specifically, the TASKTIME was measured from the first moment that the participant glanced at the interface when starting a task until the last moment that the participant’s hand was removed from contact with the interface after completing the task. Sometimes participants took a glance even after completing the task. In that case, TASKTIME is calculated from the first glance to the final glance because the final glance may have been to verify that the task was accomplished correctly. The NUMGLANCES and TASKTIME for the same task between the two car types, driving their own car and driving a rented car, were compared.

Participants

While the suggested minimum number of participants for basic findings for usability studies is four or five (Robert, 1992), 15 participants were recruited from a university campus. The sample size was determined using a power calculation based on an initial data set with five participants. All participants had at least three years of driving experience, with no history of epilepsy, affirmed that they had not been drinking alcohol within the past 24 hours, were not taking medication that could result in sleepiness, and were not sleepy or too tired to drive at the time of the experiment. Every participant also affirmed that his/her car had passed inspection within the past year and had current insurance. Among the 15 participants, three did not complete some task conditions in their own cars, resulting in a total of 12 participants in the study with complete data. The participants were instructed to perform certain driving tasks before starting to drive their car. To mitigate interference with their natural driving routine, the researcher did not instruct the participants to perform the tasks while driving. Hence, some of the participants forgot to perform a few tasks. The researcher did note the tasks that were forgotten. After the participants did not complete a couple of the tasks in their own cars. These 12 participants were included in the final analysis. A summary of participant demographics is shown in Table 1.

Table 1. Demographics of Participants in Study 1 and Study 2

		Study 1^*		Study 2^**
Characteristics		Frequency	Percentage	Frequency	Percentage
Gender	Males	7	58.3%	8	61.5%
Gender	Females	5	41.7%	5	38.5%
Age	24-32	9	75.0%	9	69.2%
	33-39	1	8.3%	2	15.4%
	40-46	2	16.7%	2	15.4%
Years of driving experience	4-12	8	66.7%	8	61.5%
	13-21	1	8.3%	2	15.4%
	22-30	3	25.0%	3	23.1%

^*n = 12 participants

^**n = 13 participants

Note. Only participants with complete data were included in the analyses. Thus, while 15 participants were recruited for each study, only 12 of the 15 participants in Study 1 and 13 of the 13 participants in Study 2 had complete data sets.

Apparatus

Study 1 was conducted in a large empty parking lot. A rented Zipcar vehicle and the participants’ cars were used to compare the user experiences of performing tasks in a familiar car and in an unfamiliar car. An eye tracking device similar to a larger set of headphones with a sensor was used to record the participant’s eye movement while driving. Two GoPro cameras were used to document the usage of the secondary controls.

Procedure

The researcher rented a car, and the participant met the researcher at an empty parking lot with their own car at a scheduled time. The participant was required to present his/her valid driver’s license to the researcher. The researcher and the participant then got into either the participant’s car or the rented car parked in the empty parking lot and informed consent was provided by the participant.

After providing informed consent, two GoPro cameras were placed in the front and rear of the car using suction cups. These two cameras were positioned slightly overhead so that they did not obstruct the participant’s line of sight. To avoid sound isolation, the eye tracking device was positioned so that it did not cover the participant’s ear canal (see Figure 2).

Figure 2. Images of how to wear the eye tracking device (Study 1).

Because participants were anticipated to rapidly move their heads (e.g., looking over their shoulder) for contextual awareness, a headband was used to secure the eye tracking device. The eye tracking device was calibrated in each car. After the calibration, the participants were instructed to perform the following four simple tasks while driving:

turning on the radio/audio
selecting a radio station/music
controlling the audio volume
controlling the HVAC

To replicate a natural driving experience, the participant was asked to drive naturally and perform the tasks based on the participant’s daily routine, regardless of the order. The participants were then asked to start driving the car in the parking lot. After the participant completed the first set of driving tasks with the car, the participant was asked to move to the other car. The two GoPro cameras were moved to the same front and rear locations in the second car; the participant was still wearing the eye tracking device. The eye tracking device was calibrated again once the participant was seated in the second car.

The participant was asked to perform the same simple tasks (turning on the radio, selecting the radio station, controlling the radio volume, and controlling the HVAC) as those completed while driving the first car. After the participant completed the driving task with the second car, the participant was interviewed regarding their driving experience (see Figure 3).

Figure 3. Snapshots of tasks, equipment, and a visual heat map in Study 1.

To mitigate order effects in Study 1, the order in which participants drove the cars (personal or rented) was randomized. This randomization did not result in a completely counterbalanced design. Therefore, the mean of the TASKTIMEs (using 1 standard deviation for the range of comparison) was assessed to compare the order of car use. No significant differences were found based on car use order. Participants chose to control some functions, such as the audio volume, either from the steering wheel controls or center fascia controls based on their preference, and the data from the chosen controls were collected.

After completing the driving tasks, participants were asked to participate in a 10- to 15-minute interview. During the interview, participants described the differences between the cars and the difficulty they experienced while performing tasks with the rented car.

Results

The same type of car (4-door sedan with automatic transmission) from three different car brands (Ford, Honda, and Hyundai) was rented from Zipcar for Study 1. For the participants’ own cars, there were two different types (4-door SUV and 4-door sedan both with automatic transmissions) from 7 different car brands (Ford, Honda, Hyundai, Jeep, Kia, Toyota, and Volvo).

SPEED (Inverse of TASKTIME)

To stabilize variance, TASKTIME was transformed into speed (SPEED) using an inverse transformation (SPEED = 1/task time; Whelan, 2008). A greater SPEED value indicates faster task completion. SPEED data was analyzed using a repeated-measure analysis of variances (rmANOVA). There were two within-subject factors: car type and task. There was a significant main effect of car type, F(1,11) = 35.81, p < .001, as participants were much faster in their own car (M = .35) than in a Zipcar (M = .16). Overall, SPEED did not vary significantly among tasks (turning on the radio/audio, .29; selecting a radio station, .20; controlling the audio volume, .29; controlling the HVAC, .23), F(3,33) = 1.61, p = .205. The interaction between car type and task was not significant, F(3,33) = .68, p = .570. A summary of means and data range of both TASKTIME and transformed SPEED are provided in Table 2. Illustration of data in its raw form, TASKTIME, is provided in Figure 4.

NUMGLANCES

Data on NUMGLANCES was analyzed using a repeated-measure analysis of variances (rmANOVA). There were two within-subject factors: car type and task. There was a significant main effect of car type, F(1,11) = 24.52, p < .001, as participants performed the tasks with many fewer glances in their own cars (1.60) compared to in the Zipcar (3.85). Overall, NUMGLANCES did not vary significantly among tasks (turning on the radio/audio, 3.17; selecting a radio station, 3.17; controlling the audio volume, 1.96; controlling the HVAC, 2.63), F(3,33) = 1.83, p = .160. The interaction between car type and task was not significant (Figure 5), F(3,33) = 1.51, p = .229. A summary of means and data range is provided in Table 2.

Estimated marginal means from rmANOVA are visualized to compare the different driving experiences (see Figure 4 and Figure 5).

Table 2. TASKTIME, SPEED, and NUMGLANCES in Study 1

Task

Participant’s car**

Rented car from Zipcar**

Avg. TASKTIME^*

[min, max]

Avg.
SPEED

[min, max]

Avg. NUMGLANCES

[min, max]

Avg. TASKTIME^*

[min, max]

Avg.
SPEED

[min, max]

Avg. NUMGLANCES

[min, max]

1. Turning on the radio/audio

3.17

^{[1.00, 8.00]}

0.41

^{[0.13, 1.00]}

1.50

^{[1.00, 2.00]}

12.83

^{[3.00, 38.00]}

0.17

^{[0.03, 0.33]}

4.92

^{[1.00, 13.00]}

2. Selecting a radio station/music

5.75

^{[2.00, 16.00]}

0.25

^{[0.06, 1.14]}

2.00

^{[1.00, 4.00]}

13.42

^{[4.00, 29.00]}

0.11

^{[0.03, 0.25]}

4.50

^{[2.00, 9.00]}

3. Controlling the audio volume

3.92

^{[1.00, 7.00]}

0.33

^{[0.14, 1.00]}

1.50

^{[1.00, 3.00]}

6.00

^{[2.00, 19.00]}

0.23

^{[0.05, 0.50]}

2.50

^{[1.00, 7.00]}

4. Controlling the HVAC

4.25

^{[1.00, 7.00]}

1.19

^{[0.14, 1.00]}

1.75

^{[1.00, 4.00]}

10.33

^{[4.00, 22.00]}

0.13

^{[0.05, 0.25]}

3.50

^{[1.00, 9.00]}

Average

4.27

^{[1.25, 9.50]}

0.55

^{[0.12, 0.88]}

1.69

^{[1.00, 3.25]}

10.65

^{[3.25, 27.00]}

0.16

^{[0.04, 0.33]}

3.85

^{[1.25, 9.50]}

^* Time presented in seconds

^** n = 12 participants

Figure 4. TASKTIME across four tasks in participants’ cars or rented cars in Study 1. Error bars represent +/- 1 standard error.

Figure 5. NUMGLANCES across four tasks in participants’ cars or rented cars in Study 1. Error bars represent +/- 1 standard error.

Based on the data presented in Table 2, the results from the direct observation indicated the following (because TASKTIME is easier to compare and understand than SPEED, TASKTIME is used to describe the differences between the two car types instead of SPEED):

Averaging TASKTIME across tasks, the TASKTIME was 149.4% longer when participants were driving the rented car compared to their own car.
Averaging NUMGLANCES across tasks, the average NUMGLANCES was 127.8% greater when participants were driving the rented car compared to their own car.
The average TASKTIME for each of the tasks were longer (at least 53.1% more) with the rented car.
The average NUMGLANCES for each of the tasks were greater (at least 66.7% more) with the rented car.
For TASKTIME, there were several interesting differences that were observed at the participant level:
- Twelve participants showed an increase in TASKTIME in the rented car during the turning on the audio task compared to their car.
- Ten participants showed an increase in TASKTIME in the rented car during the selecting a radio station/music task compared to their car.
- Eight participants showed an increase in TASKTIME in the rented car during the controlling the audio volume task compared to their car.
- Ten participants showed an increase in TASKTIME in the rented car during the controlling the HVAC task compared to their car.
For NUMGLANCES, there were several interesting differences that can be noted at the participant level:
- Nine participants showed an increase in NUMGLANCES in the rented car during the turning on the audio task compared to their car.
- Ten participants showed an increase in NUMGLANCES in the rented car during the selecting a radio station/music task compared to their car.
- Six participants showed an increase in NUMGLANCES in the rented car during the controlling the audio volume task compared to their car, while 5 participants had the same NUMGLANCES for their car and the rented car.
- Eight participants showed an increase in NUMGLANCES in the rented car during the controlling the HVAC task compared to their car.

While each participant’s driving experience was visualized to compare different driving experiences, Participant 2’s visualization most clearly depicts the difference between driving the participant’s own car and a rented car among all participants and thus was chosen for illustration in this paper for discussion (see Figure 6). In the visualization, each task, NUMGLANCES, and TASKTIME are depicted using icons, colors, and circles. Different kinds of tasks that the participant performed during direct observation are presented as simple icons. Changes in NUMGLANCES is represented by using different colors. For instance, if the participant glanced once or twice while performing a task, the color for the circle is gray. If the participant glanced three, four, or five+ times, the color of the circle is yellow, orange, or red, respectively. The amount of time that the participants spent completing the task is indicated by the diameter of the circle. This visualization highlights the merging of qualitative and quantitative data which help the design researchers understand the challenges faced by the participants, providing insights to inform the development of the prototypes. The development of the visualizations was a part of the data synthesis and prototype type development, enhancing the data-driven design-development process.

The visualization for Participant 2 indicates the following:

It took more time for Participant 2 to start driving the rented car than her personal car. This implies she was in a learning phase. Quite a bit of this time was spent interacting with the HVAC controls.
Participant 2 preferred to use steering wheel controls for certain functions in both of the cars.
Besides controlling the HVAC, all of the tasks took more glances and required greater time to complete tasks while driving the rented car.
Participant 2 chose to stop driving the rented car to adjust certain controls.

Figure 6. Visualized graph of Study 1 data for Participant 2.

Based on the observations during the driving task, participants tended to have similar control sequences of the functions that are closely related to each other. For example, when drivers controlled the audio system, most of the time they turned on the audio and adjusted the volume, especially in a rented car from Zipcar. Selection of previous/next songs happened after adjusting the volume. Most participants adjusted the audio system first. One participant accidentally activated the function which affected driving speed in a rented car from Zipcar.

The semi-structured interview results revealed that most of the participants preferred using steering wheel controls for certain functions, such as controlling volume, changing the media source, and selecting previous/next songs in their own cars. More specifically, only one of the participants who had steering wheel controls did not choose to use them. One participant commented that “I am focusing more on this [pointing at the steering wheel area] part [when I am driving].” Participants also mentioned that different labels for identical functions created confusion for them. For instance, the label for changing between media sources depends on the car brand (e.g., source, CD/AUX, and audio). Several participants also shared their previous experiences related to renting a car. The participants mentioned when they rented a car for a day or two, they used only a limited number of secondary functions because finding desired functions from center fascia controls that they were not familiar with was sometimes overwhelming.

Discussion

The overall results of Study 1 document the difficulty of users’ experience while controlling the secondary functions in an unfamiliar car when compared to a familiar car. In addition, during direct observation, some participants found that it was necessary to stop the rented car to locate the desired control(s). In addition to inconvenience, the unfamiliar locations and unfamiliar type of controls may have an effect on driving. The results of the semi-structured interview reinforce the findings from the observations. Because the interview was conducted immediately after the driving experience, there were many valuable comments and suggestions. During the interview, one participant mentioned the difficulty of controlling gear shifting function in a rented car. The participant accidently clicked the “grade assist button” and that affected the driving speed. The participant described that moment as a “very embarrassed moment and I would had been in trouble if I were on the road.” The “grade assist button” was not in the scope of Study 1 because it was a primary control which directly affects driving speed. However, this issue strongly addresses how unfamiliar controls affect the safety of drivers using a car-sharing system.

The use of eye tracking equipment during the observational study supported the calculation of TASKTIME and NUMGLANCES. The comparison of TASKTIME and NUMGLANCES between the two different driving experiences documents how much more time the participants spent and how many more glances were used to control the desired function in a car that they were not familiar with compared to their own car. Fixation time per glance and the distance between fixation locations were also intended measures. However, because the eye tracking device is light-sensitive and the data was collected outdoors, the time of day significantly impacted the eye tracking system. The time of day (affording consistent exposure to daylight) was not controlled by the experimenter; instead, the data collection sessions were scheduled to accommodate the participants. Thus, the calculation of fixation time and the distance between fixation locations were not feasible.

The correlation between TASKTIME and NUMGLANCE has been measured, and the result is fairly high but shows a different result in between participants’ own cars (0.47) and the rented cars from Zipcar (0.88). When the driving tasks were performed in the rented car from Zipcar, because participants were not familiar with the location of controls and interaction type, NUMGLANCES and TASKTIME were more likely correlated. However, in the participants’ own cars, the participants already know the location of controls and interaction type. This affects fewer NUMGLACES than with a rented car, but NUMGLACES did not always affect TASKTIME. For instance, Participant 1 presented two NUMGLANCES and 16 TASKTIMEs for adjusting the radio station. This implies that Participant 1 started adjusting the radio station with 1 to 2 NUMGLANCES and did not accumulate additional NUMGLANCES for the rest of the TASKTIMEs because of familiar tactile feedback from familiar interaction type. Hence, TASKTIME and NUMGLANCE are still meaningful to be presented separately.

Car Control Redesign

Before starting Study 2, an in-depth market review and data synthesis were conducted to understand the most common location of controls on the center fascia and the steering wheel in recent cars. Among 20 recent cars (2015–2017) from nine different car companies (see Table 3), 10 cars were chosen to present in this paper.

Table 3. Car Manufacturers for the In-Depth Market Review

U.S.A.

Europe

Republic of Korea

Japan

Ford

General Motors

Audi*

Volkswagen

Porsche*

Hyundai

Kia

Toyota

Honda

Note. Seven chosen car manufacturers for the in-depth market review are from the top 10 car manufacturers based on the “OICA Correspondents Survey Report” (OICA, 2015). Two European cars manufacturers (indicated with *) were chosen for the in-depth market review.

The secondary controls from Study 1 were chosen to conduct an in-depth market review (see Table 4).

Table 4. The Secondary Controls for the In-Depth Market Review

Audio system	Power on radio/audio system, radio station/music selection, and volume control
Temperature system	Temperature control

All the images for the in-depth market review were collected from either car dealerships or online magazines, such as Motor Trend. To synthesize the collected data, the images of center fascia from each car were cropped 2 by 2 inches and marks, such as orange dots and steering wheel icons, were used (see Table 5). The orange dots indicate the location of a control on center fascia. If a function is controlled by both a center fascia control and a steering wheel control, a small image of a steering wheel control is presented on the bottom left side of the center fascia control picture. If the control is located on the left side of the steering wheel, an orange steering wheel shaped icon is indicated on the left side of the steering wheel control picture.

Table 5. Process of Synthesizing the Collected Data from an In-Depth Market Review (Power on Audio System/Control Volume, 2017 Buick)

Pictures	Interpretation	Result
	The location of a volume control button is on the top middle of the audio system instrumentation group on the center fascia.
	The location of a volume control button is on the middle of the audio system instrumentation group on the steering wheel.
The result of synthesizing one car

After that, 10 images with orange dots and steering wheel icons were overlapped to synthesize the trend of the most common location. The example of synthesized images from the in-depth market review is shown in Figure 7.

Figure 7. Example of the in-depth market review synthesis (Powering on Audio System/Control Volume).

The synthesis of the most common location and interaction type for audio system controls for recent cars (2015–2017) is presented in Figure 8. The data shows that the most common location of powering on audio/radio system and controlling volume on the center fascia is bottom left, and the most common interaction type is knob type (10 out of 10). The most common location of powering on audio/radio system and controlling volume on a steering wheel control is left, and the most common interaction type is button type (button type: 8 and scrolling type: 2), but the layout of button types is different (vertical: 6 and horizontal: 2). There are no on/off buttons for audio system controls on the steering wheel. An instrumentation group does not have a single interaction type. The summary of the most common location and the interaction type for the most frequently used audio system controls in cars are shown in Table 6.

Figure 8. Visualization of the most common location and interaction type for audio system controls.

Table 6. The Most Common Location and Interaction Type for Audio System Controls

The most frequently used audio system controls	Center fascia		Steering wheel
The most frequently used audio system controls	The most common location	The most common interaction type	The most common location	The most common interaction type
Audio system instrumentation group	Above the temperature system instrumentation group	–^*	Left	–^*
Powering on audio/radio system	Bottom left	Knob type	Left	Button type
Controlling volume	Top left	Knob type	Left	Button type
Radio station/music selection	Top middle	Button type	Left	Button type

^* No common interaction type.

The synthesis of the most common location and interaction type for temperature system controls is shown in Figure 9. The data shows that the most common location of controlling temperature is bottom left/right, and the most common interaction type is the knob type (knob type: 8, button type: 2). There is no temperature control on the steering wheel. An instrumentation group does not have a single interaction type. The summary of the most common location and the interaction type for the most frequently used temperature system controls in cars are shown in Table 7.

Figure 9. Visualization of the most common location and interaction type for temperature system controls.

Table 7. The Most Common Location and Interaction Type for Temperature System Controls

Temperature system controls	The most common location	The most common interaction type
Temperature system instrumentation group	Lower part of the audio system instrumentation group	–^*
Temperature control	Left, right	Knob type

^* No common interaction type.

After the in-depth market review, a mini study was conducted with five participants. All of the controls were movable, and the participants were asked to choose the most frequently-used controls and arrange them in the participants’ preferred location (see Figure 10). After that, a semi-structured interview was conducted to understand why the participants configured the controls as they did. The result of the mini study indicated that some of the preferred location and the interaction types of controls were different from the result of the in-depth market review. For example, the mini study suggested that a scrolling type control for volume is the preferred interaction type, which is less common than the button type according to the in-depth market review. In this case, both directions were sketched, and the sketches were reviewed by other designers. Finally, the scroll type was chosen. Most participants from the mini study commented that they would like to have the most frequently used controls on the steering wheel on their dominant hand side. While there were a number of ideas regarding the construction of the steering wheel prototype, a remote-control device that can be installed on the steering wheel based on the participant’s preference was chosen for development.

Based on the results from the study, the in-depth market review, and the mini study, two sets of prototypes for the secondary controls (one each for the center fascia and the steering wheel) were developed to improve the usability and safety in the car sharing experience. All parts were 3D printed and were painted black with white text and icons to mimic actual controls (see Figure 11). Figure 11 presents the location and interaction type of prototypes compared to the result from the in-depth market review. The prototypes provided haptic feedback to users (knobs could be turned, buttons pushed, and scrolls rotated); however, they were not functional (e.g., they did not adjust the volume or change the temperature of the air).

Figure 10. Development of prototype of secondary controls.

Figure 11. The location and interaction type of prototypes comparing to the result of in-depth market review.

Purpose of Study 2

A lab-based usability study was conducted to evaluate the improvement of usability of the secondary controls prototype using a driving simulator. The use of the driving simulator was chosen to mitigate potential safety concerns of using a prototype in a real car while on the road.