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Ethnography and Engineering: How Qualitative Methods can Help Build the Car of

the Future Tyler Brickle , Stephen Gonzalez, Logan McLaughlin, and Heather S. Roth (University of North Texas)

Paper Presented at the Society for Applied Anthropology Annual Meeting

March 27, 2015

The central theme of this session is the role of qualitative data in the

“quantitative” world of business; however in this paper, we seek to challenge that

dichotomy because it is not always the most salient way to categorize research methods

in projects conducted within the high tech sector. Secondary to this theme is the value of

ethnography to the fields of engineering and technology. We intend to support these

theses based on our participation in an applied research project led by Dr. Christina

Wasson in partnership with the Nissan Research Center in Silicon Valley (NRC-SV), a

lab dedicated to developing autonomous vehicle technology (AV). Dr. Brigitte Jordan

consults at the NRC-SV and acted as lab liaison to the class during this project. The

research was conducted as part of a Design Anthropology course which took place

between August and December of 2014.

While other papers in this session describe situations in which the key

methodological contrast was the

use of qualitative versus

quantitative data, the contrast

between our class project and the

methodology used by the Lab was

ethnography versus experiment.

Our class undertook a decidedly

ethnographic approach to analyze

the social life of cars. We found

that in engineering research on

autonomous vehicles, there is a

heavy emphasis on experimental

methodologies, that is to say

various forms of testing. These

methods can be both quantitative

and qualitative. With regard to

qualitative methods, labs focus on

lean research because of the

perception that there is not

enough time to study the way

people behave over long periods.

They use market surveys and

bring people into the lab for qualitative evaluation and testing.

The idea of a self-driving car is not a new one; writers have been envisioning such

things since the early days of science fiction. By the 1950s it had even entered into the

public consciousness with fantastical advertisements for America’s Electric Light and

Power Companies, as shown in Figure 1. However it has only been within the last decade

that the technology for such a future may finally be in reach. The Defense Advanced

Figure 1: "Electricity May be the Driver, one day your car may speed along an electric super-highway, speed and steer controlled by electronic devices embedded in the road. Highways will be made safe - by electricity!” (Paleofuture.com) )2010).

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Research Projects Agency’s (DARPA) first driverless car challenge was issued in 2002.

Fifteen teams competed in the challenge but none of them were able to get their vehicles

to complete the seven mile course set in the Mojave Desert (DARPA 2014). One year

later they reconvened and several teams were able to complete the challenge. It was a

sign that driverless vehicles were possible. By 2009, Google hired many of these same

researchers to carry on their work. As a result of these initial autonomous vehicle

prototypes, AV research has now been kicked into high gear. This is an emerging and

rapidly developing field, so the academic literature on the topic is sparse. No doubt a lot

of research is hiding behind Non-Disclosure Agreements as companies battle to get the

first true AV experience on the road. Every major car manufacturer is entering the fray,

but what methods are they using to design these driverless cars? And how are

anthropologists and other social scientists contributing to the research and design of these

vehicles? (Or rather, how could they contribute?) The following sections explore the

existing literature and current landscape of the industry, specifically the methodologies

being used in the research and design of connected and autonomous vehicles, our own

project with Nissan Research Center in Silicon Valley (NRC-SV), and our

recommendations for the future of AV research.

Literature and Industry Review As previously mentioned, the academic literature on AV is still sparse, even

among various engineering and transportation journals (CAR 2012). This is especially

true for anthropology, but even if we explore cars more broadly, there has only been

some limited ethnography completed about various car cultures around the world (Miller

2001). In other disciplines, sociologists and psychologists have often assisted in market

research by exploring the personal and emotional aspects of car ownership. Sheller

(2004) speaks about car consumption as never being simply about rational economic

choices, but also about "aesthetic, emotional and sensory responses to driving." We

expected these types of responses in our own research, indeed the engineers and

researchers at NRC-SV expected it as well. However we found that the majority of our

participants were led by rational economic choices. Even the owner of a brand new 2014

red Mustang convertible viewed his car as primarily a vehicle for work, his previous

Jaguar ”dream” vehicle was ultimately unable to meet the functional needs he required.

And so the question of whether society at large is ready to ‘give up’ driving may not be

as problematic as one might think. Evidence shows that fewer and fewer teenagers are

acquiring their driver's license, with only 49% of 17 year olds getting theirs in 2008

compared to 75% in 1978 (KPMG and CAR 2012).

The world of automated driving is a veritable alphabet soup, so it is important to

establish some terminology first. Although our project was aimed at exploring current

driver behavior in order to better inform NRC-SV's design of AV technology, and indeed

the current research zeitgeist gripping the industry is directed towards fully autonomous

vehicles, even the most optimistic scenarios don't envision a fully automated world for at

least two decades (Lin et al 2013). In the interim, vehicle-to-vehicle (V2V) and vehicle-

to-infrastructure (V2I) communication technologies are being tested in pilot programs

around the country (Narla 2013). Known collectively as V2X in the U.S. and Car2X in

Europe, such technologies will be instrumental in an AV world. From an infrastructure

standpoint, another umbrella term is intelligent transportation systems (ITS). ITS refers to

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the myriad of telecommunications and traffic management systems being developed to

handle all the data that V2X technologies will create (Narla 2013).

Historically, automotive research has taken place in an experimental paradigm,

usually in the form of driving simulations or usability testing of new prototype

technologies. However, recent technological advances have led to a more “quasi-

ethnographic” method that seeks to observe driver behavior unobtrusively for long

periods of time (Nes et al 2013). This methodology is termed ‘naturalistic driving studies’

or NDS for short. One of the primary means of data collection used by NDS researchers

is the use of low-instrumented cars (LICs) and highly instrumented cars (HICs). These

vehicles contain different kinds of data acquisition systems, ranging from GPS loggers to

eye-tracking equipment, interior and exterior video cameras, and speed, acceleration, and

steering sensors (Valero-Mora et al 2013). Some examples of NDS studies include cell

phone usage in the car (Fitch 2014), holistic sensing and active displays (Trivedi and

Cheng 2007), and right-turn behavior when in the presence of bicyclists (Nes et al 2013).

Valero-Mora et al (2013) looked at three NDS research programs in the UK, Greece, and

Spain, comparing and contrasting the pros and cons of each. One of their conclusions was

that for all the massive amounts of information that can be collected, analyzing hundreds

of hours of video and sensor data is simply not feasible (Valero-Mora et al 2013). These

NDS studies are actually quite similar to our own project in terms of their goal to observe

driving behavior. Yet where NDS projects focus on collecting massive amounts of data

and video with participants driving test cars in test situations, our study relied on

ethnographic fieldwork with individuals driving their own cars in everyday life.

Although NDS studies put an emphasis on observing the behavior of driving, our

project sought to make the act of driving visible, understanding more of its intricacies

than just the behavior itself. There has been little exploration about what people actually

do while they drive in everyday life. Certainly, the naturalistic driving studies described

above attempt just that, but only in response to very narrow research questions. The

broader ethnography of cars is curiously lacking when you consider that driving has been

a ubiquitous activity for a large segment of human society for the past century.

Questionnaires and surveys have been used to explore consumer attitudes towards

the coming shift to connected vehicle and AV technology. Of note to us is a survey of

public opinion on AV technology conducted in the U.S., U.K., and Australia (Schoettle

and Sivak 2014). A similar study by Payre et al (2014) used a mixed methods approach,

first conducting limited interviews about AV technology and then building a

questionnaire out of those results. A previous study by the Center for Automotive

Research conducted focus groups for Michigan’s Department of Transportation (CAR

2012). These studies all seem to suggest the same thing, that people are cautiously

optimistic about AV technology.

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In terms of coming technology developments, Google has aggressively pioneered

the AV landscape, and they want their driverless cars on the road by 2017 (Newcomb

2014). Nissan has announced that their Autonomous Drive technology will be available

to consumers by 2020 (Newcomb 2014). Mercedes-Benz, whose current vehicles already

contain some of the most advanced driver assistance technology on the market, officially

unveiled their luxurious F 015 autonomous concept earlier this year at the Consumer

Electronic Show (Wilson 2015). Their vision is decidedly more futuristic, with a chromed

out body, swivel chairs, and more LEDs and touchscreens than you can count. In

contrast, Toyota has stated

unequivocally that they are

not making a driverless car

but that hasn’t stopped them

from developing an

Advanced Safety Research

Lexus, capable of steering

itself in certain driving

conditions (Newcomb 2014).

Toyota stated at the 2014

ITS World Congress that

they see driving as a,

“collaboration between the

driver and technology”

(Newcomb 2014). Similarly,

GM has announced that

certain 2017 Cadillac models

will have Super Cruise

Technology, providing

hands-off (and feet-off)

braking, speed control, and

lane following (Newcomb

2014). Perhaps the hope for

some manufacturers is that

all this driver assistance will

just slowly turn into true AV

before consumers notice.

Google doesn’t seem

interested in being subtle

though; their prototypes have

already ditched the steering

wheel and look less like cars

and more like the driverless pods that are already operating at the Heathrow Airport in

London, as shown in Figure 2.

Figure 2: (Top) - London Heathrow PRT Pod (Sharpe 2011). (Bottom)- Google self-driving car (Google self-driving car project 2014).

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So how are all these cars and systems actually being designed? Again, it is

difficult to know exactly what’s going on behind closed doors at these companies, and to

what extent they may be using ethnography or other qualitative methods in their research

and design. One high-profile, public testing ground that is currently under construction,

and expected to be open later this year, is the M City facility at the University of

Michigan in Ann Arbor. Under the newly established Mobility Transformation Center,

the M City facility will be a one of a kind testing ground for connected and autonomous

vehicles. It is being supported by both

U.S. and Michigan Departments of

Transportation as well as a number of

corporate sponsors, including car

manufacturers Ford Motor Company,

GM, Honda, Nissan, Toyota, and other

businesses like Delphi Automotive, State

Farm, Verizon, and Xerox (Mobility

Transformation Center 2015). The

Mobility Transformation Center is also

collaborating across multiple university

departments, so the research to be

conducted will hopefully be varied in

discipline, theory, and methodology, see

Figure 3.

Sophisticated testing facilities

will be complementary to sophisticated

infrastructure and connected networks. As

Zafiroglu (2013) mentions in response to Healy’s glorious vision of an automated

wonderland (2013), smart cars are useless without smart roads. The Institute of

Transportation Engineers echoed Zafiroglu’s sentiments in a recent survey where

respondents felt “they are on the sidelines in the creation of these technologies" (Lin et al

2013). Anthropologists are often called upon to be the cultural negotiators in such

instances. We can continue to do so even in the realm of advanced technologies like AV

cars, bridging the gap between designers, engineers, traffic management, and consumers

(Zafiroglu 2013).

Our Project So, where do the realms of anthropology and engineering overlap when it comes

to the design of AV technologies? A close examination of our project will reveal how it

served as a supplement to the qualitative, quantitative, and experimental work the lab had

already done. This serves as a basis for a discussion about research methodologies and

how ethnography can contribute to the future of AV. Our project was exploratory and

ethnographic in the sense that we employed an array of qualitative research methods that

added a contextual richness that is so often overlooked in the engineering world at the

fuzzy front end. Most notably we wanted to answer: what is the social life of the car?

And how can our understanding of driving impact self-driving cars?

A total of 18 student researchers were paired in teams of two, one design student

and one anthropologist, for a total of nine teams. Each of these teams then recruited a

Figure 3: University Partners (Mobility Transformation Center 2015)

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study participant from the Dallas/Fort Worth metroplex. The study participants consisted

of friends, friends of friends and family members in a convenience sample of the

population. Although not truly representative, student researchers attempted to gather a

sample population of varying demographics with an age range from early twenties to

mid-sixties with an even balance of genders to better understand the views of the truly

massive possible user base for AV.

Our investigation was divided into three sections: a pre-driving interview, a

driving observation, and finally a post-driving interview. To understand driving habits

and behaviors among participants, we conducted in-depth, open-ended interviews. During

the pre-driving interview participants were asked to give the researchers a walk-through

of the car and unpack its contents and discuss what objects they carry in their car. The

researchers also employed participant observation to understand and make visible the

natural act of driving. During the driving observation, participants were accompanied on

a variety of different activities such as commuting to work, taking children to gym class,

and purchasing items from a gas station. The post-driving interview allowed the

researchers to reflect on the experience of driving to derive a richer understanding of the

ethnographic process.

Since each section was video recorded, we did not have to rely solely on memory

to find meaning in the micro-interactions between drivers and their cars. Each pair of

student researchers wrote a set of field notes, which correlated to the video recordings via

precise timestamps. This resulted in 27 total sets of field notes that were then analyzed

and coded using online qualitative analysis software known as Dedoose. This process

allowed the researchers to link participants’ behaviors and attitudes together, creating

patterns that offered insight into how people act and what they do when they drive. The

findings generated by this process allowed researchers to make design recommendations

for the Lab.

Discussion: challenging the assumptions of the session

Going into this project the class was aware that the NRC-SV had already

collected a vast amount of technical knowledge on the subject of cars, yet their

conclusions were derived from an experimental research framework. Thus our class

sought to address the gaps in knowledge formed from qualitative research conducted

experimentally in a lab versus qualitative research conducted ethnographically in a

natural setting. Not only would we answer questions about cars and driving through

ethnographic context, but we would also develop a more complex vision for future

research by demonstrating the usefulness of ethnography to an experimental framework.

In our specific case it was not a clash between the cold science of quantitative

methods and the rich personal nature of qualitative methods, but rather an entirely new

methodological framework. This is because we cannot label our methods wholly

qualitative and those of the lab wholly quantitative. In our case it was unavoidable to

quantify the data in order to understand the importance and frequency of certain patterns

of behavior. Such that, when we communicated our data to the Lab, we often phrased

patterns in terms of “x out of nine participants demonstrated behavior y.” For example

seven out of nine participants sang in their cars. We recognized the importance of

including client needs. As young scholar-practitioners, our goal was to adapt to the

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research culture of the Lab and complement their methods with ours, not clash with them.

This exercise realistically integrated anthropology in the high tech sector.

The research methods we used allowed us to gain a fresher, more nuanced

perspective of how people actually drive and understand their cars by redefining the

interactions between researcher and study participant that are not typically seen in an

experimental approach. For instance the necessity of building rapport was paramount to

obtaining a genuine level of social interaction between student researcher and study

participant. We met drivers in their homes, at cafes, and outside of their workplace,

flipping the logic of laboratory-experimental settings and disbanding the anonymity of

market survey research. Researchers carefully guided the pre and post interviews by

asking open-ended questions, allowing participants to digress on themes most important

to them. Student researchers also sat in the cars of study participants, observing them in

their natural setting while driving. The presence of a researcher is something that was

truly innovative in our study. Finally, and most importantly, we studied participants

driving their very own cars. Naturalistic driving studies often neglect this crucial detail,

instead mounting sensors and cameras in test vehicles to objectively record the driver’s

interactions (Valero-Mora et al 2013). We argue that much is lost in this process. The

subtleties of ethnographic fieldwork generate a compelling set of rich, contextual data

previously untapped by experimental methodologies that employed similar methods.

The utilitarian relationship drivers had with their cars is just one example of a

finding our ethnographic methodology uncovered in direct contrast to market research

studies investigating the same phenomenon. Student researchers found that drivers had

utilitarian relationships with their cars rather than an emotional attachment. This finding

was revealed through a series of discoveries researchers stumbled upon after gently

prompting participants to answer open-ended questions about the exterior of their own

car. For example one participant mentioned a broken door handle that may have gone

unnoticed from mounted cameras and sensors. In addition, the participant explained

further that the broken door handle had been in that condition for quite some time without

being fixed. Other participants experienced obnoxiously loud engines and dents in the

exterior as trivial annoyances to the functionality of the vehicle. The car’s ability to travel

was the important thing, and this logic was used to put off repairs because they were too

expensive or deemed unnecessary. These findings may challenge current market-studies

that label the car as a significant portion of the American identity. Furthermore, instead of

mounting sensors and video cameras on the car, student researchers actively explored the

exterior and interior of the vehicle themselves, driving along, and empirically

investigating what naturalistic driving studies could not possibly do.

Thus the traditional dichotomy of quantitative versus qualitative did not actually

exist in our research. Instead our study aimed to add substance, focusing on people’s

natural driving habits that could not be reproduced in a lab. This allowed us to add to the

complexity of the Lab’s wealth of experimental data, rendering a more complete picture

of the driving experience. The goal of our project was to include context and social

interaction during research and present the Lab with findings that could not come from

their own methods of data collection. This speaks to the value of ethnography in the high

tech sector and to a greater shift in the business sector for practicing anthropologists. Our

class learned to respond to client needs, preparing the next generation of scholar-

practitioners as adaptable superheroes in the corporate sector and beyond. Research

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cultures will differ for every startup, business, and organization in the field, rendering the

quantitative-qualitative dichotomy one way to describe the difference in methodological

styles, but not necessarily the only way. We as students are already learning how to seek

creative avenues that combine various research methodologies and adapt to different

contexts by extending ethnographic richness to whatever industry in which we may find

ourselves.

In this way anthropological methods have the potential to leave a huge impact on

AV technology and it is precisely the relationship between ethnographic and

experimental methodologies that can catalyze the process. The project we did is only the

first step into a new type of hybridized ethnographic perspective on design, one that

builds on the experiments and methods that engineers have already built. The division

between quantitative and qualitative is an epistemological artifact of an age before

applied anthropology and an age before mixed methods became commonplace. Much like

the engineers setting their sights on a future of automated vehicles, we too must set our

sights on a future of integrating ethnography, not solely qualitative methods into design

research.

The future of AV research The future of AV is not a distant one, in a sense we are no longer designing “the

car of the future” in some science fiction sense; we are designing the car of today. We’ve

already painted a picture of the AV landscape and, in short, AV technology extends far

beyond this research with NRC-SV. So where does that situate applied research, not only

within the scope of AV but of the technology sector as well? How do we need to adapt

ethnography to supplement the experimental paradigm the tech sector has come to rely

on? One of the things we found seemingly most important in our research was easing the

transition into AV technology for people. Not only were we concerned with the

affordances of AV and how they can meet the basic performance requirements of the user

base, but looking into how to make people comfortable with the idea of a car without a

driver.

Exploratory user research can offer quite a bit to both designers and engineers

when it comes to proper prototyping and testing of new products or technologies. AV is a

technology that will fundamentally change the lives of millions of people, so there are

important questions to ask about accessibility and safety. These grey areas have obvious

anthropological considerations because cars are embedded within cultures, which

significantly impacts their use around the world. We really have to ask the question if AV

technology can meet the needs of all of its users within our very own culture. Other

important stakeholders we have to consider are both the internal and external consumers

of AV technology, as end users and as intermediaries, the car companies themselves, and

the industries related to cars that will be influenced by the advancement of AV

technology.

These are all issues we can tackle with applied anthropology, not only

understanding the initial implications of AV, but how the technology itself will impact

society. This initial research opens doors into projects looking at commuters who use

public transit so we can better understand what people may do with the time they would

otherwise spend driving. We can determine the implications AV will have for long haul

freight services and how factories will need to innovate to produce these new vehicles.

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We can look at how cities will have to change the urban landscape to accommodate the

transition to autonomous vehicles. There are many other implications to the existence of

AV technology, much like the introduction of the home computer or the smart phone,

which could fundamentally change the way we live our day-to-day lives. The way people

drive their cars and the overall user experience is critical to understand, but these are by

no means the only aspects of AV that we as anthropologists can or even should take on

with ethnographic study.

Conclusion Mixed methods approaches are the cornerstone of industry research, so much so

that the traditional dichotomy of quantitative and qualitative methods is one that needs to

be expanded upon. While the quantitative-qualitative dichotomy is a reliable, traditional

starting place, research cultures of various industries may demonstrate new dichotomies,

much like the one we identified during our project. In the fluid and innovative high tech

sector, it is a set of interdisciplinary methods that should become the focus of how

anthropology can have an impact on the world of engineering and business. Therefore we

should endeavor to bring ethnography, in as full a sense as we can, into the

varied research cultures applied practitioners find themselves in.

Ethnography is our lens of choice to examine the messy present and explore

issues beyond the fuzzy front-end. Understanding that human behavior is often chaotic in

all of its varying contexts, we need to consider these contexts that extend into our very

own workplaces and research. The project conducted by our design class adapted and

integrated an ethnographic approach to the Lab’s experimental research model. For that

reason we were able to innovate, reinforce, and add valuable, rich information to NRC-

SV’s understanding of the human factors of AV. They had already used surveys

conducted by other groups and tested mockups of dashboard prototypes with people.

What we did differently was what came naturally to us as anthropologists, we went into

our own lab of the real world, and conducted research in the way that we knew how,

ethnographically. All of these experiences have led us to conclude that in order to treat

“Anthropology as a Profession” we must adapt to the myriad of professional worlds, their

distinct research cultures, and aggressively demonstrate the value of ethnographic context

for innovative technological projects.

Acknowledgements

Special thanks to Dr. Christina Wasson and Dr. Brigitte Jordan for making this project

possible and to the entire Design Anthropology Class for working on the project: Cate

Ferman, Chris Ferrell, Marwah Halwani, Hira Hasan, Austin Hartt, Alexandra Hickling,

Jung Kim, Luis Machado, Andy Pottkotter, Molly Shade, Tricia Smith, Amanda

Whatley.

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