=Paper=
{{Paper
|id=Vol-2857/ds_paper1
|storemode=property
|title=Methods and Guidelines for Incorporating Human Factors Requirements in Automated Vehicles Development
|pdfUrl=https://ceur-ws.org/Vol-2857/ds1.pdf
|volume=Vol-2857
|authors=Amna Pir Muhammad
|dblpUrl=https://dblp.org/rec/conf/refsq/Muhammad21
}}
==Methods and Guidelines for Incorporating Human Factors Requirements in Automated Vehicles Development==
https://ceur-ws.org/Vol-2857/ds1.pdf
Methods and Guidelines for Incorporating Human
Factors Requirements in Automated Vehicles
Development
Amna Pir Muhammad
Dept. of Computer Science and Engineering
Chalmers | University of Gothenburg
Gothenburg, Sweden
Abstract
Automated vehicles (AV) are transforming the future of the transportation and improving the quality
of life. However, due to their societal impact in urban environments, AV development challenges the
current development process. Particularly, it is unclear how human factors requirements can be com-
municated to developers of AI-based AV. It is quite challenging especially in agile development, where
the focus is on continuous deployment and rapid release cycles with short lead-times.
Due to the importance of human factors and its impact on trust, acceptance, and safety of AV in
urban environments, my work aims at providing a suitable requirements engineering perspective and
method.
Keywords
Requirements Engineering, Autonomous Vehicles, AI systems, Human Factors
1. Introduction
Automated vehicles (AV) can improve the safety and reduce the number of accidents. Today, an
increasing number of automated vehicles are already on the roads [1], and it is expected that by
2045 half of new cars will be autonomous [2]. Many of the features up to SEA level 3 [3] are
already operational. Examples include lane changing [4], adaptive cruise control (ACC) [5], and
to some extent car parking [6].
But with the increasing number of AV, many researchers [7, 8, 9] are worried about neglecting
human factors while designing automated systems. Human factors is a discipline that considers
the physical, physiological and cognitive behavior of humans and apply this information to the
design, operation and use of the products for increasing human interaction with the systems by
improving human safety, performance and/or satisfaction[10].
These researchers [7, 8, 9] believe that automation brings not only benefits, but also potential
disadvantages. Moreover, humans can also mis-use and eventually mislead the technology. To
In: F.B. Aydemir, C. Gralha, S. Abualhaija, T. Breaux, M. Daneva, N. Ernst, A. Ferrari, X. Franch, S. Ghanavati, E.
Groen, R. Guizzardi, J. Guo, A. Herrmann, J. Horkoff, P. Mennig, E. Paja, A. Perini, N. Seyff, A. Susi, A. Vogelsang
(eds.): Joint Proceedings of REFSQ-2021 Workshops, OpenRE, Posters and Tools Track, and Doctoral Symposium, Essen,
Germany, 12-04-2021
" amnap@chalmers.se (A. P. Muhammad)
© 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
Workshop
Proceedings
http://ceur-ws.org
ISSN 1613-0073
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cope with these issues of AV technology, human factors must play an important role throughout
the engineering and development life cycle of AV, yet it is unclear how human factors perspective
can be communicated to AV engineers.
Human factors requirements are important to consider in many scenarios. Such as for the
communication between pedestrians and AV,
to build and enhance the safety [11] and trust, [12] driving performance and [13] driver’s
interaction with AV [14].
But the human factors field has not evolved with the pace of AV technology and remains
poorly understood in design and development of automated driving systems [15]. Particularly,
while adopting agile development methodology, software teams aim to shorten time-to-market,
and tend to focus on the technical perspective and neglect human factors aspects.
My studies aim to investigate and suggest how to resolve the communication challenges
between human factors requirements with the AV engineers. To do so, we have started with a
qualitative study. The rest of the paper is divided into seven sections. In Section 2, we depict
the problem, whereas, Section 3 presents the relevance. Section 4 and 5 illustrates proposed
solution and novelty of the topic respectively. Section 6 provides research methods and Section
7 describes the progress. Finally, the last Section concludes the work.
2. Problem Statement
Human factors skills are used to collect real world data and manage this data for each feature
(how do people deal with these vehicles, when do they turn off and on different features). But
currently, instead of collecting such requirements (user’s behavior) directly, AV developers are
using more data-driven techniques, due to the challenge of short time frame.
Requirements communication is very challenging, agility has added even more complexity to
that. The processes for requirements engineering are better explored for traditional development.
Traditionally, most of the requirements in most setups were communicated through proper
documentation. Now its quite challenging particularly in large scale agile development.
It is difficult to communicate requirements in agile development because there is no clearly
defined requirements communication method. It is different across various organizational
cultures. Because in agile development, developers are using just-in-time requirements and
there is no traditional documented requirements given to them. It is more difficult because in
some scenarios it is less about handing over requirements, but instead being there for discussion
of the concepts.
Human factors experts play an important role to describe and discuss concepts related to
human behavior. They need to communicate with engineers to point out the user expectations
before the development, to guide developers during the development and to validate the product
in the end with human factors knowledge. But with agility and being not in a development
team, causes a big challenge for human factors requirements communication. Since the lead
time to release new functions needs to decrease, developers are much focused on technical
requirements.
Thus our problem statement is: to integrate human factors requirements in the agile develop-
ment of AI-based AV.
3. Relevance
AV developers are usually concerned with improving the technology. For example, early AV
keep the car exactly in the center of a lane. But when overtaking a truck, humans would prefer
to leave a bit more space. Understanding such problems are crucial and also difficult. Human
factors experts are aware of such aspects and could help defining such requirements.
These requirements are very important to increase the system trust, acceptance and safety:
Trust leads to acceptance, acceptance leads to safety (since automated safety features are not
deactivated or overridden). To achieve this we need to understand the humans, their behavior,
how they would react in certain scenarios and what they expect from the system in certain
situations.
For instance, to communicate with pedestrian, human factors requirements provide guidelines
about communication strategies. A report [16] shows that currently people would not feel safe
while crossing AV because they do not trust when they do not see any driver on the driving
seat.
On the other hand, for requirements elicitation, engineers are also using statistics to under-
stand specific driver behavior. Sometimes with the availability of large data sets, it seems that
we know how humans will react under certain conditions but in reality, it is not always in a
way we anticipate. People can possibly behave in strange ways, which a particular set of data
fails to comprehend. Therefore, to ensure the success of the system, we need to determine the
right system behavior in situations where a person is doing something unexpected. To define
such system behavior we need a good requirements process. Our preliminary research shows
that today, we are not yet very good at managing such requirements efficiently.
4. Solution
For enabling continuous deployment, automotive companies have initiated working on vehicles
using agile approaches. But it is hard to systematically describe the requirements for agile
system development [17]. This is particularly true for AI parts, due to their inductive training
nature.
In summary, it is very difficult for human factors experts to communicate their knowledge
as requirements to developers. One solution could be, to modify agile interventions [18] to
address human factors aspects or to include human factors experts in development teams. But
given the shortage on human factors experts in the field, there is no defined procedure about
how and where the human factors should be optimally placed in the team or how to train the
agile teams so that they can learn and include the human factors aspects during development.
Therefore, the first step is to come up with a solution about where we can properly introduce
human factors in AV development cycle.
We need to address and integrate human factors knowledge throughout the agile AV devel-
opment cycle for continuous software development. Aiming to propose a framework for agile
teams to provide guidelines to include human factors knowledge and define their roles and re-
sponsibilities during AV development. A framework that allows engineers (AI/SE/Automotive)
to leverage human factors perspective when building AI intense systems, to facilitate the
understanding, communication and V&V of human factors requirements.
5. Novelty
Requirements engineering focuses much on socio-technical requirements, but human factors
knowledge also considers other aspects such as distractions and behaviors which are important
to consider for the successful deployment of AV. For example, consider there is a driver in AV
and the control lies with AV. As AV is in control, the driver can be relaxed and therefore can
be distracted by other things or she might feel sleepy. We are also aware of the fact that AV
still require intervention of human driver. Because of this, we have driver monitoring system
(DMS). Hence, if the DMS functionality detects that the driver is distracted or sleepy, then how
should it behave? Such kind of requirements are provided by human factors experts. I notice
that human factors relate to the most difficult requirements, those which are tacit and users
would not be able to describe them in their own words.
Many researchers are performing research on different perspectives of human factors in AV
development. For example, Merat et al. [19] conduct a study on communication procedure
between vehicles and other objects without human to human correspondence. Schoettle and
Sivak [20] present a study about peoples acceptance of AV, it has reported that as the level of
automation increases, peoples’ acceptance of AV decreases. Van Maanen et.al. [21] discuss
how human factors can be integrated in AI for the better human machine cooperation (HMC).
Chen et al,[22] also present a model for AV transparency considering AI and humans as integral
part. Kirsten [23] developed a method for interface design to include human factors before the
system development.
In summary, the gap between human factors and design or development of automated
vehicles has also been identified in research. But it is unclear how HF knowledge can be
included throughout the development life cycle of AV.
6. Research Method
Within the interdisciplinary research environment of this work, we will use a mixture of research
methods.
The goal of my PhD studies is to create a method to bridge the communication gap between
human factors experts, requirements engineers, and AV developers to communicate human
factors requirements.
In our first study, we interviewed 10 professionals including both human factors experts and
AV engineers. We did a qualitative analysis on these semi-structured interviews and address
the following research questions in context of AV development:
1. Definition of human factors in relation to agile.
2. Properties of human factors and agile.
3. Implications for agile developers.
4. Implications for human factors.
5. Implications for requirements.
Based on this interview study, we formulated the problem statement for the design science
research.
During the course of my doctoral studies, I have two secondments: one in automotive
company and one at another university. These secondments will support my research. While
working in an automotive company (which work with agile development of AV), I will analyse
the problem in practice. I will then attempt to build a solution based on a literature review as
well as discussions with practitioners to solve the problem. I aim to re-evaluate and iterate the
process if required. Overall, I am planning to use the design science research method, and to
conduct several studies in accordance to this method. I aim to evaluate a proposed methodology
for including HF knowledge in AV engineering through a case study at an automotive company,
in which I will use interviews or a questionnaire to collect data.
My purpose of visiting another university is to work on the concept in detail and to ensure
its usefulness for human factors experts and researchers.
Within the design science research framework, we may use other research methods to support
the study such as surveys and case studies.
7. Progress
Within the broad topic of reducing the communication gap between human factors experts and
AV developers in agile development, our first study particularly focused on discovering how
human factors knowledge can be captured as requirements in agile development.
Our findings present several challenges and implications for agile developers, requirements
engineers and for human factors experts, who are engaged in AV development.
While addressing research question one, it was observed that everyone has different human
factors definition depending upon different aspects, particularly in the context of AV develop-
ment. But it could be problematic, while communicating human factors requirements to others.
So it is important to have one common understanding of basic concepts. That is why, we have
synthesized one definition of human factors for AV development, considering our interviewees
perspective and established a definitions of human factors.
Here, we provide an overview of our findings for above mentioned research questions 2-5.
We have found properties of human factors and agile methods in AV development. Properties of
agile methods are highlighted as iterative nature and responsiveness to changing requirements.
Further, agile methods shift responsibility to autonomous teams, which often dislike static,
detailed requirements. Instead, they prefer to explore requirements just-in-time by themselves.
We find that both agile methods and human factors focus on quality in use. We learned that to
remove the communication gap of human factors requirements with AV developers, it would be
desirable to have a human factors expert in each team. Human factors experts then can provide
the basic knowledge related to human factors requirements and guide developers in which
direction to look for system test and experiments. We believe that requirements engineering can
support this by managing the knowledge gained from experiments effectively and by expressing
design decisions in relation to human factors requirements in system requirements.
With this qualitative study being almost concluded, we will now focus on the secondment
with the industry partner next.
8. Conclusion
Due to the agile development and fast increments, it is unclear how human factors fit into
the current practice of AV development. We need to develop a strong setup with protocols
where we can support an environment for human factors’ experiments and user-studies, so that
developers can actually create knowledge and data with good reliability when needed for their
design decisions. We expect that such a setup can provide a good conceptual framework that
guides engineers in all relevant disciplines on how to manage human factors knowledge and to
balance the role of human factors for AV development in scaled-agile setups.
Acknowledgement
I would like to extend my gratitude to my supervisors Eric Knauss and Jonas Bärgmann for
their patient guidance, encouragement and throughout advice. I am extremely lucky to have
these people as my torch bearers. I am also very much thankful to my mentor Alessia Knauss
for overall counselling and recommendations.
This SHAPE-IT project has received funding from the European Union’s Horizon 2020
research and innovation program under the Marie Skłodowska-Curie grant agreement 860410.
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