Popular scientific abstract
The world of transportation is undergoing a transformation thanks to advancements in automated technology, which promise to reduce road fatalities and improve mobility for both individuals and society. While some autonomous vehicle (AV) technology is already in use on our roads, there has been insufficient consideration given to the human factors involved in AV development. Understanding how humans interact with AVs, both inside and outside the vehicle, is essential for their success and widespread acceptance. Solid knowledge about human factors is crucial throughout the entire AV development process to ensure the safety and trust of users.
However, the recent trend in the automotive industry towards agile development methodologies makes it difficult to incorporate human factors knowledge into requirements. This study aims to investigate how to effectively bring human factors requirements to AV developers in large-scale agile development and provide guidelines and methodologies for doing so.
Who am I?
I am Amna Pir Muhammad, a Ph.D. student at the Chalmers | University of Gothenburg. Currently, I am working under the supervision of Dr. Eric Knauss and Dr. Jonas Bargman on a Marie Skłodowska-Curie Action Innovative Training Network project.
My research focuses on bringing Human Factors (HF) knowledge to AV developers. I believe it is vital to incorporate HF knowledge into AV development to make it more reliable and efficient. Before my Ph.D., I specialized in Software Engineering and worked as a lecturer at the Comsats University of Islamabad.
My passion lies in shaping the relationship between humans and AI-based autonomous systems, particularly in the fields of autonomous vehicle development, large-scale agile development, requirements engineering, and human factors.
Eric Knauss: firstname.lastname@example.org
Jonas Bärgman: email@example.com
Alessia Knauss: firstname.lastname@example.org
Introduction and Motivation
By moving towards eliminating human-driver-caused crashes, automated Vehicles (AVs) promise a number of benefits: fewer accidents, injuries, and deaths, as well as enabling drivers to engage in other activities while in the car [1, 2, 3]. Due to this promise, the automotive industry is currently competing to develop and market AVs with increasing levels of automation , ranging from specific automated functions in Advanced Driver Assistance Systems (ADAS) that can support the driver in the driving task to fully autonomous vehicles that take over all driving tasks—at least under specific conditions (Operational Design Domains; ODDs; )—that do not require supervision. AVs are always software-intense and often rely on artificial intelligence (AI). Consequently, AVs are complex systems that require careful consideration in their design.
On the other hand, in spite of all their benefits, AVs also pose various challenges to humans, such as over-trust and over-reliance, extra workload on humans, or driver engagement and re-engagement [6, 7]. The challenges are not limited to drivers; other road users who interact with AVs will also be affected. Actually, unsafe and non-human-centered interactions between AVs and drivers and other road users can substantially reduce the benefits of AVs, affecting humans both inside and outside the vehicle.
To overcome the issues of managing human factors in vehicle automation (see, e.g.,  for examples of automation failures) and achieve the full potential of automation, human factors researchers strongly advocate considering knowledge about human factors when designing AVs [9, 10, 11]. This field, the study of human factors, involves researching human capabilities and limitations and other human characteristics and applying the findings to the design of systems to improve performance, safety, and comfort .
In order to include human factors when designing automation, researchers recommend incorporating human factors knowledge into the early stages of development [13, 14, 15]. Traditionally such knowledge has been included in system requirements that have been specified up-front and form the foundation of subsequent design work . The process of eliciting, analyzing, documenting, and validating the requirements during the engineering process is called Requirements Engineering (RE) . However, the recent trend in the automotive industry to adopt agile development methodologies changes the role of RE significantly. Agile development methodologies are a collection of approaches based on incremental and iterative development in which self-organizing and cross-functional teams work together to generate requirements and functions . Agile methods aim to deliver faster in less time to market since, due to competition, developers want to deliver faster; they focus on technical details and often neglect others, such as those provided by human factors. Moreover, because agile methodologies do not focus on the processes, RE processes are not well integrated with agile methodologies and face different challenges .
Without a clear role for RE in agile development, there is a risk that introducing human factors knowledge as requirements will be difficult. This risk is increased by the lack of empirical research on how to include human factors knowledge in agile development; practitioners struggle with a lack of clear guidelines.
The main objectives of this research are
- To understand and describe how AI-based AV design can account for human factors (for example, how human comfort-zone boundaries and acceptance can be considered when designing AI-based strategies for AV control)
- To develop methods to incorporate results from studies on acceptance which will improve AI-based AV-designs
- To identify and integrate disparate requirements from AV human factors researchers and designers of AI-based AV control in order to improve road-user acceptance, AV transparency, and vehicle safety
The expected results are:
- Methods and guidelines for incorporating explicit human factors knowledge into AI-based AV designs (requirements)
- Recommendations on how information should be communicated between AV human factors researchers and AI-based AV designers to improve road-user acceptance, AV transparency, and vehicle safety
- Recommendations on how to optimize communication (particularly knowledge transfer) between human factors researcher and AI-based AV designers
- Muhammad, A. P., Knauss, E., Batsaikhan, O., Haskouri, N. E., Lin, Y. C., & Knauss, A. (2022, November). Defining Requirements Strategies in Agile: A Design Science Research Study. In Product-Focused Software Process Improvement: 23rd International Conference, PROFES 2022, Jyväskylä, Finland, November 21–23, 2022, Proceedings (pp. 73-89). Cham: Springer International Publishing.
- Muhammad, A. P. (2022). Managing Human Factors and Requirements in Agile Development of Automated Vehicles: An Exploration (Licentiate dissertation, Chalmers Tekniska Hogskola (Sweden)).
- Heyn, H. M., Knauss, E., Muhammad, A. P., Eriksson, O., Linder, J., Subbiah, P., … & Tungal, S. (2021, May). Requirement engineering challenges for ai-intense systems development. In 2021 IEEE/ACM 1st Workshop on AI Engineering-Software Engineering for AI (WAIN) (pp. 89-96). IEEE.
- Muhammad, A. P. (2021). Methods and Guidelines for Incorporating Human Factors Requirements in Automated Vehicles Development. In REFSQ Workshops.
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