ESR8 – Human Factors in AI-based Automation Design

Popular scientific abstract

The recent advancements in Automated transport game-changers – for society as well as for individuals, promising the reductions in road fatalities while improving the mobility. Some of the Autonomous Vehicle technology is already rolling out on the roads, but the processes of AV development is primarily “technology-focussed” and insufficient consideration has been given to human factors. However, understanding humans and how they interact with AVs both inside and outside the vehicle is central for success. It will be the deciding factor in whether AVs will be used and accepted.  When developing AVs, solid knowledge about human factors throughout the developing organization is crucial to ensure safety and trust of humans. My topic of research is “Human factors In AI-Based Automation Design” and the focus is on how to make engineers developing AVs understand human factors requirements:

  • To understand and describe how AI-based AV design can account for human factors.

To provide guidelines on what and in which way human factors knowledge should be communicated to AV designers.

My affiliation

Supervisors email:

Eric Knauss:               

Jonas Bärgman:            


Autonomous Vehicles (AV) are expected to bring considerable benefits to society, such as traffic optimization and accidents reduction. They rely heavily on advances in many Artificial Intelligence (AI) approaches and techniques. However, while some researchers in this field believe AI is the core element to enhance safety, others believe AI imposes new challenges to assure the safety of these new AI-based systems and applications [1]. Peter Hancock issued a stark warning to the field of human factors that attention must be focused on the appropriate design of a new class of technology: highly autonomous systems. He further argued that while development of these new systems is proceeding at breakneck speed by practitioners, the study of the psychological and human factors implications might be ignored. [2]

Catherine argued that human factors as a discipline is not keeping up with the pace of technological change. Human factors researchers must rapidly embrace the development of richer automation models, more complex laboratory studies, and naturalistic studies in the field to generate relevant insights into human automation interaction [3].

As human road users have established elaborated interaction strategies to coordinate their actions among each other, one challenge that human factors experts and vehicle designers are facing today is how to design AVs in a way that they can safely and intuitively interact with other traffic participants [4].

Our preliminary work shows that engineers don’t have enough Input from HF or there is not really an infrastructure to use knowledge of HF and from literature we know such gaps can be problematic. So we think that something so impactful such as AD need to find a more structured way to connect these areas.

Aims and objectives

The main objectives of this research are

  1. 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)
  2. To develop methods to incorporate results from studies on acceptance which will improve AI-based AV-designs
  3. 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

Research description

My research topic is “Human Factors in AI-based Automation Design”. The goal of my research is to develop design guidelines ensuring, in an urban environment, that the interfaces between the AV and its users are transparent—so AV users know the AV’s capabilities and limitations. My research aims to   study how transparency and acceptance can be considered integral to the development of AVs based on AIs, and ultimately providing guidelines for incorporating human factors into AI-based AV design guidelines. Ultimately we want to build a bridge to integrate knowledge about human factors into AI-based AV designs.


The expected results are:

  1. Methods and guidelines for incorporating explicit human factors knowledge into AI-based AV designs (requirements)
  2. Recommendations on what 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

My publications

To come…

References and links

  • Alexandre Moreira Nascimento, Lucio Flavio Vismari , Caroline Bianca Santos Tancredi Molina, Paulo Sergio Cugnasca, João Batista Camargo, Jr. , Member, IEEE, Jorge Rady de Almeida, Jr., Rafia Inam, Elena Fersman, Maria Valeria Marquezini, and Alberto Yukinobu Hata. A Systematic Literature Review About the Impact of Artificial Intelligence on Autonomous Vehicle Safety. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2019)
  • Hancock, P. A. 2017. “Imposing Limits on Autonomous Systems.” Ergonomics 60 (2): 284–291.
  • Ergonomics 60 (2): 284–291.Catherine M. Burns. Automation and the Human Factors Race to Catch Up, Journal of Cognitive Engineering and Decision Making 201X, Volume XX, Number X, Month 2017, pp. 1–3 DOI: 10.1177/1555343417724975
  • Anna Schieben, Marc Wilbrink, Carmen Kettwich, Ruth Madigan, Tyron Louw, Natasha Merat. Designing the interaction of automated vehicles with other traffic participants: design considerations based on human needs and expectations. Cognition, Technology & Work (2017)