Popular scientific abstract
Integrating automated vehicles (AVs) into the traffic system may contribute to substantial reductions in road-traffic fatalities and injuries while improving mobility. Even though traffic in the future may become fully automated, there will still be vulnerable road users (VRUs) like pedestrians and cyclists interacting with the AVs. We currently lack information on how mixed urban traffic will be affected by the interaction between the different the road users in terms of safety, trust and transparency. The aim of ESR 10: Human machine interfaces (HMIs) on bicycles promoting transparent AV interactions is to investigate whether a device can enhance the communication between cyclists and AVs. Through a series of interviews and surveys, we will identify the cyclists’ needs and preferences for useful HMI modalities that promote safe, transparent and trustworthy AV-cyclist interaction. We will test these HMI devices in virtual and real life traffic. Combined with the research from the other ESRs, the knowledge acquired in this project will help solve the upcoming challenges in traffic and prepare us for the traffic environment of tomorrow.
Who am I?
My name is Siri Hegna Berge, and I have a background in psychology. I have a Master of Philosophy in Psychology degree from the University of Oslo, specializing in human factors and human-computer interaction by studying trust in artificial intelligence during emergency management in my master thesis. After finishing my degree, I have worked as a Research Psychologist at the Institute of Transport Economics, the Norwegian Centre for Transport Research (TØI) at the Department of Safety, Security and Behaviour.
Working on a variety of transport research projects in an inter-disciplinary environment such as TØI has sparked an increased interest in the interaction between humans and technology, and how human factors affect the safety, trust and transparency of this interaction. What I find particularly fascinating is how the interaction between humans and AVs may be enhanced by designing human-machine interfaces (HMIs) from the perspective of vulnerable road users.
The SHAPE-IT project and ESR 10: HMI on bicycle promoting transparent AV interactions, is the perfect opportunity to pursue this research interest further and at the same time, contribute to the safer traffic environment of tomorrow.
My affiliation
My host university is Delft University of Technology (TU Delft), and I work in the TU Delft Faculty of Civil Engineering and Geosciences, at the Department of Transport and Planning.
My supervisors are Prof.dr. Marjan Hagenzieker and Dr.ir Joost de Winter, both at TU Delft.
Background
Increased urbanization and economic globalization paired with a dramatic population growth and a consequently increased impact on the environment call for new and better transport systems. Removing the human driver by integrating AVs into the traffic system may contribute to substantial reductions in road-traffic fatalities and injuries while improving mobility. However, introducing fully automated vehicles into the traffic system may also increase traffic congestion and cause breakdowns of the transport system [1, 2].
AV technology is already being implemented on public roads and highways, and continuously tested in today’s traffic. This generates an increasing amount of knowledge on automation and the development of AVs. However, the perspective of this research is inherently technological- or driver-focused, with insufficient consideration to how humans interact with and influence AVs in traffic.
In line with the unsustainability of today’s transport systems, road users are encouraged to use more active forms of transportation, like walking and cycling [3, 4]. Even though traffic in the future may become fully automated, there will still be vulnerable road users (VRUs) like pedestrians and cyclists interacting with the AVs. We currently lack information on how this mixed urban traffic will be affected by the interaction between the different road users in terms of safety, trust and transparency.
Today, the interaction between road users is determined by factors such as traffic rules and regulations, individual differences, expectations, behavioural adaptation, and informal rules and non-verbal communication [5]. For instance, road users may signalize their intentions by using behavioural cues like facial expressions, hand gestures or eye contact [6]. Other actions, like a reduction in vehicle speed or flashing the headlights may indicate behavioural intentions as well. To further complicate road user interaction, the implicit cues may differ from country to country and culture to culture. External human-machine interfaces (eHMIs) show promise as potential substitutes for human non-verbal communication [6-9]. Still, we are at the very beginning of gathering information about how the AV-VRU interaction will be affected once vehicles become automated and the driver is no longer in the loop.
To ensure the safe and acceptable integration of AVs into tomorrow’s mixed urban traffic environments, we need insight on the interaction between road users such as AVs, pedestrians and cyclists. The knowledge generated by SHAPE-IT is our contribution to help solve the upcoming challenges and prepare us for the traffic environment of tomorrow.
Aims and objectives
In ESR 10, we will investigate the possibility of a device (an HMI) that helps cyclists communicate with AVs. The aim of the project is to facilitate transparent, trustworthy interactions between cyclists and AVs, and in turn, improve the safety of not just the people inside the vehicles, but the road users outside as well.
The objectives of the research are to:
- Establish how on-bike devices can enhance communication from AVs to cyclists.
- Establish what modalities are useful for on-bicycle HMIs, and how the HMIs interact with the cyclist.
- Ensure that the HMI system can incorporate communication from infrastructure, such as traffic lights and other I2X functionalities.
- Evaluate cyclists’ trust and acceptance of HMIs across different biker characteristics (e.g. age, gender, and personality).
Research description
To establish the best way to approach the project objectives, we will start by doing a series of interviews with cyclists. The interviews are exploratory and will have a varied sample of cyclists to explore and compare the needs and preferences for traffic interaction with traditional motorized vehicles as well as AVs, within a broad spectrum of cyclist characteristics. The overall objective of the interviews is to investigate what modalities are useful for on-bike HMIs when the goal is to enhance AV-cyclist interaction in terms of safety, trust and transparency.
The focus of the interviews will be to generate knowledge on:
- Road user interaction from the cyclist’s perspective, both in current traffic and in future scenarios with AVs.
- Improving the perceived safety of cyclists in mixed urban traffic.
- The information cyclists and AVs will need to sufficiently communicate with each other.
- HMI functionality for cyclists in mixed urban traffic.
- On-bike HMI prototypes.
The interviews will lay basis for future project experiments and field tests with cyclists, HMIs and AVs.
In addition to the interviews, we will perform a literature review to gain further insight on the field of AV-cyclist interaction, trust and acceptance of HMIs across biker characteristics such as age, gender, personality and attitude towards technology. Taken together, the interviews and literature review will uncover potential research gaps needed to be addressed, as well as make up a sound foundation for further research on on-bike HMIs in this PhD project. Based on the interviews and present literature, the plan is that ESR 10 will involve a series of real life experiments testing HMI prototypes. Due to the transnational challenges created by the COVID-19 situation, we may not be able to perform experiments with in-person participants until the later stages of the project. In the meantime, we plan on doing an experimental crowdsourcing survey testing the findings from the interviews and literature. This experimental survey is yet to be determined.
Results
During the course of this project, we expect to find:
- Which needs and preferences should be given priority in the design process of an HMI for cyclists.
- The factors that affect AV-cyclist interaction and how these factors can be incorporated into an HMI.
- Measures to improve the safety of cyclists in AV-cyclist interaction.
- In the context of AV-cyclist interaction; the most functional HMI modality.
- The HMI prototype most preferred by cyclists.
- Scenarios suitable for testing on-bike HMIs.
My publications
To come…
References and links
1. Nenseth, V., A. Ciccone, and N.B. Kristensen. (2019). Societal Consequences of Automated Vehicles–Norwegian Scenarios (1700/2019). Institute of Transport Economics. Retrieved from https://www.toi.no/getfile.php?mmfileid=50576
2. Kellett, J., et al. (2019, 2019/10/02). How Might Autonomous Vehicles Impact the City? The Case of Commuting to Central Adelaide. Urban Policy and Research, 37(4), 442-457. https://doi.org/10.1080/08111146.2019.1674646
3. POLIS. (2014). Securing the benefits of active travel in Europe: Position paper of the POLIS environment & health in transport working group. Retrieved 16th of June 2020 from https://www.polisnetwork.eu/wp-content/uploads/2019/06/polis-paper-health-and-transport_final-3-dec.pdf
4. Centers for Disease Control and Prevention. (2011). Strategies: Promote Active Transportation. Retried 16th of June 2020 from https://www.cdc.gov/healthyplaces/transportation/promote_strategy.htm
5. Vissers, L.K., et al. (2017). Safe interaction between cyclists, pedestrians and automated vehicles: what do we know and what do we need to know? SWOV. Retrieved from https://library.swov.nl/action/front/cardweb?id=131121
6. Rouchitsas, A. and H. Alm. (2019). External Human–Machine Interfaces for Autonomous Vehicle-to-Pedestrian Communication: A Review of Empirical Work. Frontiers in psychology, 10. https://doi.org/10.3389/fpsyg.2019.02757
7. De Clercq, K., et al. (2019). External human-machine interfaces on automated vehicles: effects on pedestrian crossing decisions. Human factors, 61(8), 1353-1370. https://doi.org/10.1177/0018720819836343
8. Mahadevan, K., S. Somanath, and E. Sharlin. Communicating awareness and intent in autonomous vehicle-pedestrian interaction. in Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. 2018.
9. Habibovic, A., et al. (2018). Communicating intent of automated vehicles to pedestrians. Frontiers in psychology, 9, 1336. https://doi.org/10.3389/fpsyg.2018.01336