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  • 1.
    Fabricius, Victor
    Halmstad University, School of Information Technology. RISE Research Institutes of Sweden, Gothenburg, Sweden.
    Exploring Road Traffic Interactions Between Highly Automated Vehicles and Vulnerable Road Users2023Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Understandings of road traffic interactions are largely based on human-human interactions. However, the development of vehicles controlled by highly auto- mated driving systems (ADS) would introduce a radically novel type of road user. This compilation thesis explores encounters between these “autonomous vehicles” (AVs) and human vulnerable road users (VRUs) such as pedestrians and cyclists. The included publications are connected to three research questions. First, empirical studies are reviewed to highlight existing interactive be- haviors and communication cues. This is followed by a methodological question of how to investigate AV-VRU interactions. Finally, VRUs’ experiences from initial experiments on AV crossing encounters are presented.

    While road user trajectories and kinematic behaviors are viewed as primary mechanisms to facilitate traffic interactions, they might also be influenced by cues such as appearances, gestures, eye-gaze, and external human-machine interfaces (eHMI). Using the Wizard-of-Oz approach, we are able to explore VRU encounters with a seemingly highly automated vehicle. Compared to meeting an attentive driver, AV encounters resulted in a reported lower willingness to cross, lower perceived safety, and less calm emotional state, indicating that the absence of driver-centric cues could lead to interaction issues and impede acceptance of AVs. To further explore this, we included light-based eHMI to signal the driving mode and intent of the vehicle (e.g., intent to yield). Future research should continue to investigate how AVs may co-exist with human road users focusing on aspects such as behavioral adaptations, research methodologies, and the role of various eHMI.

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    Licentiate Thesis Summary
  • 2.
    Fabricius, Victor
    et al.
    Halmstad University, School of Information Technology. RISE Research Institutes of Sweden, Gothenburg, Sweden.
    Habibovic, Azra
    Scania CV AB, Södertälje, Sweden.
    Rizgary, Daban
    RISE Research Institutes of Sweden, Gothenburg, Sweden.
    Andersson, Jonas
    RISE Research Institutes of Sweden, Gothenburg, Sweden.
    Wärnestål, Pontus
    Halmstad University, School of Information Technology.
    Interactions Between Heavy Trucks and Vulnerable Road Users – A Systematic Review to Inform the Interactive Capabilities of Highly Automated Trucks2022In: Frontiers in Robotics and AI, E-ISSN 2296-9144, Vol. 9, article id 818019Article in journal (Refereed)
    Abstract [en]

    This study investigates interactive behaviors and communication cues of heavy goods vehicles (HGVs) and vulnerable road users (VRUs) such as pedestrians and cyclists as a means of informing the interactive capabilities of highly automated HGVs. Following a general framing of road traffic interaction, we conducted a systematic literature review of empirical HGV-VRU studies found through the databases Scopus, ScienceDirect and TRID. We extracted reports of interactive road user behaviors and communication cues from 19 eligible studies and categorized these into two groups: 1) the associated communication channel/mechanism (e.g., nonverbal behavior), and 2) the type of communication cue (implicit/explicit). We found the following interactive behaviors and communication cues: 1) vehicle-centric (e.g., HGV as a larger vehicle, adapting trajectory, position relative to the VRU, timing of acceleration to pass the VRU, displaying information via human-machine interface), 2) driver-centric (e.g., professional driver, present inside/outside the cabin, eye-gaze behavior), and 3) VRU-centric (e.g., racer cyclist, adapting trajectory, position relative to the HGV, proximity to other VRUs, eye-gaze behavior). These cues are predominantly based on road user trajectories and movements (i.e., kinesics/proxemics nonverbal behavior) forming implicit communication, which indicates that this is the primary mechanism for HGV-VRU interactions. However, there are also reports of more explicit cues such as cyclists waving to say thanks, the use of turning indicators, or new types of external human-machine interfaces (eHMI). Compared to corresponding scenarios with light vehicles, HGV-VRU interaction patterns are to a high extent formed by the HGV’s size, shape and weight. For example, this can cause VRUs to feel less safe, drivers to seek to avoid unnecessary decelerations and accelerations, or lead to strategic behaviors due to larger blind-spots. Based on these findings, it is likely that road user trajectories and kinematic behaviors will form the basis for communication also for highly automated HGV-VRU interaction. However, it might also be beneficial to use additional eHMI to compensate for the loss of more social driver-centric cues or to signal other types of information. While controlled experiments can be used to gather such initial insights, deeper understanding of highly automated HGV-VRU interactions will also require naturalistic studies. © 2022 Fabricius, Habibovic, Rizgary, Andersson and Wärnestål.

  • 3.
    Habibovic, Azra
    et al.
    RISE Research Institutes of Sweden, Gothenburg, Sweden.
    Malmsten Lundgren, Victor
    RISE Research Institutes of Sweden, Gothenburg, Sweden.
    Andersson, Jonas
    RISE Research Institutes of Sweden, Gothenburg, Sweden.
    Klingegård, Maria
    RISE Research Institutes of Sweden, Gothenburg, Sweden.
    Lagström, Tobias
    RISE Research Institutes of Sweden, Gothenburg, Sweden.
    Sirkka, Anna
    RISE Research Institutes of Sweden, Gothenburg, Sweden.
    Fagerlönn, Johan
    RISE Research Institutes of Sweden, Gothenburg, Sweden.
    Edgren, Claes
    Volvo Cars Group, Gothenburg, Sweden.
    Fredriksson, Rikard
    Autoliv AB, Vårgårda, Sweden.
    Krupenia, Stas
    Scania AB, Södertälje, Sweden.
    Saluäär, Dennis
    Volvo Group AB, Gothenburg, Sweden.
    Larsson, Pontus
    Volvo Group AB, Gothenburg, Sweden.
    Communicating Intent of Automated Vehicles to Pedestrians2018In: Frontiers in Psychology, E-ISSN 1664-1078, Vol. 9, article id 1336Article in journal (Refereed)
    Abstract [en]

    While traffic signals, signs, and road markings provide explicit guidelines for those operating in and around the roadways, some decisions, such as determinations of "who will go first," are made by implicit negotiations between road users. In such situations, pedestrians are today often dependent on cues in drivers' behavior such as eye contact, postures, and gestures. With the introduction of more automated functions and the transfer of control from the driver to the vehicle, pedestrians cannot rely on such non-verbal cues anymore. To study how the interaction between pedestrians and automated vehicles (AVs) might look like in the future, and how this might be affected if AVs were to communicate their intent to pedestrians, we designed an external vehicle interface called automated vehicle interaction principle (AVIP) that communicates vehicles' mode and intent to pedestrians. The interaction was explored in two experiments using a Wizard of Oz approach to simulate automated driving. The first experiment was carried out at a zebra crossing and involved nine pedestrians. While it focused mainly on assessing the usability of the interface, it also revealed initial indications related to pedestrians' emotions and perceived safety when encountering an AV with/without the interface. The second experiment was carried out in a parking lot and involved 24 pedestrians, which enabled a more detailed assessment of pedestrians' perceived safety when encountering an AV, both with and without the interface. For comparison purposes, these pedestrians also encountered a conventional vehicle. After a short training course, the interface was deemed easy for the pedestrians to interpret. The pedestrians stated that they felt significantly less safe when they encountered the AV without the interface, compared to the conventional vehicle and the AV with the interface. This suggests that the interface could contribute to a positive experience and improved perceived safety in pedestrian encounters with AVs - something that might be important for general acceptance of AVs. As such, this topic should be further investigated in future studies involving a larger sample and more dynamic conditions. © 2018 Habibovic, Malmsten Lundgren, Andersson, Klingegård, Lagström, Sirkka, Fagerlönn, Edgren, Fredriksson, Krupenia, Saluäär and Larsson.

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  • 4.
    Malmsten Lundgren, Victor
    et al.
    Viktoria Swedish ICT, Gothenburg, Sweden.
    Habibovic, Azra
    Viktoria Swedish ICT, Gothenburg, Sweden.
    Andersson, Jonas
    Viktoria Swedish ICT, Gothenburg, Sweden.
    Lagström, Tobias
    Viktoria Swedish ICT, Gothenburg, Sweden.
    Nilsson, Maria
    Viktoria Swedish ICT, Gothenburg, Sweden.
    Sirkka, Anna
    Interactive Institute Swedish ICT, Piteå, Sweden.
    Fagerlönn, Johan
    Interactive Institute Swedish ICT, Piteå, Sweden.
    Fredriksson, Rikard
    Autoliv Research, Vårgårda, Sweden.
    Edgren, Claes
    Volvo Car Corporation, Gothenburg, Sweden.
    Krupenia, Stas
    Scania CV AB, Södertälje, Sweden.
    Saluäär, Dennis
    Volvo Group AB, Gothenburg, Sweden.
    Will There Be New Communication Needs When Introducing Automated Vehicles to the Urban Context?2017In: Advances in Human Aspects of Transportation: Proceedings of the AHFE 2016 International Conference on Human Factors in Transportation, July 27-31, 2016, Walt Disney World®, Florida, USA / [ed] Stanton, Neville A.; Landry, Steven; Di Bucchianico, Giuseppe; Vallicelli, Andrea, Cham: Springer, 2017, Vol. 484, p. 485-497Conference paper (Refereed)
    Abstract [en]

    In today’s encounters with vehicles, pedestrians are often dependent on cues in drivers’ behavior such as eye contact, postures, and gestures. With an increased level of automation, and the transfer of control from the driver to the vehicle, the pedestrians cannot rely on such cues anymore. The question is: will there be new communication needs to warrant safe interactions with automated vehicles? This question is addressed by exploring pedestrians’ willingness to cross the street and their emotional state in encounters with a seemingly automated vehicle. The results show that pedestrians’ willingness to cross the street decrease with an inattentive driver. Eye contact with the driver on the other hand leads to calm interaction between vehicle and pedestrian. In conclusion, to sustain perceived safety when eye contact is discarded due to vehicle automation, it could be beneficial to provide pedestrians with the corresponding information in some other way (e.g., by means of an external vehicle interface). © Springer International Publishing Switzerland 2017.

  • 5.
    Habibovic, Azra
    et al.
    Viktoria Swedish ICT, Gothenburg, Sweden; SAFER, Vehicle and Traffic Safety Centre at Chalmers, Gothenburg, Sweden.
    Andersson, Jonas
    Viktoria Swedish ICT, Gothenburg, Sweden; SAFER, Vehicle and Traffic Safety Centre at Chalmers, Gothenburg, Sweden.
    Nilsson, Magnus
    Viktoria Swedish ICT, Gothenburg, Sweden; SAFER, Vehicle and Traffic Safety Centre at Chalmers, Gothenburg, Sweden.
    Malmsten Lundgren, Victor
    Viktoria Swedish ICT, Gothenburg, Sweden; SAFER, Vehicle and Traffic Safety Centre at Chalmers, Gothenburg, Sweden.
    Nilsson, Jan
    Semcon Sweden AB, Gothenburg, Sweden.
    Evaluating interactions with non-existing automated vehicles: three Wizard of Oz approaches2016In: 2016 IEEE Intelligent Vehicles Symposium (IV): 19-22 June 2016, Piscataway, NJ: IEEE, 2016, p. 32-37, article id 7535360Conference paper (Refereed)
    Abstract [en]

    Highly automated test vehicles are rare today, and (independent) researchers have often limited access to them. Also, developing fully functioning system prototypes is time and effort consuming. In this paper, we present three adaptions of the Wizard of Oz technique as a means of gathering data about interactions with highly automated vehicles in early development phases. Two of them address interactions between drivers and highly automated vehicles, while the third one is adapted to address interactions between pedestrians and highly automated vehicles. The focus is on the experimental methodology adaptations and our lessons learned. © 2016 IEEE.

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