The advent of self-driving cars has sparked discussions about eye contact in traffic, particularly due to challenges that automated vehicles face in non-verbal communication with human road users. In his 1992 book, Turn Signals Are The Facial Expressions Of Automobiles, Don Norman describes how drivers in Mexico City deliberately avoid eye contact when entering a roundabout to create uncertainty in the minds of other drivers, leading the latter to yield right of way. Norman argued that such manipulative or aggressive behavior would not be tolerated in the United States. In the present study, we tested these claims through an online survey involving 3,857 respondents from 20 countries. The results confirmed that Mexican drivers reported a higher frequency of non-speeding ‘aggressive’ violations compared to those from most other countries. Regarding eye contact in the roundabout scenario presented in the survey, national differences were found not so much in the frequency of eye contact but in the reasons behind its use. Mexican drivers tended to avoid eye contact to reduce tension or avoid conflict with other drivers. However, they also frequently reported making eye contact to assert or subtly enforce their right of way. In higher-income countries like the United States, driver-driver eye contact is often deemed unnecessary. In conclusion, our findings partially correspond with Norman's anecdote based on his experiences in 1950s Mexico City. These results may have implications for understanding the stability of traffic cultures and the challenges related to eye contact and non-verbal communication faced by developers of automated vehicles.

@en

A large number of traffic accidents occur worldwide each year, of which a sizable portion involve pedestrians, making them a vulnerable group on the road. Many of these accidents occur due to visual distraction, meaning drivers and pedestrians fail to look where they should be looking. In addition to this tendency for distraction, the eyes are a means of exchanging information between road users, via behaviors such as eye contact. However, the role and importance of eye contact in traffic in connection with traffic safety and the decisions of road users is not yet entirely clear. Further, with the advent of automated vehicles, the role of eye contact in traffic may change or disappear altogether, due to the absence of drivers. One promising way to shed light on this matter is to use eye-tracking, a technology which can measure the eye movements of road users, and which might allow the engineering of solutions to mitigate the frequency and severity of accidents.

This dissertation aims to investigate the role of eye contact between drivers and pedestrians, as well as its influence on pedestrians’ road crossing intentions. Another aim of this dissertation is to assess the accuracy of eye-tracking devices and to objectively detect and operationalize driver-pedestrian eye contact using eye-tracking. Finally, this thesis aims to develop safety systems based on eye-tracking that can automatically analyze and contextualize gaze in traffic and warn vulnerable road users of danger. This thesis consists of four independently readable and empirical research papers.

The first study examines the effect of drivers’ eye contact on pedestrians’ crossing decisions using an online crowdsourced experiment. It shows that, although a car’s kinematics have a dominant effect, a driver’s eye contact also makes pedestrians feel safer and more likely to cross the road, and that the timing of the driver’s eye contact has an influence as well. The second study benchmarks the accuracies of mobile eye-trackers under static and dynamic conditions, finding that eccentricity worsens accuracy, but dynamicity does not necessarily worsen it. The third study presents a method to objectively detect and operationalize driver-pedestrian eye contact using two synchronized eye-trackers and computer vision, defining eye contact as mutual gaze within a 4° threshold. The fourth study explores the integration of mobile eye-tracking, object detection, and a vision-language model in an attempt to develop a real-time, context-aware safety system that can assess risk in traffic and enhance the situational awareness of road users.

This dissertation concludes that while eye contact is neither as powerful a cue as kinematics nor essential for crossing, it is still a “should-have” in driver-pedestrian interactions as it can increase perceived safety and willingness to cross. This thesis also concludes that certain types of external Human Machine Interfaces (eHMIs) – substitutes for the missing eye contact between pedestrians and automated vehicles – would be beneficial to maintain existing levels of comfort in interactions. Finally, this thesis also highlights the potential of using mobile eye-tracking in combination with computer vision and AI for applications in the traffic, manufacturing, medical, education, and other domains, and recommends topics for further research into eye contact and eye-tracking.
@en

Over the past few decades, there have been significant developments in eye-tracking technology, particularly in the domain of mobile, head-mounted devices. Nevertheless, questions remain regarding the accuracy of these eye-trackers during static and dynamic tasks. In light of this, we evaluated the performance of two widely used devices: Tobii Pro Glasses 2 and Tobii Pro Glasses 3. A total of 36 participants engaged in tasks under three dynamicity conditions. In the “seated with a chinrest” trial, only the eyes could be moved; in the “seated without a chinrest” trial, both the head and the eyes were free to move; and during the walking trial, participants walked along a straight path. During the seated trials, participants’ gaze was directed towards dots on a wall by means of audio instructions, whereas in the walking trial, participants maintained their gaze on a bullseye while walking towards it. Eye-tracker accuracy was determined using computer vision techniques to identify the target within the scene camera image. The findings showed that Tobii 3 outperformed Tobii 2 in terms of accuracy during the walking trials. Moreover, the results suggest that employing a chinrest in the case of head-mounted eye-trackers is counterproductive, as it necessitates larger eye eccentricities for target fixation, thereby compromising accuracy compared to not using a chinrest, which allows for head movement. Lastly, it was found that participants who reported higher workload demonstrated poorer eye-tracking accuracy. The current findings may be useful in the design of experiments that involve head-mounted eye-trackers. @en

Many fatal accidents that involve pedestrians occur at road crossings, and are attributed to a breakdown of communication between pedestrians and drivers. Thus, it is important to investigate how forms of communication in traffic, such as eye contact, influence crossing decisions. Thus far, there is little information about the effect of drivers’ eye contact on pedestrians’ perceived safety to cross the road. Existing studies treat eye contact as immutable, i.e., it is either present or absent in the whole interaction, an approach that overlooks the effect of the timing of eye contact. We present an online crowdsourced study that addresses this research gap. 1835 participants viewed 13 videos of an approaching car twice, in random order, and held a key whenever they felt safe to cross. The videos differed in terms of whether the car yielded or not, whether the car driver made eye contact or not, and the times when the driver made eye contact. Participants also answered questions about their perceived intuitiveness of the driver's eye contact behavior. The results showed that eye contact made people feel considerably safer to cross compared to no eye contact (an increase in keypress percentage from 31% to 50% was observed). In addition, the initiation and termination of eye contact affected perceived safety to cross more strongly than continuous eye contact and a lack of it, respectively. The car's motion, however, was a more dominant factor. Additionally, the driver's eye contact when the car braked was considered intuitive, and when it drove off, counterintuitive. In summary, this study demonstrates for the first time how drivers’ eye contact affects pedestrians’ perceived safety as a function of time in a dynamic scenario and questions the notion in recent literature that eye contact in road interactions is dispensable. These findings may be of interest in the development of automated vehicles (AVs), where the driver of the AV might not always be paying attention to the environment.

@en

Non-verbal communication, such as eye contact between drivers and pedestrians, has been regarded as one way to reduce accident risk. So far, studies have assumed rather than objectively measured the occurrence of eye contact. We address this research gap by developing an eye contact detection method and testing it in an indoor experiment with scripted driver–pedestrian interactions at a pedestrian crossing. Thirty participants acted as a pedestrian either standing on an imaginary curb or crossing an imaginary one-lane road in front of a stationary vehicle with an experimenter in the driver's seat. In half of the trials, pedestrians were instructed to make eye contact with the driver; in the other half, they were prohibited from doing so. Both parties’ gaze was recorded using eye trackers. An in-vehicle stereo camera recorded the car's point of view, a head-mounted camera recorded the pedestrian's point of view, and the location of the driver's and pedestrian's eyes was estimated using image recognition. We demonstrate that eye contact can be detected by measuring the angles between the vector joining the estimated location of the driver's and pedestrian's eyes, and the pedestrian's and driver's instantaneous gaze directions, respectively, and identifying whether these angles fall below a threshold of 4°. We achieved 100% correct classification of the trials involving eye contact and those without eye contact, based on measured eye contact duration. The proposed eye contact detection method may be useful for future research into eye contact.

@en