Fig 1 - uploaded by Daniel Eisele
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The different behaviors of the vehicle represented by its speed at different distances from the pedestrian (top) and the distances from the pedestrian's position at which the different segments ended (bottom).
Source publication
Effects of a frontal brake light (FBL, a potential external human–machine interface for automated vehicles) on participants’ self-reported willingness to cross a vehicle’s path were investigated. In a mixed design online study (vehicles in the experimental group were equipped with FBLs, there were no FBLs in the control group), participants observe...
Contexts in source publication
Context 1
... videos of a vehicle approaching the camera perspective were rendered using the VICOM Editor (2021). The perspective was set to an average German eye-height of 1.6 m (Windel, 2019). The top part of Fig. 1 illustrates the different behaviors of the vehicle. The different lines depict the vehicle's speed (y-axis) relative to the physical distance from the pedestrian (x-axis). Every clip started when the vehicle was 100 m away from the pedestrian. The vehicle either maintained its speed continuously (horizontal lines) or started to ...
Context 2
... Apart from being of theoretical interest, the differences in the vehicle's kinematics made the vehicle's behavior less predictable for the participants. At standstill, we left enough space between the vehicle and the viewer's perspective to convey the impression that a pedestrian could cross in front of the vehicle's hood. The dotted lines in Fig. 1 mark the five points where the different video segments were ...
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Increasing prevalence of Autonomous Vehicles (AVs) necessitates efficient communication with susceptible road users, especially pedestrians, in communal urban areas. To improve pedestrians' trust and safety, Smart Pole Interaction Units (SPIU) and external Human-Machine Interfaces (eHMI) have become crucial interfaces. In this study, we ask 12 auto...
Citations
... While empirical findings on the effects of eHMIs have been mixed, a consensus has emerged that they can indeed influence pedestrians' perceptions and behaviors, including trust, willingness to cross, and crossing timing [7,[11][12][13][14][15]. Notably, recent studies have shown that eHMIs can influence vehicle-pedestrian interactions not only when activated (e.g., increase willingness to cross by activating) but also when inactivated (e.g., decrease willingness to cross when inactivated) [7,[15][16][17]. ...
... While empirical findings on the effects of eHMIs have been mixed, a consensus has emerged that they can indeed influence pedestrians' perceptions and behaviors, including trust, willingness to cross, and crossing timing [7,[11][12][13][14][15]. Notably, recent studies have shown that eHMIs can influence vehicle-pedestrian interactions not only when activated (e.g., increase willingness to cross by activating) but also when inactivated (e.g., decrease willingness to cross when inactivated) [7,[15][16][17]. In these studies, participants changed their crossing behavior in front of vehicles with inactive eHMIs (and vehicles without eHMIs) if they had previously been exposed to vehicles with active eHMIs. ...
... Thus, any study investigating whether state eHMIs can perform as well as intent eHMIs should take situations into account in which potentially ambiguous activations of state eHMIs occur. With regard to non-activations, it has been argued that an "I am braking" eHMI that does (surprisingly) not activate (i.e., vehicle does not decelerate although one would have expected it to) also has the potential to call attention to a failure to yield and serve a warning function not to cross in front of an AV [15], as has been demonstrated for intent eHMIs [7]. ...
In recent years, there has been a debate on whether automated vehicles (AVs) should be equipped with novel external human–machine interfaces (eHMIs). Many studies have demonstrated how eHMIs influence pedestrians’ attitudes (e.g., trust in AVs) and behavior when they activate (e.g., encourage crossing by lighting up). However, very little attention has been paid to their effects when they do not activate (e.g., discourage crossing by not lighting up). We conducted a video-based laboratory study with a mixed design to explore the potential of two different eHMI messages to facilitate pedestrian-AV interactions by means of activating or not activating. Our participants watched videos of an approaching AV equipped with either a state eHMI (“I am braking”) or intent eHMI (“I intend to yield to you”) from the perspective of a pedestrian about to cross the road. They indicated when they would initiate crossing and repeatedly rated their trust in the AV. Our results show that the activation of both the state and intent eHMI was effective in communicating the AV’s intent to yield and both eHMIs drew attention to a failure to yield when they did not activate. However, the two eHMIs differed in their potential to mislead pedestrians, as decelerations accompanied by the activation of the state eHMI were repeatedly misinterpreted as an intention to yield. Despite this, user experience ratings did not differ between the eHMIs. Following a failure to yield, trust declined sharply. In subsequent trials, crossing behavior recovered quickly, while trust took longer to recover.
... As an exemplary additional eHMI, each AV was further equipped with a light that activated when an AV began to decelerate, and remained activated as long as the AV decelerated (i.e., a frontal brake light, FBL). An FBL has been shown to be salient and influence pedestrian-vehicle interaction [7,14,23,62]. As the vehicles were either equipped with these two eHMIs or none, the presence of an AV-marker light made it immediately recognizable whether a vehicle had an FBL or not. ...
The proportion of highly automated vehicles in traffic (i.e., the prevalence of AVs) is likely to increase over time. The aim of this study was to investigate whether the prevalence of AVs may influence how pedestrians interact with AVs and with conventional, human-driven vehicles (CVs). A video-based laboratory study was conducted using a two-group mixed design. Participants took the perspective of pedestrians about to cross the road in a situation where AVs (with eHMIs) and CVs were approaching their position. The prevalence of AVs was manipulated between groups (low/high). The participants indicated the moment they decided to cross in front of the vehicles. Our results show that AV prevalence did indeed significantly influence when participants decided to cross. Overall, participants decided to cross earlier in front of the more prevalent vehicle type. Therefore, taking into account the given prevalence of AVs could significantly benefit AVs in predicting pedestrian behavior.
... The absence of a well-defined Vehicle-to-Pedestrian (V2P) communication channel can hinder pedestrians ability to understand AV intentions, leading to safety concerns [12]. To ensure pedestrian safety and foster positive interactions, AVs must effectively communicate their intentions [6]. Therefore, the goal is to develop real-time, safer, and transparent communication between AVs and pedestrians in diverse scenarios. ...
Our research focuses on the smart pole interaction unit (SPIU) as an infrastructure external human-machine interface (HMI) to enhance pedestrian interaction with autonomous vehicles (AVs) in shared spaces. We extensively study SPIU with external human-machine interfaces (eHMI) on AVs as an integrated solution. To discuss interaction barriers and enhance pedestrian safety, we engaged 25 participants aged 18-40 to brainstorm design solutions for Pedestrian-AV interactions, emphasising effectiveness, simplicity, visibility, and clarity. Findings indicate a preference for real-time SPIU interaction over eHMI on AVs in multiple AV scenarios. However, the combined use of SPIU and eHMI on AVs is crucial for building trust in decision-making. Consequently, we propose innovative design solutions for both SPIU and eHMI on AVs, discussing their pros and cons. This study lays the groundwork for future autonomous mobility solutions by developing human-centric eHMI and SPIU prototypes as ieHMI.
Safe vehicles are an important pillar in reducing the number of accidents or mitigating the consequences of a collision. Although the number of autonomous safety systems in vehicles is increasing, retrofitted systems could also help reduce road accidents. A new retrofit assistance system called Front Brake Light (FBL) helps the driver to assess the intentions of other road users. This system is mounted at the front of the vehicle and works similarly to the rear brake lights. The objective of this study is to evaluate the safety performance of an FBL in real accidents at junctions. Depending on the type of accident, between 7.5% and 17.0% of the accidents analysed can be prevented. A further 9.0% to 25.5% could be positively influenced by the FBL; i.e., the collision speed could be reduced. If the FBLs were visible to the driver of the priority vehicle, the number of potentially avoidable accidents would increase to a magnitude of 11.5% to 26.2%. The range of accidents in which the consequences can be reduced increases to between 13.8% and 39.2%.
The subjective and objective safety of interactions between vulnerable road users (VRUs), such as cyclists and pedestrians, and automated vehicles (AVs) is essential for the successful integration of AVs into real-world traffic. Laboratory studies have shown that vehicle dynamics are particularly crucial for the experience and behavior of VRUs when interacting with both AVs and manually-driven vehicles (MVs). However, since AVs are still rare in urban traffic, field study results are also scarce. The present study employs the Wizard-of-Oz (WoOz) method, where a safety driver is hidden inside the vehicle, making it appear driverless from the outside. This vehicle then interacted with naïve VRUs at a signal-controlled intersection in Munich. Unlike in comparable studies, the complex traffic scenario involved crossing in front of turning vehicles. The study analyzed the extent to which the behavior (recorded via video) and experience (post-crossing survey) of the VRUs differed depending on whether the vehicle was seemingly automated or an MV. Additionally, known influencing factors, such as age, gender, and vehicle dynamics, were included in the analysis to determine whether potential effects remained significant. The results indicate that the automation status of the vehicle influenced behavior (crossing time, head movements towards the vehicle, post-crossing reactions). Furthermore, vehicle dynamics were particularly decisive for behavior and also seemed to influence perceived safety. This underscores the importance of considering vehicle dynamics in the development and implementation of AVs.
This paper presents results from a study on the impact of negative attitudes towards robots on pedestrians’ needs for technological communication capabilities of autonomous vehicles and preferred communication modalities. Further, the amount of prior information on autonomous vehicles given to test persons is varied. The study is realized in terms of an imagination scenario. Results show a significant dependency of the demand for communication of autonomous vehicles with pedestrians on the extent of negative attitudes towards robots as well as a general demand for such communication capabilities. Interestingly, these findings are independent of the amount of prior information. Differences of preferred communication modalities with respect to negative attitudes or prior information are not found. The results of this study emphasize the importance of vehicle-pedestrian communication, particularly, using multi-modal interfaces in future autonomous driving technology.
Over the last years, there has been a lively discussion whether (automated) vehicles should be equipped with novel external human-machine-interfaces (eHMIs) in order to facilitate communication with nearby vulnerable road users. This exploratory study investigated whether the introduction of eHMI-equipped vehicles to public traffic potentially influences how pedestrians interact with vehicles without eHMIs. To that goal, our participants specified their willingness to cross in front of vehicles that were either equipped with a frontal brake light eHMI or not in a video-based experiment. Between groups, the quota of eHMI-equipped vehicles in simulated traffic was varied. Our findings show that the quota of vehicles with an eHMI did indeed influence street crossing willingness in front of yielding as well as non-yielding vehicles without an eHMI. Notably, the magnitude and direction of the effect was dependent on the distance between vehicle and pedestrian. Future research on eHMIs should take potential unintended side effects of eHMIs into account.
