cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4121/16866709.v3
title: Supplementary data for the paper 'The effect of drivers’ eye contact on pedestrians’ perceived safety'

description: 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, influencfe 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.
DOI: 10.4121/16866709
title: Supplementary data for the paper 'The effect of drivers’ eye contact on pedestrians’ perceived safety'

description: 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, influencfe 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.
DOI: 10.4121/19170302.v1
title: Supplementary data for the paper 'Identifying lane changes automatically using the GPS sensors of portable devices'

description: Mobile applications that provide GPS-based route navigation advice or driver diagnostics (e.g., driving speed, driving style) are gaining popularity. However, these applications currently do not have knowledge of whether the driver is performing a lane change. Having such information may prove valuable to individual drivers (e.g., to provide more specific navigation instructions) or road authorities (e.g., knowledge of lane change hotspots may inform road design). The present study aimed to assess the accuracy of lane change recognition algorithms that rely solely on mobile GPS sensor input. Three trips on Dutch highways, totaling 158 km of driving, were performed while carrying two smartphones (Huawei P20, Samsung Galaxy S9), a GPS-equipped GoPro Max, and a USB GPS receiver (GlobalSat BU343-s4). The timestamps of 215 lane changes, acting as the ground truth, were manually extracted from the forward-facing GoPro camera footage. After connecting the GPS trajectories to the road using Mapbox Map Matching API, lane changes were identified based on the exceedance of a lateral translation threshold in set time windows. The number of true positives, false positives, true negatives, and false negatives with respect to the ground truth were tabulated, and the overall accuracy of the lane-change classification was found to be 90%. The method appears promising for highway engineering and traffic behavior research that use floating car data, but there may be limited applicability to real-time advisory systems due to the occasional occurrence of false positives.
DOI: 10.4121/19170302.v2
title: Supplementary data for the paper 'Identifying lane changes automatically using the GPS sensors of portable devices'

description: Mobile applications that provide GPS-based route navigation advice or driver diagnostics (e.g., driving speed, driving style) are gaining popularity. However, these applications currently do not have knowledge of whether the driver is performing a lane change. Having such information may prove valuable to individual drivers (e.g., to provide more specific navigation instructions) or road authorities (e.g., knowledge of lane change hotspots may inform road design). The present study aimed to assess the accuracy of lane change recognition algorithms that rely solely on mobile GPS sensor input. Three trips on Dutch highways, totaling 158 km of driving, were performed while carrying two smartphones (Huawei P20, Samsung Galaxy S9), a GPS-equipped GoPro Max, and a USB GPS receiver (GlobalSat BU343-s4). The timestamps of 215 lane changes, acting as the ground truth, were manually extracted from the forward-facing GoPro camera footage. After connecting the GPS trajectories to the road using Mapbox Map Matching API, lane changes were identified based on the exceedance of a lateral translation threshold in set time windows. The number of true positives, false positives, true negatives, and false negatives with respect to the ground truth were tabulated, and the overall accuracy of the lane-change classification was found to be 90%. The method appears promising for highway engineering and traffic behavior research that use floating car data, but there may be limited applicability to real-time advisory systems due to the occasional occurrence of false positives.
DOI: 10.4121/19170302
title: Supplementary data for the paper 'Identifying lane changes automatically using the GPS sensors of portable devices'

description: Mobile applications that provide GPS-based route navigation advice or driver diagnostics (e.g., driving speed, driving style) are gaining popularity. However, these applications currently do not have knowledge of whether the driver is performing a lane change. Having such information may prove valuable to individual drivers (e.g., to provide more specific navigation instructions) or road authorities (e.g., knowledge of lane change hotspots may inform road design). The present study aimed to assess the accuracy of lane change recognition algorithms that rely solely on mobile GPS sensor input. Three trips on Dutch highways, totaling 158 km of driving, were performed while carrying two smartphones (Huawei P20, Samsung Galaxy S9), a GPS-equipped GoPro Max, and a USB GPS receiver (GlobalSat BU343-s4). The timestamps of 215 lane changes, acting as the ground truth, were manually extracted from the forward-facing GoPro camera footage. After connecting the GPS trajectories to the road using Mapbox Map Matching API, lane changes were identified based on the exceedance of a lateral translation threshold in set time windows. The number of true positives, false positives, true negatives, and false negatives with respect to the ground truth were tabulated, and the overall accuracy of the lane-change classification was found to be 90%. The method appears promising for highway engineering and traffic behavior research that use floating car data, but there may be limited applicability to real-time advisory systems due to the occasional occurrence of false positives.
DOI: 10.4121/uuid:bef54ab8-73ef-42f3-b6b7-54e011737e72
title: An auditory dataset of passing vehicles recorded with a smartphone

description: .mp4 files and .wav files corresponding to the paper 'An auditory dataset of passing vehicles recorded with a smartphone' Also included is a MATLAB m-file that produces the figures in the paper.
DOI: 10.4121/12714215
title: An auditory dataset of passing vehicles recorded with a smartphone

description: .mp4 files and .wav files corresponding to the paper 'An auditory dataset of passing vehicles recorded with a smartphone' Also included is a MATLAB m-file that produces the figures in the paper.
DOI: 10.4121/uuid:673c9bbc-bf17-42fa-a23a-3d716e141b1f
title: Supplementary data for the following paper: Crowdsourced measurement of reaction times to audiovisual stimuli with various degrees of asynchrony.

description: Supplementary data for the following paper: Bazilinskyy, P., & De Winter, J. C. F. (2018). Crowdsourced measurement of reaction times to audiovisual stimuli with various degrees of asynchrony. Human Factors, 60, 1192–1206.
DOI: 10.4121/12697760.v2
title: Supplementary data for the following paper: Crowdsourced measurement of reaction times to audiovisual stimuli with various degrees of asynchrony.

description: Supplementary data for the following paper: Bazilinskyy, P., & De Winter, J. C. F. (2018). Crowdsourced measurement of reaction times to audiovisual stimuli with various degrees of asynchrony. Human Factors, 60, 1192–1206.
DOI: 10.4121/12697760
title: Supplementary data for the following paper: Crowdsourced measurement of reaction times to audiovisual stimuli with various degrees of asynchrony.

description: Supplementary data for the following paper: Bazilinskyy, P., & De Winter, J. C. F. (2018). Crowdsourced measurement of reaction times to audiovisual stimuli with various degrees of asynchrony. Human Factors, 60, 1192–1206.
DOI: 10.4121/14096067.v2
title: Supplementary data for the paper 'Bio-inspired intent communication for automated vehicles'

description: Various external human-machine interfaces (eHMIs) have been proposed that communicate the intent of automated vehicles (AVs) to vulnerable road users. However, there is no consensus on which eHMI concept is most suitable for intent communication. In nature, animals have evolved the ability to communicate intent via visual signals. Inspired by intent communication in nature, this paper investigated three novel and potentially intuitive eHMI designs that rely on posture, gesture, and colouration, respectively. In an online crowdsourcing study, 1141 participants viewed videos featuring a yielding or non-yielding AV with one of the three bio-inspired eHMIs, as well as a green/red lightbar eHMI, a walk/don’t walk text-based eHMI, and a baseline condition (i.e., no eHMI). Participants were asked to press and hold a key when they felt safe to cross and to answer rating questions. Together, these measures were used to determine the intuitiveness of the tested eHMIs. Results showed that the lightbar eHMI and text-based eHMI were more intuitive than the three bio-inspired eHMIs, which, in turn, were more intuitive than the baseline condition. An exception was the bio-inspired colouration eHMI, which produced a performance score that was equivalent to the text-based eHMI when communicating ‘non-yielding’. Further research is necessary to examine whether these observations hold in more complex traffic situations. Additionally, we recommend combining features from different eHMIs, such as the full-body communication of the bio-inspired colouration eHMI with the colours of the lightbar eHMI.
DOI: 10.4121/14096067
title: Supplementary data for the paper 'Bio-inspired intent communication for automated vehicles'

description: Various external human-machine interfaces (eHMIs) have been proposed that communicate the intent of automated vehicles (AVs) to vulnerable road users. However, there is no consensus on which eHMI concept is most suitable for intent communication. In nature, animals have evolved the ability to communicate intent via visual signals. Inspired by intent communication in nature, this paper investigated three novel and potentially intuitive eHMI designs that rely on posture, gesture, and colouration, respectively. In an online crowdsourcing study, 1141 participants viewed videos featuring a yielding or non-yielding AV with one of the three bio-inspired eHMIs, as well as a green/red lightbar eHMI, a walk/don’t walk text-based eHMI, and a baseline condition (i.e., no eHMI). Participants were asked to press and hold a key when they felt safe to cross and to answer rating questions. Together, these measures were used to determine the intuitiveness of the tested eHMIs. Results showed that the lightbar eHMI and text-based eHMI were more intuitive than the three bio-inspired eHMIs, which, in turn, were more intuitive than the baseline condition. An exception was the bio-inspired colouration eHMI, which produced a performance score that was equivalent to the text-based eHMI when communicating ‘non-yielding’. Further research is necessary to examine whether these observations hold in more complex traffic situations. Additionally, we recommend combining features from different eHMIs, such as the full-body communication of the bio-inspired colouration eHMI with the colours of the lightbar eHMI.
DOI: 10.4121/14046107.v1
title: Supplementary data for the paper 'Automated vehicles that communicate implicitly: examining the use of lateral position within the lane'

description: It may be necessary to introduce new modes of communication between automated vehicles (AVs) and pedestrians. This research proposes using the AV’s lateral deviation within the lane to communicate if the AV will yield to the pedestrian. In an online experiment, animated video clips depicting an approaching AV were shown to participants. Each of 1104 participants viewed 28 videos twice in random order. The videos differed in deviation magnitude, deviation onset, turn indicator usage, and deviation-yielding mapping. Participants had to press and hold a key as long as they felt safe to cross, and report the perceived intuitiveness of the AV’s behaviour after each trial. The results showed that the AV moving towards the pedestrian to indicate yielding and away to indicate continuing driving was more effective than the opposite combination. Furthermore, the turn indicator was regarded as intuitive for signalling that the AV will yield.<br>
DOI: 10.4121/14046107.v2
title: Supplementary data for the paper 'Automated vehicles that communicate implicitly: examining the use of lateral position within the lane'

description: It may be necessary to introduce new modes of communication between automated vehicles (AVs) and pedestrians. This research proposes using the AV’s lateral deviation within the lane to communicate if the AV will yield to the pedestrian. In an online experiment, animated video clips depicting an approaching AV were shown to participants. Each of 1104 participants viewed 28 videos twice in random order. The videos differed in deviation magnitude, deviation onset, turn indicator usage, and deviation-yielding mapping. Participants had to press and hold a key as long as they felt safe to cross, and report the perceived intuitiveness of the AV’s behaviour after each trial. The results showed that the AV moving towards the pedestrian to indicate yielding and away to indicate continuing driving was more effective than the opposite combination. Furthermore, the turn indicator was regarded as intuitive for signalling that the AV will yield.<br>
DOI: 10.4121/14046107
title: Supplementary data for the paper 'Automated vehicles that communicate implicitly: examining the use of lateral position within the lane'

description: It may be necessary to introduce new modes of communication between automated vehicles (AVs) and pedestrians. This research proposes using the AV’s lateral deviation within the lane to communicate if the AV will yield to the pedestrian. In an online experiment, animated video clips depicting an approaching AV were shown to participants. Each of 1104 participants viewed 28 videos twice in random order. The videos differed in deviation magnitude, deviation onset, turn indicator usage, and deviation-yielding mapping. Participants had to press and hold a key as long as they felt safe to cross, and report the perceived intuitiveness of the AV’s behaviour after each trial. The results showed that the AV moving towards the pedestrian to indicate yielding and away to indicate continuing driving was more effective than the opposite combination. Furthermore, the turn indicator was regarded as intuitive for signalling that the AV will yield.<br>
DOI: 10.4121/15134037.v2
title: Supplementary data for the paper 'Towards the detection of driver–pedestrian eye contact'

description: 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.
DOI: 10.4121/15134037
title: Supplementary data for the paper 'Towards the detection of driver–pedestrian eye contact'

description: 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.
DOI: 10.4121/19102133.v1
title: Supplementary data for the paper 'Crowdsourced assessment of 227 text-based eHMIs for a crossing scenario'

description: Future automated vehicles may be equipped with external human-machine interfaces (eHMIs) capable of signaling whether pedestrians can cross the road. Industry and academia have proposed a variety of eHMIs featuring a text message. An eHMI message can refer to the action to be performed by the pedestrian (egocentric message) or the automated vehicle (allocentric message). Currently, there is no consensus on the correct phrasing of the text message. We created 227 eHMIs based on text-based eHMIs observed in the literature. A crowdsourcing experiment (<i>N</i> = 1241) was performed with images depicting an automated vehicle equipped with an eHMI on the front bumper. The participants indicated whether they would (not) cross the road, and response times were recorded. Egocentric messages were found to be more compelling for participants to (not) cross than allocentric messages. Furthermore, Spanish-speaking participants found Spanish eHMIs more compelling than English eHMIs. Finally, it was established that some eHMI texts should be avoided, as signified by compellingness, long responses, and high inter-subject variability.
DOI: 10.4121/19102133.v2
title: Supplementary data for the paper 'Crowdsourced assessment of 227 text-based eHMIs for a crossing scenario'

description: Future automated vehicles may be equipped with external human-machine interfaces (eHMIs) capable of signaling whether pedestrians can cross the road. Industry and academia have proposed a variety of eHMIs featuring a text message. An eHMI message can refer to the action to be performed by the pedestrian (egocentric message) or the automated vehicle (allocentric message). Currently, there is no consensus on the correct phrasing of the text message. We created 227 eHMIs based on text-based eHMIs observed in the literature. A crowdsourcing experiment (<i>N</i> = 1241) was performed with images depicting an automated vehicle equipped with an eHMI on the front bumper. The participants indicated whether they would (not) cross the road, and response times were recorded. Egocentric messages were found to be more compelling for participants to (not) cross than allocentric messages. Furthermore, Spanish-speaking participants found Spanish eHMIs more compelling than English eHMIs. Finally, it was established that some eHMI texts should be avoided, as signified by compellingness, long responses, and high inter-subject variability.