Psychological and Technology Factor Contribute to Social Media Addiction

In the present-day context of worldwide connectivity, social media has emerged as an integral component of many adolescents' everyday routines. However, the seemingly harmless practice of utilizing social networking platforms can swiftly transform into a significant dependency, leading to unfavorable consequences. Adolescents' excessive dependence on social media platforms has garnered significant attention from scholars and practitioners in the mental health field. Psychological and technological elements are recognized as contributing to social media addiction, which has detrimental consequences for adolescents. Hence, the primary objective of this study is to gain a comprehensive understanding of the existing literature about the psychological and technological elements contributing to addiction to social media platforms. The discourse outcomes will illuminate the strategies employed to mitigate social media addiction by addressing the abovementioned factors. This conclusion has significant implications, as it will stimulate further discussion and prompt additional research reviews on the various elements contributing to social media addiction

Evaluating a VR System for Collecting Safety-Critical Vehicle-Pedestrian Interactions

Autonomous vehicles (AVs) require comprehensive and reliable pedestrian trajectory data to ensure safe operation. However, obtaining data of safety-critical scenarios such as jaywalking and near-collisions, or uncommon agents such as children, disabled pedestrians, and vulnerable road users poses logistical and ethical challenges. This paper evaluates a Virtual Reality (VR) system designed to collect pedestrian trajectory and body pose data in a controlled, low-risk environment. We substantiate the usefulness of such a system through semi-structured interviews with professionals in the AV field, and validate the effectiveness of the system through two empirical studies: a first-person user evaluation involving 62 participants, and a third-person evaluative survey involving 290 respondents. Our findings demonstrate that the VR-based data collection system elicits realistic responses for capturing pedestrian data in safety-critical or uncommon vehicle-pedestrian interaction scenarios.Comment: In submission to CHI 202

Variable-Drift Diffusion Models of Pedestrian Road-Crossing Decisions

Peer reviewe

External Human–Machine Interfaces Can Be Misleading: An Examination of Trust Development and Misuse in a CAVE-Based Pedestrian Simulation Environment

Objective To investigate pedestrians’ misuse of an automated vehicle (AV) equipped with an external human–machine interface (eHMI). Misuse occurs when a pedestrian enters the road because of uncritically following the eHMI’s message. Background Human factors research indicates that automation misuse is a concern. However, there is no consensus regarding misuse of eHMIs. Methods Sixty participants each experienced 50 crossing trials in a Cave Automatic Virtual Environment (CAVE) simulator. The three independent variables were as follows: (1) behavior of the approaching AV (within-subject: yielding at 33 or 43 m distance, no yielding), (2) eHMI presence (within-subject: eHMI on upon yielding, off), and (3) eHMI onset timing (between-subjects: eHMI turned on 1 s before or 1 s after the vehicle started to decelerate). Two failure trials were included where the eHMI turned on, yet the AV did not yield. Dependent measures were the moment of entering the road and perceived risk, comprehension, and trust. Results Trust was higher with eHMI than without, and the −1 Group crossed earlier than the +1 Group. In the failure trials, perceived risk increased to high levels, whereas trust and comprehension decreased. Thirty-five percent of the participants in the −1 and +1 Groups walked onto the road when the eHMI failed for the first time, but there were no significant differences between the two groups. Conclusion eHMIs that provide anticipatory information stimulate early crossing. eHMIs may cause people to over-rely on the eHMI and under-rely on the vehicle-intrinsic cues. Application eHMI have adverse consequences, and education of eHMI capability is required

Pedestrians’ perceptions of automated vehicle movements and light-based eHMIs in real world conditions: A test track study

The development of increasingly automated vehicles (AVs) is likely to lead to new challenges around how they will interact with other road users. In the future, it is envisaged that AVs, manually driven vehicles, and vulnerable road users such as cyclists and pedestrians will need to share the road environment and interact with one another. This paper presents a test track study, funded by the H2020 interACT project, investigating pedestrians’ reactions towards an AV’s movement patterns and external Human Machine Interfaces (eHMIs). Twenty participants, standing on the side of a test-track road and facing an approaching AV, were asked to raise their arm to indicate: (1) when they could perceive the AV’s eHMI, which consisted of either a Full Light Band (FLB) or a Partial Light Band (PLB); (2) when they perceived the deceleration of the AV (with eHMI vs. no eHMI); and (3) when they felt safe to cross the road in front of the approaching AV (with eHMI vs. no eHMI). Statistical analyses revealed no effects of the presence of an eHMI on the pedestrians’ crossing decision or deceleration perception, but significant differences were found regarding the visibility of the FLB and PLB designs. The PLB design could be perceived at further distances than the FLB design. Both eHMI solutions were generally well-received, and participants provided high ratings of perceived safety, and confidence around the AV

Studying Pedestrian’s Unmarked Midblock Crossing Behavior on a Multilane Road When Interacting With Autonomous Vehicles Using Virtual Reality

This dissertation focuses on the challenge of pedestrian interaction with autonomous vehicles (AVs) at unmarked midblock locations where the right-of-way is unspecified. A virtual reality (VR) simulation was developed to replicate an urban unmarked midblock environment where pedestrians cross a four-lane arterial roadway and interact with AVs. One research goal is to investigate the impact of roadway centerline features (undivided, two-way left-turn lane, and median) and AV operational schemes portrayed through on-vehicle signals (no signal, yellow negotiating indication, and yellow/blue negotiating/no-yield indications) on pedestrian crossing behavior. Results demonstrate that both roadway centerline design features and AV operations and signaling show significant impacts on pedestrians\u27 unmarked midblock crossing behavior, including the waiting time at the curb, waiting time in the middle of the road, and the total crossing time. Whereas, only the roadway centerline design features significantly impact the walking time, and only the AV operations and signaling significantly impact the accepted gap. Participants in the undivided centerline scene spent longer time waiting at the curb and walking on the road. Also, pedestrians are more likely to display risky behavior and cross in front of AVs indicating blue signals with non-yielding behavior in the presence of a median centerline scene. The inclusion of a yellow signal, which indicates the detection of pedestrians and signifies that the AVs will negotiate with them, resulted in a significant reduction in pedestrian waiting time both at the curb and in the middle of the road, when compared to AVs without a signal. Interaction effects between roadway centerline design features and AV operations and signaling are significant only for waiting time in the middle of the road. It is also found that older pedestrians tend to wait longer at the curb and are less likely to cross in front of AVs showing a blue signal with non-yielding behavior. Another research goal is to investigate how this VR experience change pedestrians’ perception of AVs. Results demonstrated that both pedestrians’ overall attitude toward AVs and trust in the effectiveness of AV systems significantly improved after the VR experience. It is also found that the more pedestrians trust the yellow signals, the more likely they are to improve their perception of AVs. Further, pedestrians who exhibit more aggressive crossing behavior are less likely to change their perception towards AVs as compared to those pedestrians who display rule-conforming crossing behaviors. Also, if the experiment made pedestrians feel motion sick, they were less likely to experience increased trust in the AV system\u27s effectiveness