Smartphones have become an integral part of our everyday lives and keep us busy while doing other primary activities such as driving, cycling or walking in traffic. The problem of digital distraction among drivers has been largely addressed, and interest is growing also on vulnerable road users as well. In fact, high percentages of pedestrians and cyclists are accustomed to checking their devices while moving in traffic. This research links to the presented theme and aims to investigate the extent to which digital distraction in the form of social media app checking influences pedestrian behavior. The focus of the study is specifically on signalized intersections. An outdoor, eye-tracking experiment was conducted on a specific route consisting of various elements typical of urban areas. Participants were asked to walk the predefined route twice, encountering three signalized intersections: the first time they were asked to walk with their smartphone in hand, the second time without. The recordings of each participant’s route were then analyzed, examining reaction time, crossing time and speed, fixations and gaze paths. The results show a clear impact of digital devices on pedestrians’ attention by increasing their reaction and crossing times and decreasing crossing speeds. In addition, the analysis of fixations found that 82.54% of the time was devoted to the smartphone, while interest in other street elements decreased from 16.64% to 4.03%.

Pedestrian safety is a well-known issue, such that many road safety associations emphasize measures to improve this aspect. One of the main conflict points is pedestrian crossings, where motorized and non-motorized traffic flows directly interact and where pedestrian attention and reaction are two elements that can strongly influence their safety. Nowadays, these aspects are often deviated by the use of smartphones to surf the Internet or social media. The aim of the present study is to find out (1) whether and how intersection typology affects pedestrian behavior, both in terms of attention and crossing performance, and (2) whether and how gaze and behavioral characteristics are affected by smartphone use and social media browsing. To achieve this goal, eye-tracking technology was used to obtain qualitative and quantitative information on the number of fixations, their duration, and reaction times of pedestrians. Additionally, from the eye-tracking videos, it was possible to derive pedestrian waiting times, crossing times, and speeds. Statistical tests were conducted to determine if there is a significant difference in pedestrian behavior at the three different types of intersections and in their behavior when using or not using their device. Results confirm the initial hypotheses and quantify the difference in pedestrian gaze behavior and crossing performance when walking across three different types of signalized crosswalks.

Motorcyclists remain a disproportionately large group of vulnerable road users, with fatality rates significantly higher than that in other road groups. Additionally, fatal accidents involving motorcyclists have a more slowly decreasing trend in comparison to that of other road users, while the number of this kind of users is growing fast. For all these reasons, there is a need to understand what the key factors leading to fatal accidents are in order to identify the possible measures to minimize the accidents themselves or at least their consequences. This would permit, indeed, to positively impact the road traffic system, leading to the creation of the safest road traffic system possible, as it is the goal of the Sustainable Safety approach. The aim of this study is to dive into the mentioned problem, analyzing fatal motorcycle accidents in Slovenia over a decade, highlighting the key factors contributing to these incidents. By integrating data from four databases, the study evaluated accident trends, infrastructural elements, and rider behavior through a multi-stage analysis. Firstly, data were collected from four national, up-to-date databases that contain information about road accidents themselves, the road infrastructure, additional police data, and media descriptions. After merging this information into one comprehensive database, where each row represents all the data available for one accident, a general analysis of accidents’ trends over the considered 10-year period was developed, considering at first all fatal road accidents, then deepening it to accidents caused by a motorcyclist, and finally to single-vehicle accidents. A statistical analysis followed, aimed at identifying a statistical correlation between the accidents and the factors leading to them. The results of the first accident analysis indicated that excessive speed, incorrect driving direction, and overtaking maneuvers are the primary causes of fatal accidents, especially on non-urban roads preferred by motorcyclists. Single-vehicle accidents frequently involve collisions with roadside objects, including safety barriers and poles, underscoring the need for targeted infrastructural improvements. The following correlation analysis revealed that a total of seven factors were statistically significant: three human factors (age, gender, experience)—which were the ones with the strongest correlations—one infrastructural factor (pavement width), and three factors belonging to external conditions (accident type, cause, and location). Of these, four were positively correlated to the causer, while three, i.e., pavement width, causes, and road location, were negatively correlated. This study provides a foundation for future research on less severe accidents and proactive risk behavior analysis, aiming to improve motorcyclist safety comprehensively.