Cyclists' eye movements and crossing judgments at uncontrolled intersections: An eye-tracking study using animated video clips

A discrete choice latent class method for capturing unobserved heterogeneity in cyclist crossing behaviour at crosswalks

Conflicts between cyclists and motorized vehicles at crosswalks often lead to severe collisions. The varied behaviour of cyclists at these crossings introduces unobserved heterogeneity. Despite this, there is a notable research gap in studying the cyclist behaviour at roundabout crosswalks. To address this gap, we propose a discrete choice latent class method to capture the multi-level latent heterogeneity in cyclists' crossing behaviour at roundabout crosswalks. Latent heterogeneity can be captured at multiple levels: site-level, interaction-level, choice-attribute level, and individual-level. This method, rooted in behavioural theory, aims to provide a deeper understanding of cyclists' crossing decisions, enhancing safety measures at these intersections. We present an application of the proposed method to two publicly available drone datasets of naturalistic road user trajectories at roundabouts, including 8 roundabout sites that exhibit some level of similarity to minimize site heterogeneity. We capture the latent heterogeneity in the cyclists' membership to a distinct behavioural class at two levels using these datasets: the individual level, represented by the speed of the cyclist as they enter the crosswalk, and the interaction level, defined by the presence of vehicles approaching the cyclist. Our findings align with previous studies that emphasize the significance of the initial speed variable in influencing cyclists' subsequent behaviour and decisions. We identified two distinct classes of cyclists. We hypothesize that Class 1 cyclists, whom we refer to as passers, tend to bypass or overtake other road users at the crosswalk, especially in the absence of vehicles, prioritizing speed and efficiency. We also hypothesize that Class 2 cyclists, referred to as followers, exhibit more cautious behaviour, preferring to maintain a steady pace and avoid overtaking, particularly when vehicles are present. The proposed latent class model effectively captures this behavioural distinction, offering a more granular view of cyclists' decision-making processes at roundabout crosswalks. A key finding is that the discrete choice model with a latent class structure outperforms the basic model without it, despite having more degrees of freedom, as it achieves a lower BIC and AIC but improved model fit statistic. This demonstrates that latent heterogeneity can be effectively captured, leading to improved predictions and outperforming the basic non-latent class model. Classifying cyclists into distinct behavioural classes not only enhances cyclist safety at crosswalks but also provides valuable insights for the development of autonomous vehicle-cyclist interactions.

Visual behavior of racing bike cyclists in multi-tasking situations

Distracted biking can have serious repercussions for the rider such as accidents. The purpose of the present experiment was to determine the effect of visually monitoring two parameters, the cadence, and the heart rate on a bike computer fixed on a racing bike, and simultaneously detect hazardous traffic situations. Individuals (n = 20) were instructed to ride a racing bike that was fitted onto a roller trainer. After conducting a bicycle step test to assess the maximal heart rate (HFmax), participants were assigned to a within subject-design on a separate day. They were instructed to perform the riding task in two single-task conditions (only watching the traffic at the video with occluded or without occluded bike computer), two multi-tasking conditions (monitoring the cadence of 70 RPM or 90 RPM, monitoring the heart rate, and observing the traffic) and one control condition (no instructions). Percentage dwell time of the eye movements, the constant error from the target cadence, keeping the heart rate in an interval of 50% - 70% of the HFmax, and percentage of the recognized hazard traffic situations were analyzed. The analysis indicated that monitoring the parameters on the bike computer induced no significant decline in perceived hazardous traffic situations.

Development of a hazard prediction test for Chinese cyclists and its association with crash involvement

Introduction

Hazard perception is the ability to sense the road environment and predict and respond to the upcoming dangerous events, and this factor is closely related to cyclists' crash involvement. However, due to a lack of valid instruments, studies concerning the hazard predictions and crashes of cyclists in China remain limited. This study attempted to develop a hazard prediction test for cyclists.

Method

The experiment presented 44 video clips filmed from cyclists' perspectives to 61 children aged 13-16 years and 119 adults aged 18-30 years. After the video clip displayed a black screen, participants were asked to answer the following questions: "What is the hazard?" (question 1), "Where is the hazard?" (question 2), and "What happens next?" (question 3). The differences in test scores between cyclists with high and low levels of experience, cyclists of different ages, and crash-involved and noncrash-involved cyclists were compared to examine the validity of the test.

Results

The final test contained 21 video clips and the internal consistency reliabilities of the three questions were satisfactory. Experienced cyclists are better able to identify and predict hazards than are cyclists with less experience, and adult cyclists have better hazard prediction abilities than child cyclists. More importantly, crash-involved cyclists receiving lower scores with respect to their ability to identify and predict hazards than noncrash-involved cyclists, thus indicating that the discriminant validity of the test was acceptable.

Practical applications

This newly-developed test exhibits acceptable reliability and validity and can be used as an effective tool to measure the hazard prediction abilities of cyclists with different ages and levels of experience in China. The natural driving videos and test in the study may hold promise for future practical applications, and the implications for road safety are discussed.

An Eye-Tracking Study on the Effect of Different Signalized Intersection Typologies on Pedestrian Performance

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.

How automated vehicles should operate to avoid fatal crashes with cyclists?

The study assesses what kind of features would allow highly automated vehicles' (HAVs) safe operation in encounters with cyclists and allow avoiding fatal crashes between cyclists and passenger cars. Five features of HAVs' capabilities are formed based on previous studies and evaluated qualitatively using data from fatal crashes between driver-managed passenger cars and cyclist in Finland. By analysing these crashes, it is assessed which features HAVs should have in order to avoid each crash in a hypothetical setting, in which driver-managed cars would be replaced by HAVs. The necessary features of HAVs for crash avoidance are analysed crash-by-crash by considering the obligation to yield, visual obstacles at the crash scene and driver's behaviour prior to the crash. In order to avoid different types of fatal crashes with cyclists, the HAVs should be able to recognize nearby cyclists (feature 1), be aware of the priority rules in various intersections and traffic situations (2), indicate its intentions to cyclists (3), maintain safe driving patterns and anticipate future situations (4), and assess cyclists' intentions (5). Albeit the number of different features to allow crash avoidance is only five, implementing these features is a considerable challenge for HAVs' programming and design, as these should function in various and complex traffic situations. The study discloses the complexity in the encounters between HAVs and cyclists, which are to be considered in further studies and real-world implementations.

Analysis and Evaluation of Eye Behavior for Marine Operation Training - A Pilot Study

This paper presents a new analysis approach for evaluating situation awareness in marine operation training. Taking advantage of eye tracking technology, the situation awareness reflected by visual attention can be visualized and analyzed. A scanpath similarity comparison method that allows group-wise comparisons is proposed. The term 'Expert zone' is introduced to evaluate the performance of novice operator based on expert operators' eye movement. It is used to evaluate performance of novice operators in groups in certain segment of marine operation. A pilot study of crane lifting experiment was carried out. Two target stages of operation for the load descending until total immersion to the seabed were selected and analyzed for both novice and expert operators. The group-wise evaluation method is proven to be able to access the performance of the operator. Besides that, from data analysis of fixation-related source and scanpath, the similarities and dissimilarities of eye behavior between novice and expert is concluded with the scanpath mode in target segment.

Visual Eye Gaze While Cycling: Analyzing Eye Tracking at Signalized Intersections in Urban Conditions

The manner in which cyclists visually perceive elements of the urban environment plays an important role in bicycle crashes, which have been increasing in recent years. Yet, how visual information is processed by the user while riding a bike is still poorly analyzed by researchers. This study investigates cyclists’ eye gaze behavior at signalized intersections taking into account a set of gaze characteristics. Recording cyclist’s visual fixations by mobile-eye glasses in a real outdoor environment, a total of 13 field tests have been analyzed along a three-kilometer route in the urban center of Bologna, Italy. Findings reveal key differences in gaze behavior by experience level of the cyclist and type of intersection.