Unsignalized Crosswalks Research Articles

Factors Affecting the Waiting Time of Pedestrians at Unsignalized Crosswalks of Kathmandu: A Case Study of Bagbazar and Jamal Crosswalks

Unsignalized crosswalks are the most common pedestrian crossing facilities on the city roads of Kathmandu. This sharing of the road between pedestrians and vehicles can be very unsafe for walking. To demur such conflict, analyzing pedestrians' waiting behavior and designing pedestrian signals considering different factors is the most efficient way. The degree to which pedestrians adhere to signals depends largely on their patience while waiting. Thus, it is crucial to account for pedestrian waiting tolerance when planning pedestrian signal timing. A study at unsignalized crosswalks of Bagbazar and Jamal were taken into consideration for this study. This research delves into analyzing the factors that impact the waiting time, a key indicator of pedestrian patience at unsignalized crosswalks in Kathmandu. Using SPSS, binary logistic regression is conducted with the waiting time of a pedestrian before crossing as the dependent variable and road width, the gap between vehicles, speed of accepted vehicles, pedestrian size, gender, crossing pattern, and the presence of a carried object as predictor variables. The article encountered that gender, crossing pattern, carrying any object, size of pedestrians, road width, and time gap between the vehicles at the nearer lane of a pedestrian are the significant factors that affect the waiting time. The results could be employed by planners to coordinate the design of pedestrian crossing facilities with the behavioral patterns of pedestrians at unsignalized crosswalks.

Can zigzag marking improve pedestrian safety at unsignalized crosswalks? An observational before-after study in Israel

Zigzag road marking near unsignalized pedestrian crosswalks is common in some countries but not yet allowed in Israel. An observational before-after study was conducted to explore its impacts on pedestrian crossing conditions. The measure was applied at three midblock urban crosswalks, on dual-carriageway and two-lane roads. The study examined changes in safety-related behaviors by comparing three periods: before the installation, and two weeks and two months afterwards. Shortly after the zigzag application, a significant decrease in average vehicle speeds, of 9%-16%, was observed at all study sites, but in a longer-term a decrease of 7%-8% remained at the dual-carriageway sites only. A relative increase in yielding rates to pedestrians was of 19%-20% in the short-term and of 13%-14% after two months, at dual-carriageway sites, with no change at the two-lane site. Overall, zigzag marking may improve pedestrian safety. However, as the effects were inconsistent, it was not recommended for widespread use.

Pedestrian crossing: Analysis of habits and compliance through unsignalized crosswalk in the city of Kigali

Pedestrian safety is a global issue that can be improved by monitoring and adjusting walking behaviors. This study focuses on how people walk across streets without traffic signals. It looks at whether pedestrians follow the rules and regulations for safely crossing streets. The unique aspect of this research is that it examines pedestrian behaviors on roads with two lanes for two-way traffic at various informal crosswalks rather than on one-way streets. The researchers watched video recordings to study different instances of people crossing streets. They found that 27.21% of pedestrians followed the safety rules when crossing, but a significant number did not and should be taught better crossing practices. The study identified three main behaviors that often led to rule violations: not looking both ways before crossing, being distracted, and not crossing cautiously. Pedestrians who were cautious were much more likely to follow the crossing rules compared to those moving at any speed, and those not distracted were more likely to follow the rules than those who were cautious. Additionally, 32.05% of pedestrians were distracted by activities like using phones, talking, or wearing headphones. Among these, 17.7% walked directly across the crosswalk, and 26.21% crossed in a diagonal or zigzag pattern. The study also found that 60% to 87% of the observed behaviors could predict whether a pedestrian would follow crossing rules based on statistical models.

Technological and social distractions at unsignalized and signalized campus crosswalks: A multi-stage naturalistic observation study

The use of personal listening devices (PLDs) is most prevalent among the college attending population. PLDs can be quite distracting, especially when its users are performing focused tasks such as street crossings. Such scenarios are commonplace on campuses of rural higher education institutes, where students must cross multiple unsignalized crosswalks to get to their destination. To evaluate the dangers of PLD use and pedestrian behavior while navigating crosswalks, 1274 pedestrians were systematically observed over nine hours at four crosswalks; naturalistic observations were followed by a survey of 135 pedestrians, and two focus groups with a total of eight participants following a unique three-stage protocol. Results show that societal distractions such as crossing in group settings or talking with other members of a group while crossing led to more risky pedestrian behavior, than did technological distractors such as PLDs or cellphone use. There was also a consensus on hand gesture meanings for pedestrian-driver communication despite the presence of relatively diverse population. Findings from this study can serve as guidelines to develop external human machine interfaces (eHMIs) for automated vehicles, and appropriate countermeasures to reduce pedestrian distractions at crosswalks of higher education institutes.

Analysis of Pedestrians’ Road Crossing Behavior, in Social Groups

A significant percentage of pedestrians walk in social groups (friends, families, or acquaintances who walk together). Although patterns generated by social interactions among group members have been shown to affect crowd dynamics, studies on the effect of social interactions at different crossing phases under low pedestrian density are limited. This study aims to comprehensively examine the influence of size and sex composition on pedestrians’ behaviors when walking alone and with friends in different phases before, during, and after the road crossing. For this, experiences were carried out with controlled small groups of friends (varying size and sex composition) at three unsignalized crosswalks with low pedestrian density. The average speed and distance between the young pedestrians in six segments of the trajectories (two in each phase), extracted from video recordings, were analyzed with linear mixed models. Results show that pedestrians reduce their speed when approaching the curb, they accelerate while on the crosswalk, and reduce again when they reach the other side. In all phases, the average speed of the groups was lower than the single pedestrians, and the females’ groups walked slower than the males, except during the crossing, where no sex-related differences were found. On the contrary, before the crossing, the distance increased and decreased from the second segment in the crosswalk. The smallest distance was observed between the female groups and dyads. These findings have relevant implications for research on pedestrian behavior, helping to better understand the complexity of pedestrian dynamics and improve pedestrian safety.

The impact of vehicle traffic volume on pedestrian behavior at unsignalized crosswalks

The research is focused on analyses of vehicle delays caused by pedestrian crosswalks on one-way streets. The study encompassed three particular locations of unsignalized crosswalks: on the street section between intersections, in the zone of intersection impact, and in the zone of intersection itself. The study revealed that the major impact on traffic jams is observed at a distance of 50-100 m from the unsignalized crosswalk. The study analyses pedestrian behavior and waiting time at such crosswalks. It was confirmed that the pedestrians did not immediately use their priority before passing. The paper presents the change in pedestrian waiting time when crossing the roadway depending on traffic flow. Based on that data, a model was prepared and simulations of pedestrian behavior at unsignalized crosswalks were performed.

The sustained and generalized effects of multifaceted treatment on unsignalized pedestrian crossings

IntroductionOne method of improving pedestrian safety is through a multifaceted intervention program to enhance awareness and enforcement of pedestrian right-of-way laws, which has been shown to significantly improve driver behavior toward pedestrians at unsignalized crosswalks. An intervention using this approach was performed in Saint Paul, Minnesota in 2018. However, the sustainability of the intervention's positive effects on yielding, as well as the potential contributing role of police enforcement and infrastructure such as crosswalk markings, are not as well understood. MethodsThe present study provides a reassessment of driver yielding to pedestrians at unsignalized crosswalks in Saint Paul three years after the original intervention, as well as a comparison with unsignalized crosswalks in neighboring Minneapolis, the latter of which has not received any form of high visibility enforcement. The methodology employed the use of staged crossings and natural pedestrian observations at selected unsignalized crosswalk sites. ResultsAn analysis of driver yielding found that there was a sustained improvement in driver yielding in the reassessment period at generalized non-treated sites in Saint Paul in the final phase of the 2018 intervention, compared to the original baseline pre-treatment measures. Second, comparisons between Minneapolis baseline and original 2018 Saint Paul baseline showed significantly higher yielding averages for Saint Paul, which had prior iterations of high visibility enforcement. ConclusionsThe present research indicates long-term benefits to employing a multi-method intervention to improve pedestrian safety at unsignalized crosswalks and suggests there are moderate benefits to including high visibility enforcement as a component of these programs.

Modeling Interactions of Autonomous/Manual Vehicles and Pedestrians with a Multi-Agent Deep Deterministic Policy Gradient

This article focuses on the development of a stable pedestrian crash avoidance mitigation system for autonomous vehicles (AVs). Previous works have only used simple AV–pedestrian models, which do not reflect the actual interaction and risk status of intelligent intersections with manual vehicles. The paper presents a model that simulates the interaction between automatic driving vehicles and pedestrians on unsignalized crosswalks using the multi-agent deep deterministic policy gradient (MADDPG) algorithm. The MADDPG algorithm optimizes the PCAM strategy through the continuous interaction of multiple independent agents and effectively captures the inherent uncertainty in continuous learning and human behavior. Experimental results show that the MADDPG model can fully mitigate collisions in different scenarios and outperforms the DDPG and DRL algorithms.

A Fundamental Analysis of Road Traffic Factors Affecting Drivers Yielding Behavior at Unsignalized Crosswalks - In the case of Unsignalized Crosswalks at Shinkawa in Chuo Ward, Tokyo -

A Fundamental Analysis of Road Traffic Factors Affecting Drivers Yielding Behavior at Unsignalized Crosswalks - In the case of Unsignalized Crosswalks at Shinkawa in Chuo Ward, Tokyo -

Study of Effects of the Pedestrian’s Standing Position and Behavior at Unsignalized Crosswalk on the Driver Yielding

Study of Effects of the Pedestrian’s Standing Position and Behavior at Unsignalized Crosswalk on the Driver Yielding

Assessing The Impact Of Led-Illuminated Crosswalks On Pedestrian Safety

This study focuses on the impact of LED-illuminated crosswalks on pedestrian safety. The speed profile of vehicles approaching the crosswalk was measured with a Telelaser instrument.In order to test the efficacy of the LED-lighting system on pedestrian safety, the field measurements were performed in several urban road segments in the metropolitan area of Rome (Italy) both in LED-illuminated and non-illuminated conditions. Drivers' behavior while approaching the crosswalk was analyzed in different road sections: two-lane road with one-way traffic, four-lane road with two lane in each direction and no median barrier, and two-lane road with one lane in each direction and no median barrier.The results have shown that an integrated LED-lighting system embedded in the pavement generates a significant speed-reducing effect on vehicles, improving pedestrian safety at unsignalized crosswalks. It was found that vehicles’ speed at crosswalk decreases on average by 19-32% in illuminated conditions.

A Comparative Analysis of the Effects of Road Markings on Driving Behavior when Approaching an Unsignalized Crosswalk

A Comparative Analysis of the Effects of Road Markings on Driving Behavior when Approaching an Unsignalized Crosswalk

The role of yielding cameras in pedestrian-vehicle interactions at un-signalized crosswalks: An application of game theoretical model

ObjectivePedestrian–vehicle interaction has gained substantial interest in the field of travel behavior and safety. Although traffic rules stipulate the right of way at unsignalized crosswalks, the actual behavior of road users is usually based on game-theoretical solutions. Moreover, non-cooperative games between pedestrians and drivers can be more complicated in the presence of law enforcement equipment. This study aimed to investigate the impact of yielding cameras on road users’ joint behavior at unsignalized crosswalks using a game-theoretical model.Methods and analysisA field survey was conducted using aerial and roadside cameras. In the game-theoretical model, road users were assumed to behave in accordance with the quantal response equilibrium. Additionally, the presence of a yielding camera was introduced into the payoff functions. Influencing factors, including demographics, road users’ behavioral characteristics, and environment, were incorporated into road users’ utilities. The beliefs of road users regarding other road users’ actions were also considered in the model. Furthermore, a questionnaire survey was conducted to investigate road users’ knowledge and awareness of yielding cameras and their right of way.ResultsThe results indicate that the yielding camera significantly affected driver behavior but had minimal effect on pedestrians crossing decisions because fewer pedestrians were aware of the yielding camera while crossing. Moreover, the camera increased the probability of confusion in the game between pedestrians and drivers (drivers chose to yield, whereas pedestrians chose to stay), thus adversely affecting traffic efficiency.Novelty and improvementA novel game-theoretical model was established to evaluate road users’ joint behaviors at unsignalized crosswalks. Several practical suggestions have been provided to improve the effectiveness of yielding cameras and traffic efficiency.

A Study on Pedestrian–Vehicle Conflict at Unsignalized Crosswalks Based on Game Theory

A dynamic game model based on multiple decision makers is developed to minimize pedestrian–vehicle conflicts at unsignalized crosswalks. The characteristics of pedestrians and drivers crossing the street are divided into traffic features, behavioral characteristics, and psychological factors, using data collected from a survey of pedestrian crossing behavior. Based on waiting delay and risk assessment, a utility model of pedestrian crossing choice behavior is presented, and a probability model for different phases of the waiting stage is developed by splitting the waiting process into three stages with pedestrian waiting duration. The payment function and the game model of pedestrian–vehicle conflict based on distinct previous decision makers are developed using game theory and “mixed strategy”, and they are resolved in equilibrium.

Communicating perceptions of pedestrian comfort and safety: Structural topic modeling of open response survey comments

Purely quantitative or qualitative studies of perceived comfort and safety have different strengths and limitations related to scope, reliability, and generalizability. To pursue new insights about perceptions of pedestrian comfort and safety, this study uses the novel approach of Structural Topic Modeling to organize open-response comments into prominent topics, or themes, and explore the factors affecting the prevalence and content of topics. The study data come from a survey in which participants rated short video clips of pedestrians interacting with motor vehicles or bicycles at unsignalized crosswalks, and then provided optional open-response comments about each video. Modeling results identified six topics in the text data: (1) driver behaviour and pedestrian risk, (2) pedestrian risk assessment and mitigation, (3) pedestrians not waiting before crossing, (4) cyclists leaving the bicycle lane, (5) cyclists’ yielding necessity, and (6) and cyclists’ speed modifications. The prevalence of the topics was significantly affected by attributes of the interaction (vehicle type—bicycle or car—and its proximity), and attributes of the perceiver (travel habits and self-reported risk aversion). Topic prevalence was unrelated to participants’ comfort and safety ratings for the same interactions, indicating that topic modeling provides a fundamentally different source of information than quantitative severity ratings. The findings help to illuminate why pedestrian-cyclist interactions may attract disproportionate attention from the travelling public, despite their relatively lower risk than interactions with motor vehicle drivers.

Analyzing Pedestrian Behavior at Unsignalized Crosswalks from the Drivers’ Perspective: A Qualitative Study

This study investigated drivers’ perceptions of pedestrian crossing behavior at unsignalized crosswalks, which was less fruitful in quantitative and qualitative traffic research. Subjective and snow-ball sampling were used to conduct semi-structured in-depth interviews based on drivers’ daily driving experience from qualitative research. A theoretical model of pedestrian behavior at unsignalized crosswalks was constructed using the grounded theory and the theoretical saturation test. The model involved 4 three-level codes and 13 two-level codes (main category) used to obtain seven subcategories. The results show that drivers believe that pedestrian characteristics, driver characteristics, and age factors are the three factors that affect pedestrian crossing safety. Targeted improvement measures are put forward to guide the design of pedestrian crossing facilities, pedestrian management and guidance, and future research on conflicts between autonomous vehicles and pedestrians.

Path Planning for Intelligent Vehicle Collision Avoidance of Dynamic Pedestrian Using Att-LSTM, MSFM, and MPC at Unsignalized Crosswalk

In this article, path planning for intelligent vehicle collision avoidance of dynamic pedestrian using attention mechanism-long short-term memory network (Att-LSTM), modified social force model (MSFM), and model predictive control (MPC) is systematically investigated, and pedestrian-dynamic vehicle conflict scene at an unsignalized crosswalk is covered. First, a data-driven stacking fusion model based on the Att-LSTM and MSFM is proposed for pedestrian path prediction. Pedestrian heterogeneity (age and gender) is taken into account for the first time. The data-driven stacking fusion model is verified with the existing methods. Then an MPC-based path planning-tracking system considering pedestrian path prediction is developed. The predicted path of pedestrian is treated as a pedestrian-safety region with the combination of a semiellipse and semicircle, and the front wheel steering angle is calculated to prevent the intelligent vehicle from colliding with the dynamic pedestrians. Simulink–Carsim simulations are presented to simulate the real dynamic environment where crossing pedestrians exist. The results illustrate that the developed MPC system considering pedestrian path prediction can provide dynamic path planning performance acceptably and effectively, and make it possible for the intelligent vehicle to present the great feasibility for pedestrian safety protection and traffic efficiency improvement.

Game Theory-Based Modeling of Multi-Vehicle/Multi-Pedestrian Interaction at Unsignalized Crosswalks

<div class="section abstract"><div class="htmlview paragraph">The improvement of road transport safety requires the development of advanced vehicle safety systems, whose development could be facilitated by using complex interaction models of different road users. To this end, this paper deals with the modeling of multi-vehicle/multi-pedestrian interactions at unsignalized crosswalks. This multi-agent modeling approach extends on the existing basic model covering only single-vehicle/single-pedestrian interactions. The basic model structure and parameters have remained the same, as it was previously experimentally calibrated and thoroughly verified. The proposed modeling procedure employs the basic model within the multi-agent setting based on its application to relevant single-vehicle and single-pedestrian pairs. The resulting, so-called pre-decisions are then used for making final crossing decisions in a current time step for each agent. During the decision making process, each pedestrian takes into account approaching vehicles and their expected future behavior with respect to all pedestrians (i.e., himself/herself and other pedestrians), and vice versa for vehicles. This generalized multi-agent model is conceived to support simulation scenarios concerning multi-lane roads and pedestrians approaching from both sides of a road, as well. The model is verified by means of large-scale simulations and various scenarios.</div></div>

A novel method of predictive collision risk area estimation for proactive pedestrian accident prevention system in urban surveillance infrastructure

Road traffic accidents, especially vehicle–pedestrian collisions in crosswalk, globally pose a severe threat to human lives and have become a leading cause of premature deaths. In order to protect such vulnerable road users from collisions, it is necessary to handle possible conflict in advance and warn road users, not post-facto. A breakthrough for proactively preventing pedestrian collisions is to recognize pedestrian’s potential risks based on vision sensors such as CCTVs. In this study, we propose a predictive collision risk area estimation system at unsignalized crosswalks. The proposed system applied trajectories of vehicles and pedestrians from video footage after preprocessing, and then predicted their trajectories by using deep LSTM networks. With use of predicted trajectories, this system can infer collision risk areas statistically, further severity of levels is divided as danger, warning, and caution. In order to validate the feasibility and applicability of the proposed system, we applied it and assessed the severity of potential risks in two unsignalized spots with different mobility environment in Osan City, Republic of Korea. As a result, the ratio of dangerous scenes is higher in Spot A (0.115) than in Spot B (0.077) when applying the best performance model in each spot, and we found that the risk situation varies depending on the mobility environment.

Investigating relationships among perceptions of yielding, safety, and comfort for pedestrians in unsignalized crosswalks

Interactions with other road users influence the perceived safety and comfort of pedestrians. Yet the relationships among perceptions of yielding, safety, and comfort are poorly understood. To enhance understanding of these key concepts, the objectives of this study are to determine how perception of pedestrian safety at unsignalized crosswalks differs from perception of comfort, and the relationship of each with perception of yielding. A generalized structural equations model is developed using data from an online survey in which 366 participants (i.e., “perceivers”) rated yielding, safety, and comfort for sample videos of pedestrian interactions with motor vehicles and bicycles. Results show that an individual’s perception of yielding plays a crucial role in mediating the effects of interaction attributes (e.g., vehicle speed, proximity) and perceiver attributes (e.g., travel habits) on their perceptions of pedestrian safety and comfort. For example, people who bicycle more frequently perceive pedestrians as more comfortable than people who walk more frequently, rooted in misalignment on what constitutes adequate yielding. Strategies to address pedestrian comfort can focus on a set of key yielding behaviors by drivers and cyclists – particularly allowing the pedestrian to cross first. Motor vehicle drivers must exhibit stronger yielding behavior (e.g., allow a larger time gap) than bicycles to achieve the same level of perceived pedestrian safety and comfort. Although perceptions of safety and comfort are strongly related and similarly impacted by yielding, researchers should be cautious about using the concepts interchangeably because they are differently impacted by attributes of the interaction and perceiver.