Urban Crosswalks Research Articles

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.

Examining safe spaces for pedestrians and e-bicyclists at urban crosswalks: An analysis based on drone-captured video

Despite numerous theoretical and empirical studies exploring the spatial needs of road users, a significant gap remains in validating these findings with extensive real-world data sets. This study presents the idea of “safe spaces,” outlining the buffer zones that both walkers and e-bicyclists maintain when crossing streets, while also taking safety and psychological well-being into consideration. We used drones to gather the study's trajectory data at three significant crossings in Xi'an, China. Multi-coordinate system transformation enabled us to determine the relative positions of individuals and moving objects within their visual domain. Relative position frequency heat maps were generated to explore safe distance demands in different directions. The safety space was then fitted using the least squares method. Our research demonstrates that whereas e-bicyclists maintain semi-elliptical safe spaces at street crossings, walkers maintain semi-circular safe spaces, and the sizes of these zones increase in direct proportion to their relative speeds. However, the safe space size oscillates within a defined range above a particular speed threshold. Notably, e-bicyclists require larger safety distances forward and are more sensitive to speed variations. Our knowledge of the dynamics of safe spaces for walkers and e-bicyclists at street crossings is improved by this work, with emphasis on the role of speed and pedestrian numbers in shaping these spaces. The incorporation of real-world data from drone footage significantly strengthens the validity and reliability of our findings, bridging a crucial empirical gap in the existing literature. Additionally, this paper introduces a crowding coefficient based on safe space and proposes a new method using safe space to aid traffic conflict metrics PET, providing valuable insights for identifying crowd congestion levels and capturing traffic conflict events. The practical implications of our findings extend to urban planning, traffic management, and safety of vulnerable road users. Ultimately, this research contributes to the development of safer and more efficient urban environments for all road users.

Leading Pedestrian Intervals at Urban Crosswalks: Effects on Safety for Travelers Who Are Blind

Introduction: The use of leading pedestrian intervals (LPIs) creates safer street crossings for typical pedestrians, giving them a head-start into the crosswalk. The LPI, however, delays the onset of the traditional traffic sound cue that pedestrians who are blind use to initiate crossing streets. LPIs can create situations where pedestrians who are blind will frequently begin or end crossings or both against the pedestrian signal. Methods: The researchers conducted two sets of observations in an urban environment. They measured the seconds from the initiation of the vehicular circular green signal to the front of the first vehicle passing through the center of the intersection (n = 40) to calculate the average driver's delay. Pedestrians who are blind, to confirm a straight-through surge of parallel traffic (i.e. not turning vehicles), listen for a vehicle to reach the roadway center to know it is the appropriate time to initiate a crossing. In the second set of observations (n = 40), the researchers recorded the length of the Walk, Flashing Don’t Walk, and LPI to calculate average impacts on crossing. Results: The average time for vehicles to reach the center of the intersection was 6.0 s. When there was an LPI, on average the clearance for pedestrians after reaching the far corner was 0.49 s; for Walk intervals, there was an average of 3.35 s margin of time to begin crossing. Discussion: These observational studies verify the crossing latencies for pedestrians who are blind. At crosswalks with LPI, pedestrians can be expected to cross after the Walk sign has expired 15 to 38% of the time and end their crossing 40 to 82% of the time when the visual display says Don’t Walk. Implications for Practitioners: Orientation and mobility specialists should instruct students on how to identify intersections with LPI to assist in decision making. Traffic management remediation is the installation of an accessible pedestrian signal (APS); specialists should advocate for the installation of APS where LPIs are implemented and teach students how to use APS.

Quantitative study of vehicle-pedestrian interactions: Towards pedestrian-adapted lighting communication functions for autonomous vehicles

This paper reports the main conclusions of a fielding observation of vehicle-pedestrian interactions at urban crosswalks, by describing the types, sequences, spatial distributions and probabilities of occurrence of the vehicle and pedestrian behaviors. This study was motivated by the fact that in a near future, with the introduction of autonomous vehicles (AVs), human drivers will become mere passengers, no longer being able to participate into the traffic interactions. With the purpose of recreating the necessary interactions, there is a strong need of new communication abilities for AVs to express their status and intentions, especially to pedestrians who constitute the most vulnerable road users. As pedestrians highly rely on the actual behavioral mechanism to interact with vehicles, it looks preferable to take into account this mechanism in the design of new communication functions. In this study, through more than one hundred of video-recorded vehicle-pedestrian interaction scenes at urban crosswalks, eight scenarios were classified with respect to the different behavioral sequences. Based on the measured position of pedestrians relative to the vehicle at the time of the significant behaviors, quantitative analysis shows that distinct patterns exist for the pedestrian gaze behavior and the vehicle slowing down behavior as a function of Vehicle-to-Pedestrian (V2P) distance and angle.

Roles of personal and environmental factors in the red light running propensity of pedestrian: Case study at the urban crosswalks

Pedestrian is vulnerable to mortality and severe injury in road crashes. Red light running violation of pedestrians is one of the leading causes to the crashes at signalized intersections, at which the crash involvement rates of pedestrians are high. Therefore, it is important to identify the factors that affect the propensity of red light running of pedestrian. In this study, effects of both personal factors (pedestrians’ demographics and behavior) and environmental factors (presence and behavior of other pedestrians, signal time, and traffic condition) on the individual decision of red light running violation are examined, using the video observation surveys at the signalized crossings that are prone to pedestrian-vehicle crashes and have moderate pedestrian and vehicular traffic volumes in the urban area. Crossing behaviors of 6320 pedestrians are captured. Results of a random parameter logit model indicate that pedestrian gender, age, number of lanes, presence of a companion, number of pedestrians around, presence of other violators in the same cycle, time to green, red time, traffic volume, and percentage of heavy vehicles all affect the propensity of red light running violation of pedestrians. Also, there are significant interaction effects by pedestrian’s gender and age, presence of other violators, with a companion, and traffic volume on the propensity. Findings are indicative to the development of effective engineering, enforcement and educational initiatives combating the red light running violation behavior of pedestrians. Therefore, pedestrian safety level at the signalized intersections can be enhanced.

Inferring Pedestrian Motions at Urban Crosswalks

Robust prediction of pedestrian behavior is one of the most challenging problems for autonomous driving. Particularly, predicting pedestrian crossings at crosswalks is of considerable importance for avoiding accidents on the one hand and not unnecessarily slowing down traffic on the other hand. Traditional model-based motion tracking and prediction approaches have difficulties in capturing abrupt changes in motions, as humans can perform them. In this paper, an approach for predicting pedestrian motions that combines established motion tracking algorithms with data-driven methods is presented. The approach is built upon a hierarchical structure, where first, the intent of each pedestrian is classified. Then, the approach computes several qualitative metrics, such as time-to-cross, for the pedestrians classified as crossing. The approach is evaluated on a challenging urban data set collected for different types of crosswalks such as roundabouts and straight roads. The evaluation also provides a thorough analysis of the generalization performance of the proposed approach.

Assessing the Effect of Pedestrians’ Use of Cell Phones on Their Walking Behavior: A Study Based on Automated Video Analysis

The objective of the study is to assess the effect of the use of cell phones while walking at urban crosswalks. The methodology uses recent findings in health science concerning the relationship between tempo-spatial characteristics of gait and the cognitive abilities of pedestrians. Gait measures are shown to be affected by the complexity of the task (e.g., talking and texting) performed during walking. This study focuses on the effect of distraction states, distraction types (visual such as texting/reading and auditory such as talking/listening), and pedestrian-vehicle interactions on the gait parameters of pedestrians at crosswalks. Experiments are performed on a video data set near a college campus in the city of Kamloops, British Columbia. The analysis relies on automated video-based data collection using a computer vision technique. The benefits of such an automated system include the ability to capture the natural movement of pedestrians and minimizing the risk of disturbing their behavior. Results show that pedestrians distracted by texting/reading (visually) or talking/listening (auditory) while walking tend to reduce and control their walking speed by adjusting their step length or step frequency, respectively. Pedestrians distracted by texting/reading (visually) have significantly lower step length and are less stable in walking. Distracted pedestrians involved in interactions with approaching vehicles tend to reduce and control their walking speeds by adjusting their step frequencies. This research can find applications in pedestrian facility design, modeling and calibrating pedestrian simulations, and pedestrian safety intervention programs and legislative actions.

Analysis of drivers’ performance in response to potential collision with pedestrians at urban crosswalks

Protection of vulnerable road users has been an increasingly important requirement for today's autonomous vehicles. Analysis of drivers’ response to potential collision with pedestrians can provide guidance for vehicle evasive manoeuvre and data support for traffic collision modelling. Field traffic data were collected by video recording and image processing at urban midblock crosswalks in Beijing, China and Munich, Germany. The drivers’ response to vehicle–pedestrian conflict is discussed by deceleration and acceleration phases considering the lane-based kinematics of vehicles. Some basic characteristics describing the driver behaviour in an evasive process are statistically analysed, including the yielding decision, space history of deceleration, deceleration rate choice, and accelerating behaviour. Results show significant differences in drivers’ yielding decisions. In addition, the onset of braking and the trend of the space history of average deceleration rate during the drivers’ approaching process have been quantitatively proposed. The contributing factors to driver's yielding behaviour are analysed by the Binary Logit Model. The behavioural differences address the needs to make intercultural adaptation when introducing new autonomous vehicle technologies to developing countries. This study provides a basis for establishing evasive decision corrections for drivers or driverless vehicles.

Pedestrian behaviors at and perceptions towards various pedestrian facilities: an examination based on observation and survey data

This paper presents findings from an observational study of pedestrian behaviors at various urban crosswalks and a pedestrian user survey which sought pedestrian perceptions toward various pedestrian facilities in a divided urban boulevard located next to a large university campus, Michigan State University, East Lansing, MI, USA. Such facilities included signalized and unsignalized intersection crosswalks, unsignalized marked and non-striped midblock crosswalks, physical barriers (vegetation and two-foot high concrete wall), midblock crosswalk shelters, colored paving (red brick pavement) at medians and curbs, and pedestrian warning signs at midblock crossing locations, messaging “cross only when traffic clears.” Pedestrian behavior data were obtained from the reduction of video images of pedestrian movements recorded throughout the study site. Pedestrian perceptions information was obtained through a user survey completed by pedestrians using the study site. It was found that unsignalized midblock crosswalks were the treatment of preference to pedestrians (83% reported a preference to cross) and also showed high crossing compliance rate of pedestrians (71.2%). It was also evident that the crosswalk location, relative to the origin and destination of the pedestrian, was the most influential decision factor for pedestrians deciding to cross at a designated location (90% said so). Proper traffic control can further encourage pedestrian crossings at designated locations since the effect of the availability of pedestrian signal to influence pedestrians’ decisions to cross at a specific location was quite high (74% said so). Moreover, vegetation and concrete barriers influenced the decision to cross of a significant number of pedestrians surveyed (65%). It is expected that the findings from this study will help traffic engineers, urban planners and policy makers understand pedestrian behaviors and attitudes at/towards pedestrian crosswalks.