Pedestrian Risk Research Articles

Pedestrian Single and Multi-Risk Assessment to SLODs in Urban Built Environment: A Mesoscale Approach

Pedestrians are increasingly exposed to slow-onset disasters (SLODs), such as air pollution and increasing temperatures in urban built environments (BEs). Pedestrians also face risks that arise from the combination of the BE features, the effects of SLODs on the microclimate, their own characteristics (e.g., health and ability), and the way they move and behave in indoor and outdoor BE areas. Thus, the effectiveness of sustainable risk-mitigation solutions for the health of the exposed pedestrians should be defined by considering the overlapping of such factors in critical operational scenarios in which such emergency conditions can appear. This work provides an innovative method to define a BE-oriented pedestrian risk index through a dynamic meso-scale approach that considers the daily variation of risk conditions. The method is ensured by a quick-to-apply approach, which also takes advantage of open-source repositories and tools to collect and manage input data, without the need for time-consuming in situ surveys. The resulting risk conditions are represented through meso-scale maps, which highlight the risk differences between BEs by focusing on their open spaces as fundamental parts of the urban road network. The method is applied to a significant case study (in Milan, Italy). The results demonstrate the ability of the approach to identify key input scenarios for risk assessment and mapping. The proposed methodology can: (1) provide insights for simulation activities in critical BE conditions, thanks to the identification of critical daily conditions for each of the factors and for single and multiple risks and (2) support the development of design and regeneration strategies in SLOD-prone urban BEs, as well as the identification of priority areas in the urban BE.

High School Students’ Psychometric Assessment of Pedestrian Safety and Risk Factors in Ile-Ife, Nigeria

High School Students’ Psychometric Assessment of Pedestrian Safety and Risk Factors in Ile-Ife, Nigeria

Contaminant film thickness affects walkway friction measurements.

Walkway tribometers are used to measure available friction for evaluating walkway safety and pedestrian slip risk. Numerous variables can affect tribometer measurements, including the type and distribution of contaminants on the surface. Here, we quantified the effect of application method on contaminant film thickness, and the effect of film thickness on tribometer measurements on the four reference walkway surfaces used in ASTM F2508-16e. Distilled water, 0.05% sodium lauryl sulfate (SLS) solution, and 0.04% Triton X-100 solution were poured, squirted, and sprayed onto the surfaces to quantify their naturally occurring film thicknesses. These application methods had a significant effect on the resulting film thickness (p < 0.038), with the pour method consistently generating the thickest films and the spray method generating the thinnest films. We then quantified the effect of film thickness for the three contaminants (thickness range 0.3–3.3 mm) on the friction measurements of three common tribometers (Mark IIIB, English XL, and BOT 3000E) on each reference surface. A separate ANOVA was used for each of the 3 × 4 × 3 = 36 combinations of tribometer, surface, and contaminant. Friction measured with the Mark IIIB decreased with increasing film thickness on one surface across all three contaminants and on a second surface with the SLS contaminant. Friction measured with the BOT 3000E was sensitive to film thickness on two surfaces with water and one surface with Triton. The XL was unaffected by contaminant film thickness. Overall, despite significant differences in film thickness with contaminant application method, friction measurements were either insensitive to film thickness or varied only a small amount in all cases except for the Mark IIIB on the roughest surface. Film thickness did not alter the relative slip resistance of the four ASTM F2508 reference surfaces.

A sustainable road safety approach for pedestrians in new cities of Egypt

Over the last decade, Egypt’s growing population and dynamic economy have resulted in a need for greater infrastructure development; consequently, the risk of pedestrians crossing at grade has increased tremendously. For reducing fatalities caused by the conflict between pedestrians crossing at grade and vehicles, pedestrian bridges have been established. Noting that these bridges which are dedicated to human safety are highly expensive, therefore without the fulfilment of conditions of safety, convenience and ease of accessibility they might be a wasted investment. In this respect, site visits and a SWOT analysis were conducted on three pedestrian bridges in New Cairo for monitoring and evaluating the impact of these interventions. The assessment of strengths, weaknesses, opportunities and threats of these projects formed a base for upgrading and the development of new projects. Although, there are some attempts for using escalators for encouraging usability of pedestrian bridges, the research propose a national project using small solar PV systems for the operation of outdoor escalators in a more sustainable manner, which would in turn support the 2030 Agenda for Sustainable Development. This requires joining efforts of all relevant stakeholders in coordinated and rigorous action towards achieving road safety targets.

Driver-Pedestrian Perceptual Models Demonstrate Coupling: Implications for Vehicle Automation

Developing vehicle automation that accommodates other road users and exhibits familiar behaviors may enhance traffic safety, efficiency, and fairness, leading to tolerance of the technology. However, the interdependence between vehicle automation and other road users makes them more challenging than typical control and path planning tasks. Through the lens of joint activity theory, we model driver and pedestrian behavior to explore how they balance and negotiate competing risk and velocity goals through movement. Joint activity theory informs an interpretation of these movements as signals, which can be associated with perceptual processes. We use simulation-based inference to estimate parameters of coupled driver and pedestrian perceptual models using naturalistic driving data. Perceptual models provide links between the processes guiding evaluation of risk and velocity maintenance, and how they govern driver acceleration and pedestrian walking. We found that the coupled simulations describe how drivers adjust their yielding behavior in the face of pedestrian risk, and how risk affects pedestrians’ decisions to cross. Dynamic risk and velocity parameters predicted safety, efficiency, and fairness outcomes, suggesting that the parameters and their dynamic perceptual models describe important components of the interactions. Traditional approaches employ static, summary predictors, which may fail to capture their continuous evolution and negotiation over time. Dynamic models of the interaction between drivers and pedestrians can inform vehicle automation by identifying deviations from communication norms, extracting interaction features, and evaluating communication and coordination.

Pedestrian Safety: Microscopic Analysis of Pedestrian Risk Exposure

Pedestrian Safety: Microscopic Analysis of Pedestrian Risk Exposure

Identification of contributing factors and hotspots of pedestrian-vehicle collisions in urban areas: An alternative hybrid method for small cities

Objective Traffic safety numbers in developing countries show a serious global problem that requires studies and actions to promote safety for the most vulnerable users, such as pedestrians, as a way of contributing to sustainable urban mobility. Therefore, this research proposes a hybrid method to identify contributing factors and critical points according to the profile of crashes involving pedestrians being run over by motor vehicles in small cities. Methods The proposed method uses multivariate data analysis, specifically Exploratory Factor Analysis (EFA) and Cluster Analysis (CA), combined with geospatial tools. The study scenario corresponds to pedestrian-vehicle collisions that occurred in the urban area of Cachoeira do Sul, a small city in Rio Grande do Sul, Brazil, recorded in police reports between 2015 and 2018. Additionally, Geographic Information Tools (GIS) were used to collect characteristics of the road environment. Results According to EFA, a set of attributes configured as contributing factors are discussed according to the components of the traffic system: user, road, vehicle, and environment. Subsequently, a CA was applied with the road-environmental factors, and three pedestrian-vehicle collision profiles were extracted, with clustering according to road segments with homogeneous characteristics. Moreover, a Kernel Density Estimate (KDE) was used to obtain heat maps of the pedestrian collisions profiles. The results allowed interventions to be proposed according to the contributing factors of each profile. Conclusions The multivariate statistical analysis supported the discussion of the factors contributing to the occurrence of pedestrian-vehicle collisions in small cities in developing countries. The spatial visualization of the results showed urban corridors with a high risk for pedestrians and the identification of hotspots in the city. In addition, the study demonstrated that the hybrid method tested is an alternative for the government of cities with few resources to promote safety mobility.

Integrating Vulnerable Road User Safety Criteria into Transportation Asset Management to Prioritize Budget Allocation at the Network Level

Safety is a major worldwide concern due to the increasing number of fatalities of vulnerable road users (VRUs). VRUs are pedestrians, bicyclists, and motorcyclists, and their safety is a priority when making infrastructure management decisions. Traditionally, transportation agencies have adopted transportation asset management (TAM) practices based on performance measures to assess the physical condition of transport infrastructure. This paper describes a framework to incorporate VRU’s safety into the TAM decision-making process. The main objective of the VRU-TAM framework is to mitigate pedestrian fatalities by improving the decision-making process at the strategic and operational management level. The VRU-TAM framework is composed of four phases: assessment, prioritization, scenario analysis, and results. It includes a prioritization methodology using a safety-weighted effectiveness ratio (SWER) to consider pedestrian safety factors and costs in the decision-making process. In a broader perspective, pedestrian safety is affected by driver, demographic, pedestrian, infrastructure, and policy related factors. The decision-making criteria reflected in SWER considers the asset importance, location, pedestrian safety risk, costs, and remaining life in the budget allocation process, and adopts the dynamic bubble up (DBU) technique for budget prioritization at the network level. An example is presented for crosswalks to demonstrate the applicability of the methodology to evaluate different budget-driven scenarios for funding allocation. As a conclusion, it is demonstrated that the outcomes of the budget-driven scenarios following the method that incorporates safety criteria, with tangible metrics, offer a deeper understanding of the effects of budgetary constraints on backlog costs and the remaining life of infrastructure assets.

Spatial analysis of collision risk of child pedestrians – A case of urban elementary school districts in Busan, Korea

A comprehensive understanding of the relationship between pedestrian collision risks for children and the environment is crucial for planning safety policies. Although pedestrian-vehicle collisions are an extensively studied subject in many cities, only a handful of studies focus on children. Previous studies that examined the relationship between pedestrian collision risk for children and environmental factors primarily relied on statistical models, which were limited from accounting for the relationship's spatial heterogeneity. This study takes both statistical and spatial modeling techniques to understand the geography of pedestrian collision risk for children in Busan, Korea. Namely, negative binomial regression and geographically-weighted negative binomial regression were used in modeling the relationship between child pedestrians' collision risk and various environmental factors. Utilizing the collision data from 2014 to 2019, a total of 788 collisions in 297 elementary school districts were analyzed with a set of socioeconomic, transportation, and land-use characteristics. The study found that the geographically-weighted negative binomial regression outperform the negative binomial regression, while both models provided informative results toward characterizing the collision risk of child pedestrians by identifying a set of collision-inducing factors from both global and local perspectives. This study shows that geographically-weighted negative binomial regression is a promising tool for designing safety policies accounting for different regional contexts in various cities. This study found that collision risk varies by school district and local characteristics, thus, a collaborative network between city planners, schools, and local communities is needed to create a safer walking environment for children.

Dynamic Guidance Strategy for Pedestrian Travel in Large-Scale Activity under Harsh Environment

Large-scale activities such as the Winter Olympics are usually held in areas with low temperature or other harsh environments, which greatly affects the spectating experience of pedestrians. In order to improve the travel efficiency and reduce the safety risk of pedestrians, an adaptive information-distribution strategy of VMS (variable message sign) for road networks is proposed to guide the pedestrians. In the proposed strategy, the dynamic feedback mechanism between the VMS information distribution and the state of crowded pedestrians is established, and the dynamic optimization model of the VMS information release layout is formulated. To evaluate the effectiveness of the strategy, a multiagent-based simulation method is proposed. Through numerical simulation, it is found that the guidance strategy can improve the movement efficiency by adjusting releasing duration of VMS information or improving the information obedience rate of pedestrians. In this paper, a large-scale competition area in the Xiaohaituo Mountain in Beijing was taken as an example to simulate the scenarios of ingress and egress with and without the strategy. The results show that the average walking time and the road congestion can be significantly reduced in the road network with the strategy, and the proportion of pedestrians with shorter travel time can be increased. Therefore, the research can provide theoretical foundation and data support for managers to guide passenger flows and improve the spectating experience.

Effects of automatic emergency braking systems on pedestrian crash risk

ObjectiveAutomatic emergency braking (AEB) that detects pedestrians has great potential to reduce pedestrian crashes. The objective of this study was to examine its effects on real-world police-reported crashes. MethodsTwo methods were used to assess the effects of pedestrian-detecting AEB on pedestrian crash risk. Vehicles with and without the system were examined on models where it was an optional feature. Poisson regression was used to estimate the effects of AEB on pedestrian crash rates per insured vehicle year, and quasi-induced exposure using logistic regression compared involvement in pedestrian crashes to a system-irrelevant crash type. ResultsAEB with pedestrian detection was associated with significant reductions of 25%–27% in pedestrian crash risk and 29%–30% in pedestrian injury crash risk. However, there was not evidence that that the system was effective in dark conditions without street lighting, at speed limits of 50 mph or greater, or while the AEB-equipped vehicle was turning. ConclusionsPedestrian-detecting AEB is reducing pedestrian crashes, but its effectiveness could be even greater. For the system to make meaningful reductions in pedestrian fatalities, it is crucial for it to work well in dark and high-speed conditions. Other proven interventions to reduce pedestrian crashes under challenging circumstances, such as improved headlights and roadway-based countermeasures, should continue to be implemented in conjunction with use of AEB to prevent pedestrian crashes most effectively.

Pedestrian safety system with crash prediction

Every year nearly 1.5 million people are dying in traffic collisions around the world, due to the unexpected behavior of pedestrians while crossing the road. To address this problem an augmentation function for predicting the crash risk of the active pedestrian is proposed. The augmentation function has several functions like pre-crash scenario, vehicle trajectory, and pedestrian trajectory. In a Pre-Crash scenario, pedestrian movement such as entering the road boundary or not is detected. The input comes from the sensor which is located at the head of the car. After the pre-crash scenario vehicle trajectory is used to control the speed of the vehicle. Then the Markov IRW model-based pedestrian trajectory finding is used to predict the state of each pedestrian. The states are categorized into three types: Running, Walking and Standing. In this model, the pedestrian types whether the pedestrian is a child or young or old aged people is predicted. And the crash risk is evaluated based on the Monte Carlo algorithm that calculates the minimum detection range for active pedestrians. If the crash risk is exceeded the threshold limit then an augmentation function is activating the evasive action.

Impact Assessment of Waste Odor Source Locations on Pedestrian-Level Exposure Risk

Poor wind environment in residential areas leads to the accumulation of odor from domestic waste, affecting pedestrian health. A reasonable arrangement of waste collection points can reduce pedestrian exposure risks. This study aims to investigate the hydrogen sulfide (H2S) dispersion and residents’ exposure risk at the pedestrian level for five different locations of waste collection points in a residential building array. Simulation results are consistent with the benchmark wind tunnel experiment, validating that the used turbulence model and numerical methods show good agreement with the predictions of the aforementioned problem. Results indicate that the dimensionless concentration of H2S and personal intake fraction in a residential area are lower when the collection point is at the corner of the building array periphery. When the collection point is located in the middle of the periphery of the building array or between two adjacent buildings in the center of the array, the local dimensionless concentration of H2S is 50 at the pedestrian level, and the personal intake fraction is three orders of magnitude higher than that at the corner of the building array periphery. The findings provide a reference for the layout of waste collection points in high-density residential areas and reduction in outdoor exposure risk.

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.

Impacts of enforcement cameras on pedestrians’ risk perception and drivers’ behaviors at non-signalized crosswalks

Introduction: Pedestrians are more vulnerable to traffic crashes than other road users, particularly at non-signalized crosswalks. Safety measures (such as law enforcement cameras) can be implemented to regulate road users’ behavior and traffic safety. This study evaluates the effects of such cameras on pedestrian-vehicle conflicts by investigating different interaction patterns of pedestrian risk perception and driving style. Data: Field investigations were conducted at four non-signalized crosswalks. Video data were collected using unmanned aerial vehicles and roadside cameras. Method: Two-step cluster analysis and k-means cluster analysis were employed to classify the pedestrian’s behavior and driving style, respectively. Surrogate safety measures were adopted to measure the pedestrian-vehicle conflicts. Results and conclusions: The results suggest that the implementation of cameras would decrease both the actual and perceived risks of pedestrians, while the heterogeneity between the actual and perceived risk is more obvious at camera sites. They also indicate that the cameras have a positive influence on reducing drivers’ aggressiveness and conflict severity. In terms of pedestrian-vehicle interaction patterns, the most severe conflicts occur when the pedestrian perceived risk level is low and the driving style is aggressive. Such dangerous interactions are observed more frequently at camera sites. In contrast, a safer interaction pattern is associated with a moderate driving style and cautious crossing behavior, which is more frequently observed at comparison sites. However, regardless of which interaction pattern is observed, the conflict severity is found to be lower at camera sites, indicating the effectiveness of the cameras. Practical Applications: Supplementary facilities, such as warning signs, flash lights, and speed control measures, should be implemented to maintain the effectiveness of the law enforcement cameras.

Applying Association Rules Mining to Investigate Pedestrian Fatal and Injury Crash Patterns Under Different Lighting Conditions

The pattern of pedestrian crashes varies greatly depending on lighting circumstances, emphasizing the need to examine pedestrian crashes in various lighting conditions. Using Louisiana pedestrian fatal and injury crash data (2010–2019), this study applied Association Rules Mining (ARM) to identify the hidden pattern of crash risk factors according to three different lighting conditions (daylight, dark-with-streetlight, and dark-no-streetlight). Based on the generated rules, the results show that daylight pedestrian crashes are associated with children (&lt;15 years), senior pedestrians (&gt;64 years), older drivers (&gt;64 years), and other driving behaviors such as “failure to yield,”“inattentive/distracted,”“illness/fatigue/asleep.” Additionally, young drivers (15–24 years) are involved in severe pedestrian crashes in daylight conditions. This study also found pedestrian alcohol/drug involvement as the most frequent item in the dark-with-streetlight condition. This crash type is particularly associated with pedestrian action (crossing intersection/midblock), driver age (55–64 years), speed limit (30–35 mph), and specific area type (business with mixed residential area). Fatal pedestrian crashes are found to be associated with roadways with high speed limits (&gt;50 mph) during the dark without streetlight condition. Some other risk factors linked with “high speed limit” related crashes are pedestrians walking with/against the traffic, presence of pedestrian dark clothing, and pedestrian alcohol/drug involvement. The research findings are expected to provide an improved understanding of the underlying relationships between pedestrian crash risk factors and specific lighting conditions. Highway safety experts can utilize these findings to conduct a decision-making process for selecting effective countermeasures to reduce pedestrian crashes strategically.

Exploring the impacts of street layout on the frequency of pedestrian crashes: A micro-level study

Introduction: Pedestrian safety has become a critical issue since walking is increasingly promoted as a sustainable transport mode. However, pedestrians are vulnerable to severe injury and mortality in road crashes. Therefore, it is important to understand the factors that affect the safety of pedestrians. This paper investigates the impacts of street layout on the frequency of pedestrian crashes by examining the interactive pattern of built environment, crossing facilities, and road characteristics. Method: A surrogate exposure variable of pedestrian crashes at the road-segment level is proposed by considering the locations of crossing facilities, distribution of points of interest (POIs), road characteristics, and pedestrian activities. A network-based kernel density technique is used to identify the pedestrian crash risk at the road segment level. Bayesian spatial models based on different exposure variables are employed and compared. Results: The results suggest that models using the surrogate exposure of pedestrian crashes provide better model fit than the ones simply using the density of pedestrians. It is also found that the presence of POIs is related to a higher risk of pedestrian-vehicle crash. In addition, a significantly higher number of pedestrian crashes are found to occur on segments with more bus stops and metro stations. Results also show that the longer the distance between the crossing facilities and road segments, the more pedestrian crashes are observed. Conclusions: The proposed aggregated indicator can provide more efficient exposure and higher prediction accuracy than the density of pedestrians. Besides, the POIs, crossing facilities, and road types were all significantly related to pedestrian crashes. Practical Applications: Our results suggest that the locations of POIs and transport facilities should be planned in a way that can decrease the number of road crossed or guide pedestrians to take safe crossing path.

Adverse health and environmental outcomes of cycling in heavily polluted urban environments

Cycling is a healthy habit; however, are its benefits outweighing risks when biking in heavily trafficked and air-polluted cities? Research involved studying contamination with traffic-related elements of dust collected from bike paths located in top trafficked cities of Europe in Poland. Human health risk was assessed via inhalation and ingestion pathways for adults and children. Bike path dust was heavily contaminated with Zn, Cd (Geoaccumulation index Igeo 4) and Pb (Igeo 3), sourced predominantly from nonexhaust car emissions. The concentrations of metals in dust decreased in the following descending order: Zn > Mn > Cu > Pb > Cr > Cd. A fractionation study revealed that Zn and Cd are almost entirely bioavailable (Mobility factor MF above 90%), causing hazards to humans and the environment. The highest congested intersections result in more TRAP-contaminated dust deposited on bike paths, which is easily resuspended, posing a health risk for cyclists or pedestrians. Avoiding cycling in proximity to heavily trafficked routes should be considered, when possible, as well as physical removal of dust by wet sweeping to limit dust resuspension.

Predicting effects of built environment on fatal pedestrian accidents at location-specific level: Application of XGBoost and SHAP

Understanding locally heterogeneous physical contexts in built environment is of great importance in developing preemptive countermeasures to mitigate pedestrian fatality risks. In this study, we aim to investigate the non-linear relationship between physical factors and pedestrian fatality at a location-specific level using a machine learning approach. The state-of-art machine learning algorithm, eXtreme Gradient Boosting (XGBoost), is employed for a binary classification problem, in which nationwide locations where fatal pedestrian accidents occurred for the years from 2012 to 2019 in Korea serve as positive samples (np = 13,366). For negative samples, locations with no pedestrian accidents are selected randomly to the size that is 10 times larger (nn = 133,660) than positive samples. Fifteen features under the categories of road conditions, road facilities, road networks, and land uses are assigned to both the positive and negative sample locations using Geographic Information System (GIS). A method is proposed to avoid the class imbalance problem, and a final unbiased model is utilized to predict fatal pedestrian risks at the negative sample locations. In addition, Shapley Additive Explanations (SHAP) is introduced to provide a robust interpretation of the XGBoos prediction results. It is shown that 21.6% of the negative sample locations have a probability of fatal pedestrian accidents greater than 0.5 (or 78.4% accuracy). Generally, a road segment that lies in many of the shortest routes in a dense residential area with many lively activities from aligned buildings is a potential spot for fatal pedestrian accidents. However, based on the SHAP interpretation, the relationships between the features and pedestrian fatality are found nonlinear and locally heterogeneous. We discuss the implications of this result has for drafting policy recommendations to reduce pedestrian fatalities.

Profiles of Pedestrian Risk Behavior While Crossing the Street

Profiles of Pedestrian Risk Behavior While Crossing the Street