Pedestrian Deaths Research Articles

Inclusive intervention design for vulnerable road users: Applying co-design and behaviour change model in Bangladesh

In developing countries, it is debatable whether poor design of facilities or violation of traffic rules by road users is the leading cause of pedestrian injuries and deaths. Professionals, pedestrians and drivers tend to blame each other. Shared responsibility for road safety is crucial for protecting vulnerable road users such as commuting students and workers who face higher injury risks while crossing highways. While the Safe System approach emphasises authorities’ responsibility for safe facilities, understanding user needs and promoting behaviour change remain underexplored. This study investigates the current design practices in Bangladesh. It compares the impact of conventional design with co-design on intervention quality and examines the further benefits of integrating a behaviour change model ‘COM-B’.Local road agency professionals applied the design process and suggested interventions at four highway sites. Subsequently, four focus group sessions were conducted with students and workers, followed by four design workshops. In each workshop, participants were randomly assigned to two design groups (without and with the application of the behaviour change model), where they designed interventions facilitated by professionals. Lastly, perception ratings of stakeholders and safety assessments by four experts were conducted to evaluate the efficacy of all interventions.The findings highlight major usability problems in conventional designs, while co-designed interventions demonstrate clear improvements. Notably, integrating a behaviour change model further enhances effectiveness. Stakeholder interviews reveal that co-design fosters shared responsibility and addresses the blame culture. The co-design approach and application of the behaviour change model can address design flaws and promote the proper use of facilities.

Daily motor vehicle traffic volume and other risk factors associated with road deaths in U.S. counties

Introduction: Road death risk is often characterized as deaths per volume of traffic in geographic regions, the denominator in miles or kilometers supposedly indicative of the magnitude of risk exposure. This paper reports an examination of the differences in the predictive value of factors hypothesized to influence traffic volume and road death risk. Method: The association of 11 risk factors in U.S. counties during the first 7 months of 2020 was examined for consistency of predictions of road death and traffic volume measured by cell phone and vehicle location data. The study employed least squares regression for traffic volume and Poisson regression for deaths with the population as the offset variable. Results: The directions of the regression coefficients for traffic volume and odds of road deaths per population were opposite from one another for 9 of the 11 variables in the analysis of vehicle occupant deaths. Only the coefficients for maximum daily temperature and Saturday travel were in the same direction. The confidence intervals of three risk ratios for pedestrian deaths indicated low reliability but most of the predictor variables were opposite in association with traffic volume and odds of death. Although traffic volume plunged in the first weeks of the pandemic, the results for the months before and during the COVID-19 pandemic were similar. Practical applications: Traffic volume is an inverse risk factor for road deaths at the local level, likely the result of lower speeds on congested roads. Without the application of countermeasures aimed at reducing speed and other risk factors, the reduction of road congestion is likely to increase deaths.

Injury patterns in motor vehicle collision–youth pedestrian deaths

Objective The objective of this study was to describe fatal pedestrian injury patterns in youth aged 15 to 24 years old and correlate them with motor vehicle collision (MVC) dynamics and pedestrian kinematics using data from medicolegal death investigations of MVCs occurring in the current Canadian motor vehicle (MV) fleet. Methods Based on a systematic literature review, MVC–pedestrian injuries were collated in an injury data collection form (IDCF). The IDCF was coded using the Abbreviated Injury Scale (AIS) 2015 revision. The AIS of the most frequent severe injury was noted for individual body regions. The Maximum AIS (MAIS) was used to define the most severe injury to the body overall and by body regions (MAISBR). This study focused on serious to maximal injuries (AIS 3–6) that had an increasing likelihood of causing death. The IDCF was used to extract collision and injury data from the Office of the Chief Coroner for Ontario (OCCO) database of postmortem examinations done at the Provincial Forensic Pathology Unit (PFPU) in Toronto, Canada, and other provincial facilities between 2013 and 2019. Injury data were correlated with data about the MVs and MV dynamics and pedestrian kinematics. The study was approved by the Western University Health Science Research Ethics Board (Project ID: 113440; Lawson Health Research Institute Approval No. R-19-066). Results There were 88 youth, including 54 (61.4%) males and 34 (38.6%) females. Youth pedestrians comprised 13.1% (88/670) of all autopsied pedestrians. Cars (n = 25/88, 28.4%) were the most frequent type of vehicle in single-vehicle impacts, but collectively vehicles with high hood edges (i.e., greater distance between the ground and hood edge) were in the majority. Forward projection (n = 34/88, 38.6%) was the most frequent type of pedestrian kinematics. Regardless of the type of vehicle, there was a tendency in most cases for the median MAISBR ≥ 3 to involve the head and thorax. A similar trend was seen in most of the pedestrian kinematics involving the various frontal impacts. Of the 88 cases, at least 63 (71.6%) were known to be engaged in risk-taking behaviors (e.g., activity on roadway). At least 12 deaths were nonaccidental (8 suicides and 4 homicides). Some activities may have been impairment related, because 26/63 (41.3%) pedestrians undertaking risk-taking behavior on the roadway were impaired. Toxicological analyses revealed that over half of the cases (47/88, 53.4%) tested positive for a drug that could have affected behavior. Ethanol was the most common. Thirty-one had positive blood results. Conclusion A fatal dyad of head and thorax trauma was observed for pedestrians struck by cars. For those pedestrians hit by vehicles with high hood edges, which were involved in the majority of cases, a fatal triad of injuries to the head, thorax, and abdomen/retroperitoneum was observed. Most deaths occurred from frontal collisions and at speeds more than 35 km/h.

Analysis of Factors Influencing Driver Yielding Behavior at Midblock Crosswalks on Urban Arterial Roads in Thailand

Globally, road traffic collisions cause over a million deaths annually, with pedestrians accounting for 23%. In developing countries, most pedestrian deaths occur on urban arterial roads, particularly at midblock crossings. This study analyzes the factors influencing driver yielding behavior at midblock crosswalks on urban arterial roads in Thailand. This study analyzed the factors influencing driver yielding behavior at the midblock crosswalk before and after the upgrade from a zebra crossing (C1) to a smart pedestrian crossing (C2), which is a smart traffic signal detecting and controlling pedestrians and vehicles entering the crosswalk. Video-based observations were used to assess driver yielding behavior, with multinomial logistic regression applied to develop driver yielding behavior models. The results revealed that the chances of a driver yielding at C2 were higher than at C1, and the yielding rate increased by 74%. The models indicate that the number and width of traffic lanes, width and length of crosswalks, vulnerable group, number of pedestrians, pedestrian crossing time, number of vehicles, vehicle speed, headway, post-encroachment time between a vehicle and pedestrian, and roadside parking are the significant factors influencing yielding behavior. These findings propose measures to set proper crosswalk improvements (e.g., curb extensions), speed reduction measures, enforcement (e.g., parking restrictions), public awareness campaigns, and education initiatives.

Emergency Department Visits for Pedestrians Injured in Motor Vehicle Traffic Crashes - United States, January 2021-December 2023.

Traffic-related pedestrian deaths in the United States reached a 40-year high in 2021. Each year, pedestrians also suffer nonfatal traffic-related injuries requiring medical treatment. Near real-time emergency department visit data from CDC's National Syndromic Surveillance Program during January 2021-December 2023 indicated that among approximately 301 million visits identified, 137,325 involved a pedestrian injury (overall visit proportion=45.62 per 100,000 visits). The proportions of visits for pedestrian injury were 1.53-2.47 times as high among six racial and ethnic minority groups as that among non-Hispanic White persons. Compared with persons aged ≥65 years, proportions among those aged 15-24 and 25-34 years were 2.83 and 2.61 times as high, respectively. The visit proportion was 1.93 times as high among males as among females, and 1.21 times as high during September-November as during June-August. Timely pedestrian injury data can help collaborating federal, state, and local partners rapidly monitor trends, identify disparities, and implement strategies supporting the Safe System approach, a framework for preventing traffic injuries among all road users.

Analysis of the elderly pedestrian traffic accidents in urban scenarios: the case of the Spanish municipalities

As the elderly population grows, there is a greater concern for their safety on the roads. This is particularly important for elderly pedestrians who are more vulnerable to accidents. In Spain, one of the most aged countries in the world, the elderly accounted for 70% of all pedestrian deaths in 2019. In this study, the focus was on analysing the occurrence of elderly pedestrian-vehicle collisions in Spanish municipalities and how it is related to the built environment. The study used the hurdle negative binomial model to analyse the number of elderly and non-elderly pedestrian accidents per municipality in 2016-2019. The exploratory analysis showed that cities above 50,000 inhabitants were safer for the elderly, and larger provincial capitals had lower elderly pedestrian traffic accident rates. The occurrence of all pedestrian traffic accidents was linked to the socio-demographic features. For elderly pedestrians, land use was found to be influential, with a lower proportion of land covered by manufacturing and service activities linked to a smaller number of accidents. Results showed that improving road safety for older pedestrians may not necessarily compromise the situation for the rest of population. Hence, policymakers should focus on infrastructure improvements adapted to the needs of elderly pedestrians.

Road Traffic Injuries and the Built Environment in Bogotá, Colombia, 2015-2019: A Cross-Sectional Analysis.

Nine in 10 road traffic deaths occur in low- and middle-income countries (LMICs). Despite this disproportionate burden, few studies have examined built environment correlates of road traffic injury in these settings, including in Latin America. We examined road traffic collisions in Bogotá, Colombia, occurring between 2015 and 2019, and assessed the association between neighborhood-level built environment features and pedestrian injury and death. We used descriptive statistics to characterize all police-reported road traffic collisions that occurred in Bogotá between 2015 and 2019. Cluster detection was used to identify spatial clustering of pedestrian collisions. Adjusted multivariate Poisson regression models were fit to examine associations between several neighborhood-built environment features and rate of pedestrian road traffic injury and death. A total of 173,443 police-reported traffic collisions occurred in Bogotá between 2015 and 2019. Pedestrians made up about 25% of road traffic injuries and 50% of road traffic deaths in Bogotá between 2015 and 2019. Pedestrian collisions were spatially clustered in the southwestern region of Bogotá. Neighborhoods with more street trees (RR, 0.90; 95% CI, 0.82-0.98), traffic signals (0.89, 0.81-0.99), and bus stops (0.89, 0.82-0.97) were associated with lower pedestrian road traffic deaths. Neighborhoods with greater density of large roads were associated with higher pedestrian injury. Our findings highlight the potential for pedestrian-friendly infrastructure to promote safer interactions between pedestrians and motorists in Bogotá and in similar urban contexts globally.

ANALYSIS OF PEDESTRIAN CHARACTERISTICS CROSSING ALONG ROADS

Pedestrian crossing represents a substantial problem. In Iraq, there are no spaces marked specifically for pedestrians, which causes many conflicts between vehicles and pedestrians that lead to many accidents. The pedestrian death rate has increased recently due to the deficiency in adequate pedestrian infrastructure. However, to date, limited research has measured pedestrian behavior at crossing intersections in Iraq. There is a need to carry out in-depth studies to analyze crossing behavior to increase traffic efficiency and pedestrian crossing safety. Pedestrian crossing behavior is a serious issue to be addressed to provide adequate pedestrian facilities to enhance the pedestrian traffic environment. Road safety can be improved by locating crossing locations at the right locations and enforcing laws for pedestrian crossing. This study analyzes pedestrian crossing behavior in Baghdad City, Iraq, for four intersections at an unmarked crossing in the Central Business District (CBD) area. All required data were collected by video recording and a field questionnaire. Then, the data were extracted from video recordings and classified according to the selected variables. The period for observing the behavior was during the morning peak hours (November; time: 8:00 to 9:00 a.m.) for three days per week during normal conditions. This study examines pedestrian characteristics, vehicle/pedestrian flow characteristics, and traffic environment. Crossing patterns were followed for different gender and age groups. The finding reveals that the mean pedestrian speed is 1.33 m/sec. Also, males have a higher speed than females. The influences of age, gender, group size, and road width significantly affected pedestrian speed. The pedestrian speed decreased as pedestrian age increased. Gender and group size had significant effects on distinct crossing speeds. In addition, there is a weak significant correlation between pedestrian speed and selected variables. The study recommended specific marked places where a pedestrian must be located, and according to the pedestrian speed estimated in this study, a signal control for a pedestrian is recommended to be set up beside the street to organize the crossing with appropriate time for crossing safely.

Darkness and Death in the U.S.: Walking Distances Across the Nation by Time of Day and Time of Year

This paper examines walk distances across the United States by time of day and year, using data from the National Household Travel Survey 2016/2017, to understand factors contributing to higher pedestrian deaths at night across various states. Hurdle regression predict daily walk-miles traveled (WMT) and nighttime WMT to show how decision to walk and distances walked on each survey day and night vary significantly with demographic attributes, time of year, latitude, state of residence, and other factors. Longer daylight hours and more nighttime walking do not appear to be the reasons for some states’ much higher pedestrian fatality rates.

The role of autonomous vehicles in transportation equity in Tempe, Arizona

In 2016, The National Highway Traffic Safety Administration reported that human error is involved in 94–96% of all motor vehicle crashes. Also in 2016, Bonnefon et al. predicted that autonomous vehicles could eliminate 90% of traffic collisions due to their elimination of human error. However, questions of safety, accessibility, and social equity have arisen after the first pedestrian death by an autonomous vehicle in its testing phase occurred in Tempe, AZ, in 2018. This project analyzes how social equity issues shape the discussion, creation, and implementation of governmental policies and regulations surrounding driverless automobiles in Tempe, using policy and text analysis as well as semi-structured interviews of government officials or residents of Tempe. Informed by the concept of the right to the city and critical legal studies, this research suggests that public policy around autonomous vehicles does create new and expand existing spaces for inequality in Tempe. This is exacerbated by increased awareness of inequality within Arizona’s autonomous vehicle regulation scheme and its entire transportation system after the first pedestrian death by autonomous vehicle.

Systems-Level Evaluation of Safe Routes to School Policies in El Paso, Texas: A Modeling Study on Health and Economic Outcomes.

Safe Routes to School (SRTS) policies are linked to physical health benefits for school-age children; however, few studies have assessed long-term impacts on cardiovascular disease (CVD). This study used systems science methods to predict long-term health and economic impact of SRTS among school-age children in El Paso County, Texas. We developed an agent-based model containing 2 modules: the pedestrian injury module and the CVD module. We simulated 10 000 school-age children under 2 scenarios-SRTS policies implemented and no SRTS policies implemented-and then calculated pedestrian injuries, pedestrian injury-related deaths, coronary heart disease (CHD) and stroke events, and health care costs. When SRTS policies were implemented, the model estimated 157 fewer CHD cases and 217 fewer stroke cases per 10 000 people and reduced CVD-related health care costs ($13 788 per person). The model also predicted 129 fewer pedestrian injuries and 1.3 injury-related deaths per 10 000 people and $2417 savings in injury-related health care costs. SRTS could save an estimated $16 205 per person in health care costs. This simulation shows SRTS in El Paso County could prevent pedestrian injuries among school-age children and protect cardiovascular health in the long term. Our findings provide evidence for practitioners and policy makers to advocate for SRTS policies at the local level.

Longitudinal Spatial Trends in U.S. Pedestrian Fatalities, 1999–2020

The number of pedestrian deaths from motor vehicle crashes in the U.S. has risen 59% since 2009. Several studies have researched crash characteristics—such as the people, vehicles, and roadways involved—when examining this sharp increase. But where are these fatalities occurring and what spatial characteristics of these locations could be influencing this trend? We looked at pedestrian fatality data from the National Highway Traffic Safety Administration’s Fatality Analysis Reporting System and socioeconomic, demographic, and built environment data from the U.S. Census and the U.S. Environmental Protection Agency’s Smart Location Database for the study period of 1999–2020. After inputting the data into QGIS, we made graphs with 95% confidence intervals to analyze longitudinal trends in crash location characteristics and created heat maps of pedestrian fatality locations in nine large U.S. cities to compare clustering in the beginning of the study period (1999–2002) with clustering at the end (2017–2020). The results of this study indicate that pedestrian fatalities are moving away from downtown areas (with a 63.0% decrease in study cities’ downtowns) and are now happening more in suburbs (a 32.1% increase outside downtowns). Many of these suburbs are post-war suburbs that were built in the 1950s, 1960s, and 1970s and have low population and road densities and low levels of pedestrian commuting. Additionally, these fatalities are happening in neighborhoods with high proportions of minority residents, low educational attainment, and high poverty rates that are more than 60% above the national average.

Highways and pedestrian deaths in US neighborhoods

Over 100,000 pedestrians have been struck and killed by vehicles on US roadways in the first two decades of the 21st century, representing an alarming public health issue. We examine the US Interstate Highway System’s legacy in contributing to local pedestrian deaths using historical Interstate Highway plans as an instrument for local Interstate construction. Operating an Interstate through a census tract increased local pedestrian deaths significantly. Among 17,000 tracts bisected by Interstates, we estimate the average tract experienced 2.5 additional pedestrian deaths between 2001–2020 due to the presence of the Interstate. We find these deaths occur disproportionately in Black communities.

The Most Vulnerable User: Examining the Role of Income, Race, and the Built Environment on Pedestrian Injuries and Deaths

This study examined the incidence of injurious and fatal pedestrian crashes for lower-income and affluent communities in Broward and Palm Beach counties, FL, finding notable differences in the environmental risk factors for these populations. In lower-income areas, pedestrian deaths and injuries increased with traffic volumes, multilane streets, and restaurants and shopping centers. They decreased with the presence of raised medians, which can serve as a refuge island for crossing pedestrians. These variables all suggest that, at least in lower-income areas, pedestrian death and injury was associated with difficulties safely accessing household-supporting destinations. For affluent areas, the factors associated with increased pedestrian death and injury were those relating to recreation and nightlife—specifically, bars and clubs, hotels, and restaurants. Neither traffic volumes nor multilane roads proved to be meaningfully related to increased pedestrian death or injury in affluent areas. Perhaps most notably, higher concentrations of Black populations were strongly related to increased pedestrian death and injury, even after accounting for differences in income. Considered as a whole, these results suggest that pedestrian crash risk, like much else in U.S. society, is strongly intertwined with broader issues of racial and income inequality. Attempts to address the safety of the transportation system’s most vulnerable users need to move beyond asserting that any pedestrian project constitutes a safety enhancement, and to begin to more meaningfully account for social vulnerabilities associated with race and income.

Clustering and pedestrian crashes prediction modelling: Amman case

Pedestrian casualties are a severe domestic as well as international problem. This study analyses the spatial distribution of pedestrian casualties to define contributory factors and delineate the means for their prediction. Three years of crash data were collected along with other factors and analysed using kernel density estimation (KDE), spatial autocorrelation (Moran’s I), cluster K-Means, spatial regression, and general linear regressions (GLM). Kernel density estimate defines a cluster of pedestrian deaths within 1250 meters. According to Moran’s I, 17/22 attributes about casualties, road networks, demographics, and land use have positive values, indicating similar importance clustering. The spatial pattern of pedestrian casualties is random and insignificant and does not change with time. Casualties are negatively related to the surrounding attributes, indicating a tendency towards dispersion. A K-Means analysis of multiple variables revealed that when variables included in the clustering were higher, the variance explanation percentage was lower. In the multi-variable GLM assuming Poisson distribution, the road network length alone or with the house permits combined were the best predictors of casualties. Classic regressions were not significantly enhanced by spatial dimension, and none of the autoregressive coefficients were significant. The predictions from the Poisson-based GLM model are similar to the classic regressions.

Cluster analysis of the spatial distribution of pedestrian deaths and injuries by parishes in Kampala city, Uganda

Studies on pedestrian deaths and injuries at the urban level in Africa mostly provide overall aggregated figures and do not examine variation in the sub-urban units. Using cluster analysis, this study sought to determine if the observed pattern in the distribution of pedestrian injuries and deaths among parishes in Kampala city is significant. Pedestrian crash data from 2015 to 2019 were collected from the Uganda Traffic Police database. Serious and fatal pedestrian injury rates were mapped by parish using ArcMap and cluster analyses conducted. Results from spatial autocorrelation (Moran’s Index of 0.18 and 0.17 for fatal and serious injury rates respectively) showed that the distributions were clustered within parishes crossed by highways and located in the inner city respectively. Z-scores of 3.32 (p < 0.01) for serious injury rates and 3.71 (p < 0.01) for fatal injury rates indicated that the clustering was not random. This study’s main contribution was providing a detailed spatial distribution of pedestrian fatal and serious injury rates for Kampala; a city in a low developing country in Africa at the micro-scale of a parish. This foundational exploratory paper formed the first step of a broader study examining built environment factors explaining this pattern.

Identification of factors increasing the risk of pedestrian death in road accidents involving a pedestrian with a motor vehicle

Walking is a basic form of activity for every human being and has many advantages, including health, economic and environmental benefits. Every journey made using various means of transport begins and ends on foot. As is well known, the group of road users particularly exposed to the risk of serious injury in road accidents, apart from cyclists, also includes pedestrians. These are the so-called vulnerable road users. Pedestrians are a group of road users that is often deprecated by many drivers of motor vehicles, but very important in road traffic. Pedestrian injuries and pedestrian fatalities have enormous social and economic consequences. The problem of high pedes-trian risk on Polish roads is well known and has been widely described in the scientific literature last few years. However, the reasons for this state of affairs have not been fully explained, as evidenced by the statistics of road traffic incidents. Despite many studies in this area, the causes indicated in the research often differ depending on the area of analysis, the environment in which the incident took place, location, participants of the incident, environmental conditions, behaviorism and many other features. Therefore, the main goal of the article was to determine the factors influencing the formation of fatalities in road traffic accidents among pedestrians in acci-dents involving pedestrians and motor vehicles in the Silesian Voivodeship (Poland) in 2016-2021. The logit model presented in the article allowed for the conclusion that the main attributes influencing the increasing the risk of pedestrian death in road accidents involving a pedestrian with a motor vehicle include such features as driving under the influence of alcohol by the driver, exceeding the speed limit by the vehicle driver, when the road incident involves a heavy vehicle (truck, bus), a pedestrian is a male, pedestrian is over 60 years old, is under the influence of alcohol, the incident took place outside built-up area, at night, i.e. from 10:00 p.m. up to 6:00 a.m, in other than good weather conditions. The obtained results can be used in various activities, campaigns aimed at improving the safety of pedestrian traffic in the area of the analysis.

Characteristics of Dangerous Scenarios between Vehicles Turning Right and Pedestrians under Left-Hand Traffic

Pedestrian deaths account for the highest percentage of fatality caused by traffic accidents in Japan. Increasing pedestrian safety is a key objective for reducing such deaths. For pedestrian fatality caused by vehicles at low speed, turning the vehicle toward the right was the most common behavior under left-hand traffic. Autonomous emergency braking (AEB) systems for pedestrian safety have great potential to mitigate pedestrian injuries and fatalities in traffic accidents. However, pedestrian-AEB systems, especially for vehicles turning right, are still under development. This study identified the characteristics of dangerous traffic scenarios between vehicles turning right and pedestrians, focusing on two directions of pedestrian crossing: from the left to the right side (Left-Pedestrian) and from the right to the left side (Right-Pedestrian). The ego vehicle recorded near-miss incidents using a drive recorder. The results revealed that the Left-Pedestrian and Right-Pedestrian scenarios had different features for both the width of roads going to and through the intersection and the average of the travel speeds of the ego vehicles. They had similar characteristics in terms of the presence of other vehicle categories, but differences in the relationship of numbers and/or travel directions of other vehicles. The findings of this study will contribute to the development and evaluation of safety systems for preventing collisions between right-turning vehicles and pedestrians at intersections.

Major traumatic pedestrian injury in Australia: Characteristics and in-hospital outcomes from the Australia New Zealand Trauma Registry

BackgroundThe leading global cause of death for people aged 5–29 years is road traffic injury, a quarter of which is borne by pedestrians. The epidemiology of major hospitalised pedestrian injury across Australia is not reported. This study aims to address this gap using data from the Australia New Zealand Trauma Registry. MethodsThe registry hosts information on patients admitted to 25 major trauma centres across Australia who sustain a major injury (ISS > 12) or die following injury. Patients were included if they were injured due to pedestrian injury from 1st July 2015–30 th June 2019. Analysis included patient and injury characteristics, injury patterns and in-hospital outcomes. Primary endpoints included risk-adjusted mortality and length of stay. ResultsThere were 2159 injured pedestrians; of these, 327 died. Young adults (20–25 years) were the largest group, especially on weekends. Older adults (70 + years) were the largest cohort in pedestrian deaths. The most common injuries were head (42.2 %). One-third of patients were intubated prior to or on ED arrival (n = 731, 34.3 %). ConclusionEmergency clinicians should have a high index for severe pedestrian injury. Further reduction in road speed in residential areas could reduce all-age pedestrian injury in Australia.

Applying Few-Shot Learning in Classifying Pedestrian Crash Typing

Pedestrian deaths account for 23% of all road traffic fatalities worldwide. After declining for three decades, pedestrian fatalities in the United States have been increasing with 6,941 fatalities in 2020, the highest number for more than two decades, impeding progress toward a zero-deaths transportation system. The Pedestrian and Bicycle Crash Analysis Tool (PBCAT) was developed to describe the pre-crash actions of the parties involved to better define the sequence of events and precipitating actions that lead to crashes involving motor vehicles and pedestrians or cyclists. Undoubtedly, police crash data influence decision-making processes in the transportation agencies. Using crash data from three major cities in Texas (during the period from 2018 to 2020), this study assessed the data quality of police-reported crash narratives on pedestrian-involved traffic crashes. As the pedestrian crash typing involves many categories, conventional machine-learning algorithms will not be sufficient in solving the classification problem from narrative texts. This study used few-shot learning (FSL), an advanced machine learning, to solve this issue. Using the pre-knowledge obtained from five different crash types and a few labeled data points of three unseen new crash types, the proposed model achieved roughly 40% overall accuracy. Also, four different configurations of crash types were formed and tested which indicates that the model is robust.