An analysis of the injury severity of pedestrians in Brazil using random parameters logit models

In Brazil, pedestrians represent the third largest group of crash victims, after motorcyclists and car occupants. Implementing measures to ensure pedestrian safety and prioritization requires an understanding of the risk factors associated with crash injuries. In this study, a random-parameter logit model was estimated to investigate factors influencing the severity of crashes with pedestrians in urban roads in Fortaleza, Brazil. A sample of 2,660 observations of crashes with pedestrians in the city from 2017 to 2019 was used. The injury severity levels adopted by the Crash Information System (SIAT) were grouped into three categories: mild/moderate, severe and fatal. From the investigated factors, only the variable related to the pedestrian's age over 60 years old obtained a significant random parameter. In this case, the heterogeneity in the observations may be associated, among other factors, to the body’s physical fragility and the cognitive function that may differ among individuals in this group. The results showed that the driver’s gender and age, the crash site, the motorcycle use, and the presence of speed cameras did not have a significant impact on the severity of crashes with pedestrians. On the other hand, crashes occurring at night, with heavy vehicles, on weekends, and located on roads with higher traffic classification are associated with more severe injuries. The incorporation of unobserved heterogeneity in the estimation of the model's parameters stands out as one of the main contributions of this work

Analysing traffic crashes in Riyadh City using statistical models and geographic information systems

Road safety is a serious societal concern in Riyadh city, Kingdom of Saudi Arabia. Because of the negative impact of traffic crashes which cause losses in the form of deaths, injuries and property damage, in addition to the pain and social tragedy affecting families of the victims, it is important for transport policy makers to reduce their impact and increase safety standards by reducing the severity and frequency of crashes in the city of Riyadh. It is therefore important to fully understand the relationship between traffic crash severity and frequency and their contributing factors so to establish effective safety policies which can be implemented to enhance road safety in Riyadh city. Data used in previous research have only consisted of basic information as there was unavailability of suitable and accurate data in Riyadh and there are very few studies that have undertaken as small area-wide crash analysis in Riyadh using appropriate statistical models. Therefore safety policies are not based on rigorous analyses to identify factors affecting both the severity and the frequency of traffic crashes. This research aims to explore the relationship between traffic crash severity and frequency and their contributing factors by using statistical models and a GIS approach. The analysis is based on the data obtained over a period of five years, namely AH 1425, 1426, 1427, 1428, and 1429 (roughly equivalent to 2004, 2005, 2006, 2007, and 2008). Injury crash severity data were classified into three categories: fatal, serious injury and slight injury. A series of statistical models were employed to investigate the factors that affect both crash severity (i.e. ordered logit and mixed logit models) and area-wide crash frequency (i.e. classical Poisson and negative binomial models). Because of a severe underreporting problem on the slight injury crashes, binary and mixed binary logistic regression models were also estimated for two categories of severity: fatal and serious crashes. The mixed binary logit model and the negative binomial model are found to be the best models for crash severity and crash frequency analyses respectively. The model estimation results suggest that the statistically significant factors in crash severity are the age and nationality of the driver who is at fault, the time period from 16.00 to 19.59, excessive speed, road surface and lighting conditions, number of vehicles involved and number of casualties. Older drivers are associated with a higher probability of having a fatal crash, and, as expected, excessive speeds were consistently associated with fatal crashes in all models. In the area-level crash frequency models, population, percentage of illiterate people, income per capita and income per adult were found to be positively associated with the frequency of both fatal and serious injury crashes whereas all types of land use such as percentages of residential use, transport utilities, and educational use in all models were found to be negatively associated with the frequency of occurrence of crashes. Results suggest that safety strategies aimed at reducing the severity and frequency of traffic crashes in Riyadh city should take into account the structure of the resident population and greater emphasis should be put on native residents and older age groups. Tougher enforcement should be introduced to tackle the issue of excessive speed. This thesis contributes to knowledge in terms of examining and identifying a range of factors affecting traffic crash severity and frequency in Riyadh city

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

Public Transport road safety risk for pedestrians and cyclists. Case Study of Santiago de Chile

Esta investigación examina la severidad de los siniestros de tránsito que involucran buses del transporte público en Santiago de Chile desde 2017 hasta 2021, particularmente los siniestros con peatones y ciclistas involucrados. El estudio revela que los buses de transporte público tienen un impacto en los siniestros fatales, ya que representan el 26,2 % de las muertes de peatones; 26,9% de las muertes de ciclistas y 19,5% del total de las víctimas fatales. En los atropellos a peatones por buses, es más probable que los peatones mayores y hombres estén involucrados en un siniestro fatal. Es más probable que los siniestros fatales entre peatones y buses ocurran de noche, en una intersección o cuando un bus gira o reinicia su marcha. Es menos probable que las conductoras de bus se vean involucradas en un atropello fatal a peatones, lo que sugiere la importancia de aumentar la proporción de mujeres conductoras. La investigación también evalúa el impacto de la implementación de un sistema integrado de transporte público “Transantiago” en Santiago, que redujo significativamente las fatalidades que involucran autobuses. Los resultados respaldan la implementación de sistemas de transporte públicos integrados e indican posibles beneficios para otras ciudades chilenas. Durante el periodo 2017-2021, las muertes en siniestros de tránsito con buses involucrados han disminuido significativamente. Factores como la cantidad de kilómetros recorridos por los buses y el despliegue de una nueva flota de buses parecen haber aportado a esta diminución. Pero otros factores como: el estadillo social de 2019, la pandemia de COVID-19, el aumento de la cantidad de conductoras, nuevas pistas “solo bus” y un mantenimiento mejorado de los buses pueden haber contribuido a esta disminución también. Esta investigación enfatiza la necesidad de crear políticas de seguridad vial para el sistema de bus del transporte público y propone un conjunto de recomendaciones.This research examines the severity of the road crashes involving public transport buses in Santiago de Chile from 2017 to 2021, particularly crashes involving pedestrians and cyclists. The study reveals that public transport buses play a significant role in fatal crashes, involved in 26.2% of the pedestrian fatalities; 26.9% of the cyclist fatalities and 19.5% of all fatalities. Pedestrians constitute the majority (55.8%) of fatalities in bus-related crashes. For crashes between pedestrians and public transport buses, older and male pedestrians are more likely to be involved in a fatal crash. Those crashes are more likely to be fatal at night, at an intersection or with a bus turning or restarting. Female bus drivers are less likely to be involved in pedestrian fatal crashes, suggesting the importance of increasing their representation. The research also evaluates the impact of the implementation of an integrated public transport system “Transantiago” in Santiago, which significantly reduced fatalities in crashes involving buses. The findings support the implementation of integrated transport systems and indicate potential safety benefits for other Chilean cities (which have a higher rate of fatalities in crashes involving public transport buses). During the 2017-2021 period, fatalities in bus-related crashes have notably decreased. Factors such as the reduction of the number of kilometres travelled by public transport and roll out of a new bus fleets seem to have help this reduction. However, other factors like: the 2019 Chilean protests, the COVID-19 pandemic, the increase of number of female drivers, new bus lanes with automated enforcement and bus maintenance improvement may have contributed to this reduction as well. This research emphasizes the need for targeted road safety policies for buses and proposes a set of recommendations to be implemented by Public Transport Authorities

Modelling Road Work Zone Crashes’ Nature and Type of Person Involved Using Multinomial Logistic Regression

The sustainable development goals “Good health and well-being” and “Sustainable cities and communities” of the United Nations and World Health Organization, alert governments and researchers and raise awareness about road safety problems and the need to mitigate them. In Portugal, after the economic crisis of 2008–2013, a significant amount of road assets demand investment in maintenance and rehabilitation. The areas where these actions take place are called work zones. Considering the particularities of these areas, the proposed work aims to identify the main factors that impact the occurrence of work zones crashes. It uses the statistical technique of multinomial logistic regression, applied to official data on road crashes occurred in mainland Portugal, during the period of 2010–2015. Usually, multinomial logistic regression models are developed for crash and injury severity. In this work, the feasibility of developing predictive models for crash nature (collision, run off road and running over pedestrians) and for type of person involved in the crash (driver, passenger and pedestrian), considering only one covariate (the number of persons involved in the crash), was studied. For the two predictive models obtained, the variables road environment (urban/rural), horizontal geometric design (straight/curve), pavement grip conditions (good/bad), heavy vehicle involvement, and injury severity (fatalities, serious and slightly injuries), were identified as the preponderant factors in a universe of 230 investigated variables. Results point to an increase of work zone crash probability due to driver actions such as running straight and excessive speed for the prevailing conditions.info:eu-repo/semantics/publishedVersio

Bicycle helmet use and non-use - recently published research

Bicycle traumata are very common and especially neurologic complications lead to disability and death in all stages of the life. This review assembles the most recent findings concerning research in the field of bicycle traumata combined with the factor of bicycle helmet use. The area of bicycle trauma research is by nature multidisciplinary and relevant not only for physicians but also for experts with educational, engineering, judicial, rehabilitative or public health functions. Due to this plurality of global publications and special subjects, short time reviews help to detect recent research directions and provide also information from neighbour disciplines for researchers. It can be stated that to date, that although a huge amount of research has been conducted in this area more studies are needed to evaluate and improve special conditions and needs in different regions, ages, nationalities and to create successful prevention programs of severe head and face injuries while cycling. Focus was explicit the bicycle helmet use, wherefore sledding, ski and snowboard studies were excluded and only one study concerning electric bicycles remained due to similar motion structures within this review. The considered studies were all published between January 2010 and August 2011 and were identified via the online databases Medline PubMed and ISI Web of Science

Characterization of Black Spot Zones for Vulnerable Road Users in São Paulo (Brazil) and Rome (Italy)

Non-motorized transportation modes, especially cycling and walking, offer numerous benefits, including improvements in the livability of cities, healthy physical activity, efficient urban transportation systems, less traffic congestion, less noise pollution, clean air, less impact on climate change and decreases in the incidence of diseases related to vehicular emissions. Considering the substantial number of short-distance trips, the time consumed in traffic jams, the higher costs for parking vehicles and restrictions in central business districts, many commuters have found that non-motorized modes of transportation serve as viable and economical transport alternatives. Thus, local governments should encourage and stimulate non-motorized modes of transportation. In return, governments must provide safe conditions for these forms of transportation, and motorized vehicle users must respect and coexist with pedestrians and cyclists, which are the most vulnerable users of the transportation system. Although current trends in sustainable transport aim to encourage and stimulate non-motorized modes of transportation that are socially more efficient than motorized transportation, few to no safety policies have been implemented regarding vulnerable road users (VRU), mainly in large urban centers. Due to the spatial nature of the data used in transport-related studies, geospatial technologies provide a powerful analytical method for studying VRU safety frameworks through the use of spatial analysis. In this article, spatial analysis is used to determine the locations of regions that are characterized by a concentration of traffic accidents (black zones) involving VRU (injuries and casualties) in Sao Paulo, Brazil (developing country), and Rome, Italy (developed country). The black zones are investigated to obtain spatial patterns that can cause multiple accidents. A method based on kernel density estimation (KDE) is used to compare the two cities and show economic, social, cultural, demographic and geographic differences and/or similarities and how these factors are linked to the locations of VRU traffic accidents. Multivariate regression analyses (ordinary least squares (OLS) models and spatial regression models) are performed to investigate spatial correlations, to understand the dynamics of VRU road accidents in Sao Paulo and Rome and to detect factors (variables) that contribute to the occurrences of these events, such as the presence of trip generator hubs (TGH), the number of generated urban trips and demographic data. The adopted methodology presents satisfactory results for identifying and delimiting black spots and establishing a link between VRU traffic accident rates and TGH (hospitals, universities and retail shopping centers) and demographic and transport-related data. Document type: Articl

Network-Wide Pedestrian and Bicycle Crash Analysis with Statistical and Machine Learning Models in Utah

Recent trends in crashes indicate a dramatic increase in both the number and share of pedestrian and bicyclist injuries and fatalities nationally and in many states. Crash frequency modeling was undertaken to identify crash prone characteristics of segments and non-signalized intersections and explore possible non-linear associations of explanatory variables with crashes. Crowdsourced “Strava” app data was used for bicycle volume, and pedestrian counts estimated from nearby signalized intersections were used as pedestrian volume. Multiple negative binomial models investigated crashes at different spatial scales to account for different levels of data availability and completeness. The models showed high traffic volume, steeper vertical grades on roads, frequent bus and rail stations, greater driveway density, more legs at intersections, streets with high large truck presence, greater residential and employment density, as a larger share of low-income households and non-white race/ethnicity groups are indicators of locations with more pedestrian and bicycle crashes. Crash severity model results showed that crashes occurring at mid-blocks and near vertical grades were more severe compared to crashes at intersections. High daily temperature, driving under influence, and distracted driving also increases injury severity in crashes. This study suggests potential countermeasures, policy implications, and the scope of future research for improving pedestrian and bicycle safety at segments and at non-signalized intersections

Identification of infrastructure related risk factors, Deliverable 5.1 of the H2020 project SafetyCube

The present Deliverable (D5.1) describes the identification and evaluation of infrastructure related risk factors. It outlines the results of Task 5.1 of WP5 of SafetyCube, which aimed to identify and evaluate infrastructure related risk factors and related road safety problems by (i) presenting a taxonomy of infrastructure related risks, (ii) identifying “hot topics” of concern for relevant stakeholders and (iii) evaluating the relative importance for road safety outcomes (crash risk, crash frequency and severity etc.) within the scientific literature for each identified risk factor. To help achieve this, Task 5.1 has initially exploited current knowledge (e.g. existing studies) and, where possible, existing accident data (macroscopic and in-depth) in order to identify and rank risk factors related to the road infrastructure. This information will help further on in WP5 to identify countermeasures for addressing these risk factors and finally to undertake an assessment of the effects of these countermeasures. In order to develop a comprehensive taxonomy of road infrastructure-related risks, an overview of infrastructure safety across Europe was undertaken to identify the main types of road infrastructure-related risks, using key resources and publications such as the European Road Safety Observatory (ERSO), The Handbook of Road Safety Measures (Elvik et al., 2009), the iRAP toolkit and the SWOV factsheets, to name a few. The taxonomy developed contained 59 specific risk factors within 16 general risk factors, all within 10 infrastructure elements. In addition to this, stakeholder consultations in the form of a series of workshops were undertaken to prioritise risk factors (‘hot topics’) based on the feedback from the stakeholders on which risk factors they considered to be the most important or most relevant in terms of road infrastructure safety. The stakeholders who attended the workshops had a wide range of backgrounds (e.g. government, industry, research, relevant consumer organisations etc.) and a wide range of interests and knowledge. The identified ‘hot topics’ were ranked in terms of importance (i.e. which would have the greatest effect on road safety). SafetyCube analysis will put the greatest emphasis on these topics (e.g. pedestrian/cyclist safety, crossings, visibility, removing obstacles). To evaluate the scientific literature, a methodology was developed in Work Package 3 of the SafetyCube project. WP5 has applied this methodology to road infrastructure risk factors. This uniformed approach facilitated systematic searching of the scientific literature and consistent evaluation of the evidence for each risk factor. The method included a literature search strategy, a ‘coding template’ to record key data and metadata from individual studies, and guidelines for summarising the findings (Martensen et al, 2016b). The main databases used in the WP5 literature search were Scopus and TRID, with some risk factors utilising additional database searches (e.g. Google Scholar, Science Direct). Studies using crash data were considered highest priority. Where a high number of studies were found, further selection criteria were applied to ensure the best quality studies were included in the analysis (e.g. key meta-analyses, recent studies, country origin, importance). Once the most relevant studies were identified for a risk factor, each study was coded within a template developed in WP3. Information coded for each study included road system element, basic study information, road user group information, study design, measures of exposure, measures of outcomes and types of effects. The information in the coded templates will be included in the relational database developed to serve as the main source (‘back end’) of the Decision Support System (DSS) being developed for SafetyCube. Each risk factor was assigned a secondary coding partner who would carry out the control procedure and would discuss with the primary coding partner any coding issues they had found. Once all studies were coded for a risk factor, a synopsis was created, synthesising the coded studies and outlining the main findings in the form of meta-analyses (where possible) or another type of comprehensive synthesis (e.g. vote-count analysis). Each synopsis consists of three sections: a 2 page summary (including abstract, overview of effects and analysis methods); a scientific overview (short literature synthesis, overview of studies, analysis methods and analysis of the effects) and finally supporting documents (e.g. details of literature search and comparison of available studies in detail, if relevant). To enrich the background information in the synopses, in-depth accident investigation data from a number of sources across Europe (i.e. GIDAS, CARE/CADaS) was sourced. Not all risk factors could be enhanced with this data, but where it was possible, the aim was to provide further information on the type of crash scenarios typically found in collisions where specific infrastructure-related risk factors are present. If present, this data was included in the synopsis for the specific risk factor. After undertaking the literature search and coding of the studies, it was found that for some risk factors, not enough detailed studies could be found to allow a synopsis to be written. Therefore, the revised number of specific risk factors that did have a synopsis written was 37, within 7 infrastructure elements. Nevertheless, the coded studies on the remaining risk factors will be included in the database to be accessible by the interested DSS users. At the start of each synopsis, the risk factor is assigned a colour code, which indicates how important this risk factor is in terms of the amount of evidence demonstrating its impact on road safety in terms of increasing crash risk or severity. The code can either be Red (very clear increased risk), Yellow (probably risky), Grey (unclear results) or Green (probably not risky). In total, eight risk factors were given a Red code (e.g. traffic volume, traffic composition, road surface deficiencies, shoulder deficiencies, workzone length, low curve radius), twenty were given a Yellow code (e.g. secondary crashes, risks associated with road type, narrow lane or median, roadside deficiencies, type of junction, design and visibility at junctions) seven were given a Grey code (e.g. congestion, frost and snow, densely spaced junctions etc.). The specific risk factors given the red code were found to be distributed across a range of infrastructure elements, demonstrating that the greatest risk is spread across several aspects of infrastructure design and traffic control. However, four ‘hot topics’ were rated as being risky, which were ‘small work-zone length’, ‘low curve radius’, ‘absence of shoulder’ and ‘narrow shoulder’. Some limitations were identified. Firstly, because of the method used to attribute colour code, it is in theory possible for a risk factor with a Yellow colour code to have a greater overall magnitude of impact on road safety than a risk factor coded Red. This would occur if studies reported a large impact of a risk factor but without sufficient consistency to allocate a red colour code. Road safety benefits should be expected from implementing measures to mitigate Yellow as well as Red coded infrastructure risks. Secondly, findings may have been limited by both the implemented literature search strategy and the quality of the studies identified, but this was to ensure the studies included were of sufficiently high quality to inform understanding of the risk factor. Finally, due to difficulties of finding relevant studies, it was not possible to evaluate the effects on road safety of all topics listed in the taxonomy. The next task of WP5 is to begin identifying measures that will counter the identified risk factors. Priority will be placed on investigating measures aimed to mitigate the risk factors identified as Red. The priority of risk factors in the Yellow category will depend on why they were assigned to this category and whether or not they are a hot topic