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The fifth Global Status report on Road Safety, released by the World Health Organization (WHO), shows that road traffic deaths have slightly decreased to 1.19 million per year. However, important trends remain, such as road traffic injuries (RTIs) being the leading cause of death for children and young adults aged 5-29 years, the majority of fatalities occurring in low- and middle-income countries, and over half of all road traffic deaths affecting vulnerable road users like pedestrians, cyclists, and motorcyclists. While some countries have met the target of reducing fatalities by 50%, many African and Southeast Asian countries have reported an increase in fatalities. The journal issue includes research articles from Asian and African countries covering various topics related to traffic injuries, work-related injuries, media coverage of motor vehicle crashes, and risk reduction. The articles highlight the need for research and interventions to address the specific risks faced by these regions. [Extracted from the article]

Nevertheless, Dinesh highlighted that epidemiological evidence shows that occupants of these vehicles have lower injury rates per trip than cars despite these vehicles having no surrounding steel shell and a much lower weight (Mohan et al., [36]; Mohan & Bhalla, [27]). This work included, many of the themes we have discussed above, such as studies that questioned the role of motorization, urban design and trip modal shares (Mohan et al., [25]; Mohan & Bhalla, [27]; Mohan & O'Neil, [29]). Dinesh was taking pictures of Sikh children with burn injuries, who were playing in one of the relief camps. The main ideas were presented in a series of books and edited collections, with contributions from the leading figures in the field of injury prevention (Mohan & Berger, [26]; Barss et al., [2]; Mohan & Tiwari, [33]; Peden et al., [46]; Tiwari et al., [54]; Mohan, [23]; Tiwari & Mohan, [53]). [Extracted from the article]

This paper looks at the pedestrian safety issue and the research that has followed to understand and solve the problem of pedestrian safety in the last 120 years - since the time of the first reported pedestrian fatality in 1899. Researches have studied the epidemiology of pedestrian crashes, pedestrian behaviour, pedestrian movements and pedestrian flows. The suggested strategies to reduce pedestrian crashes have ranged from controlling vehicular speeds to controlling pedestrian behaviour. This study presents a summary of the progress we have made in understanding pedestrian crash patterns. Pedestrian behaviour observed in different regions of the world tend to have similarity in pedestrian behaviour: gap acceptance, preferences of route choice and location for crossing roads. High income countries(HIC) have reported reduction in pedestrian fatalities as compared to low and middle income countries(LMICs), however pedestrian trips have also reduced in these countries leading to concerns about the effectiveness of 'known' strategies. Speed control through active measures have been found to have themaximal benefit and education and training programs for altering pedestrian behaviour on the road the least benefits. Low and middle income countries face pedestrian exposure on high speed roads. New research efforts are required to address pedestrian safety in both HIC and LMICs. [ABSTRACT FROM AUTHOR]

This article investigates the effects of highway-related correlates such as geometric design features and traffic factors on fatal accident occurrences in small-sized Indian cities, Patiala and Rajpura, by estimating Negative Binomial regression models. Between 2013 and 2015, 61 and 188 fatal accidents were recorded in Rajpura and Patiala, respectively. The study reveals that the number of traffic lanes positively influences accident occurrences in Rajpura. On the other hand, in Patiala, the width of paved road surface, segment length and average daily traffic (ADT) are positively correlated with accident rates. Intercity highways passing through rural areas near the city boundary are more prone to fatal accidents than the highway segments within urban limits. Elasticity analysis suggests that an increase in paved road width and ADT by one percent would increase accident rates by 0.7% and 0.436% in Patiala and Rajpura, respectively. The findings of this research concur with the results of previous studies that infrastructural improvements such as increasing the number of lanes and paved road width are positively correlated with accident rates. It is expected that understanding the association between accident rates and non-behavioral factors would help transportation engineers identify the deficiencies in roadway designs in the study cities. [ABSTRACT FROM AUTHOR]

Traffic crash fatalities from 2006 to 09 in Delhi, India show that pedestrians have the largest share in total road fatalities. Perception of risk provides important information to identify potential crash risk. Thus, the main objective of this paper is to explore the pedestrian perception of risk in getting involved in a traffic crash in different locations and the role of built environment features in risk perception of pedestrians. Locations having a high number of pedestrian fatal crashes were identified using GIS map of Delhi. Pedestrian perceptions of risk at forty-five actual crash sites were collected through questionnaire survey. Risk perception of pedestrians of built environment features were analyzed based on pedestrian demographic characteristics. Ordered logit model was used to examine the influence of these variables on risk perception of respondent’s neighborhood and of the location where the survey was conducted. Seventy percent respondents perceive the neighborhoods where they reside having higher risk than the actual crash locations. Several factors such as gender, number of lanes, sidewalk width, sidewalk maintenance, traffic speed and traffic volume were significantly associated with perceived risk. Survey sites were further categorized into four groups i.e. foot of flyover, four-way junctions below flyover, midblocks and intersections to find the impact of characteristics of locations on pedestrians’ risk perception of different locations. Four-way junctions below flyover were found to have higher perceived risk compared to other locations. [ABSTRACT FROM AUTHOR]

Hyeonmyeong Jeon, et al., from the Republic of Korea have sent in an essay on the factors affecting injury severity and the number of vehicles involved in a freeway traffic accident. The present issue contains several submissions which attest to the fact of an increase in the number of fruitful collaborations between researchers in various countries. Zhipeng Peng, et al., from China have sent in a paper which discusses the factors influencing injury severity of crashes in both, the day time and the night time, on a mountainous expressway in China. [Extracted from the article]

Mitchel Chatukuta et al., from the UK, have made a presentation on the functioning of the motor vehicle accident fund (MVAF), a road tax levied in Namibia to help and support road traffic injury victims. The wealthy have insurance, but most people rely on the MVAF which is an efficient system effectively helping the road traffic crash victims. They maintain that post-crash trauma and emergency care of crash victims is very poor. [Extracted from the article]

In this unending season of the coronavirus pandemic, we recognise with appreciation the efforts put in by all the contributors to our journal, including those whose work did not manage to find inclusion in these pages. Mild and soft tissue injuries were more common in urban settings, while the more severe injuries were more likely to occur in the rural areas, which would point to these factors impinging on population density. The present essay posits a linkage between hospital discharge data and crash data, which leads one to believe that this database could be extended to include other databases for further investigations in the future. [Extracted from the article]

Abstract: Pedestrians on Delhi roads are often exposed to high risks. This is because the basic needs of pedestrians are not recognized as a part of the urban transport infrastructure improvement projects in Delhi. Rather, an ever increasing number of cars and motorized two-wheelers encourage the construction of large numbers of flyovers/grade separators to facilitate signal free movement for motorized vehicles, exposing pedestrians to greater risk. This paper describes the statistical analysis of pedestrian risk taking behavior while crossing the road, before and after the construction of a grade separator at an intersection of Delhi. A significant number of pedestrians are willing to take risks in both before and after situations. The results indicate that absence of signals make pedestrians behave independently, leading to increased variability in their risk taking behavior. Variability in the speeds of all categories of vehicles has increased after the construction of grade separators. After the construction of the grade separator, the waiting time of pedestrians at the starting point of crossing has increased and the correlation between waiting times and gaps accepted by pedestrians show that after certain time of waiting, pedestrians become impatient and accepts smaller gap size to cross the road. A Logistic regression model is fitted by assuming that the probability of road crossing by pedestrians depends on the gap size (in s) between pedestrian and conflicting vehicles, sex, age, type of pedestrians (single or in a group) and type of conflicting vehicles. The results of Logistic regression explained that before the construction of the grade separator the probability of road crossing by the pedestrian depends on only the gap size parameter; however after the construction of the grade separator, other parameters become significant in determining pedestrian risk taking behavior. [Copyright &y& Elsevier]

Abstract: This paper develops the model and methodology to estimate the marginal external cost of urban road transport, which is necessary for analysing optimal urban transport prices. Four major marginal external costs analysed in this paper include the marginal external costs for congestion, air pollution, road accidents and noise. The paper estimates the marginal external costs for cars and buses in peak and off-peak periods for Delhi urban agglomeration for the year 2005. [Copyright &y& Elsevier]

Hit-and-run crashes are significant concern for many countries. Due to lack of information of offending vehicles it is difficult to understand dynamics of these crashes to have a prevention plan. The paper aims to identify the impacting vehicle in hit-and-run crashes. We studied fatal road crashes of New Delhi for eleven years (2006–2016) and found that approximately 40% fatal crashes are hit-and-run with unknown impacting vehicles. We proposed a framework using eleven different machine learning-based classification algorithms – Logistic-Regression, KNN, SVM-Linear and RBF-Kernel, Naïve-Bayes, Random-Forest, DecisionTree, AdaBoost, Multilayer-Perceptron, CART and Linear-Discriminant-Analysis. We found SVM-linear-kernel gave best results. Results reveal that cars, buses, and heavy vehicles are involved vehicles in hit-and-run crashes. Buses were primary cause leading to 39% of hit-and-run during 2006-2009 thereafter cars increased drastically. Our framework is robust and scalable to any city. The outcomes provide inputs to traffic engineers for better policy prescription and road user safety. [ABSTRACT FROM AUTHOR]

An editorial is presented on the studies which have focused on the impact of infrastructure designs. This includes evaluating the impact of roundabouts in Ghana, spatial analysis of traffic crashes in three different locations – Galle, Sri Lanka, Shanghai, China and Moshi, Tanzania. The evaluation of traffic crashes at recently implemented roundabouts in Kumasi, Ghana with the help of studies.

An introduction is presented in which the editor discusses various reports within the issue on topics including crash frequency modelling, the pattern of road traffic accidents, and the effects of parental decision-making on child restrain use in vehicles.

An introduction is presented in which the editor discusses articles in the issue on topics including traffic accidents, automobile drivers and seat belts.

An introduction is presented in which the editor discusses various articles within the issue on topics including laws regarding the use of seat belts and child restraints in the vehicles in different countries, thoracic injury patterns of drivers and statistics of road accidents in Russia.

The author reflects on studies that examine the patterns of death and injuries of major road accidents on the basis of collected data from several countries including China, Qatar and Pakistan. She highlights the role of traffic police and need to promote safety awareness issues among people. An overview of demographical data which shows high rate of road accidents among motorists of 16-35 years of age group is also included.

An introduction is presented in which the editor discusses various reports within the issue on topics including road traffic injuries, preventive and control measures of injuries, and multiple drowning syndromes.

An introduction to the journal is presented in which the editor discusses an article on List of All Deficits (LOAD) framework by Ronan A. Tyons and colleagues, one on incidences of fatal and non-fatal road traffic injuries in 2005 in Mexico by David Bartels and colleagues, one related to surveillance system on road traffic and health impacts in between 2001-2005 in Lazlio, Italy by Francesco Chini and colleagues.

An introduction to the journal is presented in which the editor discusses various articles published within the issue including an article on road traffic injuries in Iran, another on violence among married or cohabiting couples in Chile and one on the use of poisning agent, Cleistanthus collinus among suiciders in India.

• Hit-and-run accidents are a global problem to solve as an accident causing vehicle is 'unknown'. • Knowledge of unknown vehicles can be useful in better planning for ensuring road user's safety. • Experimental approach followed with six learning models - Logistic Regression, Naïve Bayes, LDA, CART, KNN and SVM to identify unknown. • Accident data from five mid-sized Indian cities- Agra, Amritsar, Bhopal, Ludhiana and Vizag is used in our experiment. • Analysis of performance of the learning models are presented with recommendations. Road accidents are globally accepted challenges. They are one of the significant causes of deaths and injuries besides other direct and indirect losses. Countries and international organizations have designed technologies, systems, and policies to prevent accidents. However, hit-and-run accidents remain one of the most dangerous types of road accidents as the information about the vehicle responsible for the accident remain unknown. Therefore, any mechanism which can provide information about the impacting vehicle in hit-and-run accidents will be useful in planning and executing preventive measures to address this road menace. Since there exist several models to predict the impacting unknown vehicle, it becomes important to find which is the most accurate amongst those available. This research applies a process-based approach that identifies the most accurate model out of six supervised learning classification models viz. Logistic Reasoning, Linear Discriminant Analysis, Naïve Bayes, Classification and Regression Trees, k-Nearest Neighbor and Support Vector Machine. These models are implemented using five-fold and ten-fold cross validation, on road accident data collected from five mid-sized Indian cities: Agra, Amritsar, Bhopal, Ludhiana, and Vizag (Vishakhapatnam).This study investigates the possible input factors that may have effect on the performance of applied models. Based on the results of the experiment conducted in this study, Support Vector Machine has been found to have the maximum potentiality to predict unknown impacting vehicle type in hit-and-run accidents for all the cities except Amritsar. The result indicates that, Classification and Regression Trees have maximum accuracy, for Amritsar. Naïve Bayes performed very poorly for the five cities. These recommendations will help in predicting unknown impacting vehicles in hit-and-run accidents. The outcome is useful for transportation authorities and policymakers to implement effective road safety measures for the safety of road users. [ABSTRACT FROM AUTHOR]