Digital technologies and Artificial Intelligence (AI) based solutions to enable safer mobility and transportation systems are being promoted in all countries. Policy makers and other stakeholders, specifically in low and middle income countries where the traffic fatalities continue to rise, are pinning their hopes on digital technologies to reduce traffic injuries and fatalities. The applications range from the use of AI-based Advance Driver Assistance Systems (ADAS), identification of black spots, and detection of violations of traffic laws and regulations, to promoting road safety awareness and driver training. Can we rely on the digital technology revolution alone to solve the growing burden of traffic injuries? This issue of the journal presents results from research studies addressing the varied dimensions of traffic and other injuries where sometimes, digital technologies assist in providing more reliable data. However, the continuation of sound scientific methods using many different sets of data can show the way forward for improving our understanding of new and emerging problems of traffic injuries.
Rahul Goel from India, reports on the population-level estimate of bicycle use and fatality risk in a data-poor setting. While the number of injuries per unit distance helps in the comparison of risks in different categories of vehicles, the author here suggests a new method to estimate the fatality risk per km for cyclists, motorcyclists, and car occupants. He uses the annual city-wide motorcycle distance, and the ratio of city-wide motorcycle volume to cycle volume counts. This is a case study of Delhi, India. The three-year annual average number of fatalities for cyclists is 52; for motorcyclists 541 and 52.6 for car occupants. Dividing these figures by the average person-kilometres travelled, we arrive at the average fatality risk of 20.8 per km for cyclists; 9.5 for motorcyclists; and 0.53 for car occupants.
Zhiyuan Sun et al. from China, have made a submission on the subject of vulnerable road users and motor vehicles. This study is based on police-reported crash data from Shenyang in China. Unlike the generally used clustering techniques to divide crashes, the authors, in a hybrid approach, use a latent class analysis which uses a probabilistic model to describe the data distribution and identify the important and often unobserved heterogeneity of factors that contribute to clustering and crash injury severity. It is suggested that more contributing variables can be introduced in further studies of vulnerable road user motor vehicle crashes.
Melvin Joy et al. from India, UK, UAE, USA, and Canada, have jointly sent in a paper, based on the evidence of three national surveys over a period of eighteen years, on specific risk factors and the possible reasons for the reduction in the prevalence of spousal physical violence against women in India. Over the period under study, there was a significant decline of ten percent in the physical violence against women in India, where the Protection of Women from Domestic Violence Act of 2005 was introduced and may have been a major contributory factor. More needs to be done to empower women by providing them with higher education and an improved socio-economic status.
Vladimir Hernandez et al. from Ciudad Juárez, Mexico, have made a longitudinal study on the relationship between three risk exposure factors—demographics, road-network, and land use—on the frequency of road crashes during the COVID-19 pandemic in Mexico, and consider using the pre- and post-pandemic periods as a baseline. Some of the major risk factors are the heavy traffic flow of heterogeneous traffic, the absence at intersections of vertical and horizontal signalling, and the built environment. Under these circumstances, the vulnerable road users are subjected to great risk.
Mohammed Almannaa et al. from Saudi Arabia, have studied the effects of the road conditions and vacations on crash severity using machine learning algorithms on a dataset of 59,000 accidents over a four-year period. Of the 16 variables of road conditions studied, only four were seen as contributing to crash severity: paints, cat eyes, side fence, and metal cable.
Molly McCarthy et al. from UK, have sent in a study on the demographic, socioeconomic, health, and lifestyle factors associated with self-harm and the attendance at the emergency department for self-harm, in relatively deprived communities in England. Youth/young age, physical and mental health co-morbidity, low financial status, and lack of social connectivity, were seen as significant risk factors for self-harm. These findings strengthen the already known evidence that helps in the formulation and implementation of suicide prevention strategies.
Esther Bayiga Zziwa et al. from Uganda, have studied pedestrian deaths and injuries at the ward level, which is the lowest reference unit for planning and administration in Kampala City. This exploratory work focuses on the areal distribution of pedestrian injuries and deaths, in an attempt to see if the differences between the observed clustering patterns are significant. Most crashes were found to be in the inner city along the major highways. The built environment and the passage of high-speed roads through the central business district were major factors in the increase in the number of pedestrian accidents.
Mariana Teixeira da Silva et al. from Brazil and USA, have made a presentation on the built environment as a factor in the incidence of elderly pedestrian collisions in Maringa city, based on data collected over a period of four years from 2014 to 2018. The study found a significant association between elderly pedestrian victims and the structured social spaces of the city: traffic lights at road crossings, roundabouts, schools, and hospitals.
Christine Ufashingabire Minani et al. from Malaysia and Rwanda, have sent in a systematic review of non-healthcare professionals and the effectiveness on them, of first-aid education in road traffic crashes. The data for the study covered a period of ten years from 2011 to 2021. The four principal factors under consideration in the evaluation of the non-healthcare professionals were knowledge, skills, attitude, and behaviour. It was found that further studies should be conducted on first-aid training that combines outcomes, knowledge, skills, and attitude to improve the rescue of road traffic crash victims.
Ramdane Oudha et al. from Algeria, have studied the best way to integrate road safety into the early phases of project design, by proposing an analytical tool to microscopically target road safety problems. The whole road to be studied is divided into sections of 100 m each. The methodology consists of combining the International Road Assessment Program with the multiple linear regression models, which allows for the prediction of road risk for every 100 m segment, thus facilitating onsite road safety audit inspections.
We hope that various applications of digital technologies will be guided by the outcomes of the sound scientific research as illustrated in these research articles. Perhaps, digital technologies will also assist in identifying new research areas and new research questions to support the target of reducing road traffic injuries by 50% in 2030.
Transportation Research and Injury Prevention Centre, Indian Institute of Technology Delhi, New Delhi, India
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