Applying fast and frugal tree heuristic algorithm to identify factors influencing crash severity of bicycle-vehicle crashes in Tamilnadu.
31 Aug 2020-International Journal of Injury Control and Safety Promotion (Taylor & Francis)-Vol. 27, Iss: 4, pp 482-492
TL;DR: From the results of the present study, FFT acts as a complementary tool to other complex machine learning algorithms such as support vector machines, random forest, logistic regression and CART for reducing the severity of bicycle-involved crashes at the planning and operations levels.
Abstract: Though bicycle as a mode of transport has many environmental and societal benefits as well as health benefits, bicyclists are one of the most vulnerable road users. According to the report by the M...
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01 May 2021
TL;DR: In this paper, the authors investigated the injury pattern in heavy-duty single vehicle crashes and provided appropriate countermeasures and techniques that can mitigate heavy duty single-vehicle collisions in India.
Abstract: According to the reports of NITI (National Institute of Transforming India) Aayog Freight 2018, Road freight is the prime mode (59%) of transport in India with the highest per ton-mile cost than rail or water freight (NITI Aayog, 2018). This road freight usually uses heavy-duty vehicles to transmit voluminous goods and services to the destination in time. Due to this, the heavy-duty vehicle population increased on the Indian roads. Heavy-duty vehicle crashes cause a substantial economic burden to the nation and result in more severity to the involved because of differences in weight, speed, and size. Among heavy-duty vehicle crashes, a significant proportion of crashes are heavy-duty single-vehicle crashes. Single-vehicle crashes are those crashes where the vehicle drivers either involve in self-skidding or hit a stationary object (like a tree). The purpose of this study is to investigate the injury pattern in heavy-duty single vehicle crashes.
For this study, the data is extracted from the RADMS (Road Accident Database Management System) database and linked with hospital data. This data includes demographic information, road, environmental and injury characteristics. Later, descriptive statistics performed on the dataset to analyse all heavy-duty single-vehicle crashes between January 2013 and December 2018. Overall, 4704 single heavy-duty vehicle crashes occurred during this period, among which 1244 were fatal crashes. Results show that male drivers aged 26 to 64 years old suffered more fatalities (88%), followed by the 18-25 age group (8%). Examination of injury information found that heavy-duty vehicle drivers mostly sustained multiple injuries (9.05%), head injuries (5.05%), followed by leg injuries (4.29%). The results showed that specific road and environmental factors increase the chance of fatal crashes among heavy-duty vehicle drivers. Furthermore, the proposed study gives insight into the injury characteristics and key contributing factors causing heavy-duty single-vehicle crashes. Finally, this study provides appropriate countermeasures and techniques that can mitigate heavy-duty single-vehicle collisions.
TL;DR: In this article , a simulation-based bicycle-vehicle conflict data generation and assessment approach is proposed, which uses a three-dimensional visualization and virtual reality platform, integrating traffic microsimulation to reproduce a naturalistic driving/cycling-enabled experimental environment.
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TL;DR: It is argued that certain duties of patients counterbalance an otherwise unfair captivity of doctors as helpers and that vulnerability does not exclude obligation.
Abstract: There has been a shift from the general presumption that “doctor knows best” to a heightened respect for patient autonomy. Medical ethics remains one-sided, however. It tends (incorrectly) to interpret patient autonomy as mere participation in decisions, rather than a willingness to take the consequences. In this respect, medical ethics remains largely paternalistic, requiring doctors to protect patients from the consequences of their decisions. This is reflected in a one-sided account of duties in medical ethics. Medical ethics may exempt patients from obligations because they are the weaker or more vulnerable party in the doctor-patient relationship. We argue that vulnerability does not exclude obligation. We also look at others ways in which patients’ responsibilities flow from general ethics: for instance, from responsibilities to others and to the self, from duties of citizens, and from the responsibilities of those who solicit advice. Finally, we argue that certain duties of patients counterbalance an otherwise unfair captivity of doctors as helpers.
17,373 citations
TL;DR: The results imply that bicyclist fault is more closely correlated with greater bicyclist injury severity than driver fault, which supports the commonly used 30km/h speed limit in residential neighborhoods.
503 citations
TL;DR: The analysis shows that walking and cycling have population-level health benefits even after adjustment for other physical activity (PA), and public health approaches would have the biggest impact if they are able to increase walked and cycling levels in the groups that have the lowest levels of these activities.
Abstract: Background and objective: Walking and cycling have shown beneficial effects on population risk of all-cause mortality (ACM). This paper aims to review the evidence and quantify these effects, adjusted for other physical activity (PA). Data sources: We conducted a systematic review to identify relevant studies. Searches were conducted in November 2013 using the following health databases of publications: Embase (OvidSP); Medline (OvidSP); Web of Knowledge; CINAHL; SCOPUS; SPORTDiscus. We also searched reference lists of relevant texts and reviews. Study eligibility criteria and participants: Eligible studies were prospective cohort design and reporting walking or cycling exposure and mortality as an outcome. Only cohorts of individuals healthy at baseline were considered eligible. Study appraisal and synthesis methods: Extracted data included study population and location, sample size, population characteristics (age and sex), follow-up in years, walking or cycling exposure, mortality outcome, and adjustment for other co-variables. We used random-effects meta-analyses to investigate the beneficial effects of regular walking and cycling. Results: Walking (18 results from 14 studies) and cycling (8 results from 7 studies) were shown to reduce the risk of all-cause mortality, adjusted for other PA. For a standardised dose of 11.25 MET.hours per week (or 675 MET. minutes per week), the reduction in risk for ACM was 11% (95% CI = 4 to 17%) for walking and 10% (95% CI = 6 to 13%) for cycling. The estimates for walking are based on 280,000 participants and 2.6 million person-years and for cycling they are based on 187,000 individuals and 2.1 million person-years. The shape of the dose–response relationship was modelled through meta-analysis of pooled relative risks within three exposure intervals. The dose–response analysis showed that walking or cycling had the greatest effect on risk for ACM in the first (lowest) exposure interval. Conclusions and implications: The analysis shows that walking and cycling have population-level health benefits even after adjustment for other PA. Public health approaches would have the biggest impact if they are able to increase walking and cycling levels in the groups that have the lowest levels of these activities. (Continued on next page)
383 citations
TL;DR: In this article, the authors investigated risk factors that significantly contribute to the injury severity of bicyclists in bicycle/motor-vehicle crashes while systematically accounting for unobserved heterogeneity within the crash data.
249 citations
TL;DR: The main pathways between cycling and health are reviewed and discussed under two perspectives — generalizable epidemiological evidence for health effects and specific impact modeling to quantify health impacts in concrete settings.
222 citations