Pedestrian injuries are a leading cause of death among South African children, and young children residing in low-income communities are more at risk, due to various factors such as inadequate road infrastructure, exposure to traffic due to reliance on walking as a means of transport, and lack of supervision. This study used a cross-sectional, non-randomized self-report survey to assess pedestrian safety knowledge, road-crossing behaviour and pedestrian injuries of primary school children in selected low-income settings in Cape Town. The survey focused on three primary schools that had joined the Safe Kids Worldwide Model School Zone Project and was administered to 536 children aged 6-15 years, in their home language of isiXhosa. Descriptive and bivariate analyses as well as multivariate regression analyses were conducted to investigate potential predictor variables for pedestrian collision severity and unsafe road-crossing behaviour. Walking was the sole form of travel for 81% of the children, with a large proportion regularly walking unsupervised. Children who walk to or from school alone were younger and reported riskier road-crossing behaviour, although children who walk accompanied tended to have higher pedestrian collision severity. "Negligent Behaviour" related to road-crossing was significantly associated with higher pedestrian collision severity, with predictors of "Negligent Behaviour" including the lack of pedestrian safety knowledge and greater exposure to traffic in terms of time spent walking. More than half of the reported pedestrian collisions involved a bicycle, and older boys (10-15 years) were most at risk of experiencing a severe pedestrian injury. The findings substantiate emerging evidence that children in low-income settings are at greater risk for child pedestrian injury, and emphasise the need for evidence-based safety promotion and injury prevention interventions in these settings.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.aap.2016.11.020 | DOI Listing |
J Phys Act Health
January 2025
Department of Urban Planning and Architectural Design, German University of Technology, Muscat, Oman.
Background: Ensuring a livable and healthy built environment that addresses challenges of climate change and the pandemic of noncommunicable diseases should include creating an environment support of physical activity. This study aims to build local evidence on improving the residential areas by assessing the built environment of 4 residential areas in Oman.
Methods: This study uses the Microscale Audit of Pedestrian Streetscapes-Mini, a 15-item tool with 4 subscales (destinations and land use, aesthetics, pedestrian infrastructure, and crossings/traffic safety), to conduct environmental audits of 4 areas in Barka and Nizwa, Oman.
Accid Anal Prev
December 2024
Department of Traffic Engineering, University of Shanghai for Science and Technology, Shanghai, China.
Right-turning vehicles and pedestrians share the right-of-way during the permitted signal phase at intersections in countries with right-handed traffic. Although right-turning vehicles are required to stop or yield to pedestrians according to the traffic rules, there still remains circumstances where the two will compete, posing significant safety risks to pedestrians. To investigate the impact mechanism of right-turn configurations, driver characteristics, and traffic operational features on vehicle-pedestrian conflict risk, a driving simulator experiment was conducted.
View Article and Find Full Text PDFSci Rep
December 2024
School of Electronics Engineering, Vellore Institute of Technology, Vellore, India.
Autonomous vehicles, often known as self-driving cars, have emerged as a disruptive technology with the promise of safer, more efficient, and convenient transportation. The existing works provide achievable results but lack effective solutions, as accumulation on roads can obscure lane markings and traffic signs, making it difficult for the self-driving car to navigate safely. Heavy rain, snow, fog, or dust storms can severely limit the car's sensors' ability to detect obstacles, pedestrians, and other vehicles, which pose potential safety risks.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Electrical Engineering, Imam Khomeini Naval Science University of Nowshahr, Nowshahr, Iran.
Road traffic crashes (RTCs) are considered one of the major public health issues in many countries worldwide. Investigating factors of traffic crashes, accidents, and disasters can facilitate and aid in identifying measures to mitigate their frequency and severity as well as occurrence and impact, thereby enhancing road safety. This study aims to investigate the factors that contribute to road traffic accidents in the Gaza Strip, Palestine.
View Article and Find Full Text PDFJ Imaging
December 2024
School of Innovation, Design and Technology (IDT), Mälardalen University, 72123 Västerås, Sweden.
As the demand for autonomous driving (AD) systems has increased, the enhancement of their safety has become critically important. A fundamental capability of AD systems is object detection and trajectory forecasting of vehicles and pedestrians around the ego-vehicle, which is essential for preventing potential collisions. This study introduces the Deep learning-based Acceleration-aware Trajectory forecasting (DAT) model, a deep learning-based approach for object detection and trajectory forecasting, utilizing raw sensor measurements.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!