scholarly journals Gender Effects in Young Road Users on Road Safety Attitudes, Behaviors and Risk Perception

2016 ◽  
Vol 7 ◽  
Author(s):  
Pierluigi Cordellieri ◽  
Francesca Baralla ◽  
Fabio Ferlazzo ◽  
Roberto Sgalla ◽  
Laura Piccardi ◽  
...  
BMJ Open ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. e035007 ◽  
Author(s):  
Sergio Useche ◽  
Francisco Alonso ◽  
Luis Montoro ◽  
Leandro Garrigós

ObjectiveThis study had two objectives: first, to test the effects of sociodemographic variables, and the effects of three key road safety skills (knowledge–risk perception–attitudes) on the use of passive safety elements (PSEs) among teenagers; and second, to assess the differential impact of the study variables on PSEs use from a gender-based perspective.Setting and participantsThis cross-sectional study was framed in the paradigm of primary care, and it involved students from several educational centres in Spain. A sample of 827 Spanish teenagers (52.4% females and 47.6% males) with a mean age of M=14.41–7 (12–19) years was used.ResultsThrough SEM modelling, we found that the use of PSEs is largely explained by psychosocial variables through the mediation of three road safety skills: risk perception (β=0.103***), rule knowledge (β=0.095*) and attitudes towards road safety (β=0.186***). Furthermore, multigroup analyses showed that, although most variables explain the use of PSEs among teenagers in a similar way, key gender-based differences exist in this regard.ConclusionsRoad safety skills have a significant effect on the use of PSEs among Spanish teenagers, and gender explains some differences in the mechanisms which predict them. Also, in the study we discuss the need for strengthening school-based interventions aimed at helping this vulnerable group of road users acquire and develop positive behavioural competences.


Author(s):  
Dagmara Jankowska-Karpa ◽  
Justyna Wacowska-Slezak ◽  
Aneta Wnuk
Keyword(s):  

Safety ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. 40
Author(s):  
Robert Zůvala ◽  
Kateřina Bucsuházy ◽  
Veronika Valentová ◽  
Jindřich Frič

Road accident occurrence is often the result of driving system malfunctions, and road safety improvements need to focus on all basic driving components—the vehicle, road infrastructure, and road users. Only focusing on one type of improvement does not necessarily lead to increased road safety. Instead, improved road safety requires comprehensive measures that consider all factors using in-depth accident analysis. The proposed measures, based on the findings from in-depth data that have general applicability, are necessary to determine whether data gained from in-depth studies adequately represent national statistics. This article aims to verify the representativeness of the Czech In-Depth Accident Study at a national level. The main contribution of this article lies in the use of a weighting method (specifically, a raking procedure) to generalise research results and render them applicable to a whole population. The obtained results could be beneficial at the national level, in the Czech Republic, and also on the supranational level. The applicability of this method on accident data is verified; thus, the method can be applied also in other countries or can be used to verify the applicability of conclusions from the Czech in-depth study also on a European or worldwide level.


2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Abd-Elhamid M. Taha

The Safe System (SS) approach to road safety emphasizes safety-by-design through ensuring safe vehicles, road networks, and road users. With a strong motivation from the World Health Organization (WHO), this approach is increasingly adopted worldwide. Considerations in SS, however, are made for the medium-to-long term. Our interest in this work is to complement the approach with a short-to-medium term dynamic assessment of road safety. Toward this end, we introduce a novel, cost-effective Internet of Things (IoT) architecture that facilitates the realization of a robust and dynamic computational core in assessing the safety of a road network and its elements. In doing so, we introduce a new, meaningful, and scalable metric for assessing road safety. We also showcase the use of machine learning in the design of the metric computation core through a novel application of Hidden Markov Models (HMMs). Finally, the impact of the proposed architecture is demonstrated through an application to safety-based route planning.


ICCD ◽  
2019 ◽  
Vol 2 (1) ◽  
pp. 601-606
Author(s):  
Widodo Budi Dermawan ◽  
Dewi Nusraningrum

Every year we lose many young road users in road traffic accidents. Based on traffic accident data issued by the Indonesian National Police in 2017, the number of casualties was highest in the age group 15-19, with 3,496 minor injuries, 400 seriously injured and 535 deaths. This condition is very alarming considering that student as the nation's next generation lose their future due to the accidents. This figure does not include other traffic violations, not having a driver license, not wearing a helmet, driving opposite the direction, those given ticket and verbal reprimand. To reduce traffic accident for young road user, road safety campaigns were organized in many schools in Jakarta. This activity aims to socialize the road safety program to increase road safety awareness among young road users/students including the dissemination of Law No. 22 of 2009 concerning Road Traffic and Transportation. Another purpose of this program is to accompany school administrators to set up a School Safe Zone (ZoSS), a location on particular roads in the school environment that are time-based speed zone to set the speed of the vehicle. The purpose of this paper is to promote the road safety campaigns strategies by considering various campaign tools.


2016 ◽  
Vol 26 (5) ◽  
pp. 13-19
Author(s):  
Birutė Strukčinskienė ◽  
Robert Bauer ◽  
Sigitas Griškonis ◽  
Vaiva Strukčinskaitė

The aim of the study was to examine the long-term trends in pedestrian mortality for children (aged 0 to 14 years) and young people (aged 15 to 19 years) over four decades in transitional Lithuania. Methods. Road traffic fatality data were obtained from Statistics Lithuania and the Archives of Health Information Centre. Trends were analysed by linear regression using “Independence” as a slopechanging intervention in 1991 and population as a further explanatory factor in structural time series models. Results. The impact of the interventions, along with the reforms and changes related with the Independence, on pedestrian fatality trends in our time series model was found highly statistically significant for children 0 to 14 years (p<0.001) and still significant for young people 15 to 19 years (p<0.05). No significant impact on the trend of road traffic deaths was found for the “control-groups” of non-pedestrian road users in the age group 0 to 14 years and adult pedestrians (over 19 years of age). For the age group 15 to 19 years the effect of reforms was also significant for non-pedestrians (p<0.05). These results indicate that the effect of measures and changes used in the post-independence period was more specific in children that participated in road traffic as pedestrians than in adult pedestrians, or in nonpedestrian road users. Conclusions. Pedestrian deaths in Lithuania fell significantly in the age groups 0-14 and 15-19 years. A declining trend was found in road traffic fatalities and in pedestrian deaths in transitional Lithuania in the post-independence period. Socioeconomic and political transformations, systematic reforms in healthcare along with sustainable preventive measures may have contributed to this decrease. Targeted road safety measures were road traffic regulations, pedestrian education and environmentally based prevention measures. As child pedestrians are the most vulnerable group of road users, continued road safety education and promotion are recommended in order to maintain this trend, and to involve adult pedestrians in this development.


Author(s):  
Ahmet Yıldız

Traffic roads are a core element of GIS and many volunteered systems like openstreetmaps have the goal to make road data publicly available. Road users collecting geographical information and sharing them according some rules are a great opportunity to make our roads a safer place. Traffic accidents are a major cause of death and with increase in urbanization and motorization the risk is expected to rise higher. Research regarding road safety is mostly reactive; sections of the road where a lot of accidents has already happened are investigated and possibly causes are identified and then improved. This means, that people have to die in order to make those road sections safe. The system described in this chapter is a proactive method and can be operated by the community or some responsible authority. The gathered data is also very useful for different research areas like social sciences or civil engineering.


Safety ◽  
2018 ◽  
Vol 4 (4) ◽  
pp. 58 ◽  
Author(s):  
Francesca Demasi ◽  
Giuseppe Loprencipe ◽  
Laura Moretti

Attention to the most vulnerable road users has grown rapidly over recent decades. The experience gained reveals an important number of fatalities due to accidents in urban branch roads. In this study, an analytical methodology for the calculation of urban branch road safety is proposed. The proposal relies on data collected during road safety inspections; therefore, it can be implemented even when historical data about traffic volume or accidents are not available. It permits us to identify geometric, physical, functional, and transport-related defects, and elements which are causal factors of road accidents, in order to assess the risk of death or serious injuries for users. Traffic volume, average speed, and expected consequences on vulnerable road users in case of an accident allow us to calculate both the level of danger of each homogeneous section which composes the road, and the hazard index of the overall branch. A case study is presented to implement the proposed methodology. The strategy proposed by the authors could have a significant impact on the risk management of urban roads, and could be used in decision-making processes to design safer roads and improve the safety of existing roads.


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