Road Safety Reimagined: Exploring Causes, Effects, and Innovative Educational Interventions for Accident Prevention | Chapter 1 | An Overview of Literature, Language and Education Research Vol. 7

This chapter is focused on road traffic accidents, exploring the causes and effects of road traffic accidents as well as the safety education intervention that could be employed to enhance the knowledge and awareness of motorists so as to prevent road traffic accidents. In the course of the study regional disparities in road safety were explored. Based on the content explored in this chapter, revealed that road accidents are a major cause of morbidity and mortality worldwide, especially in low and middle-income countries due to poor road infrastructures and poor knowledge and attitude towards driving. It was also noted that road accidents are caused by a number of factors which include environmental factors, vehicle factors (road pavement condition factors, and vehicle operator or driver factors). It was also finally stated that Safety Education Intervention which comprises safety training intervention, supportive supervision and capacity building are key intervention programs that can be adopted to enhance the knowledge and awareness of road users in order to reduce the prevalence of road accidents.

 

Author (s) Details

 

Kayode V. Fowode
Centre for Occupational Health, Safety and Environment, University of Port Harcourt, Port Harcourt, Nigeria.

 

Ify L. Nwaogazie
Department of Civil & Environmental Engineering, University of Port Harcourt, Port Harcourt, Nigeria.

 

Please see the book here:- https://doi.org/10.9734/bpi/aoller/v7/2900

Categorization of Road Accidents Related to the Default of Signaling: A Case Study of the Yaoundé-Douala Highway, Southern Cameroon | Chapter 13 | New Approaches in Engineering Research Vol. 12

 This chapter examines the types of road accidents caused by a lack of signposting, as numerous accidents have happened in Cameroon as a result of poor signposting. This investigation will take place on the Yaoundé-Douala motorway. Available The examination of each accident was made possible using field data collected in the years 2007, 2009, and 2011. It shows that 108 occurrences (about 20%) of the 569 accidents documented across a 114-kilometer stretch were caused by a failure or lack of signage. On the one hand, a clinical analysis revealed four collision scenarios, while on the other, seven were developed based on factors such as lack of signposting at crossroads, lack of vertical and/or horizontal alignment or a slightly raised bump, and lack of signpost for normal parking layouts or no parking at certain critical points.

Author(S) Details

Zogo Tsala Simon Armand
Department of Civil Engineering, ENSET, University of Yaoundé 1, Ebolowa, Cameroon and Technology and Applied Sciences Laboratory, University of Douala, P.O.Box 7236, Douala, Cameroon.

Ayissi Zacharie Merlin
Laboratory of Energy Materials Modelisation and Method, University of Douala, Douala, Cameroon.

Noah Pierre Marcel Anicet
Department of Mechanical Engineering, ENSET, University of Douala, Douala, Cameroon and Laboratory of Mechanics, University of Douala, Douala, Cameroon.

Betene Ebanda Fabien
Department of Mechanical Engineering, ENSET, University of Douala, Douala, Cameroon and Laboratory of Mechanics, University of Douala, Douala, Cameroon.

Ayina Ohandja Louis Max
National Advanced School of Engineering, University of Yaoundé 1, Yaoundé, Cameroon.

View Book:- https://stm.bookpi.org/NAER-V12/article/view/3847

Categorization of Road Accidents Related to the Default of Signaling: A Case Study of the Yaoundé-Douala Highway, Southern Cameroon | Chapter 13 | New Approaches in Engineering Research Vol. 12

This chapter examines the types of road accidents caused by a lack of signposting, as numerous accidents have happened in Cameroon as a result of poor signposting. This investigation will take place on the Yaoundé-Douala motorway. Available The examination of each accident was made possible using field data collected in the years 2007, 2009, and 2011. It shows that 108 occurrences (about 20%) of the 569 accidents documented across a 114-kilometer stretch were caused by a failure or lack of signage. On the one hand, a clinical analysis revealed four collision scenarios, while on the other, seven were developed based on factors such as lack of signposting at crossroads, lack of vertical and/or horizontal alignment or a slightly raised bump, and lack of signpost for normal parking layouts or no parking at certain critical points.

Author (S) Details

Zogo Tsala Simon Armand

Department of Civil Engineering, ENSET, University of Yaoundé 1, Ebolowa, Cameroon and Technology and Applied Sciences Laboratory, University of Douala, P.O.Box 7236, Douala, Cameroon

Ayissi Zacharie Merlin

Laboratory of Energy Materials Modelisation and Method, University of Douala, Douala, Cameroon.

Noah Pierre Marcel Anicet

Department of Mechanical Engineering, ENSET, University of Douala, Douala, Cameroon and Laboratory of Mechanics, University of Douala, Douala, Cameroon.

Betene Ebanda Fabien

Department of Mechanical Engineering, ENSET, University of Douala, Douala, Cameroon and Laboratory of Mechanics, University of Douala, Douala, Cameroon.

Ayina Ohandja Louis Max

National Advanced School of Engineering, University of Yaoundé 1, Yaoundé, Cameroon.

View Book :- https://stm.bookpi.org/NAER-V12/article/view/3847

A Prudence Introspection of Road Accident Prediction through Deep Learning | Chapter 8 | Emerging Trends in Engineering Research and Technology Vol. 4

The research is based on the vehicle mishaps venture to gather and structure a dynamic, secure transportation lamentably vehicle crashes were unavoidable. The accident prediction related to the risky environment data collection and arrangements based on highest priority of reality of accidents. The social activity and roadway structures are useful in the progression of traffic security control approach. We accept that to secure the best possible setback decline impacts with constrained budgetary resources, it is fundamental that measures  be  set up  on coherent and objective studies of the explanations behind mishaps and seriousness of wounds. A survey based on the different algorithms able to predict the road accident prevention methods. This paper exhibits a couple of models to predict the reality of harm that occurred in the midst of car accidents using three artificial intelligent approaches (AI). The proposed scheme contributes a neural system prepared utilizing decision trees and fluffy c implies clustering methodology for division.

Author (s) Details

V. Priya
Department of Computer Science, School of Computing Sciences, Vels Institute of Science, Technology and Advanced Studies, (VISTAS), Chennai, India and Department of Computer Appications, Dr. MGR Janaki College of Arts and Science for Women, Chennai, India.

Dr. C. Priya
Department of Information Technology, School of Computing Sciences, Vels Institute of Science, Technology and Advanced Studies, (VISTAS), Chennai India.

View Book :- http://bp.bookpi.org/index.php/bpi/catalog/book/180