2020 ◽  
Vol 54 (2) ◽  
pp. 117-124
Author(s):  
Byeong-Hyo Cho ◽  
◽  
Yun-Sik Shin ◽  
Jin-Woo Yun ◽  
Gil-Ho Kim ◽  
...  

Author(s):  
Seok-Ji Park ◽  
Duk-Kyu Park ◽  
Chang-Joo Kim ◽  
Young-Heung Kang

Author(s):  
Adoh Lucky Ugochukwu ◽  
Mutswatiwa Lovejoy ◽  
Akello fiona Mercy

Safety and security are among the major basic needs for the public in daily life and transportation plays a crucial role in satisfying this need. According to the World Health Organization (WHO) data, estimates of 1.2 million people worldwide died as a result of road traffic injuries in 2013 and it is estimated that road traffic injuries will be the 6th leading cause of death by 2030. Among the various types of road traffic injuries, accidents between trains and road vehicles are the deadliest and are associated with high cost of accidents. As Railway transportation continues to be an important piece to the overall national transportation puzzle in Ethiopia and as congestion continues to increase on the nation’s roadways, commuters continue to flock to public transit as an alternative transportation mode. In Addis Ababa Light Rail Transit, there are over 20 level crossings, this represent a significant safety hazard to both road and rail users. In this paper, we used safety demonstration by complete system analysis to carry out safety demonstration for level crossing at Addis Ababa Light Rail Transit, and Failure mode effect analysis was used for identifying the potential hazards associated with the system and their root causes. Hazards associated with Addis Ababa Light Rail Transit level crossing are identified and classified, and results showed that 41% of the hazards are caused by Human errors, technical problems has 32%, non-compliance with standard operating procedures takes 18% and 9% are caused by other factors. Our Failure mode effect analysis result shows that safe redesign of the level crossing, management and operation of level crossings can reduce risks, and frequent orientation of road vehicle users to always give attention to traffic signal in level crossing can reduce the number of fatal and serious incidents and collisions.


2021 ◽  
Vol 39 (2) ◽  
pp. 107-128
Author(s):  
SeoHyeon Min ◽  
Min-Kyu Lee ◽  
SUNGMOON JUNG

2021 ◽  
Vol 11 (19) ◽  
pp. 8828
Author(s):  
Alamirew Mulugeta Tola ◽  
Tamene Adugna Demissie ◽  
Fokke Saathoff ◽  
Alemayehu Gebissa

The reduction of traffic crashes, as well as their socio-economic consequences, has captivated the attention of safety professionals and transportation agencies. The most important activity for an effective road safety practice is to identify hazardous roadway areas based on a spatial pattern analysis of crashes and an evaluation of crash spatial relations with neighboring areas and other relevant factors. For decades, safety researchers have adopted several techniques to analyze historical road traffic crash (RTC) information using the advanced GIS-based hot spot analysis. The objective of this study is to present a GIS technique for identifying crash hot spots based on spatial autocorrelation analysis using a four-year (2014–2017) crash data across Ethiopian regions, as well as zones and towns in the Oromia region. The study considered the corresponding severity values of RTCs for the analysis and ranking of crash hot spot areas. The spatial autocorrelation tool in ArcGIS 10.5 was used to analyze the spatial patterns of RTCs and then the Getis Ord Gi* statistics tool was used to identify high and low crash severity cluster zones. The results showed that the methods used in this analysis, which incorporated Moran’s I spatial autocorrelation of crash incidents, Getis Ord Gi* and crash severity index, proved to be a fruitful strategy for identifying and ranking crash hot spots. The identified crash hot spot areas are along the entrance to and exit from Addis Ababa, Ethiopia’s capital city, so the responsible bodies and traffic management agencies should give top priority attention and conduct a thorough study to reduce the socio-economic effect of RTCs.


Sign in / Sign up

Export Citation Format

Share Document