Riders' Satisfaction with Public Transportation Performance: The Case of Addis Ababa Light Rail Transit (AALRT)

2021 ◽  
Vol 37 (1) ◽  
pp. 79-101
Author(s):  
Mintesnot G. Woldeamanuel ◽  
Berhanu Woldetensae
Keyword(s):  
Public Transportation ◽  
Addis Ababa ◽  
Light Rail ◽  
Rail Transit ◽  
Light Rail Transit

Estimation of the Environmental Load Caused by Introducing Light Rail Transit Using an Urban Transportation Simulator

2013 ◽  
Vol 295-298 ◽  
pp. 669-672
Author(s):  
Nozomi Kudo ◽  
Hideo Nakamura
Keyword(s):  
Public Transportation ◽  
Urban Transportation ◽  
Light Rail ◽  
Rail Transit ◽  
Environmental Load ◽  
Light Rail Transit ◽  
Low Carbon ◽  
Modal Shift

A modal shift from automobiles is imperative in the transportation field for realizing a low-carbon society. We have developed a simulator that can quantitatively assess the effect of a modal shift by simulating track-based public transportation, such as LRT (Light Rail Transit), and automobile transportation. This paper presents an example in which we used the simulator to calculate the effect in a case where track-based transportation is implemented.

scholarly journals Passenger Flows Estimation of Light Rail Transit (LRT) System in Izmir, Turkey Using Multiple Regression and ANN Methods

1970 ◽  
Vol 24 (1) ◽  
pp. 1-14
Author(s):  
Mustafa Özuysal ◽  
Gökmen Tayfur ◽  
Serhan Tanyel
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Multiple Regression ◽  
Public Transportation ◽  
Light Rail ◽  
Rail Transit ◽  
Light Rail Transit ◽  
Passenger Flow ◽  
Feed Forward Back Propagation ◽  
Artificial Neural

Passenger flow estimation of transit systems is essential for new decisions about additional facilities and feeder lines. For increasing the efficiency of an existing transit line, stations which are insufficient for trip production and attraction should be examined first. Such investigation supports decisions for feeder line projects which may seem necessary or futile according to the findings. In this study, passenger flow of a light rail transit (LRT) system in Izmir, Turkey is estimated by using multiple regression and feed-forward back-propagation type of artificial neural networks (ANN). The number of alighting passengers at each station is estimated as a function of boarding passengers from other stations. It is found that ANN approach produced significantly better estimations specifically for the low passenger attractive stations. In addition, ANN is found to be more capable for the determination of trip-attractive parts of LRT lines.   Keywords: light rail transit, multiple regression, artificial neural networks, public transportation

scholarly journals Safety Demonstration and Risk Management at Rail-Road Level Crossing at Addis Ababa Light Rail Transit Network

2019 ◽  
pp. 103-109
Author(s):  
Adoh Lucky Ugochukwu ◽  
Mutswatiwa Lovejoy ◽  
Akello fiona Mercy
Keyword(s):  
Road Traffic ◽  
Addis Ababa ◽  
Light Rail ◽  
Rail Transit ◽  
Light Rail Transit ◽  
Level Crossing ◽  
Effect Analysis ◽  
Road Traffic Injuries ◽  
Mode Effect ◽  
Failure Mode Effect Analysis

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.

scholarly journals The governance of Addis Ababa Light Rail Transit

2021 ◽  
Author(s):  
Meseret Kassahun
Keyword(s):  
Addis Ababa ◽  
Light Rail ◽  
Rail Transit ◽  
Light Rail Transit ◽  
African Cities

Chapter 11 in the book Refractions of the National, the Popular and the Global in African Cities.

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