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Title: Rgonomics Assessment and Prediction Model of Passengers Comfort In A.A-LRT
???metadata.dc.contributor.*???: Gulelat Gatew (PhD)
Surafel, Shiferaw
Keywords: Engineering Anthropometry, biomechanics;ergonomic design;Addis Ababa Light Rail Transit (AA-LRT);Body surface area;Body mass index;Seat configuration
Issue Date: Jun-2015
Publisher: AAU
Abstract: Most problems in Ethiopia are the improper allocation of the job to the right because the areas do not properly allocate workers to the correct knowledge of the works since ergonomics principles and benefits are not yet known well in our country. The research study was intended to investigate whether the new rail vehicle interior design is appropriate with the sense of passenger comfort and goodness of passenger fit in seating dimensions with passenger’s anthropometric variables since the population of Addis Ababa human posture size are not being considered using ergonomics design and principle. The aim of this field study was to explore passenger comfort through the development of prediction model using statistical methods using passenger’s anthropometric variables. The data’s ware collected and analyzed for both passenger seat and standing capacities where a descriptive statistics such as means, standard deviations, fifth, seventy fifth and ninety fifth percentiles were being analyzed for the passenger seat dimensions. A multiple regression prediction model was also conducted to estimate the anthropometric parameters on passenger’s standing. As per the analysis of goodness of fit between the percentiles of passengers anthropometric and the train vehicles seats, a passenger mismatch has been observed in only male’s shoulder breadth and vehicles backrest width, and passengers mismatch had been also investigated using T-test using descriptive analysis in three corresponding parameters. These are between (hip breadth and seat width), (shoulder breadth and backrest width), and (knee height and seat height). Multiple regression models demonstrated, Passenger body mass index is the most statistically significant factor in predicting the passenger comfort using passenger anthropometric variables inside the rail vehicles. Therefore Passenger body mass index has been found as a better predicting model instead of passenger capacity models in better predicting passenger comfort and space allocations along Addis Ababa light rail transits.
Appears in Collections:Railway Engineering

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