Statistical Analysis for Identification of Motor Vehicle Crash Black Spots and Low-Cost Improvements (Case of Addis Ababa To Debre Birhan Road)
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Date
2017-11
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Addis Ababa University
Abstract
A study was conducted to Statistical Analysis for Identification of Motor Vehicle Crash
Black Spots and Low Cost Improvements on the road from Addis Ababa to Debre
Birhan. The research was conducted exhausting both historically recorded crash data
and Predictive Empirical Bayesian statistical methods of analysis for identifying and
prioritizing black spot segments.
Consistent with results of black spot, the Upper Control Limit through Crash Rate
(using Dangerous Factor, DF), Crash Score and Mixed Crash Frequency-Crash Rate
statistical methods were simultaneously applied and used to rank the most probable
hazardous road segments through crash consequence types.
The predictive Empirical Bayesian method of statistical analysis was further used to
identify black spots which combine the observed actual number of Crash Frequency with
the predicted number of Crash Frequency. Then subsequently, the excess number of
Crash Frequency was used to identify and rank segments.
The total number of Motor Vehicle Crashes reported was 587 within 2012/13-2015/16
period of study years, but some crashes contributed for more than one fatal, serious, slight
and property damage consequences. Hence, based on the crash severity results, there were
160 fatal, 254 serious injuries, 330 slight injuries and 488 property damages obtained
from police recorded archive booklet files resulted for a total of 1,232 consequences.
Accordingly, 20 segments among the 108 segments were identified as black spots.
Established on the results, for six segments low cost improvements were recommended.
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Keywords
Motor Vehicle Crashes