Accident Prediction Model at Unsignalized Intersection Using Multiple Linear Regression Method
| Autor: | N. K. Oghoyafedo, J. O. Ehiorobo, Ebuka Nwankwo |
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| Rok vydání: | 2017 |
| Předmět: | |
| Zdroj: | July 2017. 1:379-389 |
| ISSN: | 2616-0501 2616-051X |
| Popis: | The issue of road accidents is an increasing problem in developing countries. This could be due to increasing road traffic/vehicle occupancy, geometric characteristics and road way condition. The factors influencing accidents occurrence are to be analysed for remedies. The purpose of this research is to develop an accident prediction model as a measure for future study, aid planning phase preceding the designed intervention, enhance the production of updated design standards to enable practitioners design unsignalized intersection for optimal safety, reduce the number of accidents at unsignalized intersections. Five intersections were selected randomly within Benin City and traffic count carried out at these intersections as well as geometric characteristics and roadway conditions. The prediction model was developed using multiple linear regression method and the standard error of estimate was computed to show how close the observed value is to the regression line. The model was validated using coefficient of multiple determination. The establishment of the relationship between accidents and traffic flow site characteristics on the other hand would enable improvement to be more realistically accessed. This study will also enhance the production of updated design standards to enable practitioners design unsignalized intersection for optimal safety, reduce the number of accidents at unsignalized intersections. |
| Databáze: | OpenAIRE |
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