Investigating fatal road accident data

[摘要] ENGLISH ABSTRACT: This thesis concerns the investigation of four analyses techniques in terms of their utility and adequacyfor analyzing fatal road accident data in South Africa.PROBLEM DEFINITION: Road accident data are summarized annually in various forms, but the relationships between thedifferent categorical variables are not determined. The study aimed to address this problem.Road accident rates are published in order to compare year-to-year change in an accident rate. It wasnecessary to investigate a method to determine whether these year-to-year changes are statisticallysignificant and whether there should necessarily be a reason for concern when an increase in accidentrate is detected.Multiple regression models also including qualitative variables were investigated in this study.ACCIDENT DATA AND ANALYSIS TECHNIQUES: Road accident data were found available in the format of a MS Access database which could bemanually investigated. Traffic and speed data were readily available from Mikros Traffic Monitoring(Pty) Ltd in the form of SANRAL's CTO Yearbooks and was found to be reliable and sufficientlydetailed. Any road geometric data were omitted from the study due to insufficient detail available.All data were found to show levels of poor data quality. Certain variables were thus omitted from thestudy e.g. the age group variable.The fatal road accident database was analysed using Correspondence Analysis and Association Rules(for analyses of the categorical variables) and, the application of the Poisson distribution for chancevariation analyses and Multiple Regression Analyses (for the continuous variables).METHODOLOGY: Fatal road accident data were gathered by performing queries in the fatal road accident database.Traffic and Speed data were gathered by manually investigating the SANRAL CTO Yearbooks andmanipulating the data to be integrated with the fatal road accident database. After all data manipulation was completed, the four analyses techniques mentioned above were applied using the software packageStatistica.FINDINGS: Correspondence Analysis and Association Rules were found to be adequate for analysing categoricalroad accident data variables with some data quality limitations and insufficient data sampling. Thetime period used for chance variation analysis was too short to deliver significant results. Threemultiple regression models were created with one of the models being able to predict the number offatalities per fatal accident with k equal to approximately 40%.CONCLUSIONS AND RECOMMENDATIONS: The following conclusions are drawn and recommendations are made based on the findings of thisstudy:~ Detailed and quality road accident data for South Africa is unavailable. Better quality data areurgently needed for the purpose of analysis.~ Correspondence Analysis is found to be the most appropriate technique for road accident dataanalysis and should be applied on an annual basis.~ Association Rules Analysis results are influenced by small sample sizes and too many unknownvariable categories. Larger sample sizes and exclusion of the unknown categories might improvethe results.~ The analysis period for chance variation is too short and a longer period will provide moresignificant results.~ The multiple regression model predicting the number of fatalities per fatal accident is accepted interms of utility and adequacy.

[发布机构] Stellenbosch University