Browsing by Author "Gadisa, Layo"

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    Analysis of Road Traffic Violations in Addis Ababa City (The cause of Arada sub-city)
    (Addis Ababa University, 2018-10) Gadisa, Layo; Getu, Segni (PhD)
    Road traffic injury death rates are highest in the African region. Violation of traffic rules, which is a human factor, is an important factor behind traffic crashes and many lives could be saved if all drivers complied with the rules and regulations of road. Other than piece of reports from traffic police, very few is known about magnitude, trends and characteristics of traffic offences in Addis Ababa City. In addition, almost no literatures exists on differences in traffic offences by driver and vehicle characteristics in Addis Ababa city. The objective of this research is to characterize and identify most common traffic offences, trends and magnitudes of traffic offences in Arada sub city over 3 years. Further, this study also investigates differences in traffic offences by drivers and vehicle characteristics. Finally, this study finds attitudes of traffic offenders towards unsafe driving behaviors. Methodology-To achieve the objectives of this research two methods were followed. The first method was secondary traffic offence data collection from Arada sub city over (2007E.C2010E.C) and analyzed. The second method was through questionnaires results from 385 traffic offenders at sub city traffic police department who come to take back their driving license and vehicle plate after paying traffic offence fines. Questions containing traffic offender and vehicle characteristics, history on traffic crashes and frequency of traffic offences for selected traffic offence types and attitudes towards unsafe driving behaviors were prepared. These collected data were analyzed by Excel and SPSS; Independent t-test, one-way ANOVA test, Chi-square, Descriptive and frequencies were used. Results-Over all, 154436 traffic offences registered, 95.6% occurred by male. It showed an increase of 8.3% and 13.04% in 2008 E.C and 2009 E.C respectively. But, the rate is decreasing for female averagely by 2.4% and increasing for male averagely by 13.7%. The most common traffic offences were traffic flow obstruction (12.9%), disrespecting prohibiting signs (11.3%), parking of motor vehicles on prohibited areas (8.5%), overloading (8.2%) and using mobile phone while driving (7.8%). Youth groups (18-30 years) are the most traffic offenders than any other age category and drivers older than 50 were the second traffic offenders as compared to licensed driver population in the city. Drivers with license level 4, 5 and license level 6 (with old licensing system) were more involved in traffic offences than others as compared to their corresponding license population in the city. Code 1, 5 and others (T, CD, UN, ET and police) vehicles showed higher involvement in risk factors of road traffic crashes. Further, vehicles coded 1 showed higher involvement in total traffic offences. Results of Chi-square showed that there is an association of driver and vehicle characteristics and crash involvements. Traffic offenders with degree and above education level, 11-15 years of driving experience, low income, code 3, new vehicles with (0-5 service year) and privately owned vehicles showed higher involvement in traffic crashes than others . Results showed that male (p-value=0.002), in-friendship or cohabited (p-value=0.0022), 3-5 years of driving experience (p-value=0.036), taxis (p-value=0.036), medium income (p-value=0.001) traffic offenders showed higher significant score in speeding at 5%. In case of red-light running, traffic offenders of 24-29 years old, (p-value=0.012), private workers, (p-value=0.003), vehicle service year, 6-10 years (p-value=0.001) showed significant higher score. Finally, respondents have negative attitudes towards unsafe driving behaviors but they still don’t completely translate into positive behaviors. Conclusions- It can be concluded that male, 18-30 years, vehicles coded-1 (taxis), coded-3 (commercial vehicles) and coded-5, and drivers with license level-4, license level-5 and license level-6 were highly connected to traffic offences. In addition, young age (24-29years), new vehicles (0-5years), single and private workers, higher education levels (degree and above), experienced drivers, Buses and private cars also showed higher connection with number of traffic offences and crash involvements. More stringent effort and proper interventions should be done towards these groups and the most common traffic