Road Safety Policy Formulation towards Road Traffic Accidents Risk Mitigation the Case of Zambia

Abstract

A study was conducted to determine the relationship between traffic laws enforcement as dependent variable and independent variables; latent and active failures such as over speeding, aggressive driving, poor road conditions, failure to put on seat belts, vehicle failures, distractive driving and insufficient safety campaign. In this case multiple linear regression model deployed with the sample size of 400. The results show that independent variables significantly correlate with the dependent variable. For instance, road conditions has a positive coefficient (b=0.121, P<0.05) implying that weak traffic law enforcement increases when road conditions worsens, proposing the need to upgrade the road infrastructure to improve on road users adherence to traffic laws consequently, safety. The implications of the predictive model suggest that safety culture improvement requires integration of safety in school curricular to create fertile grounds to traffic law enforcers in Zambia. The association between lack of safety campaign and weak traffic laws enforcement gives attention that the law enforcers must develop a deliberate safety education to the public so as to improve on traffic laws enforcement in Zambia. Additionally, the number of vehicles keeps on increasing prompting the use of latest technology to improve on monitoring and controlling of safety standards unlike highly dependence on traffic officers. Installation of safety monitoring system would great improve on enforcement of traffic laws. The multiple linear regression model proposes measures to address road traffic accidents in this study. The study argues for that mitigating road traffic accidents covers addressing latent and active failures. For instance, improve the status of the road infrastructure plays a key law in improving in enforcement of traffic laws. For safety or traffic laws to be in the minds of the public safety campaign must be conducted regularly.