Abstract
Road congestion influences the quality of lifestyle for urban areas including Kuala Lumpur, the capital city of Malaysia. It is predicted that the demand for mobility in the city will be increased tremendously in the next ten years. Consequently, this problem has contributed to air pollution caused by carbon dioxide emissions. One of the solutions suggested by the expertise is road pricing via a direct charge to drivers who use the road during peak hours. In this regard, this research aims to develop a computer simulation based on a system dynamic approach for mitigating congestion and carbon dioxide emission via a road pricing strategy. Firstly, the identified variables were correlated to understand the behavior of the system. Subsequently, the correlated variables were embedded in the stock-flow diagram based on the system dynamics approach to investigate how a variable affects another variable. Then, the developed model was simulated for evaluating the impact of road pricing strategy in reducing congestion and carbon dioxide emission. As a result, the emission of carbon dioxide can be reduced to 6 percent in six days if road pricing is implemented. From the managerial perspective, this research helps highway stakeholders in Malaysia towards making a better decision in enforcing road pricing strategy in the fast-moving city for a better lifestyle and environment.
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