This document provides a comprehensive literature review and analysis of various traffic prediction techniques. It begins with an abstract that outlines the need for accurate traffic forecasting to address issues caused by increased road traffic. The document then reviews several existing traffic prediction methods and technologies, including fuzzy logic-based systems, intelligent traffic signal controllers, dynamic traffic information systems, and frameworks that utilize IoT, cloud computing, and machine learning. It identifies gaps in current literature, such as a lack of sensor data and advanced application frameworks for prediction. Finally, the document presents several comparison tables analyzing traffic prediction techniques based on the datasets, parameters, merits and demerits of each approach. The overall purpose is to conduct a systematic analysis of past work and identify future research