hour of prediction.Moreover, we are interested in not only predicting incidents' impact but informing the drivers about the current and future traffic state is also our area of concern. Currently, in order to inform or alert the commuters about the traffic situation during the road incidents, several LED displays, better known as variable message signs or VMS messages, have been installed by the LTA on the expressways of Singapore. Therefore, apart from building the predicting models, this thesis also aims to evaluate the impact of VMS displays on the overall traffic distribution of Singapore whether these displays are really helpful to the drivers or not. To this end, the incidents data and their corresponding VMS messages are collected from the two busiest expressways of Singapore, namely Pan Island Expressway (PIE) and Central Expressway (CTE). The analysis shows that approximately 14% of the vehicles change their direction after the VMS messages have been activated.Lastly, since Singapore is a tropical country having a significant amount of rainfall throughout the entire year, the weather condition has a noticeable impact on the traffic of Singapore. Therefore, we also aim to analyze the influence of rainfall on traffic incidents if the frequency of these incidents, especially accidents, increases after rainfall or not. Therefore, the rainfall data acquired from the National Environmental Agency (NEA) of Singapore is analyzed to investigate the correlation between the occurrence of traffic incidents and rainfall. Overall, the obtained results support the hypothesis that the frequency of traffic incidents is higher during rainfall as compared to dry periods. Moreover, the frequency is the highest after rainfall. Besides, it is observed that traffic speed and flow decrease by 10.14% and 3.88% respectively during rainy weather.Overall, this thesis aims to help avoid incident-induced traffic jams by designing the urban traffic prediction models. Thus, the cost of time and fuel can be saved, which will benefit the national economy as a whole.