Global Journal of Computer Science and Technology, D: Neural & Artificial Intelligence, Volume 23 Issue 2

[6]. Similarly, vehicle detection and surveillancefunctions are always subject to constantly being improved inorder to increase vehicle detection and monitoring, observing traveling direction, counting their speed, and categorizing vehicles [6]. There is no doubt that vehicle identification and monitoring are vital components of both successful traffic management and ITMS. Similarly more effective traffic management may be achieved if future traffic volume estimates can be made through predictions. It performs a vitalservice for traffic management. Because the traffic density prediction methods depend on several factors, such as current and historic traffic measurements [6]. Accurate calculations are always important for accurate predictions. Therefore, theoverall success predictions depend on the precise and efficient operation of the utilized medium to monitor traffic behavior. The remainder of this paper is organized as follows. In section II, the research problem is discussed under the contextof Sri Lanka. In section III, background and earlier studies carried out on real-time traffic monitoring and forecasting arepresented, evaluating the research gaps. Moreover, part A and B of section III provide an extensive evaluation of each trafficmonitoring and forecasting method, including tables that compare the performances of each technology. Section IV expresses the methodology, whereas section V includes the results and validation. Section VI summarizes all the facts asa conclusion and introduces future work. II. R esearch P roblem D efinition in the C ontext of S ri lanka Traffic congestion is one of the major issues in Sri Lanka. Initially, this problem was found only in the urban areas, including Colombo, but now with the increasing number of vehicles being added to the road day by day, the problem is further enhanced in other suburban areas as well [7], becoming traffic congestion is a prominent issue. Excessive fuel consumption due to prolonged travel time results in economic loss and frequent acceleration and breakage, leading to frequent repairs and replacements, which create a significant loss to the national economy [8]. The costof traffic congestion in Sri Lanka's Western Province exceedsRs. 20,000 million per year, which is approximately 2% of regional GDP [9]. Total greenhouse gas (GHG) and CO2 emissions in the Sri Lankan transport sector are accounted for 25% of GHG and 47% of CO2 which indicates that traffic congestion has a substantial environmental impact in Sri Lanka when compared to global averages [10]. Nowadays Sri Lankan government is grappling with a large fiscal deficit, with the depreciation of the Sri Lankan rupee against major currencies and high debt. Traffic congestion is also a factor affecting a country's economy. Andespecially in a country like Sri Lanka, which is suffering fromfuel and energy crises along with recent economic losses, this traffic congestion problem now has become an issue that canno longer be overlooked. Several remedial strategies have been taken by the government to avoid rising traffic jams and to prevent it being worsening the congestion level. Short-term strategies such as adding new transport infrastructures: new roads, and expressways, and improving existing infrastructure capacitiesto be compatible with increasing road and transport capacity have been taken. Similarly, as with other possible alternativeactions, the number of lane miles has been expanded, and alternate routes have been created to increase capacity and enhance the efficiency of existing infrastructure [4]. Long- term strategies such as introducing new vehicle ownership and public transport strategies and policies to be compatible with existing road and transport capacity have been taken to overcome this issue [9]. But the existing traffic congestion proves that those actions are insufficient to create an effectiveimpact on traffic management. Figure 1: Traffic Behaviour of Countries Such as Australlia,Russia and European Countries © 2023 Global Journals Global Journal of Computer Science and Technology Volume XXIII Issue II Version I 38 ( ) Year 2023 D Traffic Flow Forecast based on Vehicle Count