Traffic Data Analysis and Forecasting

Traffic data analysis plays a central role in understanding the dynamics of vehicular movement and identifying patterns that offer profound perspectives for transportation planning, analysis and predict traffic data at different time intervals. Traffic data analysis faces many problems and challenges, including large-scale datasets, detecting outliers, and accurately predicting and forecasting traffic patterns. This paper provides an exhaustive overview on Traffic data analysis by making use various methodologies like Exploratory Data Analysis (EDA), Time-Series Analysis and Deep Learning techniques like Long-Short Term Memory (LSTM).