Forecasting Future Traffic Trend by Short-Term Continuous Observation

Abstract

Annual Average Daily Traffic (AADT) is a key parameter to understand the traffic flow rates, traffic density and to design any highway. Generally, short period observed traffic data mainly depends on that season in which the traffic surveys were conducted, which may be high or low compared to the other seasons. So, the behavior of seasonal variation of traffic must be considered for the AADT analysis. These seasonal variations can be found out using the past recorded data of that selected location. But in the case of a location where the past annual traffic data is not available, an alternative method is required to calculate the seasonal variation of the traffic data. The present study deals with the analysis of seasonal variation factors to estimate the AADT from the fuel sale data collected from the nearby petrol stations at the traffic survey point. This work explains how Annual Average Daily Traffic (AADT) can be estimated from a week’s limited traffic data when there is a scarcity of automatic traffic data collecting systems.