Investigating effect of holidays on daily traffic counts - Time series approach

Abstract

Different modeling philosophies are explored to explain and to forecast daily traffic counts. The main objectives of this study are the analysis of the impact of holidays on daily traffic and the forecasting of future traffic counts. Data from single inductive-loop detectors, collected in 2003, 2004, and 2005, were used for the analysis. The different models investigated showed that the variation in daily traffic counts could be explained by weekly cycles. The Box-Tiao modeling approach was applied to quantify the effect of holidays on daily traffic. The results showed that traffic counts were significantly lower for holiday periods. When the different modeling techniques were compared with a large forecast horizon, Box-Tiao modeling clearly outperformed the other modeling strategies. Simultaneous modeling of both the underlying reasons of travel and the revealed traffic patterns certainly is a challenge for further research.