Travel Time Prediction on the Network Using Time Series (Case study: zone 1 in Mashhad)

In urban service systems, the lack of travel time between two different destinations could be felt. The main factor in many systems, which are based on routing vehicles, is travel time estimation. If a driver had travel time information before the trip was set about, he could make a good decision about his alternative routes. So, it needs to estimate travel times for routes, before routes traversed. According to traffic conditions at intersections and routes of the urban center, several methods are employed to obtain travel time. But among them, the role of spatial data to define the travel time has better performance compared to other ones. This paper intends to predict future traffic volume by using traffic volume pattern which obtained in the past and then, estimate travel time in the arc and delay in intersection with travel time-volume and Webster functions. This report is done for streets of zone 1 Mashhad including three types of retractable and arterial Grade 1 and 2. The results of the paired T-Test, by using the mentioned method, show that travel time estimation is acceptable.