GPS Data Based Speed Pattern Estimation and Route Guidance in City Road Networks
Date Issued
2010
Date
2010
Author(s)
Wen, Tsun-Jui
Abstract
Traffic congestion is an important problem in city. It could lead a significant waste of money and time. In recent years, cars equipped with GPS devices become widespread and the location information of those cars could be very useful to estimate traffic condition in the complex city road network. According to the accurate traffic condition estimation, we can provide appropriate route guidance to road drivers and they can avoid the congestion.
In this thesis, we use the GPS coordinates of cars driving on the city road network to estimate the traffic condition of road segments. We propose a speed pattern model to describe traffic condition as the travel speed pattern. And we propose a classification-based route guidance model by learning the historic traffic data using machine learning technique. The route guidance model could provide route guidance to drivers according to current traffic condition and how traffic condition would change by the experience learned from historic traffic data.
Subjects
speed pattern estimation
route guidance
machine learning
Type
thesis
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