Decision Trees as a Tool for Real-Time Travel Time Estimation on Highways

Abstract

This paper presents a time travel estimation model based on a decision tree. Input parameter for travel time prediction is occupancy of detectors. The proposed model was tested on the most widely used arterial in Prague and also in the Czech Republic. This road section has many unmeasured inputs and outputs and with regards to only two detectors within a section it is difficult to estimate the travel time. A temporary installation of ALPR system is used for training the decision tree model which consequently provides reliable travel time estimation.