Prediction of bus travel time is a crucial tool for passengers. We present methods to predict bus travel time over intervals between pairs of adjacent bus stops using city bus probe data. We apply Gradient Boosting Decision Trees to several kinds of features extracted from the probe data. Experimental results illustrate that adding a combination of features improves the accuracy of travel time prediction over the target interval. In particular, the method using a combination of the travel time over the interval previous to the target one and the number of stops the bus makes before reaching the target interval has better performance than the other methods which use all the other combinations of four features used in this study.
Prediction of Bus Travel Time over Intervals between Pairs of Adjacent Bus Stops Using City Bus Probe Data
Int. J. ITS Res.
International Journal of Intelligent Transportation Systems Research ; 19 , 2 ; 456-467
2021-06-01
12 pages
Article (Journal)
Electronic Resource
English
Prediction of Bus Travel Time Over Unstable Intervals between Two Adjacent Bus Stops
Springer Verlag | 2020
|DISTRIBUTION OF DISTANCES BETWEEN ADJACENT CITY TRANSPORT STOPS AS COMPONENTS OF PASSENGER ROUTE
DOAJ | 2013
|Evaluation of Travel Time at Conventional Bus Stops
ASCE | 2014
|Confidence Intervals for Real Time Freeway Travel Time Prediction
British Library Conference Proceedings | 2003
|Prediction Intervals to Account for Uncertainties in Travel Time Prediction
Online Contents | 2011
|