Bus running times are a key element of time reliability for bus operators and passengers. Hence, their evaluation is crucial in order to build reliable schedules for transit operations. This study analyses three alternative offline methods for estimating bus running times using automatic vehicle location (AVL) data: the average method, the percentile method and an adjusted Kalman filter method, which is amended in order to be implemented for offline use. Experiments are conducted using ∼92,000 real‐world archived AVL records, which are provided by an Italian bus operator. The results can be used to revise scheduled running times along a specific route by these methods.
Evaluating alternative methods to estimate bus running times by archived automatic vehicle location data
IET Intelligent Transport Systems ; 13 , 3 ; 523-530
2019-03-01
8 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
adjusted Kalman filter method , bus running times , Kalman filters , passengers , road safety , scheduling , archived automatic vehicle location data , percentile method , bus operators , average method , AVL data , Italian bus operator , scheduled running times , road vehicles , public transport , offline methods , time reliability
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