Publication | Closed Access
Predicting Bus Arrival Time on the Basis of Global Positioning System Data
113
Citations
9
References
2007
Year
Transport Network AnalysisEngineeringPositioning SystemTransportation Systems ModelingLocalizationIntelligent Traffic ManagementData ScienceTraffic PredictionBus Arrival TimeTrain Timetable OptimizationSystems EngineeringTransportation Systems AnalysisTransportation EngineeringPublic TransportationTransportation ModelingPredictive AnalyticsComputer EngineeringNew SystemForecastingTransportation System ManagementBus Arrival TimesRoute PlanningLocation InformationLocation ManagementTransportation Systems
Accurate real‑time bus arrival predictions are essential for operations and passenger information, yet existing methods often fall short of satisfactory performance. This study introduces a system for predicting expected bus arrival times at individual stops along a route. The system fuses real‑time GPS locations with segment‑level average speeds, historical travel data, and traffic variations, uses GIS map‑matching to project positions onto the network, and is implemented as a finite state machine evaluated on a real bus route. Evaluation shows the system achieves satisfactory arrival‑time accuracy and perfect travel‑direction prediction.
The ability to obtain accurate predictions of bus arrival time on a real-time basis is a vital element to both bus operations control and passenger information systems. Several studies had been devoted to this arrival time prediction problem; however, few resulted in completely satisfactory algorithms. This paper presents a new system that can be used to predict the expected bus arrival times at individual bus stops along a service route. The proposed prediction algorithm combines real-time location data from Global Positioning System receivers with average travel speeds of individual route segments, taking into account historical travel speed as well as temporal and spatial variations of traffic conditions. A geographic information system–based map-matching algorithm is used to project each received location onto the underlying transit network. The system is implemented as a finite state machine to ensure its regularity, stability, and robustness under a wide range of operating conditions. A case study on a real bus route is conducted to evaluate the performance of the proposed system in terms of prediction accuracy. The results indicate that the proposed system is capable of achieving satisfactory accuracy in predicting bus arrival times and perfect performance in predicting travel direction.
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