Rolling Horizon Predictions of Bus Trajectories

• Bus travel times are subject to inherent and recurrent uncertainties. A real-time prediction scheme regarding how the transit system evolves will potentially facilitate more adaptive operations as well as more adaptive passengers’ decisions. This scheme should be tractable, sufficiently fast and reliable to be used in real time applications. For this purpose, a heuristic hybrid scheme for departure time estimation is proposed in this study. The prediction generated by the proposed hybrid scheme consists of three travel time components: schedule, instantaneous and historical data sources. Genetic algorithm is applied in order to specify the contribution of each data source component to the prediction scheme. The proposed scheme was applied for a trunk bus line in Stockholm, Sweden. In addition, the currently deployed scheme was replicated in order to compare the performance of both schemes. The results suggest that the proposed scheme reduces the overall mean absolute error by almost 20%. Moreover the proposed scheme provides better predictions except for very long term predictions where both schemes yield the same performance. 

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Samhällsbyggnadsteknik -- Transportteknik och logistik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Civil Engineering -- Transport Systems and Logistics (hsv//eng)

Nyckelord

Bus departure time

Optimization

Prediction

Travel time and Genetic algorithm

Publikations- och innehållstyp

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