Bus travel time analysis plays a key role in transit operation planning, and methods are needed for investigating its variability and for forecasting need. Nowadays, telematics is opening up new opportunities, given that large datasets can be gathered through automated monitoring, and this topic can be studied in more depth with new experimental evidence. The paper proposes a time-series-based approach for travel time forecasting, and data from automated vehicle monitoring (AVM) of bus lines sharing the road lanes with other traffic in Rome (Italy) and Lviv (Ukraine) are used. The results show the goodness of such an approach for the analysis and reliable forecasts of bus travel times. The similarities and dissimilarities in terms of travel time patterns and city structure were also pointed out, showing the need to take them into account when developing forecasting methods.

Comi, A., Polimeni, A. (2020). Bus travel time: experimental evidence and forecasting. FORECASTING, 2(3), 309-322 [10.3390/forecast2030017].

Bus travel time: experimental evidence and forecasting

Comi, Antonio
;
Polimeni, Antonio
2020-08-01

Abstract

Bus travel time analysis plays a key role in transit operation planning, and methods are needed for investigating its variability and for forecasting need. Nowadays, telematics is opening up new opportunities, given that large datasets can be gathered through automated monitoring, and this topic can be studied in more depth with new experimental evidence. The paper proposes a time-series-based approach for travel time forecasting, and data from automated vehicle monitoring (AVM) of bus lines sharing the road lanes with other traffic in Rome (Italy) and Lviv (Ukraine) are used. The results show the goodness of such an approach for the analysis and reliable forecasts of bus travel times. The similarities and dissimilarities in terms of travel time patterns and city structure were also pointed out, showing the need to take them into account when developing forecasting methods.
ago-2020
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore ICAR/05 - TRASPORTI
English
travel time forecasting; time series; bus service; transit systems; sustainable urban mobility plan; bus travel time
https://www.mdpi.com/2571-9394/2/3/17
Comi, A., Polimeni, A. (2020). Bus travel time: experimental evidence and forecasting. FORECASTING, 2(3), 309-322 [10.3390/forecast2030017].
Comi, A; Polimeni, A
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/253327
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