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handle: 2108/194562
Abstract Bus travel time analysis is essential for transit operation planning. Then, this topic obtained large attention in transport engineering literature and several methods have been proposed for investigating its variability. Nowadays, the availability of large data quantities through automated monitoring allows more in-depth this phenomenon to be pointed out with new experimental evidence. The paper presents the results of some analyses carried out using automatic vehicle location (AVL) data of bus lines and automated vehicle counter (AVC) data on some corridors in the urban area of Rome where the bus services are mixed with other traffic and travel times are subject to high degrees of variability. The results show the effect of temporal dimension and similarity between travel time and traffic temporal patterns, and could open the road for the improvement of the short-term forecasting methods, too.
traffic data processing, travel time analyse, 380, Transportation, Settore ICAR/05 - TRASPORTI, automated traffic data, time serie, bus travel time, travel speed analysi, automated traffic data; bus travel time; time series; traffic data processing; travel speed analysis; travel time analyses; Transportation
traffic data processing, travel time analyse, 380, Transportation, Settore ICAR/05 - TRASPORTI, automated traffic data, time serie, bus travel time, travel speed analysi, automated traffic data; bus travel time; time series; traffic data processing; travel speed analysis; travel time analyses; Transportation
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 34 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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