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Exploiting GPS Data in Public Transport Journey Planners

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Experimental Algorithms (SEA 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8504))

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Abstract

Current journey planners for public transport are mostly based on timetabling, i.e., they hinge on the assumption that all transit vehicles run on schedule. Unfortunately, this might not always be realistic, as unpredictable delays may occur quite often in practice. In this case, it seems quite natural to ask whether the availability of real-time updates on the geo-location of transit vehicles may help improving the quality of the solutions offered by routing algorithms. To address this question, we consider the public transport network of the metropolitan area of Rome, where delays are not rare events, and report the results of our experiments with two journey planners that are widely used for this city: one based on timetabling information only (Google Transit) and one which makes explicit use of GPS data on the geo-location of transit vehicles (Muovi Roma).

Work partially supported by the Italian Ministry of Education, University and Research, under Project AMANDA (Algorithmics for MAssive and Networked DAta).

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Allulli, L., Italiano, G.F., Santaroni, F. (2014). Exploiting GPS Data in Public Transport Journey Planners. In: Gudmundsson, J., Katajainen, J. (eds) Experimental Algorithms. SEA 2014. Lecture Notes in Computer Science, vol 8504. Springer, Cham. https://doi.org/10.1007/978-3-319-07959-2_25

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  • DOI: https://doi.org/10.1007/978-3-319-07959-2_25

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07958-5

  • Online ISBN: 978-3-319-07959-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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