Abstract
Barcelona has recently started a new strategy to control and understand Last Mile Delivery, AreaDUM. The strategy is to provide freight delivery vehicle drivers with a mobile app that has to be used every time their vehicle is parked in one of the designated AreaDUM surface parking spaces in the streets of the city. This provides a significant amount of data about the activity of the freight delivery vehicles, their patterns, the occupancy of the spaces, etc.
In this paper, we provide a preliminary set of analytics preceded by the procedures employed for the cleansing of the dataset. During the analysis we show that some data blur the results and using a simple strategy to detect when a vehicle parks repeatedly in close-by parking slots, we are able to obtain different, yet more reliable results. In our paper, we show that this behavior is common among users with \(80\%\) prevalence. We conclude that we need to analyse and understand the user behaviors further with the purpose of providing predictive algorithms to find parking lots and smart routing algorithms to minimize traffic.
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Notes
- 1.
The authors want to thank B:SM and, in particular the Innovation team, leaded by Carlos Morillo and Oscar Puigdollers for their support in this paper.
- 2.
A medoid is a representative object of a dataset or a cluster with a data set whose average dissimilarity to all the objects in the cluster is minimal.
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Kolbay, B., Mrazovic, P., Larriba-Pey, J.L. (2018). Analyzing Last Mile Delivery Operations in Barcelona’s Urban Freight Transport Network. In: Longo, A., et al. Cloud Infrastructures, Services, and IoT Systems for Smart Cities. IISSC CN4IoT 2017 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 189. Springer, Cham. https://doi.org/10.1007/978-3-319-67636-4_2
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DOI: https://doi.org/10.1007/978-3-319-67636-4_2
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