Replication package for the paper: Vehicular crowd-sensing with high-mileage vehicles: investigating spatio-temporal coverage dynamics in historical cities with complex urban road networks
Creators: name: Starace, Luigi Libero Lucio
name: Rocco di Torrepadula, Franca
name: Di Martino, Sergio
name: Mazzocca, Nicola
Publisher: name: Zenodo
Year: 2022

description: This package includes supplementary materials and a KNIME workflow to replicate our case study investigating the road-network coverage achievable by different-sized fleets of taxis in the cities of Porto (PT) and Rome (IT). As follows, we give detailed instructions to reproduce our results. Download and install the KNIME Analytics Platform (version 4.3). Download and install <strong>KNOT</strong>: <strong>KN</strong>ime m<strong>O</strong>bility <strong>T</strong>oolkit, the custom KNIME extension we deleveloped (version 1.0.1). To enable visualization of the results on an interactive map, download and install the third-party KNIME Spatial Processing Nodes extension; Download the provided KNIME workflow<strong> </strong>files (<strong>rome-coverage-experiment.knwf</strong> and <strong>porto-coverage-experiment.knwf</strong>), and import them into your KNIME instance. If you want to re-execute the provided workflow from scratch, follow these additional steps: Download the provided data (<strong>porto-taxi-trajectories-dataset.csv</strong> and <strong>porto.osm</strong> files for the Porto experiments, <strong>taxi_febryary.txt</strong> and <strong>rome.osm</strong> for the Rome experiments); Note that the the trajectory dataset is downloaded from https://archive.ics.uci.edu/ml/datasets/Taxi+Service+Trajectory+-+Prediction+Challenge,+ECML+PKDD+2015, which is based on the work Moreira-Matias, L., Gama, J., Ferreira, M., Mendes-Moreira, J., Damas, L., ”Predicting Taxi–Passenger Demand Using Streaming Data”. In: IEEE Transactions on Intelligent Transportation Systems, vol.14, no.3, pp.1393-1402, September (2013).<br> <br> The Rome trajectory dataset has been downloaded from https://crawdad.org/roma/taxi/20140717/ The map-matching procedure requires an OSRM instance capable of serving routing requests over the city of Porto. For your convenience, we prepared a virtual machine image with OSRM installed and configured (<strong>OSRM-Porto-Ubuntu-20.04LTS.ova</strong>).You can run this virtual machine with VirtualBox and login with the credentials Username: User; Password: user. After login, it is possible to start the OSRM instance by opening a terminal and running the following command: <pre><code class="language-bash">osrm-routed --max-matching-size 3000 OSRM-data/porto/porto.osrm</code></pre> Take note of the local IP address of the virtual machine (you may use the ifconfig command to get it). To run the Rome experiments, it is necessary to add the Rome road network (which can be downloaded from geofabrik) to the OSRM instance. For more detail, refer to the official OSRM docs. Make sure that the CSV Reader node is configured so that it reads the <strong>porto-taxi-trajectories-dataset.csv </strong>for the Porto experiments (resp. <strong>taxi_february.txt</strong> file for the Rome experiments)<strong> </strong>file you downloaded. Similarly, configure the Map Matcher node so that it reads the <strong>porto.osm </strong>(resp. <strong>rome.osm</strong>) file for you downloaded, and so that the IP address of the OSRM instance is correct. Run the KNIME workflows.