CRAWDAD ufrj/london-trajectories

Citation Author(s):
Leonardo Solé
Rodrigues
Matteo
Sammarco
Marcin
Detyniecki
Miguel Elias M.
Campista
Submitted by:
CRAWDAD Team
Last updated:
Tue, 08/03/2021 - 08:00
DOI:
10.15783/ejej-de94
Data Format:
License:
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Abstract 

600 sets of routes from different origin/destination pairs from London

This dataset contains 600 sets of routes from different origin/destination pairs. Each route has information about trip duration, route length, traffic, criminality, accidents, nature and tourist attractions nearby. The routes were calculated by HERE Maps, along with duration estimates, criminality and accidents were acquired from the UK Government open data website, and nature and tourist attractions were downloaded from OpenStreetMap.

This dataset was used to research alternative route classification methods, that evaluates different metrics besides the usual time and length parameters, like criminality, accidents, nature and attractions.

institution :

ufrj

version :

2021-03-22

external url :

https://github.com/leosole/LondonTrajectories

Traceset

trajectoriesgps

  • files: LondonTrajectoriesDataset.zip
  • description: 600 route sets of different origin/destination pairs from London.
  • tech description: This dataset contains 600 route sets of different origin/destination pairs from London, each with information about trip duration, route length, traffic, criminality, accidents, nature and tourist attractions nearby.
  • collection method: The traces a GPS routes calculated by the HERE Maps API. These routes were provided with length and duration already. We estimated a visible area taking into account the route segments and a margin of 100 m for the left and right side for some of the features calculations. The nature feature was calculated intersecting the natural area polygons given by OpenStreetMap and the visible area. The attractions feature was calculated as the number of tourist attractions given by OpenStreetMap inside the route's visible area. The criminality was calculated as the sum of the severity of the crimes, provided by the UK police crime dataset, found inside the visible area. The severity of the crimes were weighted by the UK Office for National Statistics Crime Severity Score. The normalization of the features was done relatively to the maximum feature variation found in each route set (routes with the same origin and destination). The accidents feature was calculated as the sum of accidents severity and accidents casualties that happened in the route. The accidents data was provided by the UK Government Open Data Website. The traffic feature was calculated as the ratio between the no-traffic route duration and the route duration considering traffic. Both values are given by the HERE Maps API.
  • incorrectly_meas_data: There is no incorrectly measured data.
  • methodology limitations: The routes origins and destinations were randomized within the city of London, the data does not represent the city as a whole.
  • missing data: There is no missing data.
  • sanitization: The data didn't require any sanitization.
  • dataname: trajectoriesgps
  • version: 2021-03-22
  • date/time of measurement start: 2020-12-01
  • date/time of measurement end: 2020-12-15

trajectoriesgps Traces

    • LondonTrajectoriesDataset.zip: undefined
  • last modified: 2021-08-03
  • dataname: LondonTrajectoriesDataset.zip
  • url: /download/ufrj/london-trajectories/2021-03-22/london-traceset/LondonTrajectoriesDataset.zip
Instructions: 

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About CRAWDAD: the Community Resource for Archiving Wireless Data At Dartmouth is a data resource for the research community interested in wireless networks and mobile computing. 

CRAWDAD was founded at Dartmouth College in 2004, led by Tristan Henderson, David Kotz, and Chris McDonald. CRAWDAD datasets are hosted by IEEE DataPort as of November 2022. 

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Citation:

Leonardo Solé Rodrigues, Matteo Sammarco, Marcin Detyniecki, Miguel Elias M. Campista, CRAWDAD dataset ufrj/london-trajectories (v. 2021-03-22), https://doi.org/10.15783/ejej-de94 , Mar 2021.

 

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These datasets are part of Community Resource for Archiving Wireless Data (CRAWDAD). CRAWDAD began in 2004 at Dartmouth College as a place to share wireless network data with the research community. Its purpose was to enable access to data from real networks and real mobile users at a time when collecting such data was challenging and expensive. The archive has continued to grow since its inception, and starting in summer 2022 is being housed on IEEE DataPort.

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