Curiel, RP;
Ramirez, HG;
Bishop, SR;
(2018)
A novel rare event approach to measure the randomness and concentration of road accidents.
PLoS ONE
, 13
(8)
10.1371/journal.pone.0201890.
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Abstract
BACKGROUND: Road accidents are one of the main causes of death around the world and yet, from a timespace perspective, they are a rare event. To help us prevent accidents, a metric to determine the level of concentration of road accidents in a city could aid us to determine whether most of the accidents are constrained in a small number of places (hence, the environment plays a leading role) or whether accidents are dispersed over a city as a whole (hence, the driver has the biggest influence). METHODS: Here, we apply a new metric, the Rare Event Concentration Coefficient (RECC), to measure the concentration of road accidents based on a mixture model applied to the counts of road accidents over a discretised space. A test application of a tessellation of the space and mixture model is shown using two types of road accident data: an urban environment recorded in London between 2005 and 2014 and a motorway environment recorded in Mexico between 2015 and 2016. FINDINGS: In terms of their concentration, about 5% of the road junctions are the site of 50% of the accidents while around 80% of the road junctions expect close to zero accidents. Accidents which occur in regions with a high accident rate can be considered to have a strong component related to the environment and therefore changes, such as a road intervention or a change in the speed limit, might be introduced and their impact measured by changes to the RECC metric. This new procedure helps us identify regions with a high accident rate and determine whether the observed number of road accidents at a road junction has decreased over time and hence track structural changes in the road accident settings.
| Type: | Article |
|---|---|
| Title: | A novel rare event approach to measure the randomness and concentration of road accidents |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1371/journal.pone.0201890 |
| Publisher version: | http://dx.doi.org/10.1371/journal.pone.0201890 |
| Language: | English |
| Additional information: | © 2018 Prieto Curiel et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
| Keywords: | Science & Technology, Multidisciplinary Sciences, Science & Technology - Other Topics, COMPUTER-ASSISTED ANALYSIS, TRAFFIC ACCIDENTS, ALGORITHMS, LOCATIONS, MIXTURES, WEALTH, MODEL, LAW |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Mathematics UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Centre for Advanced Spatial Analysis |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10056709 |
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