A novel rare event approach to measure the randomness and concentration of road accidents
Road accidents are one of the main causes of death around the world and yet, from a time-space 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 co...
| 主要な著者: | , , |
|---|---|
| フォーマット: | Journal article |
| 言語: | English |
| 出版事項: |
Public Library of Science
2018
|
| _version_ | 1826296313016221696 |
|---|---|
| author | Curiel, R Ramírez, H Bishop, SR |
| author_facet | Curiel, R Ramírez, H Bishop, SR |
| author_sort | Curiel, R |
| collection | OXFORD |
| description | Road accidents are one of the main causes of death around the world and yet, from a time-space 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).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.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. |
| first_indexed | 2024-03-07T04:14:25Z |
| format | Journal article |
| id | oxford-uuid:c8ee405d-be78-4ae3-a6fb-cc39d8d9484b |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T04:14:25Z |
| publishDate | 2018 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | oxford-uuid:c8ee405d-be78-4ae3-a6fb-cc39d8d9484b2022-03-27T06:55:29ZA novel rare event approach to measure the randomness and concentration of road accidentsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:c8ee405d-be78-4ae3-a6fb-cc39d8d9484bEnglishSymplectic Elements at OxfordPublic Library of Science2018Curiel, RRamírez, HBishop, SRRoad accidents are one of the main causes of death around the world and yet, from a time-space 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).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.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. |
| spellingShingle | Curiel, R Ramírez, H Bishop, SR A novel rare event approach to measure the randomness and concentration of road accidents |
| title | A novel rare event approach to measure the randomness and concentration of road accidents |
| title_full | A novel rare event approach to measure the randomness and concentration of road accidents |
| title_fullStr | A novel rare event approach to measure the randomness and concentration of road accidents |
| title_full_unstemmed | A novel rare event approach to measure the randomness and concentration of road accidents |
| title_short | A novel rare event approach to measure the randomness and concentration of road accidents |
| title_sort | novel rare event approach to measure the randomness and concentration of road accidents |
| work_keys_str_mv | AT curielr anovelrareeventapproachtomeasuretherandomnessandconcentrationofroadaccidents AT ramirezh anovelrareeventapproachtomeasuretherandomnessandconcentrationofroadaccidents AT bishopsr anovelrareeventapproachtomeasuretherandomnessandconcentrationofroadaccidents AT curielr novelrareeventapproachtomeasuretherandomnessandconcentrationofroadaccidents AT ramirezh novelrareeventapproachtomeasuretherandomnessandconcentrationofroadaccidents AT bishopsr novelrareeventapproachtomeasuretherandomnessandconcentrationofroadaccidents |