Application of naïve Bayesian approach in detecting reproducible fatal collision locations on freeway.

Detecting high-collision-concentration locations based solely on collision frequency may produce different results compared to those considering the severities of the collisions. In particular, it can lead government agencies focusing sites with a high collision frequency while neglecting those with...

Full description

Bibliographic Details
Main Authors: Eui-Jin Kim, Oh Hoon Kwon, Shin Hyoung Park, Dong-Kyu Kim, Koohong Chung
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2021-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0251866
_version_ 1818434980812947456
author Eui-Jin Kim
Oh Hoon Kwon
Shin Hyoung Park
Dong-Kyu Kim
Koohong Chung
author_facet Eui-Jin Kim
Oh Hoon Kwon
Shin Hyoung Park
Dong-Kyu Kim
Koohong Chung
author_sort Eui-Jin Kim
collection DOAJ
description Detecting high-collision-concentration locations based solely on collision frequency may produce different results compared to those considering the severities of the collisions. In particular, it can lead government agencies focusing sites with a high collision frequency while neglecting those with a lower collision frequency but a higher percentage of injury and fatal collisions. This study developed systematic ways of detecting reproducible fatal collision locations (R) using the naïve Bayes approach and a continuous risk profile (CRP) that estimates the true collision risk by filtering out random noise in the data. The posterior probability of fatal collisions being reproducible at a location is estimated by the relationship between the spatial distribution of fatal-collision locations (i.e., likelihood) and the CRP (i.e., prior probability). The proposed method can be used to detect sites with the highest proxy measure of the posterior probability (PMP) of observing R. An empirical evaluation using 5-year traffic collision data from six routes in California shows that detecting R based on the PMP outperform those based on the SPF-based approaches or random selection, regardless of various conditions and parameters of the proposed method. This method only requires traffic collision and annual traffic volume data to estimate PMP that prioritize sites being R and the PMPs can be compared across multiple routes. Therefore, it helps government agencies prioritizing sites of multiple routes where the number of fatal collisions can be reduced, thus help them to save lives with limited resources of data collection.
first_indexed 2024-12-14T16:45:37Z
format Article
id doaj.art-393b24a9822f4beda808bf9441c78dd1
institution Directory Open Access Journal
issn 1932-6203
language English
last_indexed 2024-12-14T16:45:37Z
publishDate 2021-01-01
publisher Public Library of Science (PLoS)
record_format Article
series PLoS ONE
spelling doaj.art-393b24a9822f4beda808bf9441c78dd12022-12-21T22:54:11ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-01165e025186610.1371/journal.pone.0251866Application of naïve Bayesian approach in detecting reproducible fatal collision locations on freeway.Eui-Jin KimOh Hoon KwonShin Hyoung ParkDong-Kyu KimKoohong ChungDetecting high-collision-concentration locations based solely on collision frequency may produce different results compared to those considering the severities of the collisions. In particular, it can lead government agencies focusing sites with a high collision frequency while neglecting those with a lower collision frequency but a higher percentage of injury and fatal collisions. This study developed systematic ways of detecting reproducible fatal collision locations (R) using the naïve Bayes approach and a continuous risk profile (CRP) that estimates the true collision risk by filtering out random noise in the data. The posterior probability of fatal collisions being reproducible at a location is estimated by the relationship between the spatial distribution of fatal-collision locations (i.e., likelihood) and the CRP (i.e., prior probability). The proposed method can be used to detect sites with the highest proxy measure of the posterior probability (PMP) of observing R. An empirical evaluation using 5-year traffic collision data from six routes in California shows that detecting R based on the PMP outperform those based on the SPF-based approaches or random selection, regardless of various conditions and parameters of the proposed method. This method only requires traffic collision and annual traffic volume data to estimate PMP that prioritize sites being R and the PMPs can be compared across multiple routes. Therefore, it helps government agencies prioritizing sites of multiple routes where the number of fatal collisions can be reduced, thus help them to save lives with limited resources of data collection.https://doi.org/10.1371/journal.pone.0251866
spellingShingle Eui-Jin Kim
Oh Hoon Kwon
Shin Hyoung Park
Dong-Kyu Kim
Koohong Chung
Application of naïve Bayesian approach in detecting reproducible fatal collision locations on freeway.
PLoS ONE
title Application of naïve Bayesian approach in detecting reproducible fatal collision locations on freeway.
title_full Application of naïve Bayesian approach in detecting reproducible fatal collision locations on freeway.
title_fullStr Application of naïve Bayesian approach in detecting reproducible fatal collision locations on freeway.
title_full_unstemmed Application of naïve Bayesian approach in detecting reproducible fatal collision locations on freeway.
title_short Application of naïve Bayesian approach in detecting reproducible fatal collision locations on freeway.
title_sort application of naive bayesian approach in detecting reproducible fatal collision locations on freeway
url https://doi.org/10.1371/journal.pone.0251866
work_keys_str_mv AT euijinkim applicationofnaivebayesianapproachindetectingreproduciblefatalcollisionlocationsonfreeway
AT ohhoonkwon applicationofnaivebayesianapproachindetectingreproduciblefatalcollisionlocationsonfreeway
AT shinhyoungpark applicationofnaivebayesianapproachindetectingreproduciblefatalcollisionlocationsonfreeway
AT dongkyukim applicationofnaivebayesianapproachindetectingreproduciblefatalcollisionlocationsonfreeway
AT koohongchung applicationofnaivebayesianapproachindetectingreproduciblefatalcollisionlocationsonfreeway