Exploring the influential factors of roadway departure crashes on rural two-lane highways with logit model and association rules mining
Roadway departure (RwD) crashes are a major contributor of rural two-lane (R2L) highway crashes and fatalities. For targeted reduction of crashes and fatalities due to roadway departure, a thorough understanding of factors associated with RwD crashes is necessary. This study quantitatively assessed...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2021-06-01
|
| Series: | International Journal of Transportation Science and Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2046043020300800 |
| _version_ | 1827829469092511744 |
|---|---|
| author | M. Ashifur Rahman Xiaoduan Sun Subasish Das Sushmita Khanal |
| author_facet | M. Ashifur Rahman Xiaoduan Sun Subasish Das Sushmita Khanal |
| author_sort | M. Ashifur Rahman |
| collection | DOAJ |
| description | Roadway departure (RwD) crashes are a major contributor of rural two-lane (R2L) highway crashes and fatalities. For targeted reduction of crashes and fatalities due to roadway departure, a thorough understanding of factors associated with RwD crashes is necessary. This study quantitatively assessed the available pre-crash factors that might influence the RwD crashes by developing a logit model comparing roadway, crash environment, and the vehicle and driver-related characteristics of 122,978 crashes that occurred in Louisiana over thirteen years. With a high prediction accuracy (81.9% area under the receiver operating characteristics curve), the model presented significant individual associations across crash characteristics with RwD crashes on R2L highways, for example – animals on roadways, snow/sleet/hail, 50–55 mph speed limit, AADT of 1,001–5,000 vehicles per day, drug intoxication, motorcycles, driving during 12 am to 6 am, curve radius of 501–1,000 ft., absence of streetlight, alcohol intoxication. Investigation on these top factors using association rules mining reveals findings such as – a higher likelihood of RwD crashes can be strongly associated animal presence coupled with the absence of streetlights, male drivers during the early morning (12 am to 6 am), male drivers driving with no passengers, drivers being intoxicated by both drugs and alcohol, etc. Findings from this study are expected to help highway safety specialists not only in identifying and predicting RwD crashes but also in an improved understanding of associated contributing factors leading to the application of proper countermeasures for the strategic reduction of RwD crashes. |
| first_indexed | 2024-03-12T04:04:49Z |
| format | Article |
| id | doaj.art-86c0194a9895442ab8d9c2e89091bc3f |
| institution | Directory Open Access Journal |
| issn | 2046-0430 |
| language | English |
| last_indexed | 2024-03-12T04:04:49Z |
| publishDate | 2021-06-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | International Journal of Transportation Science and Technology |
| spelling | doaj.art-86c0194a9895442ab8d9c2e89091bc3f2023-09-03T11:23:13ZengKeAi Communications Co., Ltd.International Journal of Transportation Science and Technology2046-04302021-06-01102167183Exploring the influential factors of roadway departure crashes on rural two-lane highways with logit model and association rules miningM. Ashifur Rahman0Xiaoduan Sun1Subasish Das2Sushmita Khanal3University of Louisiana, Lafayette, LA, United States; Corresponding author at: 131 Rex St, Madison Hall Rm 223, Lafayette, LA, United States.University of Louisiana, Lafayette, LA, United StatesTexas A&M Transportation Institute, San Antonio, United StatesUniversity of Louisiana, Lafayette, LA, United StatesRoadway departure (RwD) crashes are a major contributor of rural two-lane (R2L) highway crashes and fatalities. For targeted reduction of crashes and fatalities due to roadway departure, a thorough understanding of factors associated with RwD crashes is necessary. This study quantitatively assessed the available pre-crash factors that might influence the RwD crashes by developing a logit model comparing roadway, crash environment, and the vehicle and driver-related characteristics of 122,978 crashes that occurred in Louisiana over thirteen years. With a high prediction accuracy (81.9% area under the receiver operating characteristics curve), the model presented significant individual associations across crash characteristics with RwD crashes on R2L highways, for example – animals on roadways, snow/sleet/hail, 50–55 mph speed limit, AADT of 1,001–5,000 vehicles per day, drug intoxication, motorcycles, driving during 12 am to 6 am, curve radius of 501–1,000 ft., absence of streetlight, alcohol intoxication. Investigation on these top factors using association rules mining reveals findings such as – a higher likelihood of RwD crashes can be strongly associated animal presence coupled with the absence of streetlights, male drivers during the early morning (12 am to 6 am), male drivers driving with no passengers, drivers being intoxicated by both drugs and alcohol, etc. Findings from this study are expected to help highway safety specialists not only in identifying and predicting RwD crashes but also in an improved understanding of associated contributing factors leading to the application of proper countermeasures for the strategic reduction of RwD crashes.http://www.sciencedirect.com/science/article/pii/S2046043020300800Roadway departure crashesRural two-lane highwaysCrash contributing factorAssociation rule miningLogit model |
| spellingShingle | M. Ashifur Rahman Xiaoduan Sun Subasish Das Sushmita Khanal Exploring the influential factors of roadway departure crashes on rural two-lane highways with logit model and association rules mining International Journal of Transportation Science and Technology Roadway departure crashes Rural two-lane highways Crash contributing factor Association rule mining Logit model |
| title | Exploring the influential factors of roadway departure crashes on rural two-lane highways with logit model and association rules mining |
| title_full | Exploring the influential factors of roadway departure crashes on rural two-lane highways with logit model and association rules mining |
| title_fullStr | Exploring the influential factors of roadway departure crashes on rural two-lane highways with logit model and association rules mining |
| title_full_unstemmed | Exploring the influential factors of roadway departure crashes on rural two-lane highways with logit model and association rules mining |
| title_short | Exploring the influential factors of roadway departure crashes on rural two-lane highways with logit model and association rules mining |
| title_sort | exploring the influential factors of roadway departure crashes on rural two lane highways with logit model and association rules mining |
| topic | Roadway departure crashes Rural two-lane highways Crash contributing factor Association rule mining Logit model |
| url | http://www.sciencedirect.com/science/article/pii/S2046043020300800 |
| work_keys_str_mv | AT mashifurrahman exploringtheinfluentialfactorsofroadwaydeparturecrashesonruraltwolanehighwayswithlogitmodelandassociationrulesmining AT xiaoduansun exploringtheinfluentialfactorsofroadwaydeparturecrashesonruraltwolanehighwayswithlogitmodelandassociationrulesmining AT subasishdas exploringtheinfluentialfactorsofroadwaydeparturecrashesonruraltwolanehighwayswithlogitmodelandassociationrulesmining AT sushmitakhanal exploringtheinfluentialfactorsofroadwaydeparturecrashesonruraltwolanehighwayswithlogitmodelandassociationrulesmining |