Contributing factors to near-miss experiences of motorcyclists in Thailand: A random parameter probit model approach
Road accidents cause a large number of deaths, especially in Thailand. When considered in depth, motorcycles account for the highest percentage of fatalities. According to Heinrich's Safety Triangle Model, a decrease in near misses will reduce the number of road accidents. There is still a lack...
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| Format: | Article |
| Language: | English |
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Elsevier
2023-12-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S240584402309833X |
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| author | Sajjakaj Jomnonkwao Thanapong Champahom Chamroeun Se Natthaporn Hantanong Vatanavongs Ratanavaraha |
| author_facet | Sajjakaj Jomnonkwao Thanapong Champahom Chamroeun Se Natthaporn Hantanong Vatanavongs Ratanavaraha |
| author_sort | Sajjakaj Jomnonkwao |
| collection | DOAJ |
| description | Road accidents cause a large number of deaths, especially in Thailand. When considered in depth, motorcycles account for the highest percentage of fatalities. According to Heinrich's Safety Triangle Model, a decrease in near misses will reduce the number of road accidents. There is still a lack of studies on risky behaviors contributing to near misses involving motorcycles. This study aims to comprehend the various factors that influence the frequency of near-miss experiences using a questionnaire on near-miss incidents. The contributing factors include road factors (e.g., road surface, number of traffic lanes, speed limit), environmental factors (e.g., driving at night), and driver factors (e.g., using a phone while driving). Of the 2002 respondents, a total of 1547 people have occasionally experienced a near-miss incident. A random parameter probit model (RPOP) was used for analyzing the relationship between the contributing factors and the near-miss frequency, and model statistics clearly confirm that RPOPs that import only significant variables are the most suitable models. The study found 14 factors that affect near-miss frequency, and there are 5 variables that are random parameters. Variables that increase the chance of a near-miss incident include driving at night (both with and without lights), roads with concrete road surfaces, and roads with unclear lane markings. This study provides policy recommendations for relevant agencies that were identified to reduce near-miss motorcycle accidents. |
| first_indexed | 2024-03-08T21:29:43Z |
| format | Article |
| id | doaj.art-f5e98d9282ed4bb5b179c691dc5f72e8 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-03-08T21:29:43Z |
| publishDate | 2023-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-f5e98d9282ed4bb5b179c691dc5f72e82023-12-21T07:34:04ZengElsevierHeliyon2405-84402023-12-01912e22625Contributing factors to near-miss experiences of motorcyclists in Thailand: A random parameter probit model approachSajjakaj Jomnonkwao0Thanapong Champahom1Chamroeun Se2Natthaporn Hantanong3Vatanavongs Ratanavaraha4School of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand; Corresponding author.Department of Management, Faculty of Business Administration, Rajamangala University of Technology Isan, Nakhon Ratchasima, 30000, ThailandSchool of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima, 30000, ThailandSchool of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima, 30000, ThailandSchool of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima, 30000, ThailandRoad accidents cause a large number of deaths, especially in Thailand. When considered in depth, motorcycles account for the highest percentage of fatalities. According to Heinrich's Safety Triangle Model, a decrease in near misses will reduce the number of road accidents. There is still a lack of studies on risky behaviors contributing to near misses involving motorcycles. This study aims to comprehend the various factors that influence the frequency of near-miss experiences using a questionnaire on near-miss incidents. The contributing factors include road factors (e.g., road surface, number of traffic lanes, speed limit), environmental factors (e.g., driving at night), and driver factors (e.g., using a phone while driving). Of the 2002 respondents, a total of 1547 people have occasionally experienced a near-miss incident. A random parameter probit model (RPOP) was used for analyzing the relationship between the contributing factors and the near-miss frequency, and model statistics clearly confirm that RPOPs that import only significant variables are the most suitable models. The study found 14 factors that affect near-miss frequency, and there are 5 variables that are random parameters. Variables that increase the chance of a near-miss incident include driving at night (both with and without lights), roads with concrete road surfaces, and roads with unclear lane markings. This study provides policy recommendations for relevant agencies that were identified to reduce near-miss motorcycle accidents.http://www.sciencedirect.com/science/article/pii/S240584402309833XThailandRoad factorsEnvironmental factorsNear crashMotorcycle rider behavior questionnaire |
| spellingShingle | Sajjakaj Jomnonkwao Thanapong Champahom Chamroeun Se Natthaporn Hantanong Vatanavongs Ratanavaraha Contributing factors to near-miss experiences of motorcyclists in Thailand: A random parameter probit model approach Heliyon Thailand Road factors Environmental factors Near crash Motorcycle rider behavior questionnaire |
| title | Contributing factors to near-miss experiences of motorcyclists in Thailand: A random parameter probit model approach |
| title_full | Contributing factors to near-miss experiences of motorcyclists in Thailand: A random parameter probit model approach |
| title_fullStr | Contributing factors to near-miss experiences of motorcyclists in Thailand: A random parameter probit model approach |
| title_full_unstemmed | Contributing factors to near-miss experiences of motorcyclists in Thailand: A random parameter probit model approach |
| title_short | Contributing factors to near-miss experiences of motorcyclists in Thailand: A random parameter probit model approach |
| title_sort | contributing factors to near miss experiences of motorcyclists in thailand a random parameter probit model approach |
| topic | Thailand Road factors Environmental factors Near crash Motorcycle rider behavior questionnaire |
| url | http://www.sciencedirect.com/science/article/pii/S240584402309833X |
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