Temporal Analysis of Road Traffic Accidents at Major Intersections in Khon Kaen Province, Thailand: A Time Series Investigation from 2012 to 2021
Issued Date
2024-07-01
Resource Type
ISSN
16866576
eISSN
26730014
Scopus ID
2-s2.0-85202062439
Journal Title
International Journal of Geoinformatics
Volume
20
Issue
7
Start Page
43
End Page
58
Rights Holder(s)
SCOPUS
Bibliographic Citation
International Journal of Geoinformatics Vol.20 No.7 (2024) , 43-58
Suggested Citation
Tippayanate N., Impool T., Sujayanont P., Muttitanon W., Chemin Y.H., Som-Ard J. Temporal Analysis of Road Traffic Accidents at Major Intersections in Khon Kaen Province, Thailand: A Time Series Investigation from 2012 to 2021. International Journal of Geoinformatics Vol.20 No.7 (2024) , 43-58. 58. doi:10.52939/ijg.v20i7.3403 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/100663
Title
Temporal Analysis of Road Traffic Accidents at Major Intersections in Khon Kaen Province, Thailand: A Time Series Investigation from 2012 to 2021
Corresponding Author(s)
Other Contributor(s)
Abstract
This research paper presents a comprehensive analysis of accidents at 23 intersections within Muang Khon Kaen district over the period from 2012 to 2021. The 10 years data were collected and analyzed utilizing Global Moran’s I to investigate the existence of spatial autocorrelation among the intersections. And Anselin Local Moran’s I was adopted to identify the cluster of the accidents at the intersections. The result found that the spatial pattern did not exist, which indicates that the accident numbers at each intersection is independent from each other. However, a hotspots and high outliers were found at Mitraparp-Bankok (MB) and Sricharn-Chatapadoong (SC) intersections, respectively, in 2020. The study identifies 2018 as the year with the highest incidence of accidents, followed by a notable decline post-2018, potentially influenced by the onset of the COVID-19 pandemic in early 2020. The analysis of accident hotspots reveals the Sricharn-Chatapadoong (SC) intersection as the most accident-prone location, contrasting starkly with the absence of incidents at the Prachasamosorn-Bakham (PB) and Robbueng-Srithat (RS) intersections. The MB intersection ranks second in accidents, consistent with hotspot identification in cluster analysis. Additionally, intersections ML and MS tie for third place in accident frequency. Temporal analysis uncovers a peak in accidents between 2:00 AM and 4:00 AM, likely attributable to driving under the influence (DUI) compounded by the closure of entertainment venues nationwide at 2:00 AM. Accidents are predominantly observed among males aged 18 to 25 years, frequently involving motorcycles as their primary mode of transportation. The concentration of educational institutions along Sricharn road contributes to heavy traffic flow, particularly during peak hours, increasing the risk of accidents, notably among adolescent motorcycle commuters. Consequently, the SC intersection emerges as a high-risk area, necessitating intensified surveillance and accident prevention measures. In conclusion, this study offers valuable insights into road safety challenges within Muang Khon Kaen district, providing evidence-based recommendations to reduce accidents. Decision-makers and authorities can leverage this information to implement targeted interventions and enhance road safety measures, locally and beyond.
