Risk Factors Influencing Fatal Powered Two-Wheeler At-Fault and Not-at-Fault Crashes: An Application of Spatio-Temporal Hotspot and Association Rule Mining Techniques
Studies have explored the factors influencing the safety of PTWs; however, very little has been carried out to comprehensively investigate the factors influencing fatal PTW crashes while considering the fault status of the rider in crash hotspot areas. This study employs spatio-temporal hotspot anal...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-05-01
|
| Series: | Informatics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-9709/10/2/43 |
| _version_ | 1797594243497197568 |
|---|---|
| author | Reuben Tamakloe |
| author_facet | Reuben Tamakloe |
| author_sort | Reuben Tamakloe |
| collection | DOAJ |
| description | Studies have explored the factors influencing the safety of PTWs; however, very little has been carried out to comprehensively investigate the factors influencing fatal PTW crashes while considering the fault status of the rider in crash hotspot areas. This study employs spatio-temporal hotspot analysis and association rule mining techniques to discover hidden associations between crash risk factors that lead to fatal PTW crashes considering the fault status of the rider at statistically significant PTW crash hotspots in South Korea from 2012 to 2017. The results indicate the presence of consecutively fatal PTW crash hotspots concentrated within Korea’s densely populated capital, Seoul, and new hotspots near its periphery. According to the results, violations such as over-speeding and red-light running were critical contributory factors influencing PTW crashes at hotspots during summer and at intersections. Interestingly, while reckless riding was the main traffic violation leading to PTW rider at-fault crashes at hotspots, violations such as improper safety distance and red-light running were strongly associated with PTW rider not-at-fault crashes at hotspots. In addition, while PTW rider at-fault crashes are likely to occur during summer, PTW rider not-at-fault crashes mostly occur during spring. The findings could be used for developing targeted policies for improving PTW safety at hotspots. |
| first_indexed | 2024-03-11T02:20:49Z |
| format | Article |
| id | doaj.art-e14c370797404ec0a147448f1b4e4e06 |
| institution | Directory Open Access Journal |
| issn | 2227-9709 |
| language | English |
| last_indexed | 2024-03-11T02:20:49Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Informatics |
| spelling | doaj.art-e14c370797404ec0a147448f1b4e4e062023-11-18T10:54:03ZengMDPI AGInformatics2227-97092023-05-011024310.3390/informatics10020043Risk Factors Influencing Fatal Powered Two-Wheeler At-Fault and Not-at-Fault Crashes: An Application of Spatio-Temporal Hotspot and Association Rule Mining TechniquesReuben Tamakloe0Department of Transportation Engineering, University of Seoul, 163 Seoulsiripdae-ro Dongdaemun-gu, Seoul 02504, Republic of KoreaStudies have explored the factors influencing the safety of PTWs; however, very little has been carried out to comprehensively investigate the factors influencing fatal PTW crashes while considering the fault status of the rider in crash hotspot areas. This study employs spatio-temporal hotspot analysis and association rule mining techniques to discover hidden associations between crash risk factors that lead to fatal PTW crashes considering the fault status of the rider at statistically significant PTW crash hotspots in South Korea from 2012 to 2017. The results indicate the presence of consecutively fatal PTW crash hotspots concentrated within Korea’s densely populated capital, Seoul, and new hotspots near its periphery. According to the results, violations such as over-speeding and red-light running were critical contributory factors influencing PTW crashes at hotspots during summer and at intersections. Interestingly, while reckless riding was the main traffic violation leading to PTW rider at-fault crashes at hotspots, violations such as improper safety distance and red-light running were strongly associated with PTW rider not-at-fault crashes at hotspots. In addition, while PTW rider at-fault crashes are likely to occur during summer, PTW rider not-at-fault crashes mostly occur during spring. The findings could be used for developing targeted policies for improving PTW safety at hotspots.https://www.mdpi.com/2227-9709/10/2/43spatio-temporal hotspot analysispowered two-wheelerassociation rule miningfatal crashcrash risk factor |
| spellingShingle | Reuben Tamakloe Risk Factors Influencing Fatal Powered Two-Wheeler At-Fault and Not-at-Fault Crashes: An Application of Spatio-Temporal Hotspot and Association Rule Mining Techniques Informatics spatio-temporal hotspot analysis powered two-wheeler association rule mining fatal crash crash risk factor |
| title | Risk Factors Influencing Fatal Powered Two-Wheeler At-Fault and Not-at-Fault Crashes: An Application of Spatio-Temporal Hotspot and Association Rule Mining Techniques |
| title_full | Risk Factors Influencing Fatal Powered Two-Wheeler At-Fault and Not-at-Fault Crashes: An Application of Spatio-Temporal Hotspot and Association Rule Mining Techniques |
| title_fullStr | Risk Factors Influencing Fatal Powered Two-Wheeler At-Fault and Not-at-Fault Crashes: An Application of Spatio-Temporal Hotspot and Association Rule Mining Techniques |
| title_full_unstemmed | Risk Factors Influencing Fatal Powered Two-Wheeler At-Fault and Not-at-Fault Crashes: An Application of Spatio-Temporal Hotspot and Association Rule Mining Techniques |
| title_short | Risk Factors Influencing Fatal Powered Two-Wheeler At-Fault and Not-at-Fault Crashes: An Application of Spatio-Temporal Hotspot and Association Rule Mining Techniques |
| title_sort | risk factors influencing fatal powered two wheeler at fault and not at fault crashes an application of spatio temporal hotspot and association rule mining techniques |
| topic | spatio-temporal hotspot analysis powered two-wheeler association rule mining fatal crash crash risk factor |
| url | https://www.mdpi.com/2227-9709/10/2/43 |
| work_keys_str_mv | AT reubentamakloe riskfactorsinfluencingfatalpoweredtwowheeleratfaultandnotatfaultcrashesanapplicationofspatiotemporalhotspotandassociationruleminingtechniques |