مشروع البحث: CRASH SEVERITY ASSESSMENT USING BINARY LOGIT MODEL WITH DIFFERENT DATA AGGREGATION METHODS
| dc.contributor.advisor | UNIVERSITI KEBANGSAAN MALAYSIA | |
| dc.date.accessioned | 2024-12-09T12:12:16Z | |
| dc.date.available | 2024-12-09T12:12:16Z | |
| dc.description | ABSTRACT Road traffic crashes (RTCs) have long been a substantial health problem for the public and government agencies. Identifying factors influencing road traffic injury severity is essential to saving human lives, especially in nations with high road traffic mortality rates, such as Libya. Unfortunately, RTCs data is lacking in Libya, which imposes restrictions on data analysis. The present study aims to fill the gap by conducting an injury severity analysis employing reliable and detailed RTCs data. RTCs data for a decade (2001–2010) was extracted directly from hard copy investigation reports stored in Ajdabiya Traffic Police Department archive. More than 2,300 investigation reports (urban and rural areas) were reviewed and converted into an electronic format to build the RTCs database. Binary Logit Model (BLM) was applied to assess the severity of crash injuries on the freeway in Ajdabiya | |
| dc.description.abstract | ABSTRAK Kemalangan lalu lintas jalan raya (RTC) telah lama menjadi masalah keselamatan yang besar bagi orang awam dan agensi kerajaan. Mengenal pasti faktor yang mempengaruhi keparahan kecederaan lalu lintas jalan raya adalah penting untuk menyelamatkan nyawa manusia, terutamanya di negara yang mempunyai kadar kematian trafik jalan raya yang tinggi, seperti Libya. Malangnya, data RTC kurang di Libya, yang mengenakan sekatan ke atas analisis data. Kajian ini bertujuan untuk mengisi jurang dengan menjalankan analisis keparahan kecederaan menggunakan data RTC yang boleh dipercayai dan terperinci. Data RTC selama sedekad (2001–2010) diekstrak terus daripada laporan penyiasatan salinan cetak yang disimpan dalam arkib Jabatan Polis Trafik Ajdabiya. Lebih daripada 2,300 laporan penyiasatan (kawasan bandar dan luar bandar) telah disemak dan ditukar kepada format elektronik untuk membina pangkalan data RTC. Model Logik Penduaan (BLM) telah digunakan | |
| dc.identifier | 129 | |
| dc.identifier.uri | https://dspace.academy.edu.ly/handle/123456789/681 | |
| dc.title | CRASH SEVERITY ASSESSMENT USING BINARY LOGIT MODEL WITH DIFFERENT DATA AGGREGATION METHODS | |
| dspace.entity.type | Project | |
| project.endDate | 2024 | |
| project.funder.name | الفلسفة | |
| project.investigator | عمر محمد ابوسيف | |
| project.startDate | 2023 | |
| relation.isOrgUnitOfProject | 5b44e99f-ae43-484b-a321-bd4eb13fa0e1 | |
| relation.isOrgUnitOfProject.latestForDiscovery | 5b44e99f-ae43-484b-a321-bd4eb13fa0e1 |