Elrasheed Ismail Mohommoud ZAYID, Nadir Abdelrahman Ahmed FARAH, Turki Mohammed Abdullah AL-SHEHRI, Ali Mohammed Saeed ALRAYAYAEI, Somaia Mohammed Ali ELIMAM
{"title":"沙特阿拉伯东南亚地区基于模拟的交通事故测试","authors":"Elrasheed Ismail Mohommoud ZAYID, Nadir Abdelrahman Ahmed FARAH, Turki Mohammed Abdullah AL-SHEHRI, Ali Mohammed Saeed ALRAYAYAEI, Somaia Mohammed Ali ELIMAM","doi":"10.1109/CAIDA51941.2021.9425144","DOIUrl":null,"url":null,"abstract":"In terms of fatalities caused by Traffic Accidents (TAs), Saudi Arabia occupies a top position in the world. Notably, the most affected age group is young people (i.e. age 18 -25 years). In this study, we addressed the major causes of TAs in the Aseer Region, which is the southern Saudi area. To accurately perform the correct simulation, we used two different datasets. The first one was called ataset1 (DS1), which was extracted from 116 volunteer young participants in the region, each of whom reported a full TA they had survived or witnessed. The second dataset (DS2) was generated using a powerful simulation and modeling algorithm. DS1 was used as input for performing the simulation. For accurate statistical computing TA simulation and modeling purposes, the MATLAB 2018 computing environment was the best candidate to validate our postulates. More than 14 different TA factors were examined to prove the extent of devastation caused by TAs. The contributions of several TA metrics were calculated, and smartphone use while driving and speeding were found to be the primary factors that contributed to TAs. The number of death(s) registered from the public hospital(s) in the region was greater than 22%, which is extraordinary, making this the highest traffic risk in the area. Comparing this study findings with those of previous related ones, the study offers promising results that could be utilized to secure the local community from the current and frequent TA threats. One of the main recommendations in this study, is to incorporate the driving behavior of young people in the primary educational systems.","PeriodicalId":272573,"journal":{"name":"2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Simulation-based Traffic Accident Testing in the Aseer Region of Saudi Arabia\",\"authors\":\"Elrasheed Ismail Mohommoud ZAYID, Nadir Abdelrahman Ahmed FARAH, Turki Mohammed Abdullah AL-SHEHRI, Ali Mohammed Saeed ALRAYAYAEI, Somaia Mohammed Ali ELIMAM\",\"doi\":\"10.1109/CAIDA51941.2021.9425144\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In terms of fatalities caused by Traffic Accidents (TAs), Saudi Arabia occupies a top position in the world. Notably, the most affected age group is young people (i.e. age 18 -25 years). In this study, we addressed the major causes of TAs in the Aseer Region, which is the southern Saudi area. To accurately perform the correct simulation, we used two different datasets. The first one was called ataset1 (DS1), which was extracted from 116 volunteer young participants in the region, each of whom reported a full TA they had survived or witnessed. The second dataset (DS2) was generated using a powerful simulation and modeling algorithm. DS1 was used as input for performing the simulation. For accurate statistical computing TA simulation and modeling purposes, the MATLAB 2018 computing environment was the best candidate to validate our postulates. More than 14 different TA factors were examined to prove the extent of devastation caused by TAs. The contributions of several TA metrics were calculated, and smartphone use while driving and speeding were found to be the primary factors that contributed to TAs. The number of death(s) registered from the public hospital(s) in the region was greater than 22%, which is extraordinary, making this the highest traffic risk in the area. Comparing this study findings with those of previous related ones, the study offers promising results that could be utilized to secure the local community from the current and frequent TA threats. One of the main recommendations in this study, is to incorporate the driving behavior of young people in the primary educational systems.\",\"PeriodicalId\":272573,\"journal\":{\"name\":\"2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA)\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-04-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CAIDA51941.2021.9425144\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 1st International Conference on Artificial Intelligence and Data Analytics (CAIDA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAIDA51941.2021.9425144","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Simulation-based Traffic Accident Testing in the Aseer Region of Saudi Arabia
In terms of fatalities caused by Traffic Accidents (TAs), Saudi Arabia occupies a top position in the world. Notably, the most affected age group is young people (i.e. age 18 -25 years). In this study, we addressed the major causes of TAs in the Aseer Region, which is the southern Saudi area. To accurately perform the correct simulation, we used two different datasets. The first one was called ataset1 (DS1), which was extracted from 116 volunteer young participants in the region, each of whom reported a full TA they had survived or witnessed. The second dataset (DS2) was generated using a powerful simulation and modeling algorithm. DS1 was used as input for performing the simulation. For accurate statistical computing TA simulation and modeling purposes, the MATLAB 2018 computing environment was the best candidate to validate our postulates. More than 14 different TA factors were examined to prove the extent of devastation caused by TAs. The contributions of several TA metrics were calculated, and smartphone use while driving and speeding were found to be the primary factors that contributed to TAs. The number of death(s) registered from the public hospital(s) in the region was greater than 22%, which is extraordinary, making this the highest traffic risk in the area. Comparing this study findings with those of previous related ones, the study offers promising results that could be utilized to secure the local community from the current and frequent TA threats. One of the main recommendations in this study, is to incorporate the driving behavior of young people in the primary educational systems.