U. L. M. A. Uswaththa, H. Pasindu, J. Bandara, D. Jayaratne
{"title":"非均匀条件下多车道公路通行能力评价方法的适用性研究","authors":"U. L. M. A. Uswaththa, H. Pasindu, J. Bandara, D. Jayaratne","doi":"10.1109/MERCon52712.2021.9525674","DOIUrl":null,"url":null,"abstract":"Highway capacity is an essential element in highway planning and traffic management. There are a number of methods developed to estimate highway capacity. Most of them focus on identifying the maximum flow or throughput using a traffic speed-flow model. However, it has been found that these capacity estimates are not practical as they cannot be sustained for long, under normal flow conditions. This research mainly focuses on using the breakdown probability approach, in capacity estimation methods which are currently used to estimate the capacity mainly for freeways. Breakdown probability methods such as the Product Limit Method (PLM), the Sustained Flow Index (SFI), the Highway Capacity Manual (HCM) method are used to check the applicability of the breakdown probability approach in calculating highway capacity under heterogeneous conditions. These breakdown probability methods were applied for data collected from two multilane highway locations where heterogeneous flow conditions were observed. The capacity values obtained through the breakdown probability approach were compared with the capacity values obtained from the Greenberg model which is the considered conventional method. The breakdown approach resulted in capacity values which are less by an overall range of 7.4% to 30.9% for both locations.","PeriodicalId":6855,"journal":{"name":"2021 Moratuwa Engineering Research Conference (MERCon)","volume":"46 1","pages":"474-479"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Study On The Applicability Of Capacity Estimation Methods To Evaluate Multilane Highway Capacity Under Heterogeneous Conditions\",\"authors\":\"U. L. M. A. Uswaththa, H. Pasindu, J. Bandara, D. Jayaratne\",\"doi\":\"10.1109/MERCon52712.2021.9525674\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Highway capacity is an essential element in highway planning and traffic management. There are a number of methods developed to estimate highway capacity. Most of them focus on identifying the maximum flow or throughput using a traffic speed-flow model. However, it has been found that these capacity estimates are not practical as they cannot be sustained for long, under normal flow conditions. This research mainly focuses on using the breakdown probability approach, in capacity estimation methods which are currently used to estimate the capacity mainly for freeways. Breakdown probability methods such as the Product Limit Method (PLM), the Sustained Flow Index (SFI), the Highway Capacity Manual (HCM) method are used to check the applicability of the breakdown probability approach in calculating highway capacity under heterogeneous conditions. These breakdown probability methods were applied for data collected from two multilane highway locations where heterogeneous flow conditions were observed. The capacity values obtained through the breakdown probability approach were compared with the capacity values obtained from the Greenberg model which is the considered conventional method. The breakdown approach resulted in capacity values which are less by an overall range of 7.4% to 30.9% for both locations.\",\"PeriodicalId\":6855,\"journal\":{\"name\":\"2021 Moratuwa Engineering Research Conference (MERCon)\",\"volume\":\"46 1\",\"pages\":\"474-479\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 Moratuwa Engineering Research Conference (MERCon)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MERCon52712.2021.9525674\",\"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 Moratuwa Engineering Research Conference (MERCon)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MERCon52712.2021.9525674","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Study On The Applicability Of Capacity Estimation Methods To Evaluate Multilane Highway Capacity Under Heterogeneous Conditions
Highway capacity is an essential element in highway planning and traffic management. There are a number of methods developed to estimate highway capacity. Most of them focus on identifying the maximum flow or throughput using a traffic speed-flow model. However, it has been found that these capacity estimates are not practical as they cannot be sustained for long, under normal flow conditions. This research mainly focuses on using the breakdown probability approach, in capacity estimation methods which are currently used to estimate the capacity mainly for freeways. Breakdown probability methods such as the Product Limit Method (PLM), the Sustained Flow Index (SFI), the Highway Capacity Manual (HCM) method are used to check the applicability of the breakdown probability approach in calculating highway capacity under heterogeneous conditions. These breakdown probability methods were applied for data collected from two multilane highway locations where heterogeneous flow conditions were observed. The capacity values obtained through the breakdown probability approach were compared with the capacity values obtained from the Greenberg model which is the considered conventional method. The breakdown approach resulted in capacity values which are less by an overall range of 7.4% to 30.9% for both locations.