{"title":"从乘客上车和下车数据中估计巴士收入的方法:斯里兰卡的案例研究","authors":"Sabeen Sharic, S. Bandara, S. Fernando","doi":"10.1109/MERCon52712.2021.9525713","DOIUrl":null,"url":null,"abstract":"A methodology is developed to estimate the revenue of a bus trip based on data available on passenger boarding & alighting. Three scenarios are explained. First is when individual passenger data on boarding and alighting is available. The second is when the boarding and alighting data at stop level or by fare section and the third is when, only the total demand or only the past demand distribution pattern is available. First step is to determine passenger cumulative boarding and alighting by fare sections of a route based on bus ticket information or boarding and alighting counts. Then the cumulative boarding and alighting information is used for revenue estimation. To estimate the revenue, the bus fare for a given trip length is used for the first scenario and the moving average of sectional fare increments is used for others. A computer algorithm is developed to accommodate any scenarios. This algorithm helps to estimate the revenue of buses based on passenger boarding and alighting information and can estimate revenue for a given route or sections of a route, different passenger demand situations, different bus capacities and any service frequencies.","PeriodicalId":6855,"journal":{"name":"2021 Moratuwa Engineering Research Conference (MERCon)","volume":"43 1","pages":"597-601"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Methods to Estimate Bus Revenue from Passenger Boarding and Alighting Data: Case Study for Sri Lanka\",\"authors\":\"Sabeen Sharic, S. Bandara, S. Fernando\",\"doi\":\"10.1109/MERCon52712.2021.9525713\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A methodology is developed to estimate the revenue of a bus trip based on data available on passenger boarding & alighting. Three scenarios are explained. First is when individual passenger data on boarding and alighting is available. The second is when the boarding and alighting data at stop level or by fare section and the third is when, only the total demand or only the past demand distribution pattern is available. First step is to determine passenger cumulative boarding and alighting by fare sections of a route based on bus ticket information or boarding and alighting counts. Then the cumulative boarding and alighting information is used for revenue estimation. To estimate the revenue, the bus fare for a given trip length is used for the first scenario and the moving average of sectional fare increments is used for others. A computer algorithm is developed to accommodate any scenarios. This algorithm helps to estimate the revenue of buses based on passenger boarding and alighting information and can estimate revenue for a given route or sections of a route, different passenger demand situations, different bus capacities and any service frequencies.\",\"PeriodicalId\":6855,\"journal\":{\"name\":\"2021 Moratuwa Engineering Research Conference (MERCon)\",\"volume\":\"43 1\",\"pages\":\"597-601\"},\"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/MERCon52712.2021.9525713\",\"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/MERCon52712.2021.9525713","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Methods to Estimate Bus Revenue from Passenger Boarding and Alighting Data: Case Study for Sri Lanka
A methodology is developed to estimate the revenue of a bus trip based on data available on passenger boarding & alighting. Three scenarios are explained. First is when individual passenger data on boarding and alighting is available. The second is when the boarding and alighting data at stop level or by fare section and the third is when, only the total demand or only the past demand distribution pattern is available. First step is to determine passenger cumulative boarding and alighting by fare sections of a route based on bus ticket information or boarding and alighting counts. Then the cumulative boarding and alighting information is used for revenue estimation. To estimate the revenue, the bus fare for a given trip length is used for the first scenario and the moving average of sectional fare increments is used for others. A computer algorithm is developed to accommodate any scenarios. This algorithm helps to estimate the revenue of buses based on passenger boarding and alighting information and can estimate revenue for a given route or sections of a route, different passenger demand situations, different bus capacities and any service frequencies.