{"title":"基于不同软件的埃尔比勒市信号交叉口排队问题评价","authors":"D. H. Omar, Salar K. Hussein","doi":"10.2174/18744478-v16-e221024-2022-3","DOIUrl":null,"url":null,"abstract":"\n \n The aim of this study is to evaluate the queue length of isolated signalized intersections which used HCS2010, and SIDRA Intersection 8 traffic software.\n \n \n \n One of the important parameter to evaluate the performance of traffic management system is Queue length, especially in congested traffic situations. For the estimation of Back of Queue length, many traffic analyzing models are used based on Highway Capacity Manual (HCM2010).\n \n \n \n The values of queue length obtained from these two software to be compared with observed queue length from field. The study also aids to conduct a model of optimization for back of queue length to decrease the value of storage length of vehicles following GA procedure.\n \n \n \n In this study, four isolated signalized intersections were used in Erbil city, the capital of Iraqi Kurdistan Region. The values of the measured Back of Queue lengths are compared with the values obtained from Highway Capacity Software HCS2010(HCS+T7F) and Signalized and Unsignalized Intersection Design and Research (SIDRA Intersection 8) Aid Australian Road Research Board (ARRB) software.\n \n \n \n The results of regression analysis showed that SIDRA Intersection 8 Back of Queue model with adjusted R2 0.8465 have a stronger relationship with the field measured Back of the Queue for linear relationship compered to HCS2010 Back of Queue model. Furthermore, the study tends to optimize the signalized intersections under study using HCS2010 and SIDRA Intersection 8 software based on the Genetic Algorithm (GA) to minimize the Back of Queue length. The percent of average reduction in HCS2010 and SIDRA Intersection 8 Back of Queue models are 36% and 29%, respectively. The main objective to optimize the timing plan was to minimize the average storage Queue length at signalized intersections that follow the Highway Capacity Manual (TRB 2010) procedure for Queue length calculation. Moreover, 95th and 98th values of the percentiles were chosen to estimate the expectancy of upstream lane blockage and the expectancy of short lane overflow that was related to the Back of the Queue percentile.\n \n \n \n The improvement of vehicle storage for upstream lanes was conducted by the two software systems mentioned before. The results showed significant improvement in performance of the intersections under study with reduction of queue length.\n","PeriodicalId":38631,"journal":{"name":"Open Transportation Journal","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluation of Back of Queue at Signalized Intersections in Erbil City using Different Software\",\"authors\":\"D. H. Omar, Salar K. Hussein\",\"doi\":\"10.2174/18744478-v16-e221024-2022-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n \\n The aim of this study is to evaluate the queue length of isolated signalized intersections which used HCS2010, and SIDRA Intersection 8 traffic software.\\n \\n \\n \\n One of the important parameter to evaluate the performance of traffic management system is Queue length, especially in congested traffic situations. For the estimation of Back of Queue length, many traffic analyzing models are used based on Highway Capacity Manual (HCM2010).\\n \\n \\n \\n The values of queue length obtained from these two software to be compared with observed queue length from field. The study also aids to conduct a model of optimization for back of queue length to decrease the value of storage length of vehicles following GA procedure.\\n \\n \\n \\n In this study, four isolated signalized intersections were used in Erbil city, the capital of Iraqi Kurdistan Region. The values of the measured Back of Queue lengths are compared with the values obtained from Highway Capacity Software HCS2010(HCS+T7F) and Signalized and Unsignalized Intersection Design and Research (SIDRA Intersection 8) Aid Australian Road Research Board (ARRB) software.\\n \\n \\n \\n The results of regression analysis showed that SIDRA Intersection 8 Back of Queue model with adjusted R2 0.8465 have a stronger relationship with the field measured Back of the Queue for linear relationship compered to HCS2010 Back of Queue model. Furthermore, the study tends to optimize the signalized intersections under study using HCS2010 and SIDRA Intersection 8 software based on the Genetic Algorithm (GA) to minimize the Back of Queue length. The percent of average reduction in HCS2010 and SIDRA Intersection 8 Back of Queue models are 36% and 29%, respectively. The main objective to optimize the timing plan was to minimize the average storage Queue length at signalized intersections that follow the Highway Capacity Manual (TRB 2010) procedure for Queue length calculation. Moreover, 95th and 98th values of the percentiles were chosen to estimate the expectancy of upstream lane blockage and the expectancy of short lane overflow that was related to the Back of the Queue percentile.\\n \\n \\n \\n The improvement of vehicle storage for upstream lanes was conducted by the two software systems mentioned before. The results showed significant improvement in performance of the intersections under study with reduction of queue length.\\n\",\"PeriodicalId\":38631,\"journal\":{\"name\":\"Open Transportation Journal\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Open Transportation Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2174/18744478-v16-e221024-2022-3\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Transportation Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/18744478-v16-e221024-2022-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0
摘要
本研究的目的是评估使用HCS2010和SIDRA Intersection 8交通软件的孤立信号交叉口的排队长度。排队长度是评价交通管理系统性能的重要参数之一,尤其是在交通拥堵的情况下。为了估计排队后的长度,根据《公路通行能力手册》(HCM2010)使用了许多交通分析模型。将从这两个软件获得的队列长度值与字段中观察到的队列长度进行比较。该研究还有助于建立排队后长度的优化模型,以降低GA程序下车辆的存储长度值。在本研究中,在伊拉克库尔德斯坦地区首府埃尔比勒市使用了四个独立的信号交叉口。将测量的排队后长度的值与从公路通行能力软件HCS2010(HCS+T7F)和有信号和无信号交叉口设计与研究(SIDRA交叉口8)援助澳大利亚道路研究委员会(ARRB)软件获得的值进行比较。回归分析结果表明,修正R2为0.8465的SIDRA Intersection 8 Back of Queue模型与实测Back of The Queue的线性关系强于HCS2010 Back of Queue。此外,本研究倾向于使用基于遗传算法的HCS2010和SIDRA Intersection 8软件对所研究的信号交叉口进行优化,以最小化排队长度。HCS2010和SIDRA交叉口8排队后模型的平均减少百分比分别为36%和29%。优化配时计划的主要目的是最大限度地减少信号交叉口的平均存储排队长度,该交叉口遵循《公路通行能力手册》(TRB 2010)中的排队长度计算程序。此外,选择第95个和第98个百分位数来估计上游车道堵塞的预期值和与排队后百分位数相关的短车道溢流的预期值。上游车道车辆存储的改进是通过前面提到的两个软件系统进行的。结果表明,随着排队长度的减少,所研究的十字路口的性能显著提高。
Evaluation of Back of Queue at Signalized Intersections in Erbil City using Different Software
The aim of this study is to evaluate the queue length of isolated signalized intersections which used HCS2010, and SIDRA Intersection 8 traffic software.
One of the important parameter to evaluate the performance of traffic management system is Queue length, especially in congested traffic situations. For the estimation of Back of Queue length, many traffic analyzing models are used based on Highway Capacity Manual (HCM2010).
The values of queue length obtained from these two software to be compared with observed queue length from field. The study also aids to conduct a model of optimization for back of queue length to decrease the value of storage length of vehicles following GA procedure.
In this study, four isolated signalized intersections were used in Erbil city, the capital of Iraqi Kurdistan Region. The values of the measured Back of Queue lengths are compared with the values obtained from Highway Capacity Software HCS2010(HCS+T7F) and Signalized and Unsignalized Intersection Design and Research (SIDRA Intersection 8) Aid Australian Road Research Board (ARRB) software.
The results of regression analysis showed that SIDRA Intersection 8 Back of Queue model with adjusted R2 0.8465 have a stronger relationship with the field measured Back of the Queue for linear relationship compered to HCS2010 Back of Queue model. Furthermore, the study tends to optimize the signalized intersections under study using HCS2010 and SIDRA Intersection 8 software based on the Genetic Algorithm (GA) to minimize the Back of Queue length. The percent of average reduction in HCS2010 and SIDRA Intersection 8 Back of Queue models are 36% and 29%, respectively. The main objective to optimize the timing plan was to minimize the average storage Queue length at signalized intersections that follow the Highway Capacity Manual (TRB 2010) procedure for Queue length calculation. Moreover, 95th and 98th values of the percentiles were chosen to estimate the expectancy of upstream lane blockage and the expectancy of short lane overflow that was related to the Back of the Queue percentile.
The improvement of vehicle storage for upstream lanes was conducted by the two software systems mentioned before. The results showed significant improvement in performance of the intersections under study with reduction of queue length.