Pub Date : 2020-09-01DOI: 10.1109/ICITE50838.2020.9231520
Haitao Ji, Peng Wu
We study a third party logistics company, who uses highway and maritime transportation to deliver a set of commodities from their origins at their release times to their destinations no later than their deadlines. The paper aims to optimize sailing routes and speeds for these commodities by trucks and scheduled maritime services while minimizing the total cost and carbon emissions. We propose a bi-objective non-linear programming model, then develop a new algorithm to solve this model by combining the $mathcal{E}$ -constraint method and a fuzzy logic method. A set of Pareto solutions can be obtained by the former, meanwhile optimal solutions according to the preferences of decision makers can be selected by the fuzzy logic method. Finally, analysis based on a case study from road-sea intermodal transportation in China shows the potential benefits. The results of a computational study indicate that the proposed model and method can give optimal sailing routes and speeds for decision makers.
{"title":"Sailing Route and Speed Optimization for Green Intermodal Transportation","authors":"Haitao Ji, Peng Wu","doi":"10.1109/ICITE50838.2020.9231520","DOIUrl":"https://doi.org/10.1109/ICITE50838.2020.9231520","url":null,"abstract":"We study a third party logistics company, who uses highway and maritime transportation to deliver a set of commodities from their origins at their release times to their destinations no later than their deadlines. The paper aims to optimize sailing routes and speeds for these commodities by trucks and scheduled maritime services while minimizing the total cost and carbon emissions. We propose a bi-objective non-linear programming model, then develop a new algorithm to solve this model by combining the $mathcal{E}$ -constraint method and a fuzzy logic method. A set of Pareto solutions can be obtained by the former, meanwhile optimal solutions according to the preferences of decision makers can be selected by the fuzzy logic method. Finally, analysis based on a case study from road-sea intermodal transportation in China shows the potential benefits. The results of a computational study indicate that the proposed model and method can give optimal sailing routes and speeds for decision makers.","PeriodicalId":112371,"journal":{"name":"2020 IEEE 5th International Conference on Intelligent Transportation Engineering (ICITE)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132435136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICITE50838.2020.9231516
Xinchao Zhao, Juan Lu, Hao Sun, Shimin Hu
We provide an approach for solving two-way public transportation scheduling, which mainly uses tabu search algorithm and dynamic programming algorithm for vehicle scheduling. Establish a model with the goal of minimizing the number of vehicles and the number of drivers and fully consider the restrictions of drivers' rest time (dwell time), the maximum task volume of vehicles, whether they are dead heading, whether they are synchronization, etc. On the basis of significant savings in operating costs, improve the driver's work efficiency and ensure the driver's rest time (dwell time), thereby providing a guarantee for safe and efficient vehicle operation. We also applied the method to the lines of zheng zhou bus communication corporation, and the results showed that our plan was effective and efficient.
{"title":"Two-way Vehicle Scheduling Approach in Public Transit Based on Tabu Search and Dynamic Programming Algorithm","authors":"Xinchao Zhao, Juan Lu, Hao Sun, Shimin Hu","doi":"10.1109/ICITE50838.2020.9231516","DOIUrl":"https://doi.org/10.1109/ICITE50838.2020.9231516","url":null,"abstract":"We provide an approach for solving two-way public transportation scheduling, which mainly uses tabu search algorithm and dynamic programming algorithm for vehicle scheduling. Establish a model with the goal of minimizing the number of vehicles and the number of drivers and fully consider the restrictions of drivers' rest time (dwell time), the maximum task volume of vehicles, whether they are dead heading, whether they are synchronization, etc. On the basis of significant savings in operating costs, improve the driver's work efficiency and ensure the driver's rest time (dwell time), thereby providing a guarantee for safe and efficient vehicle operation. We also applied the method to the lines of zheng zhou bus communication corporation, and the results showed that our plan was effective and efficient.","PeriodicalId":112371,"journal":{"name":"2020 IEEE 5th International Conference on Intelligent Transportation Engineering (ICITE)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132529395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICITE50838.2020.9231506
Zhi Yuan, Jingxian Liu, Yi Liu, B. Tu, Yue Li, Yulu Liu, Zongzhi Li
The strategy of ecological priority and green development made the fuel consumption of inland ships have received unprecedented attention. Fuel consumption prediction of inland ships can provide decision support for navigation planning and energy supervision. This paper takes the ships sailing on the Yangtze River trunk line as the research object, first of all, the navigation data is collected by the multi-source sensor. And then, consider the comprehensive influence of status monitoring data and environmental factors, the improved artificial neural network (ANN) is tailored to build the fuel consumption prediction model based on real-time monitoring data and environmental data. Finally, the constructed prediction model is analyzed and verified by a large amount of measurement data, and its performance of fuel consumption prediction is proved by comparing it with the traditional regression models.
{"title":"Prediction Model of Inland Ship Fuel Consumption Considering Influence of Navigation Status and Environmental Factors","authors":"Zhi Yuan, Jingxian Liu, Yi Liu, B. Tu, Yue Li, Yulu Liu, Zongzhi Li","doi":"10.1109/ICITE50838.2020.9231506","DOIUrl":"https://doi.org/10.1109/ICITE50838.2020.9231506","url":null,"abstract":"The strategy of ecological priority and green development made the fuel consumption of inland ships have received unprecedented attention. Fuel consumption prediction of inland ships can provide decision support for navigation planning and energy supervision. This paper takes the ships sailing on the Yangtze River trunk line as the research object, first of all, the navigation data is collected by the multi-source sensor. And then, consider the comprehensive influence of status monitoring data and environmental factors, the improved artificial neural network (ANN) is tailored to build the fuel consumption prediction model based on real-time monitoring data and environmental data. Finally, the constructed prediction model is analyzed and verified by a large amount of measurement data, and its performance of fuel consumption prediction is proved by comparing it with the traditional regression models.","PeriodicalId":112371,"journal":{"name":"2020 IEEE 5th International Conference on Intelligent Transportation Engineering (ICITE)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132581707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICITE50838.2020.9231436
Donghyun Lim, Minhyeok Lee, Junhee Seok
For navigation system, predicting future traffic conditions is crucial. To predict the traffic condition, statistical methods and neural network models have been studied. However, conventional methods have three limitations in which only the temporal properties are used, only narrow sections or time steps are predicted and not general road sections such as all section of highway but specific sections are used as test results. This paper proposes a parallel Convolutional Neural Network (CNN) that uses spatiotemporal properties and predicts for the next five hours and up to 400 km ranges in Korea's representative highway. Using a highway dataset, the proposed parallel CNN is trained and evaluated. As a result, the result of our model is improved by 10.6%, in terms of Root Mean Square Error (RMSE), compared to the conventional method. Moreover, in terms of the average of Average Speed Difference (ASD), the result of our model is improved by 63.5%.
{"title":"Long Term Traffic Prediction in Highway Using Parallel CNN","authors":"Donghyun Lim, Minhyeok Lee, Junhee Seok","doi":"10.1109/ICITE50838.2020.9231436","DOIUrl":"https://doi.org/10.1109/ICITE50838.2020.9231436","url":null,"abstract":"For navigation system, predicting future traffic conditions is crucial. To predict the traffic condition, statistical methods and neural network models have been studied. However, conventional methods have three limitations in which only the temporal properties are used, only narrow sections or time steps are predicted and not general road sections such as all section of highway but specific sections are used as test results. This paper proposes a parallel Convolutional Neural Network (CNN) that uses spatiotemporal properties and predicts for the next five hours and up to 400 km ranges in Korea's representative highway. Using a highway dataset, the proposed parallel CNN is trained and evaluated. As a result, the result of our model is improved by 10.6%, in terms of Root Mean Square Error (RMSE), compared to the conventional method. Moreover, in terms of the average of Average Speed Difference (ASD), the result of our model is improved by 63.5%.","PeriodicalId":112371,"journal":{"name":"2020 IEEE 5th International Conference on Intelligent Transportation Engineering (ICITE)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133160036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICITE50838.2020.9231440
Shuaiyu Zhang, Hui Fu, Changpei Huang
Accurate estimation of bus speed can improve urban mobility by helping passengers plan their trips better. However, it is difficult to estimate bus speed because of the interaction of social vehicles and buses in the road network. In this paper, a vine copula-based approach is proposed to model conditional probability distribution of bus speed by accounting for cars correlation. The marginal distributions of car speed and bus speed of consecutive segments along on arterial road are estimated by fusing multi-resource data. The D-vine copula model is introduced to model the dependent structure of bimodal traffic speed in the adjacent segments between bus stops. Moreover, the conditional probability distribution curves are estimated based on the D-vine copula model. The simulated results illustrate that the proposed D-vine copula model is applicable for revealing complex correlation between buses and cars using the corresponding conditional probability distribution of bus speed.
{"title":"Estimating Bus Speed Distribution of Bimodal Traffic Using Vine Copula","authors":"Shuaiyu Zhang, Hui Fu, Changpei Huang","doi":"10.1109/ICITE50838.2020.9231440","DOIUrl":"https://doi.org/10.1109/ICITE50838.2020.9231440","url":null,"abstract":"Accurate estimation of bus speed can improve urban mobility by helping passengers plan their trips better. However, it is difficult to estimate bus speed because of the interaction of social vehicles and buses in the road network. In this paper, a vine copula-based approach is proposed to model conditional probability distribution of bus speed by accounting for cars correlation. The marginal distributions of car speed and bus speed of consecutive segments along on arterial road are estimated by fusing multi-resource data. The D-vine copula model is introduced to model the dependent structure of bimodal traffic speed in the adjacent segments between bus stops. Moreover, the conditional probability distribution curves are estimated based on the D-vine copula model. The simulated results illustrate that the proposed D-vine copula model is applicable for revealing complex correlation between buses and cars using the corresponding conditional probability distribution of bus speed.","PeriodicalId":112371,"journal":{"name":"2020 IEEE 5th International Conference on Intelligent Transportation Engineering (ICITE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130148815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICITE50838.2020.9231381
Naiyu Wang, M. Shen, Yongcun Wei
Optimization of equipment configuration is a key technology to improve the efficiency of loading and unloading transfer. Aiming at the allocation problem of rail-sea intermodal transportation handling equipment in container terminals, this paper summarizes the factors that affect the rail-sea intermodal transportation handling equipment configuration, and puts forward the principles that should be considered when configuring the equipment. Under the loading and unloading process of “quay crane, truck, rail crane”, the flow of equipment quantity configuration is designed. It provides an important basis for the equipment configuration of the sea-rail intermodal container port.
{"title":"Research on Handling Equipment Allocation of Rail-Sea Intermodal Transportation in Container Terminals","authors":"Naiyu Wang, M. Shen, Yongcun Wei","doi":"10.1109/ICITE50838.2020.9231381","DOIUrl":"https://doi.org/10.1109/ICITE50838.2020.9231381","url":null,"abstract":"Optimization of equipment configuration is a key technology to improve the efficiency of loading and unloading transfer. Aiming at the allocation problem of rail-sea intermodal transportation handling equipment in container terminals, this paper summarizes the factors that affect the rail-sea intermodal transportation handling equipment configuration, and puts forward the principles that should be considered when configuring the equipment. Under the loading and unloading process of “quay crane, truck, rail crane”, the flow of equipment quantity configuration is designed. It provides an important basis for the equipment configuration of the sea-rail intermodal container port.","PeriodicalId":112371,"journal":{"name":"2020 IEEE 5th International Conference on Intelligent Transportation Engineering (ICITE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114313759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICITE50838.2020.9231395
Hao Li, Yifan Tan, Y. Pu
Blind signal processing is an effective feature extraction method for mechanical vibration signals. However due to noise corruption, independent source signals can't always be accurately recovered or separated from the acquired sensor observations. Then feature information extracted from source signals can't naturally represent machine states of the detected mechanical equipment. Generally in blind signal processing, the separating matrix may contain as much information contents as the separated source signals. The separating matrix can directly be processed to extract its singular values as useful feature information by the singular value decomposition (SVD) method. Thus a blind information extraction method was proposed to extract singular values of separating matrix as the desired feature information of the detected machine. The experimental results of gear pump indicate that this method can be applied to feature extraction of mechanical equipment.
{"title":"Blind Information Extraction of Machine Faults Based on Separating Matrix","authors":"Hao Li, Yifan Tan, Y. Pu","doi":"10.1109/ICITE50838.2020.9231395","DOIUrl":"https://doi.org/10.1109/ICITE50838.2020.9231395","url":null,"abstract":"Blind signal processing is an effective feature extraction method for mechanical vibration signals. However due to noise corruption, independent source signals can't always be accurately recovered or separated from the acquired sensor observations. Then feature information extracted from source signals can't naturally represent machine states of the detected mechanical equipment. Generally in blind signal processing, the separating matrix may contain as much information contents as the separated source signals. The separating matrix can directly be processed to extract its singular values as useful feature information by the singular value decomposition (SVD) method. Thus a blind information extraction method was proposed to extract singular values of separating matrix as the desired feature information of the detected machine. The experimental results of gear pump indicate that this method can be applied to feature extraction of mechanical equipment.","PeriodicalId":112371,"journal":{"name":"2020 IEEE 5th International Conference on Intelligent Transportation Engineering (ICITE)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133676320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The FAO system is a new-generation railway signaling system, the comprehensive and accurate testing is the main means to verify the safety and stability of the system, and the design and generation of test cases is an important link of the system testing. Traditionally, test cases are manually generated, which is inefficient, time-consuming and inaccurate. To solve this problem, we proposed an automatic test case generation method for the FAO system specified scenario using the CT-LSSVM algorithm. The CT algorithm was used to realize multi-factor combination to generate test cases, and the LSSVM method was used to predict and analyze the expected results of the test cases. The results showed that when the LSSVM method was used to model and analyze the test cases generated by the CT five-factor combination, the recognition rate of the calibration set was 96.58% and the recognition rate of the test set was 97.73%; At the same time, some test cases of the twelve-factor combination were predicted and analyzed, and the recognition rate reached 98.57%. This proves that the CT-LSSVM method can be applied to the test case generation of the FAO system.
{"title":"A Method of Automatic Test Case Generation Based on CT-LSSVM Algorithm in FAO Systems","authors":"Sha Wang, Qingyuan Shang, Zhujun Ling, Dandan Liu, Xiangxian Chen","doi":"10.1109/ICITE50838.2020.9231435","DOIUrl":"https://doi.org/10.1109/ICITE50838.2020.9231435","url":null,"abstract":"The FAO system is a new-generation railway signaling system, the comprehensive and accurate testing is the main means to verify the safety and stability of the system, and the design and generation of test cases is an important link of the system testing. Traditionally, test cases are manually generated, which is inefficient, time-consuming and inaccurate. To solve this problem, we proposed an automatic test case generation method for the FAO system specified scenario using the CT-LSSVM algorithm. The CT algorithm was used to realize multi-factor combination to generate test cases, and the LSSVM method was used to predict and analyze the expected results of the test cases. The results showed that when the LSSVM method was used to model and analyze the test cases generated by the CT five-factor combination, the recognition rate of the calibration set was 96.58% and the recognition rate of the test set was 97.73%; At the same time, some test cases of the twelve-factor combination were predicted and analyzed, and the recognition rate reached 98.57%. This proves that the CT-LSSVM method can be applied to the test case generation of the FAO system.","PeriodicalId":112371,"journal":{"name":"2020 IEEE 5th International Conference on Intelligent Transportation Engineering (ICITE)","volume":"315 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133795637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICITE50838.2020.9231348
Juan Liu, Danping Zou, Yuchun Chen, Zhongjian Chu
In future, electric vehicle (EV) charging enterprises will change from simple charging service to data service, information service and other modes. This paper analyzes the operating platform data of EV charging facilities from multiple perspectives. From the user's point of view, this paper analyzes the user's mobile terminal, gender and age distribution, consumption ability and payment habits. According to time dimensions of week, quarter and hour, the charging behavior pattern and charging load distribution are mainly explored. From the perspective of operators, this paper studies the load distribution of charging stations, the utilization rate, and income of AC/DC piles in different areas, recharge income, transaction amount and so on. Finally, the user group is depicted, the benefit points of charging operators are summarized, and corresponding suggestions are put forward for charging facility operation, in the hope of improving user experience and stickiness, and exploring a business model that can further create added value.
{"title":"Analysis of Electric Vehicle Charging Facilities Operation Data","authors":"Juan Liu, Danping Zou, Yuchun Chen, Zhongjian Chu","doi":"10.1109/ICITE50838.2020.9231348","DOIUrl":"https://doi.org/10.1109/ICITE50838.2020.9231348","url":null,"abstract":"In future, electric vehicle (EV) charging enterprises will change from simple charging service to data service, information service and other modes. This paper analyzes the operating platform data of EV charging facilities from multiple perspectives. From the user's point of view, this paper analyzes the user's mobile terminal, gender and age distribution, consumption ability and payment habits. According to time dimensions of week, quarter and hour, the charging behavior pattern and charging load distribution are mainly explored. From the perspective of operators, this paper studies the load distribution of charging stations, the utilization rate, and income of AC/DC piles in different areas, recharge income, transaction amount and so on. Finally, the user group is depicted, the benefit points of charging operators are summarized, and corresponding suggestions are put forward for charging facility operation, in the hope of improving user experience and stickiness, and exploring a business model that can further create added value.","PeriodicalId":112371,"journal":{"name":"2020 IEEE 5th International Conference on Intelligent Transportation Engineering (ICITE)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132773711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICITE50838.2020.9231340
Y. Zhang, Hongqi Liu, Jian Wang, Guanyun Wang
Modern roundabouts are widely implemented abroad because of high capacity and well safety performance, whereas there are few studies on related theories of modern roundabouts in China. Only one three-leg modern roundabout with single-lane approaches was deployed in Suichang, Zhejiang Province of China, at present. In this paper, traffic flow were collected by laser velocimeter and digital cameras, and a simulation model was established by the SIDRA, the operations of the three-leg roundabout were analyzed, and the influences of the proportion of left-turning traffic in entering traffic volume on operations have been studied. Retrieve the critical parameters, including minimum headway, following headway and critical gap from the traffic flow data collected on-site, and select average control delay, the 95th percentile queue length and V/C as the assessment indicators. The results indicate that the 95th percentile queue length and delay will increase gently with the increase of traffic volume when the entering traffic volume is less than or equal to 600 veh/h with the proportion of left-turn traffic flow less than 20‰, or it is less than or equal to 500 veh/h with the proportion of left turn less than 20‰, and vice versa. The Level of Service of modern roundabouts can basically reach Level-III when the entering traffic volume is less than or equal to 600 veh/h.
{"title":"The SIDRA Based Analysis on Operations of Three-Leg Modern Roundabout with Single-Lane Approaches","authors":"Y. Zhang, Hongqi Liu, Jian Wang, Guanyun Wang","doi":"10.1109/ICITE50838.2020.9231340","DOIUrl":"https://doi.org/10.1109/ICITE50838.2020.9231340","url":null,"abstract":"Modern roundabouts are widely implemented abroad because of high capacity and well safety performance, whereas there are few studies on related theories of modern roundabouts in China. Only one three-leg modern roundabout with single-lane approaches was deployed in Suichang, Zhejiang Province of China, at present. In this paper, traffic flow were collected by laser velocimeter and digital cameras, and a simulation model was established by the SIDRA, the operations of the three-leg roundabout were analyzed, and the influences of the proportion of left-turning traffic in entering traffic volume on operations have been studied. Retrieve the critical parameters, including minimum headway, following headway and critical gap from the traffic flow data collected on-site, and select average control delay, the 95th percentile queue length and V/C as the assessment indicators. The results indicate that the 95th percentile queue length and delay will increase gently with the increase of traffic volume when the entering traffic volume is less than or equal to 600 veh/h with the proportion of left-turn traffic flow less than 20‰, or it is less than or equal to 500 veh/h with the proportion of left turn less than 20‰, and vice versa. The Level of Service of modern roundabouts can basically reach Level-III when the entering traffic volume is less than or equal to 600 veh/h.","PeriodicalId":112371,"journal":{"name":"2020 IEEE 5th International Conference on Intelligent Transportation Engineering (ICITE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130601853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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