Pub Date : 2018-09-01DOI: 10.1109/ICITE.2018.8492711
Q. Luo, Yufei Hou, Wei Li, Xiongfei Zhang
In order to reduce the impact of normal large passenger flow on rail transit stations, trains and operations, a qualitative and quantitative approach is adopted to analyze the process of propagation and dissipation of large passenger flow on rail transit lines. Based on the timetable of trains and the AFC swiping card data of passengers entering and leaving the station, the connection between passengers and trains in space and time is analyzed. The formation and spread of large passenger flow are analyzed from several aspects: the number of arriving passenger flow, the number of boarding passengers and alighting passengers, retention rate, train capacity and train full load rate, so as to study the mechanism of large passenger flow propagation based on train capacity constraints. Finally, combined with the specific route, it can be concluded that the spread of large passenger flow in time and space is continuous, and the large passenger flow at a single station will affect the travel of passengers at subsequent stations.
{"title":"Study on the Propagation Mechanism of Large Passenger Flow in Urban Rail Transit","authors":"Q. Luo, Yufei Hou, Wei Li, Xiongfei Zhang","doi":"10.1109/ICITE.2018.8492711","DOIUrl":"https://doi.org/10.1109/ICITE.2018.8492711","url":null,"abstract":"In order to reduce the impact of normal large passenger flow on rail transit stations, trains and operations, a qualitative and quantitative approach is adopted to analyze the process of propagation and dissipation of large passenger flow on rail transit lines. Based on the timetable of trains and the AFC swiping card data of passengers entering and leaving the station, the connection between passengers and trains in space and time is analyzed. The formation and spread of large passenger flow are analyzed from several aspects: the number of arriving passenger flow, the number of boarding passengers and alighting passengers, retention rate, train capacity and train full load rate, so as to study the mechanism of large passenger flow propagation based on train capacity constraints. Finally, combined with the specific route, it can be concluded that the spread of large passenger flow in time and space is continuous, and the large passenger flow at a single station will affect the travel of passengers at subsequent stations.","PeriodicalId":336951,"journal":{"name":"2018 3rd IEEE International Conference on Intelligent Transportation Engineering (ICITE)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134410752","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}
In this paper, predictive current controller (PCC) is implemented for controlling voltage source inverter (VSI) for a feedback linearization controlled (FLC) induction motor (IM) drive for better rotor speed and torque dynamics. Two new control inputs are developed using output of Proportional Integral (PI) controllers which regulate the rotor flux and rotor speed. Reference currents are the input to the PCC. The PCC regulates stator current of the IM according to the generated reference signal received. Error between predicted stator currents and reference current generated using control algorithm is minimized using the cost function defined in PCC. The best switching state which gives the minimum value of cost function is selected and applied to the switches of the three-leg VSI without any use of modulation stage and linear regulators. The proposed method is validated using MATLAB/Simulink for different operating points.
{"title":"Predictive Current Control of Feedback Linearized Induction Motor Drive","authors":"Ambrish Devanshu, Madhusudan Sinah, Narendra Kumar","doi":"10.1109/ICITE.2018.8492622","DOIUrl":"https://doi.org/10.1109/ICITE.2018.8492622","url":null,"abstract":"In this paper, predictive current controller (PCC) is implemented for controlling voltage source inverter (VSI) for a feedback linearization controlled (FLC) induction motor (IM) drive for better rotor speed and torque dynamics. Two new control inputs are developed using output of Proportional Integral (PI) controllers which regulate the rotor flux and rotor speed. Reference currents are the input to the PCC. The PCC regulates stator current of the IM according to the generated reference signal received. Error between predicted stator currents and reference current generated using control algorithm is minimized using the cost function defined in PCC. The best switching state which gives the minimum value of cost function is selected and applied to the switches of the three-leg VSI without any use of modulation stage and linear regulators. The proposed method is validated using MATLAB/Simulink for different operating points.","PeriodicalId":336951,"journal":{"name":"2018 3rd IEEE International Conference on Intelligent Transportation Engineering (ICITE)","volume":"16 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114119366","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 : 2018-09-01DOI: 10.1109/ICITE.2018.8492597
Yun Cai, Qiao Jun Xianu, Yan Li, X. Ming
Based on the traffic conflict technique, this paper analyzes the aerial photography video of the highway interchanges, obtains the survey data, and calibrates the parameters of VISSIM and SSAM. Traffic conflict prediction models for single lane ramp and two-lane ramp are established. The negative binomial distribution model is selected as the single-lane ramp collision prediction model, and the Poisson distribution model is selected for the two-lane ramp collision prediction model. The test results show that the model has high accuracy, and MAPE is 8.41 % and 12.0% respectively. The results show the models can provide a basis for the safety assessment of highway merging area and the decrease of traffic accidents.
{"title":"Collision Prediction Model for Interchange Mergring Area Based on Traffic Conflict Technique","authors":"Yun Cai, Qiao Jun Xianu, Yan Li, X. Ming","doi":"10.1109/ICITE.2018.8492597","DOIUrl":"https://doi.org/10.1109/ICITE.2018.8492597","url":null,"abstract":"Based on the traffic conflict technique, this paper analyzes the aerial photography video of the highway interchanges, obtains the survey data, and calibrates the parameters of VISSIM and SSAM. Traffic conflict prediction models for single lane ramp and two-lane ramp are established. The negative binomial distribution model is selected as the single-lane ramp collision prediction model, and the Poisson distribution model is selected for the two-lane ramp collision prediction model. The test results show that the model has high accuracy, and MAPE is 8.41 % and 12.0% respectively. The results show the models can provide a basis for the safety assessment of highway merging area and the decrease of traffic accidents.","PeriodicalId":336951,"journal":{"name":"2018 3rd IEEE International Conference on Intelligent Transportation Engineering (ICITE)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122738158","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 : 2018-09-01DOI: 10.1109/ICITE.2018.8492610
Zhenhua Liu, Yanling Liu, Hao Liu
With the continuous deterioration of the global environment, energy conservation and emission reduction has become a common development strategy of all countries in the world. The control of energy consumption and emission in the field of transportation is an important way to promote the energy saving and emission reduction of the whole society. Monitoring the accurate energy consumption and emission of vehicles is the key premise to realize the energy saving and emission reduction of transportation. At present, it is a technical difficulty to measure the actual fuel consumption of trucks. The traditional method of estimating oil consumption of trucks is of low precision, so an optimized method for dynamic measurement of trucks' oil consumption was put forward in this paper. This method does not need to refit the trucks, but precisely calibrate the oil volume and deeply analyze the collected dynamic data, so as to significantly improve the measurement accuracy of trucks' fuel consumption.
{"title":"A Method for Dynamic Measurement of Trucks' Fuel Consumption","authors":"Zhenhua Liu, Yanling Liu, Hao Liu","doi":"10.1109/ICITE.2018.8492610","DOIUrl":"https://doi.org/10.1109/ICITE.2018.8492610","url":null,"abstract":"With the continuous deterioration of the global environment, energy conservation and emission reduction has become a common development strategy of all countries in the world. The control of energy consumption and emission in the field of transportation is an important way to promote the energy saving and emission reduction of the whole society. Monitoring the accurate energy consumption and emission of vehicles is the key premise to realize the energy saving and emission reduction of transportation. At present, it is a technical difficulty to measure the actual fuel consumption of trucks. The traditional method of estimating oil consumption of trucks is of low precision, so an optimized method for dynamic measurement of trucks' oil consumption was put forward in this paper. This method does not need to refit the trucks, but precisely calibrate the oil volume and deeply analyze the collected dynamic data, so as to significantly improve the measurement accuracy of trucks' fuel consumption.","PeriodicalId":336951,"journal":{"name":"2018 3rd IEEE International Conference on Intelligent Transportation Engineering (ICITE)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127550342","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：