{"title":"Oversaturated traffic signal optimization based on active control","authors":"Xiao Meng, Shaohu Tang, Xiaoming Liu, Liang Zhang","doi":"10.1109/ICITE.2016.7581314","DOIUrl":"https://doi.org/10.1109/ICITE.2016.7581314","url":null,"abstract":"In order to solve the decrease of traffic efficiency of road network, which is caused by overlarge traffic demand of urban regions at peak time, and resource waste of roads due to the heterogeneity of traffic distribution in regions, this paper proposes an active control model for oversaturated area based on border demand control and internal balance control of regional network, builds the bi-level programming optimization of objective function for boundary and internal signal control. The simulation results verify the validity of this method.","PeriodicalId":352958,"journal":{"name":"2016 IEEE International Conference on Intelligent Transportation Engineering (ICITE)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123554334","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}
Zhiying He, Jianling Huang, Yong Du, Bo Wang, Haitao Yu
{"title":"The prediction of passenger flow distribution for urban rail transit based on multi-factor model","authors":"Zhiying He, Jianling Huang, Yong Du, Bo Wang, Haitao Yu","doi":"10.1109/ICITE.2016.7581320","DOIUrl":"https://doi.org/10.1109/ICITE.2016.7581320","url":null,"abstract":"The lack of the historical data of new rail line makes the passenger flow distribution prediction be a challenge. Traditional methods always use simple factors, which can not reflect the complexity of OD distribution. This paper proposes a novel passenger flow distribution prediction method based on multi-factor model. This method obtains quantitative impact factors of OD distribution by analyzing the historical data of existing stations, and then constructs the multi-factor model. The model considers the influence of the nature of the station, as well as the impact of rail network structure, which makes it more precision. Validation experiment results show that the model is reasonable.","PeriodicalId":352958,"journal":{"name":"2016 IEEE International Conference on Intelligent Transportation Engineering (ICITE)","volume":"353 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132305010","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}
{"title":"Motion trajectory generation using updating final-state control","authors":"S. Hara, Masaki Tsukamoto, T. Maeda","doi":"10.1109/ICITE.2016.7581303","DOIUrl":"https://doi.org/10.1109/ICITE.2016.7581303","url":null,"abstract":"Manual motion control (MMC) problems are seen in the conveyance of a large amount of products in factories and stores. One of the most successful examples of MMC is power assist. The power-assisted systems have been introduced to reduce workers' loads in industrial production. In near future, in order to improve its efficiency, the power-assisted systems should include automatic operational modes. This paper discusses an obstacle collision avoidance control system design method for such an automatic operation. Concretely, an existing cart is applied as a controlled object example and it is assumed that the cart moves automatically using the cart's actuator and stops by itself in front of obstacles without any collision. Then, this study applies an improvement of the final-state control (FSC), the updating final-state control (UFSC) to the automatic operation for the obstacle collision avoidance. By using UFSC, the automatic operated cart can decelerate gradually. The responses of the proposed control system are verified by comparing with a model predictive control (MPC) by simulations and an experimental example.","PeriodicalId":352958,"journal":{"name":"2016 IEEE International Conference on Intelligent Transportation Engineering (ICITE)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116696222","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}