KMS Of Academy of mathematics and systems sciences, CAS
| Statistical estimation in passenger-to-train assignment models based on automated data | |
| Xiong, Shifeng1; Li, Chunya2; Sun, Xuan3; Qin, Yong4; Wu, Chien-Fu Jeff5 | |
| 2021-12-23 | |
| Source Publication | APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY
 |
| ISSN | 1524-1904 |
| Pages | 21 |
| Abstract | With the rapid development of metro systems, it has become increasingly important to study phenomena such as passenger flow distribution and passenger boarding behavior. It is difficult for existing methods to accurately describe actual situations and to extend to the whole metro system due to the limitations from parameter uncertainties in their mathematical models. In this article, we propose a passenger-to-train assignment model to evaluate the probabilities of individual passengers boarding each feasible train for both no-transfer and one-transfer situations. This model can be used to understand passenger flows and crowdedness. The input parameters of the model include the probabilities that the passengers take each train and the probability distribution of egress time, which is the time to walk to the tap-out fare gate after alighting from the train. We present the likelihood method to estimate these parameters based on data from the automatic fare collection and automatic vehicle location systems. This method can construct several nonparametric density estimates without assuming the parametric form of the distribution of egress time. The EM algorithm is used to compute the maximum likelihood estimates. Simulation results indicate that the proposed estimates perform well. By applying our method to real data in Beijing metro system, we can identify different passenger flow patterns between peak and off-peak hours. |
| Keyword | EM algorithm Gaussian process interpolation nonparametric density estimation passenger flow spline |
| DOI | 10.1002/asmb.2660 |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | High-level Talents Training Program of Ministry of Transportation of China[I18I00010] ; National Natural Science Foundation of China[12171462] ; National Natural Science Foundation of China[11871033] ; Foundation Sciences of Beijing Jiaotong University[2020YJS206] ; NSF[1914632l] |
| WOS Research Area | Operations Research & Management Science ; Mathematics |
| WOS Subject | Operations Research & Management Science ; Mathematics, Interdisciplinary Applications ; Statistics & Probability |
| WOS ID | WOS:000733650700001 |
| Publisher | WILEY |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.amss.ac.cn/handle/2S8OKBNM/59740 |
| Collection | 中国科学院数学与系统科学研究院 |
| Corresponding Author | Qin, Yong; Wu, Chien-Fu Jeff |
| Affiliation | 1.Chinese Acad Sci, Acad Math & Syst Sci, INCMIS, KLSC, Beijing, Peoples R China 2.Shanghai Univ Engn Sci, Sch Math Phys & Stat, Shanghai, Peoples R China 3.Beijing Jiaotong Univ, Sch Traff & Transportat, Beijing, Peoples R China 4.Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing 100044, Peoples R China 5.Georgia Inst Technol, H Milton Stewart Sch Ind & Syst Engn, Atlanta, GA 30332 USA |
| Recommended Citation GB/T 7714 | Xiong, Shifeng,Li, Chunya,Sun, Xuan,et al. Statistical estimation in passenger-to-train assignment models based on automated data[J]. APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY,2021:21. |
| APA | Xiong, Shifeng,Li, Chunya,Sun, Xuan,Qin, Yong,&Wu, Chien-Fu Jeff.(2021).Statistical estimation in passenger-to-train assignment models based on automated data.APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY,21. |
| MLA | Xiong, Shifeng,et al."Statistical estimation in passenger-to-train assignment models based on automated data".APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY (2021):21. |
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