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Learning to detect subway arrivals for passengers on a train

Kuifei Yu, Hengshu Zhu, Huanhuan Cao, Baoxian Zhang, Enhong Chen, Jilei Tian, Jinghai Rao
2014 Frontiers of Computer Science  
However, in a subway environment, such positioning systems are not available for the positioning tasks, such as the detection of the train arrivals for the passengers in the train.  ...  Furthermore, we propose to explore the maximum entropy (MaxEnt) model for training a train arrival detector by learning the correlation between contextual features and train arrivals.  ...  Acknowledgements We thank the anonymous reviewers for their insightful comments and discussions. We would also like to give special thanks to Prof. Hui Xiong for his valuable comments on this work.  ... 
doi:10.1007/s11704-014-3258-8 fatcat:unhfs3jprrettivbuafebyy2yy

Learning to Detect the Subway Station Arrival for Mobile Users [chapter]

Kuifei Yu, Hengshu Zhu, Huanhuan Cao, Baoxian Zhang, Enhong Chen, Jilei Tian, Jinghai Rao
2013 Lecture Notes in Computer Science  
However, for the subway environment, such positioning systems may not be available for the positioning tasks, such as the detection of the train arrivals for the passengers in the train.  ...  Furthermore, we propose to explore the maximum entropy model for training a train arrival detector by learning the correlations between the contextual features and the events of train arrivals.  ...  Learning to Detect Subway Arrivals After contextual feature extraction, the remaining work is to train a detection model M, which can integrate multiple effective contextual features for detecting subway  ... 
doi:10.1007/978-3-642-41278-3_7 fatcat:linuuq4crradrhd4kj7awubszi

Personnel identification and distribution density analysis of subway station based on convolution neural network

Lei Wang, Kun Zhang, Jian Kang, Meng Peng, Jiayu Xu, L. Nguyen
2022 ITM Web of Conferences  
In this paper, a method based on convolution neural network and multi-camera fusion is proposed to improve the recognition accuracy of crowd and then the personnel distribution of subway station platform  ...  In this method, tensorflow is used as the deep learning training framework and the yolov4 neural network algorithm is used to identify the subway station platform area using three videos synchronously.  ...  As the train arrives, the number of recognized passengers tends to increase fast and then decrease slowly within over 120s.  ... 
doi:10.1051/itmconf/20224702036 fatcat:zxyopjjsibhjvbonm2muxwuwva

Smartphone Sensing Meets Transport Data: A Collaborative Framework for Transportation Service Analytics

Yu Lu, Archan Misra, Wen Sun, Huayu Wu
2018 IEEE Transactions on Mobile Computing  
We thus design a practical algorithm, called train arrival detection (TAD), to detect the actual train arrival time using the ticketing card data.  ...  Transportation Data Processing Layer This layer has two objectives (both based on the ticketing card data): (a) the main objective is to detect the subway train arrival events on the platform, while (b  ...  Her research interests cover a wide range of areas including body sensor network, IoT, participatory sensing, and 5G.  ... 
doi:10.1109/tmc.2017.2743176 fatcat:eb3v54t3ynasfgqqydjpy6w2ja

A Deep Learning Model with Conv-LSTM Networks for Subway Passenger Congestion Delay Prediction

Wei Chen, Zongping Li, Can Liu, Yi Ai, Andrea Monteriù
2021 Journal of Advanced Transportation  
In this paper, we use a new method based on deep learning technology to evaluate the congestion delay of subway stations.  ...  When urban rail transit is faced with a large number of commuter passengers during peak periods, passengers are often waiting for the next train because the subway is running at full load, which causes  ...  ., for providing the necessary data. is research was supported by the National Key Research and Development Program of China (2017YFB1200702).  ... 
doi:10.1155/2021/6645214 fatcat:ykctddfwjzclhmionvgwmb6tim

Effectiveness of Physical Barriers Installation for Prevention of Incidents in Mexico City's Subway System

Gerardo de Jesús Portillo-Villasana, Aida Huerta-Barrientos, Yazmin Dillarza Andrade
2017 Journal of Industrial Engineering  
One solution to prevent them is the installation of physical barriers, but their high cost is unattractive for governmental authorities.  ...  lights on subway platforms.  ...  Acknowledgments This study was partially supported by the National Council for Sciences and Technology of Mexico (CONACYT).  ... 
doi:10.1155/2017/8125430 fatcat:mdbk5bkehfddjoruntztzuxdwq

AI-enabled learning techniques for Internet of Things communications

Alireza Souri, Mu-Yen Chen, Alireza Souri, Mu-Yen Chen
2021 Journal of High Speed Networks  
and calculates the behaviour entropy of users to predict the passenger behaviour of subway passengers.  ...  It is proved that the model proposed in this paper can effectively suppress the influence of passenger flow arrival uncertainty, ensure the higher quality of service to passengers, and further improve  ... 
doi:10.3233/jhs-210660 fatcat:5v6s236qezfinn3yz3gfouguia

MetroEye: A Weather-aware System for Real-Time Metro Passenger Flow Prediction

Jianyuan Wang, Biao Leng, Junjie Wu, Heng Du, Zhang Xiong
2020 IEEE Access  
Due to its high practicality, MetroEye has been adopted by Beijing Urban Rail Transit Control Center to monitor the passenger flow status of the Beijing subway system.  ...  The offline system adopts a conditional random field (CRF) model to establish the relationship between passenger flow volume and weather factors.  ...  When a passenger arriving at the destination according to AFC system, delete the passenger immediately. 2) TRAIN THREAD When a train arriving at a station, drop the passenger to get transfer or reach  ... 
doi:10.1109/access.2020.3007538 fatcat:jocubkmyova2fjagns3otu34sm

Subway Sudden Passenger Flow Prediction Method Based on Two Factors: Case Study of the Dongsishitiao Station in Beijing

Chengguang Xie, Xiaofeng Li, Bingfa Chen, Feng Lin, Yushun Lin, Hainan Huang, Eneko Osaba
2021 Journal of Advanced Transportation  
A sudden increase in passenger flow can primitively lead to continuous congestion of a subway network and thus have a profound impact on the subway system.  ...  Sudden passenger flow events from 2014 to 2016 in the Beijing Dongsishitiao Station (DS) were used to train and verify the reliability of the prediction model.  ...  played a significant role in the forecast of the subway sudden arrival passenger flow.  ... 
doi:10.1155/2021/5577179 fatcat:4nuikan4lvdu3j64c2lofkyr7q

A Passenger-Oriented Model for Train Rescheduling on an Urban Rail Transit Line considering Train Capacity Constraint

Wenkai Xu, Peng Zhao, Liqiao Ning
2017 Mathematical Problems in Engineering  
The major objective of this work is to present a train rescheduling model with train capacity constraint from a passenger-oriented standpoint for a subway line.  ...  Based on the abundant automatic fare collection (AFC) system records, the passenger arrival rate and the passenger alighting ratio are introduced to depict the short-term characteristics of passenger flow  ...  [7] introduced a reinforcement learning method including a learning agent for train rescheduling on a single-track railway. The solutions can be obtained within reasonable computational time.  ... 
doi:10.1155/2017/1010745 fatcat:5sdr6ilfxzdmndmo3iuaxmttt4

PULSE: A Real Time System for Crowd Flow Prediction at Metropolitan Subway Stations [chapter]

Ermal Toto, Elke A. Rundensteiner, Yanhua Li, Richard Jordan, Mariya Ishutkina, Kajal Claypool, Jun Luo, Fan Zhang
2016 Lecture Notes in Computer Science  
To take on this new opportunity, we propose a real-time framework, called PULSE (Prediction Framework For Usage Load on Subway SystEms), that offers accurate multi-granular arrival crowd flow prediction  ...  Then, given a future prediction interval, we design novel stream feature selection and model selection algorithms to select the most appropriate machine learning technique for each target station and tune  ...  Prediction models for both PULSE and the baseline methods are trained using a sliding window containing a week of historical data, to predict the arrival traffic of a future interval specified by k.  ... 
doi:10.1007/978-3-319-46131-1_19 fatcat:okz4fdljofeobhjfw6qkxfiyii

Estimation of left behind subway passengers through archived data and video image processing

Charalampos Sipetas, Andronikos Keklikoglou, Eric J. Gonzales
2020 Transportation Research Part C: Emerging Technologies  
This paper combines existing data sources with an emerging technology for object detection to estimate the number of passengers that are left behind on subway platforms.  ...  Crowding is one of the most common problems for public transportation systems worldwide, and extreme crowding can lead to passengers being left behind when they are unable to board the first arriving bus  ...  Through this program, applied research is conducted on topics of importance to the Commonwealth of Massachusetts transportation agencies.  ... 
doi:10.1016/j.trc.2020.102727 pmid:32834685 pmcid:PMC7391996 fatcat:m3n3pfytk5ak7eb2dm3dzr75j4

Feeder

Desheng Zhang, Juanjuan Zhao, Fan Zhang, Ruobing Jiang, Tian He
2015 Proceedings of the 14th International Conference on Information Processing in Sensor Networks - IPSN '15  
In this paper, we propose a transit service Feeder to tackle the last-mile problem, i.e., passengers' destinations lay beyond a walking distance from a public transit station.  ...  ., minibus) to deliver passengers from existing transit stations to selected stops closer to their destinations.  ...  Ling Yin in SIAT for the data support. This work was supported in part by US NSF Grant CNS-0845994, CNS-1239226, NSFC Grant U1401258, and China 973 Program 2015CB352400.  ... 
doi:10.1145/2737095.2737121 dblp:conf/ipsn/ZhangZZJH15 fatcat:xrtojfaq6zdwdo4zrxgwxozpi4

Dynamic Robustness Analysis for Subway Network with Spatiotemporal Characteristic of Passenger Flow

Yi Fan, Fan Zhang, Shihong Jiang, Chao Gao, Zhanwei Du, Zhen Wang, Xianghua Li
2020 IEEE Access  
In this paper, we address the above problem as follows: (1) we propose a temporal subway network (TSN) to consider the dynamics of passenger flow in SN; (2) we adopt the linear threshold (LT) model to  ...  Based on the Shanghai subway smart card data, we carry out extensive experiments to analyze the effects of the cascading failure on the Shanghai SN robustness.  ...  Generally, when passengers enter the automatic fare gate, it takes a while for them to walk to the platform and wait until the train arrives [42] , [43] .  ... 
doi:10.1109/access.2020.2978279 fatcat:4knosjb3dnb4tawaswa5etfapu

Implementation of Automatic Metro Train Shuttle Between Two Station's

Shashank Shukla, Kajal Mesharam, Akshay Junghare, Ayush Raj, J. Shelke
2020 Zenodo  
It is equipped with a passenger counting section, which count the number of passengers leaving and entering the train.  ...  In case of undergoing metro transportation we use LIFI communication to pass the message to next station when any obstacle or crack is detected on track to prevent from being happening of any casualties  ...  It is equipped with a passenger counting section, which count the number of passengers leaving and entering the train.  ... 
doi:10.5281/zenodo.3713266 fatcat:v7wzskt5m5fkfp4b6pthm36ozm
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