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Completion and Augmentation based Spatiotemporal Deep Learning Approach for Short-Term Metro Origin-Destination Matrix Prediction under Limited Observable Data [article]

Jiexia Ye, Juanjuan Zhao, Furong Zheng, Chengzhong Xu
2022 arXiv   pre-print
Accurate prediction of short-term origin-destination (OD) matrix is crucial for operations in metro systems.  ...  This paper designs a deep learning approach for metro OD matrix prediction by addressing the recent destination distribution availability, augmenting the flow presentation for each station, and digging  ...  Definition 5 (OD Matrix ). The OD Matrix of a metro system at time slot t is composed of DVectors of all origin stations at t, denoted as Problem Formulation.  ... 
arXiv:2108.03900v7 fatcat:hwm2z4qa65djxn3wd6uokdxeve

Rail transit OD‐matrix completion via manifold regularized tensor factorisation

Hanxuan Dong, Fan Ding, Huachun Tan, Yuankai Wu, Qin Li, Bin Ran
2021 IET Intelligent Transport Systems  
Tensor completion is a state-of-the-art method for missing data imputation. In this paper, a novel tensor completion method for OD-matrix completion is proposed.  ...  The proposed model is applied to a case study of the metro line in Xi'an, China. The experimental results indicate that the proposed method outperforms baselines.  ...  or traffic flow data estimation [9] .  ... 
doi:10.1049/itr2.12099 fatcat:t4njrug4nrcv3jdiy7xzkaykm4

Short-term origin-destination demand prediction in urban rail transit systems: A channel-wise attentive split-convolutional neural network method [article]

Jinlei Zhang, Hongshu Che, Feng Chen, Wei Ma, Zhengbing He
2021 arXiv   pre-print
Short-term origin-destination (OD) flow prediction in urban rail transit (URT) plays a crucial role in smart and real-time URT operation and management.  ...  There is a great need to develop novel OD flow forecasting method that explicitly considers the unique characteristics of the URT system.  ...  XI, J., FEI-FAN, J. & JIA-PING, F. (2018), "An Online Estimation Method for Passenger Flow OD of Urban Rail Transit Network by Using AFC Data", Journal of Transportation Systems Engineering and  ... 
arXiv:2008.08036v2 fatcat:udyuttbgkncujo6yp6jmticzn4

Using Smart Card Data Trimmed by Train Schedule to Analyze Metro Passenger Route Choice with Synchronous Clustering

Wei Li, Qin Luo, Qing Cai, Xiongfei Zhang
2018 Journal of Advanced Transportation  
Smart card data (Automatic Fare Collection (AFC) data in metro system) including inbound and outbound swiping time are useful for analysis of the characteristics of passengers' route choices in metro while  ...  Finally, a case study was conducted to illustrate the effectiveness of the proposed algorithm. Results showed the proposed algorithm works well to analyze metro passenger route choice.  ...  Chan [11] put forward two research ideas based on London metro transit Oyster card data: one was to estimate the OD traffic matrix and the other was to build the metro transit service reliability matrix  ... 
doi:10.1155/2018/2710608 fatcat:qq4tpq3hdbgtzkohj6fz6rf3hi

Multi-Graph Convolutional-Recurrent Neural Network (MGC-RNN) for Short-Term Forecasting of Transit Passenger Flow [article]

Yuxin He, Lishuai Li, Xinting Zhu, Kwok Leung Tsui
2022 arXiv   pre-print
In general, the proposed framework could provide multiple views of passenger flow dynamics for fine prediction and exhibit a possibility for multi-source heterogeneous data fusion in the spatiotemporal  ...  The proposed method is applied to the short-term forecasts of passenger flow in Shenzhen Metro, China.  ...  Section III provides the relevant notations and formulates the short-term OD matrix forecasting problem, and describes the methodology for short-term forecasting of passenger flow in urban rail transit  ... 
arXiv:2107.13226v2 fatcat:bvovft5nerdrzengnfawntwz6a

A Hybrid Method for Predicting Traffic Congestion during Peak Hours in the Subway System of Shenzhen

Zhenwei Luo, Yu Zhang, Lin Li, Biao He, Chengming Li, Haihong Zhu, Wei Wang, Shen Ying, Yuliang Xi
2019 Sensors  
dynamic traffic simulation model to estimate recurrent congestion in this subway system.  ...  An origin-destination (OD) matrix derived from the data is used as an input in this method of predicting traffic, and the traffic congestion is presented in simulations.  ...  The research results show that it's reasonable and effective for predicting congestion in a subway system during peak hours by the hybrid method to estimate recurrent congestion in this subway system.  ... 
doi:10.3390/s20010150 pmid:31881726 pmcid:PMC6982792 fatcat:f5yig3yjfjhwzbyn77uipxtezm

Passenger Network Ridership Model Through a BRT System, the case of TransMilenio in Bogotá [article]

Arturo Argüelles, Juan D. Garcia-Arteaga, Gabriel Villalobos
2021 arXiv   pre-print
This model is implemented in the case of the Troncal component of TransMilenio, the BRT system that is the backbone of public transport in Bogot\'a.  ...  We present a ridership model of individual trajectories of users within a public transport network for which there are several different routes between origin and destiny and for which the automatic fare  ...  Data- driven model for passenger route choice in urban metro network. Physica A: Statistical Mechanics and its Applications, 524:787–798, 2019.  ... 
arXiv:2112.04009v1 fatcat:63pux4nz2bg25ngg22hftyetfi

Multi-station coordinated and dynamic passenger inflow control for a metro line

Jianjun Wu, Xingrong Wang, Xin Yang, Xin Guo, Haodong Yin, Huijun Sun
2019 IET Intelligent Transport Systems  
To address this problem, a coordinated and dynamic inflow control method is proposed to generate an optimal demand-driven control pattern in metro systems.  ...  Passenger inflow control is an efficient way to relieve peak passenger flow and reduce security risks in metro networks.  ...  Acknowledgments This work was supported by the 'Fundamental Research Funds for the Central Universities' (2019JBZ108).  ... 
doi:10.1049/iet-its.2019.0337 fatcat:v6yfy3ezije4ranscxkjq3uvru

Agent-based optimizing match between passenger demand and service supply for urban rail transit network with NetLogo

Jiamin Zhang
2021 IEEE Access  
To make the passenger demand more closely matched with service supply in urban rail transit network system at the reasonable travel cost and operational cost, the calculation formula for matching degree  ...  Both passenger demand and service supply are among the most important factors that determine the performance of urban rail transit system.  ...  In future research for real application, we will set free assumption 2 and apply the proposed matching methods to the asymmetric passenger OD flow demand (e.g., big data of passenger flow) situation for  ... 
doi:10.1109/access.2021.3060816 fatcat:mh32whvuf5cgxpf22xi2pn5emq

Assignment-based Path Choice Estimation for Metro Systems Using Smart Card Data [article]

Baichuan Mo, Zhenliang Ma, Haris N. Koutsopoulos, Jinhua Zhao
2020 arXiv   pre-print
The synthetic data test validates the model's effectiveness in estimating path choice parameters, which can outperform the purely simulation-based optimization methods in both accuracy and efficiency.  ...  The model is validated using both synthetic data and real-world AFC data in Hong Kong Mass Transit Railway (MTR) system.  ...  The authors confirm contribution to the paper as follows: study conception and design: Acknowledgements The authors would like to thank Hong Kong Mass Transit Railway (MTR) for their support and data  ... 
arXiv:2001.03196v2 fatcat:k2w77ss6e5bkvh25x5rttzn6lm

Scanning the Issue

Azim Eskandarian
2020 IEEE transactions on intelligent transportation systems (Print)  
The datasets repository is available at: Deep Learning for Intelligent Transportation Systems: A Survey of Emerging Trends M. Veres and M.  ...  As the development of both robust methods and novel metrics depends on having access to large-scale driving datasets, a comprehensive and comparative study of 54 publicly available datasets for autonomous  ...  Rather than using traditional origindestination (OD) matrix which may lead to loss of geographical information, the authors propose a new data structure, called OD tensor to represent OD flows, and a manipulation  ... 
doi:10.1109/tits.2020.3008809 fatcat:etol5qoilvdnbj6gtjxk3gheaa

Public Transport Occupancy Estimation using WLAN Probing and Mathematical Modeling

Túlio Vieira, Paulo Almeida, Magali Meireles, Renato Ribeiro
2020 Transportation Research Procedia  
Common ways to achieve quality in public transportation systems are to estimate the public transport occupancy (PTO) rate and the origin-destination matrix for a given area.  ...  Common ways to achieve quality in public transportation systems are to estimate the public transport occupancy (PTO) rate and the origin-destination matrix for a given area.  ...  Acknowledgements The authors would like to thank CEFET-MG for the infrastructure used by this project and also CAPES, CNPq and FAPEMIG for the financial support.  ... 
doi:10.1016/j.trpro.2020.08.122 fatcat:vqo6gj76enfzzkyvpiypjdpeue

Optimal congestion control strategies for near-capacity urban metros: informing intervention via fundamental diagrams [article]

Anupriya, Daniel J. Graham, Prateek Bansal, Daniel Hörcher, Richard Anderson
2022 arXiv   pre-print
Congestion; operational delays due to a vicious circle of passenger-congestion and train-queuing; is an escalating problem for metro systems because it has negative consequences from passenger discomfort  ...  The availability of large-scale smartcard and train movement data from day-to-day operations facilitates the development of models that can inform such strategies in a data-driven way.  ...  Their model uses demand data (OD matrix) and train timetable to derive flows and capacity of each section.  ... 
arXiv:2011.12487v2 fatcat:k5sncuizhrh6vo2npo6y2vs7hq

On how to incorporate public sources of situational context in descriptive and predictive models of traffic data

Sofia Cerqueira, Elisabete Arsenio, Rui Henriques
2021 European Transport Research Review  
Background European cities are placing a larger emphasis on urban data consolidation and analysis for optimizing public transport in response to changing urban mobility dynamics.  ...  Methodology We propose a methodology anchored in data science methods to integrate situational context in the descriptive and predictive models of traffic data, with a focus on the three following major  ...  Acknowledgements The authors thank the support of CARRIS, METRO and Câmara Municipal de Lisboa) (particularly, Gabinete de Mobilidade and Centro de Operações Integrado) for the data provision and valuable  ... 
doi:10.1186/s12544-021-00519-w fatcat:u3y4vk33orbsjeualot2kqawjm

Towards Better Bus Networks: A Visual Analytics Approach [article]

Di Weng, Chengbo Zheng, Zikun Deng, Mingze Ma, Jie Bao, Yu Zheng, Mingliang Xu, Yingcai Wu
2020 arXiv   pre-print
The proposed system is evaluated with two usage scenarios based on real-world data and received positive feedback from the experts.  ...  For challenge c, we incorporate a conflict resolution strategy in the progressive decision-making process to assist users in evaluating the alternative routes and finding the most optimal one.  ...  ACKNOWLEDGMENTS The work was supported by NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization (U1609217), National Key R&D Program of China (2018YFB1004300), NSFC (61761136020  ... 
arXiv:2008.10915v2 fatcat:j6h7dcod7napxfwmokgmgg2baa
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