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Journal articles on the topic 'Passengers Flow Estimation'

Author: Grafiati

Published: 28 September 2024

Last updated: 31 July 2025

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1

Yang, Taoyuan, Peng Zhao, and Xiangming Yao. "A Method to Estimate URT Passenger Spatial-Temporal Trajectory with Smart Card Data and Train Schedules." Sustainability 12, no. 6 (2020): 2574. http://dx.doi.org/10.3390/su12062574.

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Precise estimation of passenger spatial-temporal trajectory is the basis for urban rail transit (URT) passenger flow assignment and ticket fare clearing. Inspired by the correlation between passenger tap-in/out time and train schedules, we present a method to estimate URT passenger spatial-temporal trajectory. First, we classify passengers into four types according to the number of their routes and transfers. Subsequently, based on the characteristic that passengers tap-out in batches at each station, the K-means algorithm is used to assign passengers to trains. Then, we acquire passenger acce

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2

Xie, Mei-Quan, Xia-Miao Li, Wen-Liang Zhou, and Yan-Bing Fu. "Forecasting the Short-Term Passenger Flow on High-Speed Railway with Neural Networks." Computational Intelligence and Neuroscience 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/375487.

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Short-term passenger flow forecasting is an important component of transportation systems. The forecasting result can be applied to support transportation system operation and management such as operation planning and revenue management. In this paper, a divide-and-conquer method based on neural network and origin-destination (OD) matrix estimation is developed to forecast the short-term passenger flow in high-speed railway system. There are three steps in the forecasting method. Firstly, the numbers of passengers who arrive at each station or depart from each station are obtained from histori

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3

Yang, Yuedi, Jun Liu, Pan Shang, Xinyue Xu, and Xuchao Chen. "Dynamic Origin-Destination Matrix Estimation Based on Urban Rail Transit AFC Data: Deep Optimization Framework with Forward Passing and Backpropagation Techniques." Journal of Advanced Transportation 2020 (December 7, 2020): 1–16. http://dx.doi.org/10.1155/2020/8846715.

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At present, the existing dynamic OD estimation methods in an urban rail transit network still need to be improved in the factors of the time-dependent characteristics of the system and the estimation accuracy of the results. This study focuses on predicting the dynamic OD demand for a time of period in the future for an urban rail transit system. We propose a nonlinear programming model to predict the dynamic OD matrix based on historic automatic fare collection (AFC) data. This model assigns the passenger flow to the hierarchical flow network, which can be calibrated by backpropagation of the

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Su, Guanghui, Bingfeng Si, Kun Zhi, and He Li. "A Calculation Method of Passenger Flow Distribution in Large-Scale Subway Network Based on Passenger–Train Matching Probability." Entropy 24, no. 8 (2022): 1026. http://dx.doi.org/10.3390/e24081026.

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The ever-increasing travel demand has brought great challenges to the organization, operation, and management of the subway system. An accurate estimation of passenger flow distribution can help subway operators design corresponding operation plans and strategies scientifically. Although some literature has studied the problem of passenger flow distribution by analyzing the passengers’ path choice behaviors based on AFC (automated fare collection) data, few studies focus on the passenger flow distribution while considering the passenger–train matching probability, which is the key problem of p

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Teknomo, Kardi. "Axiomatization of Transit Flow Estimation." Civil Engineering Dimension 27, no. 1 (2025): 95–112. https://doi.org/10.9744/ced.27.1.95-112.

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Transit flows between stations are typically estimated indirectly using fare collecting data rather than through direct measurement. Traditional methods approximate transit flows by adapting Origin-Destination (OD) trip estimation techniques. However, these approaches have two significant limitations. First, transit link flows represent the number of passengers remaining within the transit vehicles between stations, while OD flows specifically represent passengers entering at one station and exiting at another station. Second, traditional methods rely on the assumption that a cost function is

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Nagasaki, Yusaku, Masashi Asuka, and Kiyotoshi Komaya. "A Fast Estimation Method of Railway Passengers' Flow." IEEJ Transactions on Electronics, Information and Systems 126, no. 11 (2006): 1406–13. http://dx.doi.org/10.1541/ieejeiss.126.1406.

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Xu, Junming, Zhenxing Pan, Cheng Zhang, and Xiaoguang Yang. "Leveraging Bluetooth and GPS Sensors for Route-Level Passenger Origin–Destination Flow Estimation." Sensors 25, no. 8 (2025): 2351. https://doi.org/10.3390/s25082351.

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Accurate estimation of passenger origin–destination (OD) matrices is critical for optimizing public transportation systems, yet conventional methods face challenges, such as incomplete alighting data, high infrastructure costs, and privacy concerns. With existing GPS sensors and the additional deployment of a single low-cost Bluetooth sensor (10–20 US dollars) per bus, the proposed method can derive passenger OD flow without requiring passengers to tap in or tap out. The GPS sensor updates the bus locations, and the Bluetooth sensor receives signals from surrounding devices, including those on

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Li, Wei, and Qin Luo. "A data-driven estimation method for potential passenger demand of last trains in metro based on external traffic data." Advances in Mechanical Engineering 11, no. 12 (2019): 168781401989835. http://dx.doi.org/10.1177/1687814019898357.

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The last train problem for metro is especially important because the last trains are the last chances for many passengers to travel by metro; otherwise, they have to choose other traffic modes like taxis or buses. Among the problems, the passenger demand is a vital input condition for the optimization of last train transfers. This study proposes a data-driven estimation method for the potential passenger demand of last trains. Through the geographic information, external traffic data including taxi and bus are first analyzed separately to match the origin–destination passenger flow during the

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9

Su, Guanghui, Bingfeng Si, Fang Zhao, and He Li. "Data-Driven Method for Passenger Path Choice Inference in Congested Subway Network." Complexity 2022 (February 28, 2022): 1–13. http://dx.doi.org/10.1155/2022/5451017.

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In a congested large-scale subway network, the distribution of passenger flow in space-time dimension is very complex. Accurate estimation of passenger path choice is very important to understand the passenger flow distribution and even improve the operation service level. The availability of automated fare collection (AFC) data, timetable, and network topology data opens up a new opportunity to study this topic based on multisource data. A probability model is proposed in this study to calculate the individual passenger’s path choice with multisource data, in which the impact of the network t

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Asmael, N. M., and Sh F. Balket. "Demand Estimation of Proposed Bus Rapid Route in Al Kut City." IOP Conference Series: Earth and Environmental Science 961, no. 1 (2022): 012026. http://dx.doi.org/10.1088/1755-1315/961/1/012026.

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Abstract Public transit in the city of Al-Kut faces great challenges due to the weakness of the local government abilities in providing adequate conditions for public transport such as wide vehicles, comfortable seats, and other environmentally friendly means of transport that are almost non-use in the city of Kut, where the dependence is heavily on Mini Bus (Kia) and a medium-sized bus, most of which are old, do not operate in an integrated way, compete with each other for the passengers, reduce the flexibility of movement. This study attempts to estimate the demand for the proposed bus rapid

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Cai, Chang-jun, En-jian Yao, Sha-sha Liu, Yong-sheng Zhang, and Jun Liu. "Holiday Destination Choice Behavior Analysis Based on AFC Data of Urban Rail Transit." Discrete Dynamics in Nature and Society 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/136010.

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For urban rail transit, the spatial distribution of passenger flow in holiday usually differs from weekdays. Holiday destination choice behavior analysis is the key to analyze passengers’ destination choice preference and then obtain the OD (origin-destination) distribution of passenger flow. This paper aims to propose a holiday destination choice model based on AFC (automatic fare collection) data of urban rail transit system, which is highly expected to provide theoretic support to holiday travel demand analysis for urban rail transit. First, based on Guangzhou Metro AFC data collected on Ne

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12

Han, Baoming, Weiteng Zhou, Dewei Li, and Haodong Yin. "Dynamic Schedule-Based Assignment Model for Urban Rail Transit Network with Capacity Constraints." Scientific World Journal 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/940815.

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There is a great need for estimation of passenger flow temporal and spatial distribution in urban rail transit network. The literature review indicates that passenger flow assignment models considering capacity constraints with overload delay factor for in-vehicle crowding are limited in schedule-based network. This paper proposes a stochastic user equilibrium model for solving the assignment problem in a schedule-based rail transit network with considering capacity constraint. As splitting the origin-destination demands into the developed schedule expanded network with time-space paths, the m

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13

Shang, Bin, and Xiao Ning Zhang. "Passengers Flow Forecasting Model of Urban Rail Transit Based on the Macro-Factors." Advanced Engineering Forum 6-7 (September 2012): 688–93. http://dx.doi.org/10.4028/www.scientific.net/aef.6-7.688.

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In China, many cities are planning urban rail transit system, but a comprehensive passenger flow estimation model is still lacking. The total passenger flow of urban rail transit in a city depends on many factors, such as urban population, total length of rail lines, gross domestic production of the city etc. To estimate the total passenger flow of urban rail transit, a linear regression model with multiple variables is established in the paper, based on the real data collected in many cities with urban rail transit operating. The comparison of the estimated flow and the real flow in many citi

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Chen, Ting-Zhao, Yan-Yan Chen, and Jian-Hui Lai. "Estimating Bus Cross-Sectional Flow Based on Machine Learning Algorithm Combined with Wi-Fi Probe Technology." Sensors 21, no. 3 (2021): 844. http://dx.doi.org/10.3390/s21030844.

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With expansion of city scale, the issue of public transport systems will become prominent. For single-swipe buses, the traditional method of obtaining section passenger flow is to rely on surveillance video identification or manual investigation. This paper adopts a new method: collecting wireless signals from mobile terminals inside and outside the bus by installing six Wi-Fi probes in the bus, and use machine learning algorithms to estimate passenger flow of the bus. Five features of signals were selected, and then the three machine learning algorithms of Random Forest, K-Nearest Neighbor, a

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Pavlyuk, Dmitry, Nadežda Spiridovska, and Irina Yatskiv (Jackiva). "SPATIOTEMPORAL DYNAMICS OF PUBLIC TRANSPORT DEMAND: A CASE STUDY OF RIGA." Transport 35, no. 6 (2021): 576–87. http://dx.doi.org/10.3846/transport.2020.14159.

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Sustainable urban mobility remains an emerging research topic during last decades. In recent years, the smart card data collection systems have become widespread and many studies have been focused on usage of anonymized data from these systems for better understanding of mobility patterns of Public Transport (PT) passengers. Data-driven mobility patterns can benefit transport planners at strategic, tactical, and operational levels. A particular point of interest is a spatiotemporal dynamics of mobility patterns that highlights transformation of the PT passenger flows over the time continuously

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Zhang, Jun, Jiaze Liu, and Zhizhong Wang. "Convolutional Neural Network for Crowd Counting on Metro Platforms." Symmetry 13, no. 4 (2021): 703. http://dx.doi.org/10.3390/sym13040703.

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Owing to the increased use of urban rail transit, the flow of passengers on metro platforms tends to increase sharply during peak periods. Monitoring passenger flow in such areas is important for security-related reasons. In this paper, in order to solve the problem of metro platform passenger flow detection, we propose a CNN (convolutional neural network)-based network called the MP (metro platform)-CNN to accurately count people on metro platforms. The proposed method is composed of three major components: a group of convolutional neural networks is used on the front end to extract image fea

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17

Hu, Xing Hua, and Yu Zhang. "The Application of Fluid Analogy Method for Estimating Transit Route ODs Using IC Card On-Off Passenger Data." Applied Mechanics and Materials 694 (November 2014): 73–79. http://dx.doi.org/10.4028/www.scientific.net/amm.694.73.

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Transit route ODs are important reference data for transit network planning and operation management. However, it has the difficulties in data collection, and is of high expense and survey error by means of manual investigation method. It is easy to collect the passenger boarding-alighting counts. The method of fluid analogy method (FAM) is presented for transit passenger OD estimation. It uses the concept of pipe flow, transit route and passengers are regarded as the pipe and fluid, generate bus route OD matrix based upon passenger boarding and alighting counts. The accuracy of route OD estim

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18

Zhou, Feng, Jun-gang Shi, and Rui-hua Xu. "Estimation Method of Path-Selecting Proportion for Urban Rail Transit Based on AFC Data." Mathematical Problems in Engineering 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/350397.

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With the successful application of automatic fare collection (AFC) system in urban rail transit (URT), the information of passengers’ travel time is recorded, which provides the possibility to analyze passengers’ path-selecting by AFC data. In this paper, the distribution characteristics of the components of travel time were analyzed, and an estimation method of path-selecting proportion was proposed. This method made use of single path ODs’ travel time data from AFC system to estimate the distribution parameters of the components of travel time, mainly including entry walking time (ewt), exit

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19

Conchillo, Ángela, Miguel Ángel Recarte, Luis Nunes, and Trinidad Ruiz. "Comparing Speed Estimations from a Moving Vehicle in Different Traffic Scenarios: Absence versus Presence of Traffic Flow." Spanish Journal of Psychology 9, no. 1 (2006): 32–37. http://dx.doi.org/10.1017/s1138741600005941.

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The aim of this research was to study the performance in a speed estimation task of a passenger travelling in a real car in different scenarios: a closed track used in previous experimental studies was compared with interurban traffic environment involving a secondary road and a highway. At the same time, the effect of sex and driving experience on speed estimation was analyzed. Thirty-six participants (18 male and 18 female, half of each group being drivers and half non-drivers) estimated the speed of the car in which they travelled as passengers. The actual speed values varied in the range o

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20

Ma, Xiaoyu, Wei Xi, Zuhao Chen, Han Hao, and Jizhong Zhao. "ECC: Passenger Counting in the Elevator Using Commodity WiFi." Applied Sciences 12, no. 14 (2022): 7321. http://dx.doi.org/10.3390/app12147321.

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Elevators have become a kind of indispensable facility for everyday life, which bring people both convenience and safety hazards. Specifically in the household environment, an elevator’s lifespan is expected to be more than 20 years. An appropriate and regularly maintained counterweight is conducive to extending elevator life. This paper proposes a passenger counting approach in the elevator for regular counterweight adjustment based on commodity WiFi called ECC. Since the running time of the elevator between two adjacent floors is short, the major challenge of ECC is how to count passengers f

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Prakash, Ashwini Bukanakere, Ranganathaiah Sumathi, and Honnudike Satyanarayana Sudhira. "Hybrid travel time estimation model for public transit buses using limited datasets." IAES International Journal of Artificial Intelligence (IJ-AI) 12, no. 4 (2023): 1755–64. https://doi.org/10.11591/ijai.v12.i4.pp1755-1764.

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A reliable transit service can motivate commuters to switch their traveling mode from private to public. Providing necessary information to passengers will reduce the uncertainties encountered during their travel and improve service reliability. This article addresses the challenge of predicting dynamic travel times in urban areas where real-time traffic flow information is unavailable. In this perspective, a hybrid travel time estimation model (HTTEM) is proposed to predict the dynamic travel time using the predicted travel times of the machine learning model and the preceding trip details. T

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22

Sarsam, Saad Issa. "ASSESSING THE RISK AND POTENTIAL OF PERSONAL EXPOSURE TO ROAD GENERATED POLLUTANT EMISSIONS THROUGH URBAN TRANSPORTATION SYSTEM." Journal of Engineering 14, no. 01 (2008): 2111–17. http://dx.doi.org/10.31026/j.eng.2008.01.05.

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This paper presents a study to assess the degree of personal exposure to traffic generated pollutant emission along urban arterials in Mosul. The traffic flow characteristics (volume, speed, density, and vehicle type) were determined in the field at selected locations on the arterials.The vehicular traffic which includes (drivers, number of passengers in vehicles on the road, and pedestrian) exposed to road generated emissions were obtained through field survey.The vehicle emissions of CO, VOC, and NOx were calculated using air pollution estimation computer model (Mobile 4.1). It was concluded

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23

Zhu, Wei, Feng Zhou, Jiajun Huang, and Ruihua Xu. "Validating Rail Transit Assignment Models with Cluster Analysis and Automatic Fare Collection Data." Transportation Research Record: Journal of the Transportation Research Board 2526, no. 1 (2015): 10–18. http://dx.doi.org/10.3141/2526-02.

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Passenger flow data are necessary for making and coordinating operational plans for urban rail transit (URT) systems; the availability and the service state of those systems directly influence the activity of a city and its people. Although many transit assignment models have been developed, the results of passenger flows estimated by these models as well as assumptions made in the estimation process, especially for large-scale, complex, and dynamically changing URT networks, had not been validated. This paper proposes a methodology that can validate existing URT assignment models by using aut

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Montero-Lamas, Yaiza, Margarita Novales, Alfonso Orro, and Graham Currie. "A New Big Data Approach to Understanding General Traffic Impacts on Bus Passenger Delays." Journal of Advanced Transportation 2023 (May 11, 2023): 1–15. http://dx.doi.org/10.1155/2023/4082587.

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This paper presents a new method to quantify the potential user time savings if the urban bus is given preferential treatment, changing from mixed traffic to an exclusive bus lane, using a big data approach. The main advantage of the proposal is the use of the high amount of information that is automatically collected by sensors and management systems in many different situations with a high degree of spatial and temporal detail. These data allow ready adjustment of calculations to the specific reality measured in each case. In this way, we propose a novel methodology of general application to

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Castillo-Calderón, Jairo, Rubén Carrión Jaura, Diego Díaz Sinche, and Bryan Panchana. "Estimation of Traction Energy Consumption of Urban Service Buses in an Intermediate Andean City." IOP Conference Series: Earth and Environmental Science 1141, no. 1 (2023): 012001. http://dx.doi.org/10.1088/1755-1315/1141/1/012001.

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Abstract The purpose of this work is to estimate the traction energy consumption of public transport buses in the urban sector of the city of Loja, Ecuador. Initially, with a data logger device, connected to the OBDII port, the speed and position variables of the transport units are acquired in real time, at a frequency of 1 Hz, during 25 round trips on 3 bus lines with the highest passenger flow; the effects of the slope profile are considered. To avoid information bias, 25 different HINO AK bus units, with different drivers, are monitored on full daily working days, where traffic is variable

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Nithya, D. S., Giuseppe Quaranta, Vincenzo Muscarello, and Man Liang. "Review of Wind Flow Modelling in Urban Environments to Support the Development of Urban Air Mobility." Drones 8, no. 4 (2024): 147. http://dx.doi.org/10.3390/drones8040147.

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Urban air mobility (UAM) is a transformative mode of air transportation system technology that is targeted to carry passengers and goods in and around urban areas using electric vertical take-off and landing (eVTOL) aircraft. UAM operations are intended to be conducted in low altitudes where microscale turbulent wind flow conditions are prevalent. This introduces flight testing, certification, and operational complexities. To tackle these issues, the UAM industry, aviation authorities, and research communities across the world have provided prescriptive ways, such as the implementation of dyna

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Lu, Kai, Alireza Khani, and Baoming Han. "A Trip Purpose-Based Data-Driven Alighting Station Choice Model Using Transit Smart Card Data." Complexity 2018 (August 28, 2018): 1–14. http://dx.doi.org/10.1155/2018/3412070.

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Automatic fare collection (AFC) systems have been widely used all around the world which record rich data resources for researchers mining the passenger behavior and operation estimation. However, most transit systems are open systems for which only boarding information is recorded but the alighting information is missing. Because of the lack of trip information, validation of utility functions for passenger choices is difficult. To fill the research gaps, this study uses the AFC data from Beijing metro, which is a closed system and records both boarding information and alighting information.

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Fan, Weijie, Jiao Zhang, Jianjun Shen, Xinbo Sun, and Le Feng. "Verification of Hybrid DES-FW-H Method for Estimation of Discharge Noise Induced by Turbine Cooler." Journal of Physics: Conference Series 3004, no. 1 (2025): 012047. https://doi.org/10.1088/1742-6596/3004/1/012047.

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Abstract Turbine cooler is the dominant cabin noise source of air conditioning system during aircraft ground and flight operation. The noise impact on passengers’ health can no longer be ignored, so modern commercial aircraft air conditioning system must meet low noise requirements. In this paper, turbine cooler transient flow field was calculated by detached-eddy simulation (DES), and its discharge noise is investigated using FW-H theory. The simulation analysis results and test data show that computational aeroacoustics (CAA: DES and FW-H combined method) can effectively capture the turbine

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Zhu, Wei, Wei Wang, and Zhaodong Huang. "Estimating Train Choices of Rail Transit Passengers with Real Timetable and Automatic Fare Collection Data." Journal of Advanced Transportation 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/5824051.

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An urban rail transit (URT) system is operated according to relatively punctual schedule, which is one of the most important constraints for a URT passenger’s travel. Thus, it is the key to estimate passengers’ train choices based on which passenger route choices as well as flow distribution on the URT network can be deduced. In this paper we propose a methodology that can estimate individual passenger’s train choices with real timetable and automatic fare collection (AFC) data. First, we formulate the addressed problem using Manski’s paradigm on modelling choice. Then, an integrated framework

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30

Prakash, Ashwini Bukanakere, Ranganathaiah Sumathi, and Honnudike Satyanarayana Sudhira. "Hybrid travel time estimation model for public transit buses using limited datasets." IAES International Journal of Artificial Intelligence (IJ-AI) 12, no. 4 (2023): 1755. http://dx.doi.org/10.11591/ijai.v12.i4.pp1755-1764.

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<p>A reliable transit service can motivate commuters to switch their traveling<br />mode from private to public. Providing necessary information to passengers<br />will reduce the uncertainties encountered during their travel and improve<br />service reliability. This article addresses the challenge of predicting dynamic<br />travel times in urban areas where real-time traffic flow information is<br />unavailable. In this perspective, a hybrid travel time estimation model<br />(HTTEM) is proposed to predict the dynamic travel time using the predicted&l

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Zhang, Yi, Jianhua Zhang, Baihong Tan, Shuxian He, Liqun Peng, and Tony Z. Qiu. "An Occupancy-Based Adaptive Signal Control for a Congested Signalized Intersection in the Low CV Penetration Environment." Journal of Advanced Transportation 2022 (May 14, 2022): 1–18. http://dx.doi.org/10.1155/2022/4745879.

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Adaptive signal control (ASC) is a well-researched topic that offers an efficient way for traffic management. It possesses a powerful ability to accommodate complex and constantly changing urban transportation networks. With the development of vehicular communication, CV-based ASC shows remarkable advantages compared with the traditional ASC system. Though the existing CV-based ASC strategies were proposed in the past few years, however, there are still issues to overcome. Most of the studies on CV-based ASC are based on the assumption of high CV penetration rate, which often result in poor pe

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Leurent, Fabien, and Kang Liang. "How Do Individual Walk Lengths and Speeds, Together with Alighting Flow, Determine the Platform Egress Times of Train Users?" Journal of Advanced Transportation 2022 (July 19, 2022): 1–22. http://dx.doi.org/10.1155/2022/3633293.

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Egress times of railway passengers from train alighting up to station exit typically amount to some tens of seconds, but with much variability even at the train level. Here, we first model the egress time as the ratio of the walk length to the preferred walk speed, under free-flow conditions. Then, we model the possible occurrence of congestion among the users alighting from a train as a traffic bottleneck affecting those passing at a “queue focal point” during a “queued time interval.” Analytical formulas are provided for the CDF and PDF of egress times, covering the free-flow case and the co

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Yang, Fei, Lin Chen, Yang Cheng, Xia Luo, and Bin Ran. "An Empirical Study of Parameter Estimation for Stated Preference Experimental Design." Mathematical Problems in Engineering 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/292608.

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The stated preference experimental design can affect the reliability of the parameters estimation in discrete choice model. Some scholars have proposed some new experimental designs, such as D-efficient, Bayesian D-efficient. But insufficient empirical research has been conducted on the effectiveness of these new designs and there has been little comparative analysis of the new designs against the traditional designs. In this paper, a new metro connecting Chengdu and its satellite cities is taken as the research subject to demonstrate the validity of the D-efficient and Bayesian D-efficient de

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CHEN, Suxiao, Guangjie LIU, Shen GAO, Jiming LI, and Juan WU. "A Discrete-Event Simulation System for Estimating Passenger Flow in Urban Rail Transit." Promet - Traffic&Transportation 37, no. 2 (2025): 440–55. https://doi.org/10.7307/ptt.v37i2.768.

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Establishing simulation models is a widely used and effective approach for analysing passenger flow distribution in urban rail transit systems. Recently, multi-agent and discrete event-based simulation models have shown exceptional performance in studying passenger flow information within urban rail transit systems. While simulations of passengers and trains often yield satisfactory results, few models capture the overall operational status of urban rail transit systems. The complex interactions among stations, trains and passengers make it challenging to integrate these elements into a unifie

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Cheng, Yan, Xiafei Ye, and Taku Fujiyama. "Identifying Crowding Impact on Departure Time Choice of Commuters in Urban Rail Transit." Journal of Advanced Transportation 2020 (June 23, 2020): 1–16. http://dx.doi.org/10.1155/2020/8850565.

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Crowding in urban rail transit is an inevitable issue for most of the high-density cities across the world, especially during peak time. For commuters who have considerably fixed destination arrival times, departure time choice is an important tool to adjust their trips. The ignorance of crowding impact on commuters’ departure time choice in urban rail transit may cause errors in forecasting dynamic passenger flow during peak time in urban rail transit. The paper develops a mixed logit model to identify how crowding impacts the departure time choice of commuters and their taste variation. Arri

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Utku, Anıl, and Sema Kayapinar Kaya. "Multi-layer perceptron based transfer passenger flow prediction in Istanbul transportation system." Decision Making: Applications in Management and Engineering 5, no. 1 (2022): 208–24. http://dx.doi.org/10.31181/dmame0315052022u.

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Estimating passenger movement in transportation networks is a critical aspect of public transportation systems. It allows for a greater understanding of traffic patterns, as well as efficient system evaluation and monitoring. It could also help with precise timing to emergencies or important events, as well as the improvement of urban transport system weaknesses and service quality. The number of transfer passengers demand in Istanbul, Turkey's biggest and most developed metropolis, was used to construct a real-world forecasting model in this study. The number of transfer passengers has been f

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Ozerova, Olga, Petro Yanovsky, Viktoriia Yanovska, Sergiy Lytvynenko, Larysa Lytvynenko, and Serhii Martseniuk. "Estimation of the interaction level between urban passenger transport and city train." MATEC Web of Conferences 294 (2019): 04008. http://dx.doi.org/10.1051/matecconf/201929404008.

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In the article the estimation of the interaction level between urban passenger transport and city train was made using the systems approach through application of modern methods of developing adequate easy-to-use mathematical models. Applying the systems approach, the transport node was considered as a comprehensive object, which is a single entity. It was identified that the transport node efficiency depends on the interaction level of the structure and its technology with the passenger traffic that requires designing a rational structure of the node and providing the technological interactio

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He, Bing, Kang Liu, Zhe Xue, et al. "Spatial and Temporal Characteristics of Urban Tourism Travel by Taxi—A Case Study of Shenzhen." ISPRS International Journal of Geo-Information 10, no. 7 (2021): 445. http://dx.doi.org/10.3390/ijgi10070445.

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Tourism networks are an important research part of tourism geography. Despite the significance of transportation in shaping tourism networks, current studies have mainly focused on the “daily behavior” of urban travel at the expense of tourism travel, which has been regarded as an “exceptional behavior”. To fill this gap, this study proposes a framework for exploring the spatial and temporal characteristics of urban tourism travel by taxi. We chose Shenzhen, a densely populated mega-city in China with abundant tourism resources, as a case study. First, we extracted tourist trips from taxi traj

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Yin, Haodong, Jianjun Wu, Huijun Sun, Yunchao Qu, Xin Yang, and Bo Wang. "Optimal Bus-Bridging Service under a Metro Station Disruption." Journal of Advanced Transportation 2018 (July 5, 2018): 1–16. http://dx.doi.org/10.1155/2018/2758652.

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A station disruption is an abnormal operational situation that the entrance or exit gates of a metro station have to be closed for a certain of time due to an unexpected incident. The passengers’ travel behavioral responses to the alternative station disruption scenarios and the corresponding controlling strategies are complex and hard to capture. This can lead to the hardness of estimating the changes of the network-wide passenger demand, which is the basis of carrying out a response plan. This paper will establish a model to solve the metro station disruption problem by providing optimal add

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Skirkouski, Siarhei, Uladzimir Sedziukevich, and Olha Svichynska. "JUSTIFICATION OF THE CHOICE OF PUBLIC TRANSPORT SERVICE TYPE ON THE ROUTE." Automobile transport, no. 48 (May 29, 2021): 79–85. http://dx.doi.org/10.30977/at.2219-8342.2021.48.0.79.

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Problem. Currently, there exist two main types of service on public transport routes – headway-based and timetable-based. They differ by the frequency of service at the stops and by the information available for passengers. The required frequency of service significantly affects transport operator costs and passenger travel time which, in turn, influences the cost for a passenger. One of the ways to reduce costs for both parties of the transportation process is to make a reasonable choice of the type of service or switch between the types during the day depending on the passenger flow volume.

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Zhao, Xueke. "Proportional Estimation Method of Urban Rail Passenger Flow Transfer Path Selection Based on IC Card Data." Academic Journal of Science and Technology 5, no. 2 (2023): 21–26. http://dx.doi.org/10.54097/ajst.v5i2.5927.

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Based on the analysis of the influencing factors of urban rail transit passenger flow transfer path selection behavior and the components of travel time, a method of estimating the proportion of urban rail transit passenger flow transfer path selection based on IC card data is proposed. Firstly, the research determines the shortest interchange path algorithm as Dijkstra algorithm and the graph-based depth-first search algorithm as the effective interchange path search algorithm; analyzes the factors influencing the passenger flow interchange path selection behavior as three types of travel tim

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Zhang, Jianming, Jun Cai, Mengjia Wang, and Wansong Zhang. "An Estimation Method for Passenger Flow Volumes from and to Bus Stops Based on Land Use Elements: An Experimental Study." Land 13, no. 7 (2024): 971. http://dx.doi.org/10.3390/land13070971.

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To unravel the general relationship between bus travel and land use around bus stops and along bus routes and to promote their coordinated development, this paper explores a method to estimate passenger flow volumes from and to bus stops based on land use types, intensities, and spatial distributions around bus stops and along bus routes. Firstly, following the principle of the gravity model, which considers traffic volumes analogous to gravity based on trip generation and distance impedance between traffic analysis zones (TAZs), a gravitational logic estimation method for passenger flow volum

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Misharin, A., D. Namiot, and O. Pokusaev. "On Passenger Flow Estimation for new Urban Railways." IOP Conference Series: Earth and Environmental Science 177 (August 10, 2018): 012012. http://dx.doi.org/10.1088/1755-1315/177/1/012012.

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Hou, Zhongwei, Jin Han, and Guang Yang. "Analysis of Passenger Flow Characteristics and Origin–Destination Passenger Flow Prediction in Urban Rail Transit Based on Deep Learning." Applied Sciences 15, no. 5 (2025): 2853. https://doi.org/10.3390/app15052853.

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Traditional station passenger flow prediction can no longer meet the application needs of urban rail transit vehicle scheduling. Station passenger flow can only predict station distribution, and the passenger flow distribution in general sections is unknown. Accurate short-term travel origin and destination (OD) passenger flow prediction is the main basis for formulating urban rail transit operation organization plans. To simultaneously consider the spatiotemporal characteristics of passenger flow distribution and achieve high precision estimation of origin and destination (OD) passenger flow

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Kagan, D. Z. "ESTIMATION OF DEPENDENCE OF PASSENGER TURNOVER OF TRANSPORT ON MACROECONOMIC FACTORS." World of Transport and Transportation 15, no. 1 (2017): 140–49. http://dx.doi.org/10.30932/1992-3252-2017-15-1-12.

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[For the English abstract and full text of the article please see the attached PDF-File (English version follows Russian version)].ABSTRACT The instability of the domestic transport services market, significant fluctuations in demand on the part of the population, make it necessary to evaluate the range of problems under study with particular attention. The author analyzes the impact of macroeconomic factors on passenger traffic. The article reveals the high dependence of the total passenger flow on the economic condition of the country, the population’s solvency margin. The change in the stre

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Lundaeva, Karina A., Zakhar A. Saranin, Kapiton N. Pospelov, and Aleksei M. Gintciak. "Demand Forecasting Model for Airline Flights Based on Historical Passenger Flow Data." Applied Sciences 14, no. 23 (2024): 11413. https://doi.org/10.3390/app142311413.

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This paper addresses the problem of estimating passenger demand for flights, with a particular focus on the necessity of developing precise forecasts that incorporate intricate and interdependent variables for effective resource planning within the air transport industry. The present paper focuses on the development of a model for medium-term flight demand estimation by flight destinations. This is based on the analysis of historical airline data on dates, departure times, and passenger demand, as well as the consideration of the influence of macroeconomic indicators, namely gross regional pro

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Zhang, Na, Zijia Wang, Feng Chen, Jingni Song, Jianpo Wang, and Yu Li. "Low-Carbon Impact of Urban Rail Transit Based on Passenger Demand Forecast in Baoji." Energies 13, no. 4 (2020): 782. http://dx.doi.org/10.3390/en13040782.

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There are increasing traffic pollution issues in the process of urbanization in many countries; urban rail transit is low-carbon and widely regarded as an effective way to solve such problems. The passenger flow proportion of different transportation types is changing along with the adjustment of the urban traffic structure and a growing demand from passengers. The reduction of carbon emissions brought about by rail transit lacks specific quantitative research. Based on a travel survey of urban residents, this paper constructed a method of estimating carbon emissions from two different scenari

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Raj, Jithin. "Estimation of PCU Values for Urban Roads by Considering the Effect of Signalized Intersections under Mixed Traffic Conditions." European Transport/Trasporti Europei, no. 86 (March 2022): 1–17. http://dx.doi.org/10.48295/et.2022.86.6.

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Along with multiple classes of vehicles, frequent signalized intersections on the urban roads and the platoons thus created add complexity to the estimation of Passenger Car Units (PCU). Under such scenarios of interrupted traffic, a new approach based on platoon movement of vehicles is introduced for the realistic estimation of PCU values for urban roads by incorporating the appropriate vehicle behavior and interactions. The PCU values were derived by finding the trade-off between the speed reduction caused by the flow of passenger cars and other vehicle classes, as per the given definition b

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Alina Gennadievna, Loktionova, and Shevtsova Anastasia Gennadievna. "ESTIMATION OF TECHNICAL PARAMETERS OF CARS IN THE TRAFFIC FLOW." World of transport and technological machines 2(79), no. 4 (2022): 75–80. http://dx.doi.org/10.33979/2073-7432-2022-2(79)-4-75-80.

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SUGIYAMA, Yoichi, Hiroshi MATSUBARA, Shuichi MYOJO, Kazuki TAMURA, and Naoya OZAKI. "An Approach for Real-time Estimation of Railway Passenger Flow." Quarterly Report of RTRI 51, no. 2 (2010): 82–88. http://dx.doi.org/10.2219/rtriqr.51.82.

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