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    <title>Transport Research International Documentation (TRID)</title>
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    <language>en-us</language>
    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Simulation Study of the Staircase Position to Evacuation Efficiency at the Subway Platform</title>
      <link>https://trid.trb.org/View/1634879</link>
      <description><![CDATA[In order to improve the safety and evacuation efficiency at subway platforms, this paper discusses the applicability of staircase position to evacuation efficiency. First, the authors summarize the characteristics of passengers at the subway platform. After that, three different position of staircase exits are chosen to be the object of study and a simulation scenario by AnyLogic is built based on the data of a subway platform in Beijing. Finally, the authors analyze the applicability of three scenarios by the indictor of the number of passengers and time of evacuation process. The simulation results show that, in comparison with three forms of staircase, the staircase exits at the center of the platform have the worst evacuation capacity among the three options. In addition, other two scenario are fit to different volume conditions. Those results can provide some guidance to the facilities design in subway platform.]]></description>
      <pubDate>Thu, 09 Apr 2020 09:00:51 GMT</pubDate>
      <guid>https://trid.trb.org/View/1634879</guid>
    </item>
    <item>
      <title>Optimization-based feedback control of passenger flow in subway stations for improving level of service</title>
      <link>https://trid.trb.org/View/1637742</link>
      <description><![CDATA[An analytical model is proposed to simulate the passenger flow in a subway station using the ordinary differential equation with the average passenger density in the facilities as the state variable. In order to realize the well-organized inbound process, a linear programming-based feedback control model (LFCM) is proposed to compute the optimal feedback passenger inflows of various facilities and velocities to improve the level of service. In order to deal with the unsolvable LFCM, which is caused by the cyclic operation characteristic of a subway station, a network-switch mechanism is incorporated to the LFCM to improve the performance of control model. Finally, a small numerical example is used to illustrate the features of the authors' proposed model.]]></description>
      <pubDate>Wed, 24 Jul 2019 09:35:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/1637742</guid>
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    <item>
      <title>A passenger flow routing model for high-speed railway network in different transportation organization modes</title>
      <link>https://trid.trb.org/View/1599485</link>
      <description><![CDATA[Reasonable selection of passenger flow routes considering different transportation organization modes can meet the demands of adapting to large-scale high-speed railway networks and improving network efficiency. Passenger flow routing models are developed to find and optimize a set of passenger flow routes for a high-speed railway network considering different transportation organization modes. In this paper, the authors presented a new approach minimizing the operating costs, including traveling cost, cost of travel time differences between different lines, and penalties for the in-ter-line. The network was reconstructed to solve the directed graph with four nodes (node-in-up, node-in-down, nodes-out-up, and nodes-out-down) indicating one station. To tackle their problem, the authors presented an integer non-linear programming model, and direct passenger demand was guaranteed owing to volume constraints. Binary variables were introduced to simplify the model, and the algorithm process was optimized. The authors suggested a global optimal algorithm by Lingo 11.0. Finally, the model was applied to a sub-network of the Northeast China railway system. Passenger flow routes were optimized and the transportation organization mode was discussed based on passenger volume, traveling distance, and infrastructure.]]></description>
      <pubDate>Thu, 27 Jun 2019 13:59:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/1599485</guid>
    </item>
    <item>
      <title>On pedestrian traffic management in railway stations: simulation needs and model assessment</title>
      <link>https://trid.trb.org/View/1581122</link>
      <description><![CDATA[Mass transit rail stations make up complex systems in which passenger flows have significant influence on operations and traffic conditions. Are there pedestrian simulators that can effectively contribute to the management of crowd flows? To answer this question, an assessment grid is built to address scientific principles as well as operational and organizational needs. The scientific principles encompass real-world features to be described, especially causalities to reproduce. The grid is applied to several commercially-available software (including PTVVisWalk, Legion, Anylogic, MassMotion and SimWalk) as well as to research-sourced pedestrian simulators.]]></description>
      <pubDate>Wed, 27 Mar 2019 12:47:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/1581122</guid>
    </item>
    <item>
      <title>Sensitivity Analysis of a Transit Bottleneck Model</title>
      <link>https://trid.trb.org/View/1581151</link>
      <description><![CDATA[In urban mass transit, station platforms constitute waiting areas for incoming users willing to board service vehicles. In the transit bottleneck model of Leurent et al. (2014, 2015), the passenger stocks and average wait times according to station of destination are obtained as the solution of a fixed point problem (FPP) with respect to passenger stocks: multiple service routes are allowed, each of which with residual in-vehicle capacity that can be or not saturated by the flow of users incoming at the station of interest. The paper provides a full sensitivity analysis of all model outcomes to all model inputs, namely entry flows according to destination stations, residual in-vehicle capacities and route frequencies. The method consists in partial differentiation by formal calculus, since the FPP amounts to an implicit function that is differentiable almost everywhere. As instance of application, the case of a busy commuter rail line in Paris is studied, with emphasis on the marginal congestion costs of incoming as well as on-board users onto the users waiting for boarding.]]></description>
      <pubDate>Wed, 27 Mar 2019 12:47:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/1581151</guid>
    </item>
    <item>
      <title>A Dynamic Passenger Assignment Model for High-Speed Railway Networks Based on Constrained Continuous Capacity</title>
      <link>https://trid.trb.org/View/1573277</link>
      <description><![CDATA[For high-speed railway (HSR) networks, the space-time passenger flow distribution plays an important role for determining and optimizing the space-time resource allocation (e.g., train scheduling). This study develops a modeling framework to predict space-time passenger flow distribution for HSR networks with rigid capacity constraints. In particular, the service capacity is approximated as a continuous variable, which is time-and-space-dependent under given track network for the HSR system. The travel demand to be loaded to the HSR network has two features besides the origin and destination stations: ticket-booking time and desired departure time. Following the principle of first-booking-first-served (FBFS), an assignment model is formulated with the rigid capacity constraints, where a later ticket-booking time might result in less available travel options. A solution algorithm is designed for solving the ticket-booking-time-dependent assignment model. The model and its applicability are illustrated with a large-scale Chinese HSR network example.]]></description>
      <pubDate>Fri, 01 Mar 2019 15:51:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/1573277</guid>
    </item>
    <item>
      <title>DeepPF: A deep learning based architecture for metro passenger flow prediction</title>
      <link>https://trid.trb.org/View/1586957</link>
      <description><![CDATA[This study aims to combine the modeling skills of deep learning and the domain knowledge in transportation into prediction of metro passenger flow. The authors present an end-to-end deep learning architecture, termed as Deep Passenger Flow (DeepPF), to forecast the metro inbound/outbound passenger flow. The architecture of the model is highly flexible and extendable; thus, enabling the integration and modeling of external environmental factors, temporal dependencies, spatial characteristics, and metro operational properties in short-term metro passenger flow prediction. Furthermore, the proposed framework achieves a high prediction accuracy due to the ease of integrating multi-source data. Numerical experiments demonstrate that the proposed DeepPF model can be extended to general conditions to fit the diverse constraints that exist in the transportation domain.]]></description>
      <pubDate>Tue, 26 Feb 2019 09:38:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/1586957</guid>
    </item>
    <item>
      <title>A method of mathematical modeling for transfer hub establishment in Saint Petersburg</title>
      <link>https://trid.trb.org/View/1577373</link>
      <description><![CDATA[Nowadays, it is almost impossible to design and forecast (plan) operation of transportation systems without mathematical modeling tools and special software. The paper discusses comparison and application of mathematical modeling methods in Russia and abroad for functional and spatial development of cities in the transport and urban-planning field. A method for choosing transfer hub locations in the city plan, based on the developed mathematical model, is proposed. Under the conditions of suburbanization of large agglomerations, development of a more comfortable passenger transportation system can decrease the automobilization level in the long view. The system of transfer hubs involving transport with large carrying capacity (rail transport) represents the basis for development of a larger and more sophisticated transportation system attractive for people of various social classes. When choosing transfer hubs, it is suggested to take into account subway/railway station stability and demand (given the existing population displacement) based on a comparative analysis of modeling results where modeling involved artificial delays for entrance. The modeling was conducted using a software suite developed by the Saint Petersburg R&D and Design Institute for Urban Planning and Saint Petersburg Institute for Economics and Mathematics of the Russian Academy of Sciences. Based on the experiment results, it is possible to classify stations using the proposed factor of delay value impact on the transfer passenger flow. The value of factors for delay value impact on the transfer passenger flow can be used as one of the factors for prioritizing transfer hub establishment.]]></description>
      <pubDate>Tue, 12 Feb 2019 21:09:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/1577373</guid>
    </item>
    <item>
      <title>A station-based rail transit network vulnerability measure considering land use dependency</title>
      <link>https://trid.trb.org/View/1505013</link>
      <description><![CDATA[Natural disasters, intentional attacks, and operational incidents are posing increasing threats on rail transit network. The vulnerability of rail transit network becomes an important concern of researchers and rail managers. This paper proposes a station-based accessibility approach addressing passenger flow and land use characteristics in rail transit network vulnerability analysis. Land use variables are measured as the independency degree on rail transit. The reduction ratio of network accessibility before and after incidents is calculated to measure the potential consequences. Based on results of comparisons with existing methods with the help of an example problem, the proposed accessibility measure demonstrates better and more reasonable results as not only the rail network and passenger flow but also the land use and travel alternative variables interacting with rail transit are accounted. The proposed method is then applied to Shanghai metro network. The data for analysis include rail transit network data, passenger flow data, and land use data around stations. Results indicate that the vulnerability of rail transit network is jointly affected by its network topology, passenger flow, and land use variables. Unbalanced land use, high plot ratio, and the less travel alternatives will increase the dependency of land on rail transit travel, leading to high network vulnerability once disrupted. Results of this work will inform rail transit managers of the degree of network vulnerability and critical stations and links as well as the land use dependency on vulnerability. Findings of this study may have implications not only for the planning of other transit modes to enhance the resilience of public transit network in vulnerable areas but also for the land use development around rail stations.]]></description>
      <pubDate>Thu, 29 Mar 2018 09:31:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/1505013</guid>
    </item>
    <item>
      <title>Statistical Analysis of High-Speed Railway Capacity Utilization and Passenger Distribution in China: A Case Study of Wuhan–Guangzhou High-Speed Rail</title>
      <link>https://trid.trb.org/View/1495671</link>
      <description><![CDATA[Train operation plan is subject to the distribution of passengers flow, as well as the capacity utilization of railway. The paper concentrated on the capacity utilization and passenger flow characteristics of Wuhan-Guangzhou high-speed railway（WG-HSR）based on the real word trains operation data. Firstly, the number of trains departing from each station along WG-HSR was presented, which reflected the service frequency of this line. The capacity utilization of each section was analyzed, and the spatial-temporal propagation of capacity utilization was proved. Then, the spatial-temporal characteristics of passenger flow were presented. In order to get a systematic recognition of passenger flow characteristics, the authors investigated the passenger volume during different time periods and between several origin and destination (OD) pairs to characterize travelers’ spatial-temporal preferences. The passenger distribution and passenger turnover on some long-distance trains were shown to get the number and proportion of cross-line passengers travelling on the WG-HSR. Finally, load rates of trains running on WG-HSR were displayed, which reflected the seats capacity utilization and the economic benefit of trains. The relationship between train load rate and the travelling distance was explored, which can contribute to a better train operation schedule.]]></description>
      <pubDate>Mon, 12 Mar 2018 15:02:04 GMT</pubDate>
      <guid>https://trid.trb.org/View/1495671</guid>
    </item>
    <item>
      <title>Joint optimal train regulation and passenger flow control strategy for high-frequency metro lines</title>
      <link>https://trid.trb.org/View/1465380</link>
      <description><![CDATA[To improve the headway regularity and commercial speed of high-frequency metro lines with overloaded passenger flow, this paper systematically investigates a joint optimal dynamic train regulation and passenger flow control design for metro lines. A coupled state-space model for the evolution of the departure time and the passenger load of each train at each station is explicitly developed. The dwell time of the train is affected by the number of entering and exiting passengers. Combining dynamic train regulation and passenger flow control, a dynamic optimisation problem that minimises the timetable and the headway deviations for metro lines is developed. By applying a model predictive control (MPC) method, the authors formulate the problem of finding the optimal joint train regulation and passenger flow control strategy as the problem of solving a set of quadratic programming (QP) problems, under which an optimal control law can be numerically calculated efficiently using a quadratic programming algorithm. Moreover, based on the Lyapunov stability theory, the stability (convergence) of the metro line system under the proposed optimal control algorithm is verified. Numerical examples are given to illustrate the effectiveness of the proposed method.]]></description>
      <pubDate>Thu, 25 May 2017 13:56:09 GMT</pubDate>
      <guid>https://trid.trb.org/View/1465380</guid>
    </item>
    <item>
      <title>Forecasting short-term subway passenger flow under special events scenarios using multiscale radial basis function networks</title>
      <link>https://trid.trb.org/View/1460482</link>
      <description><![CDATA[Reliable and accurate short-term subway passenger flow prediction is important for passengers, transit operators, and public agencies. Traditional studies focus on regular demand forecasting and have inherent disadvantages in predicting passenger flows under special events scenarios. These special events may have a disruptive impact on public transportation systems, and should thus be given more attention for proactive management and timely information dissemination. This study proposes a novel multiscale radial basis function (MSRBF) network for forecasting the irregular fluctuation of subway passenger flows. This model is simplified using a matching pursuit orthogonal least squares algorithm through the selection of significant model terms to produce a parsimonious MSRBF model. Combined with transit smart card data, this approach not only exhibits superior predictive performance over prevailing computational intelligence methods for non-regular demand forecasting at least 30 min prior, but also leverages network knowledge to enhance prediction capability and pinpoint vulnerable subway stations for crowd control measures. Three empirical studies with special events in Beijing demonstrate that the proposed algorithm can effectively predict the emergence of passenger flow bursts.]]></description>
      <pubDate>Mon, 01 May 2017 09:37:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/1460482</guid>
    </item>
    <item>
      <title>Collection and Processing Algorithm of Bus Passenger Flow Based on Wi-Fi Sensing</title>
      <link>https://trid.trb.org/View/1438664</link>
      <description><![CDATA[Due to the development of Wi-Fi technology and the wide use of public Wi-Fi, Wi-Fi greatly facilitates the behavior of people to communicate. Currently, many buses have provided Wi-Fi service to passengers for free and transit agencies have increasingly adopted systems for collecting data of passengers and vehicles. This paper proposes a new algorithm to collect and analyze bus passenger flow based on Wi-Fi technology. A database is created based on Wi-Fi sensing and Global Positioning System (GPS) positioning data and includes information of devices carried by passengers and the bus runs. Then the passenger flow of boarding and alighting in real time is derived and stored by matching the time of sniffing to bus location points. Then Origin-Destination (OD) matrix for a single run or all bus runs can be inferred. Moreover, this paper clarifies the method of correcting the section passenger flow.]]></description>
      <pubDate>Sat, 01 Apr 2017 22:45:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/1438664</guid>
    </item>
    <item>
      <title>A Macroscopic and Dynamic Model of Urban Rail Transit with Delay and Congestion</title>
      <link>https://trid.trb.org/View/1438650</link>
      <description><![CDATA[Urban mass transit often operates with high service frequencies to serve large passenger demand, such as those during morning commute. Their objective is to transport as many passengers as quickly as possible. To do so, they require careful planning because their operation can be delayed by two types of congestion, namely, train-congestion (i.e., knock-on delays) and passenger boarding congestion, both of which interact with each other. However, there are no tractable models representing such dynamics of transit systems; and it makes difficult to analyze management strategies of them (e.g., an optimal peak-period toll in morning commute situations) in a general and tractable way. This paper proposes a simplified model for idealized urban rail transit. The model describes passenger transport efficiency of given transit facilities with given passenger demand by considering congestion, while keeping its analytical tractability high. It can be considered as transit-specific fundamental diagram (FD) (i.e., relation among train-flow, train-density, and passenger-flow) with theoretical basis. Then, a macroscopic model of dynamic representation of the system is developed based on the FD. Finally, the macroscopic model is validated by comparing to a microscopic simulation. The results suggest that the proposed model would be useful for management strategy analysis purposes.]]></description>
      <pubDate>Fri, 10 Mar 2017 09:21:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/1438650</guid>
    </item>
    <item>
      <title>Flow capturing location problem for railway passengers</title>
      <link>https://trid.trb.org/View/1441612</link>
      <description><![CDATA[The authors construct a flow capturing location model for capturing railway passengers. Train passengers can access facilities located at the origin station and the destination station more easily than facilities located midway along the path. The authors assume that the decision maker can locate two types of facilities: smaller level 1 facilities with smaller construction cost and larger level 2 facilities with larger construction cost. Level 1 facilities can capture only travelers departing from or arriving at the stations where they are located while level 2 facilities can also attract travelers passing through them. The problem to seek the locations of both facilities which maximize the number of captured flows under the budget constraint is considered. The authors' model is applied to analyzing optimal facility locations using passenger flow data of JR Yamanote Line.Hodgsonによって提案された捕捉フロー最大化問題は、移動経路上で施設を利用可能な需要を最大化するように定められた個数の施設を配置する問題である。本稿では鉄道利用者に着目し、意思決定者が需要獲得力と設置コストの異なる二種類の施設を配置可能な状況を仮定し、総資金制約のもとで各施設の組み合わせとその配置を同時に決定する問題を提案する。鉄道利用者にとって、起点駅と終点駅にある施設はアクセルが容易であるが、途中通過駅にある施設を利用するためには途中下車が必要であるため大きなコストが発生する。これを抽象的に捉え、小施設は配置された駅を起点駅または終点駅とするフローのみを捕捉可能であり、大施設は配置された駅を移動経路に含むフローを捕捉可能であると仮定する。提案モデルを現実の山手線上の流動データに適用し、最適配置結果を詳しく分析する。また山手線上のOD表を用いて捕捉フローを可視化し解の特徴を分析する。さらに両者を組み合わせて配置可能な場合には、同一資金で一方のみを最適に配置する場合よりも多くのフローを捕捉可能なケースを示す。]]></description>
      <pubDate>Thu, 23 Feb 2017 17:06:36 GMT</pubDate>
      <guid>https://trid.trb.org/View/1441612</guid>
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