Equity-based timetable synchronization optimization in urban subway network

In the urban subway transportation system, passengers may have to make at least one transfer traveling from their origin to destination. This paper proposes a timetable synchronization optimization model to optimize passengers’ waiting time while limiting the waiting time equitably over all transfer station in an urban subway network. The model aims to improve the worst transfer by adjusting the departure time, running time, the dwelling time and the headways for all directions in the subway network. In order to facilitate solution, we develop a binary variables substitute method to deal with the binary variables. Genetic algorithm is applied to solve the problem for its practicality and generality. Finally, the suggested model is applied to Beijing urban subway network and several performance indicators are presented to verify the efficiency of suggested model. Results indicate that proposed timetable synchronization optimization model can be used to improve the network performance for transfer passengers significantly.     

地铁车站票务设备节能优化研究

为解决城市轨道交通车站售票能力冗余导致城市电力资源及地铁公司运营成本闲置的问题,分析普通车站日常客流分布,综合考虑地铁车站售票设备成本和乘客的时间成本因素,建立地铁车站售票设备开启数量优化模型,同时通过排队论和Lingo软件进行计算,获得最优化的地铁车站售票设备开启数量。以郑州地铁农业南路站的日常客流为例,应用地铁车站售票设备开启数量优化模型,计算得到农业南路站售票设备优化方案,通过优化方案进行节能成果分析证明,该方案可有效节约城市电力资源及地铁公司运营成本。     

北京地铁和平西桥站-北土城东路站区间渡线区隧道暗挖施工技术

文章主要介绍了北京地铁五号线和-北区间渡线区暗挖隧道断面转换施工技术,其经验可为今后类似城市地铁工程施工提供借鉴。     

Forecasting short-term subway passenger flow under special events scenarios using multiscale radial basis function networks

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.     

The evaluation of the spatial integration of station areas via the node place model; an application to subway station areas in Tehran

Urban planners usually consider the transportation system and land use systems in different ways. The node place model is an analytical tool that explores the interaction between the transportation and land use systems in station areas in an urban region. The essential issue with the node place model is spatial. To address this issue, spatial indices are added to the model. Another purpose of this paper is to provide a procedure to identify the most effective transportation and land use dynamics in station areas. In this respect, canonical correlation analysis was conducted on data concerning Tehran’s subway stations. The resulting spatial indices have a fairly logical relationship with other transportation and land use indices, and it is useful to incorporate these indices in the node place model. The case studies demonstrated that a well-integrated, continuous and dense spatial configuration of the street network in station areas is associated with an increase in the variety and intensity of activities, an increase in the workforce and better accessibility for the station by attracting greater pedestrian movement. Additionally, these case studies indicated that to sustain a station area, the streets that exist in a station area and the streets that are connected to a station should be connected to the streets that locally benefit from well-integrated areas within fewer steps.     

崇文门地铁车站管幕预支护施工效应模拟分析

北京地铁五号线崇文门站下穿既有地铁一号线区间隧道,车站顶板与区间隧道底板间距2.858 m,施工中为了严格控制既有环线区间隧道的沉降,确保环线地铁运营安全,首次采用了管幕预支护技术。文章采用3D-S igm a三维有限元软件对施工效应进行模拟分析,预测车站施工引起的既有隧道的沉降量,以确定合理的管幕预支护参数及其作用效果。     

Seismic Dynamic Response of an Atrium-type Subway Station北大核心CSCD

Atrium-type subway stations have been utilized for multifunctional demands. For natural lighting, the middle parts of slabs are replaced by beams. And to expand space, no columns are set for the 1st floor underground, while flat columns are set for the 2nd floor. These characteristics make the seismic response of the atrium-type subway station differ from the traditional station. In this paper, by a shaking table test of soil-structure 1/30 scale model of the atrium-type subway station, the amplification and attenuation effect of soils to the ground motion, as well as the acceleration and the strain response of the structure are analyzed when the model is subjected to lateral ground motions with different PGA and frequency contents. Subsequently, the seismic dynamic effect on the structural internal force distribution is discussed to improve the seismic design of the atrium-type subway station. © 2018, Editorial Office of "Modern Tunnelling Technology". All right reserved.     

地铁渡线地段大断面浅埋暗挖综合施工技术研究

文章结合北京地铁5号线和平西站至北土城东路站区间隧道施工实践,对地铁渡线地段浅埋、大跨、变断面隧道暗挖施工技术进行了分析,在从小断面向大断面施工、大断面向小断面施工以及双连拱地段等的施工技术方面提出了新的思路。     

单拱单柱双层浅埋暗挖地铁车站二次衬砌优化施工技术

北京地铁五号线蒲黄榆车站为22.6 m宽大跨度单拱单柱双层结构,采用中洞法开挖,开挖跨度相对较大,临时支护体系繁多,二次衬砌过程中结构受力转换复杂。文章主要介绍蒲黄榆车站二次衬砌施工分层、分段划分及临时支撑拆除代换技术。     

A G/G(n)/C/C state‐dependent simulation model for metro station corridor width design

Metro station corridor and passengers are described as a G/G(n)/C/C state‐dependent queuing system with a general random arrival interval G and a general random and state‐dependent service time G(n) to offset the shortcomings in existing design methods. The corresponding G/G(n)/C/C state‐dependent discrete event simulation model is developed, and its high‐fidelity is tested. Then the optimization algorithm based on the simulation model is designed to determine corridor width. The proposed simulation optimization method and the existing analytical optimization methods, based on M/G(n)/C/C and D/D/1/C queuing models, are applied to design corridor width in a numerical example of 48 combinations of passenger flow rates and level of service (LOS). The designed corridor widths are tested in a micro‐simulation model, and the performance measure is compared. The result shows that the corridor widths obtained by the new method are 0.357 m (7.4%) larger than that of the other two methods on average; the area per passenger of the new method increases 10.53% and 11.63%, respectively, compared with that of the other two methods; the widths designed by the new method satisfy the requirement of LOS under various passenger flows, whereas 93% of the corridor widths obtained by the other two methods fail to meet the requirement of LOS, and the corridor widths designed by the new method have high elasticity coefficients of LOS‐width. Copyright © 2015 John Wiley & Sons, Ltd.     

A case study on the coordination of last trains for the Beijing subway network

Passengers may make several transfers between different lines to reach their destinations in urban railway transit networks. Coordination of last trains in feeding lines and connecting lines at transfer stations is especially important because it is the last chance for many travellers to transfer. In this paper, a mathematical method is used to reveal the relationships between passenger transfer connection time (PTCT) and passenger transfer waiting time (PTWT). A last-train network transfer model (LNTM) is established to maximize passenger transfer connection headways (PTCH), which reflect last-train connections and transfer waiting time. Additionally, a genetic algorithm (GA) is developed based upon this LNTM model and used to test a numerical example to verify its effectiveness. Finally, the Beijing subway network is taken as a case study. The results of the numerical example show that the model improves five connections and reduces to zero the number of cases when a feeder train arrives within one headway’s time after the connecting train departed.     

An improved Dial's algorithm for logit-based traffic assignment within a directed acyclic network

Abstract

Dial's algorithm is one of the most effective and popular procedures for a logit-type stochastic traffic assignment, as it does not require path enumeration over a network. However, a fundamental problem associated with the algorithm is its simple definition of ‘efficient paths’, which sometimes produces unrealistic flow patterns. In this paper, an improved algorithm based on the route extension coefficient is proposed in order to circumvent this problem, in which ‘efficient paths’ simultaneously consider link travel cost and minimum travel cost. Path enumeration is still not required and a similar computing efficiency with the original algorithm is guaranteed. A limitation of the algorithm is that it can only be applied to a directed acyclic network because a topological sorting algorithm is used to decide the order of the sequential calculation. A numerical example based on the Beijing subway network illustrates the effectiveness of the proposed algorithm. It is found that it is able to exclude most unrealistic paths, but include all reasonable paths when compared with path enumeration and the original Dial's algorithm.     

Willingness to board: A novel concept for modeling queuing up passengers

This paper addresses an innovative concept, termed as queuing passengers’ willingness to board (WTB) the transit vehicles. In the peak hours, some queuing passengers cannot board a crowded bus/train, but when the same vehicle arrives at the next stop, some other passengers could still get on. This phenomenon reflects that passengers at different queuing locations have heterogeneous level of ambitions to board. A methodological framework is proposed for the quantitative investigation of WTB. First, a general model is proposed, together with a new least square method (LSM) for the calibration. Then, a parametric model is developed, which is also calibrated by the LSM. To refine the calibration method and deal with the biasness of survey data, a weighted least square method is further developed. Based on real survey data, the calibration results clearly support the existence of WTB, which can be used to estimate the capacity of transit vehicles. This paper also sheds some lights on the practical applications of the quantitative WTB.     

桩底后压浆技术在城市地铁车站洞桩法施工中的应用

以北京地铁光华路站洞桩法灌注桩后压浆技术的成功应用为例,详细介绍了其施工方法及施工工艺。研究表明,该项技术不仅可有效地提高桩基综合承载力,且可减少工期、降低工程成本,具有良好的社会效益和经济效益。     

Transit assignment under crowded conditions

This paper presents a transit assignment algorithm for crowded networks. Both congestion in vehicles and queuing at stations are explicitly taken into account in predicting passenger flows for a fixed pattern of origin-destination trip demands. The overflow effects due to insufficient capacity of transit lines are considered to be concentrated at transit stations, while the in-vehicle congestion effects (or discomforts) are considered to be dependent on in-vehicle passenger volume. Overflow delay at a transit station is dependent on the number of excess passengers required to wait for the next transit car. We use a logit model to determine the split between passengers that chose to wait for the next transit car and passengers that chose to board on the alternative transit lines. The proposed algorithm predicts how passenger will choose their optimal routes under both queuing and crowded conditions.     

A day-to-day and within-day dynamic stochastic assignment model

In this article a doubly dynamis assignment model for a general network is presented. It is assumed that users' choices are based on information about travel times and generalized transportation costs occurred in a finite number of previous days and, possibly, in previous periods of the same day. The information may be supplied and managed by an informative system. In this context, path and link flows vary for different subperiods of the same day (within-day dynamics) and for different days (day-to-day dynamics). The proposed model follows a nonequilibrium approach in which both within-day and day-to-day flow fluctuations are modelled as a stochastic process. A model of dynamic network loading for computing within-day variable arc flows from path flows is also presented. The model deals explicitly with queuing at oversaturated intersections and can be formulated as a fixed point problem. A solution scheme for the doubly dynamic assignment model is presented embedding a solution algorithm for the fixed-point problem.     

Hierarchical travel demand estimation using multiple data sources: A forward and backward propagation algorithmic framework on a layered computational graph

Aiming to develop a theoretically consistent framework to estimate travel demand using multiple data sources, this paper first proposes a multi-layered Hierarchical Flow Network (HFN) representation to structurally model different levels of travel demand variables including trip generation, origin/destination matrices, path/link flows, and individual behavior parameters. Different data channels from household travel surveys, smartphone type devices, global position systems, and sensors can be mapped to different layers of the proposed network structure. We introduce Big data-driven Transportation Computational Graph (BTCG), alternatively Beijing Transportation Computational Graph, as the underlying mathematical modeling tool to perform automatic differentiation on layers of composition functions. A feedforward passing on the HFN sequentially implements 3 steps of the traditional 4-step process: trip generation, spatial distribution estimation, and path flow-based traffic assignment, respectively. BTCG can aggregate different layers of partial first-order gradients and use the back-propagation of “loss errors” to update estimated demand variables. A comparative analysis indicates that the proposed methods can effectively integrate different data sources and offer a consistent representation of demand. The proposed methodology is also evaluated under a demonstration network in a Beijing subnetwork.     

Train rescheduling model with train delay and passenger impatience time in urban subway network

This paper considers the train rescheduling problem with train delay in urban subway network. With the objective of minimizing the negative effect of train delay to passengers, which is quantified with a weighted combination of travel time cost and the cost of giving up the planned trips, train rescheduling model is proposed to jointly synchronize both train delay operation constraints and passenger behavior choices. Space–time network is proposed to describe passenger schedule‐based path choices and obtain the shortest travel times. Impatience time is defined to describe the intolerance of passengers to train delay. By comparing the increased travel time due to train delay with the passenger impatience time, a binary variable is defined to represent whether the passenger will give up their planned trips or not. The proposed train rescheduling model is implemented using genetic algorithm, and the model effectiveness is further examined through numerical experiments of real‐world urban subway train timetabling test. Duration effects of the train delay to the optimization results are analyzed. Copyright © 2017 John Wiley & Sons, Ltd.     

Network traffic control based on a mesoscopic dynamic flow model

The paper focuses on Network Traffic Control based on aggregate traffic flow variables, aiming at signal settings which are consistent with within-day traffic flow dynamics. The proposed optimisation strategy is based on two successive steps: the first step refers to each single junction optimisation (green timings), the second to network coordination (offsets). Both of the optimisation problems are solved through meta-heuristic algorithms: the optimisation of green timings is carried out through a multi-criteria Genetic Algorithm whereas offset optimisation is achieved with the mono-criterion Hill Climbing algorithm. To guarantee proper queuing and spillback simulation, an advanced mesoscopic traffic flow model is embedded within the network optimisation method. The adopted mesoscopic traffic flow model also includes link horizontal queue modelling. The results attained through the proposed optimisation framework are compared with those obtained through benchmark tools.     

Simulation‐based estimates of delays at freeway work zones

Work zone related traffic delay is an important cost component on freeways with maintenance activities. This study demonstrates that delays may be underestimated by using the deterministic queuing theory. Computer simulation is a valuable approach of estimating delay under a variety of existing and future conditions. However, a single simulation run, which can be quite costly in terms of both computer and analyst time, produces a delay estimate for only one traffic level under one set of conditions. A method is developed in this paper to approximate delays by integrating limited simulation data, obtained from CORSIM and the concept of deterministic queuing theory, while various geometric conditions and time‐varying traffic distribution are considered. A calibrated and validated simulation model that can reflect work zone traffic operations on a segment of Interstate 1–80 in New Jersey is used to generate data for developing the proposed model. The comparison of delays estimated by the deterministic queuing model and the proposed model is conducted, while factors affecting the accuracy of the delay estimates are discussed.