Nanjing Metro Research Articles

Scenario-Based Allocation of Emergency Resources in Metro Emergencies: A Model Development and a Case Study of Nanjing Metro

As metro systems are becoming more and more widely used, all kinds of emergencies happen from time to time. A series of cases indicate that inefficient emergency response is a dominating cause of tremendous casualties and losses. The fast and valid allocation of emergency resources after the occurrence of metro emergencies has become a key point in improving the sustainability of metro operations. However, few studies have attempted to determine the allocation of emergency resources in metro emergencies. In this study, considering the unpredictability of different emergency scenarios in the metro system, the scenario-response mode was applied in the resource allocation decision. In this mode, a metro emergency scenario framework was first constructed through the identification of metro emergency elements. Next, a multi-objective model was established for the allocation of emergency resources in the metro emergency rescue process using a scenario-based analysis. The model aims to minimize both the penalty costs due to delays and the sum of allocation costs. The particle swarm optimization algorithm was adopted to solve the model. Eventually, a fire accident scenario at Nanjing Metro was applied to verify the feasibility and validity of the presented model and algorithm. The research results not only enrich and improve metro emergency management theoretically, but also enhance metro emergency rescue ability in practice.

A Carbon Emission Measurement Method for Individual Travel Based on Transportation Big Data: The Case of Nanjing Metro

With the strengthening of environmental awareness, the government pays much more attention to environmental protection and thus implements carbon trading schemes to promote the reduction of global carbon dioxide emissions. The carbon Generalized System of Preferences (GSP) is an incentive mechanism for citizens to value their energy conservation and carbon reduction. Individual travel needs to rely on various means of transportation, resulting in energy consumption. Carbon tax or subsidy can only be carried out after carbon GSP accurately measures individual carbon emissions. The big data acquired from the smart cards of passengers’ travels provide the possibility for carbon emission accounting of individual travel. This research proposes a carbon emission measurement of individual travel. Through establishing the network model of the Nanjing metro with a complex method, the shortest path of the passengers’ travels is obtained. Combined with the origination–destination (OD) records of the smart cards, the total distance of the passengers’ travels is obtained. By selecting the operation table to estimate the carbon emissions generated by the daily operation of the subway system, the carbon emissions per kilometer or per time of passenger travel are finally obtained. With the accurate tracking of carbon emissions for individual travel, the government may establish a comprehensive monitoring system so as to establish a carbon tax and carbon supplement mechanism for citizens.

A Hybrid Spatiotemporal Deep Learning Model for Short-Term Metro Passenger Flow Prediction

The primary objective of this study is to predict the short-term metro passenger flow using the proposed hybrid spatiotemporal deep learning neural network (HSTDL-net). The metro passenger flow data is collected from line 2 of Nanjing metro system to illustrate the study procedure. A hybrid spatiotemporal deep learning model is developed to predict both inbound and outbound passenger flows for every 10 minutes. The results suggest that the proposed HSTDL-net achieves better prediction performance on suburban stations than on urban stations, as well as generating the best prediction accuracy on transfer stations in terms of the lowest MAPE value. Moreover, a comparative analysis is conducted to compare the performance of proposed HSTDL-net with other typical methods, such as ARIMA, MLP, CNN, LSTM, and GBRT. The results indicate that, for both inbound and outbound passenger flow predictions, the HSTDL-net outperforms all the compared models on three types of stations. The results suggest that the proposed hybrid spatiotemporal deep learning neural network can more effectively and fully discover both spatial and temporal hidden correlations between stations for short-term metro passenger flow prediction. The results of this study could provide insightful suggestions for metro system authorities to adjust the operation plans and enhance the service quality of the entire metro system.

Examining the relationship between built environment and metro ridership at station-to-station level

Very few studies have examined the impact of built environment on urban rail transit ridership at the station-to-station (origin-destination) level. Moreover, most direct ridership models (DRMs) tend to involve simple a prior assumed linear or log-linear relationship in which the estimated parameters are assumed to hold across the entire data space of the explanatory variables. These models cannot detect any changes in the linear (or non-linear) effects across different values of the features of built environment on urban rail transit ridership, which possibly induces biased results and hides some non-negligible and detailed information. Based on these research gaps, this study develops a time-of-day origin-destination DRM that uses smart card data pertaining to the Nanjing metro system, China. It applies a gradient boosting regression trees model to provide a more refined data mining approach to investigate the non-linear associations between features of the built environment and station-to-station ridership. Data related to the built environment, station type, demographics, and travel impedance including a less used variable – detour, were collected and used in the analysis. The empirical results show that most independent variables are associated with station-to-station ridership in a discontinuous non-linear way, regardless of the time period. The built environment on the origin side has a larger effect on station-to-station ridership than the built environment on the destination side for the morning peak hours, while the opposite holds for the afternoon peak hours and night. The results also indicate that transfer times is more important variables than detour and route distance.

Analysis of the departure time choices of metro passengers during peak hours

In this study, a stated preference (SP) survey based on a D-efficient experimental design was conducted for the Nanjing Metro to examine the passenger flow and elaborate the heterogeneity of the departure time choice behaviour of metro passengers during peak hours. A latent class logit model was applied to calibrate the data, and the attribute variables were studied using an elasticity analysis. The survey identified four classes of metro passengers in peak hours who have different preferences for the departure time choice. The results show that fixed working hours and arrival time constraints are the major attributes that determine the classification of the passengers, while travel costs and overcrowding are the key factors that affect the departure time choice. However, passengers are more sensitive to metro fares than crowdedness. By reducing travel costs and mitigating overcrowding, passengers’ choice of departure time, especially when deciding whether to depart earlier than usual, was significantly affected. This study aims to provide theoretical support and a basis for decision-making for metro operation departments to enact passenger flow control strategies.

Bilevel Programming for Traffic Signal Coordinated Control considering Pedestrian Crossing

With the rapid development of the subway, more and more people choose it as the main method of transportation. However, practically, the large number of pedestrians near some large metro stations can also correspondingly affect the traffic of motor vehicles on the roads adjacent to the stations. In this study, coordinated control of the traffic signal which considers the pedestrian crossing delay is studied based on this background. Firstly, the model of progression band in adjacent intersections is analyzed comprehensively, and the calculation formulas of progression bandwidth and the delay of vehicles which are from the progression of traffic flow under different conditions are given. Secondly, five different models of pedestrian delay are analyzed. Under different conditions of motor vehicle and pedestrian traffic flow, the Vissim fitting and proofreading are carried out and the optimal models under different conditions are obtained. Finally, the bilevel programming problem which fuses the above two models is determined; by coding an algorithm, it can be resolved. Furthermore, taking eight signalized intersections from Jiming Temple to Daxinggong along Nanjing Metro Line 3 as the actual background, the calculation and optimization of coordinated control are carried out. It is found that at the expense of the traffic efficiency of large intersections to a certain extent, a wider progression band can be formulated on the roads between them, and pedestrian delays can be reduced in general.

Research on Location Optimization of Metro-Based Underground Logistics System With Voronoi Diagram

This paper develops a location optimization method about the metro-based underground logistics system (MULS) to transport freight by metro during off-peak periods. First, we make qualitative and quantitative feasibility analysis of the MULS through questionnaires and field surveys in metro stations. The analysis result shows that more than 85.22% of interviewees support logistics delivery by the metro. An improved $p$ -median model is developed, which considers four influencing factors. The shortest path algorithm is used to minimize the transport costs while the costs of the remaining factors are calculated using the collected data. Then, the Voronoi diagram is adopted to optimize the location of candidate metro stations and redraw the logistics service scope by adding weighted terms. Finally, the Nanjing metro is chosen as a case study to validate the effectiveness of the developed method. The optimization result shows the total cost of the logistics delivery is reduced by 33. 27% suggesting that the method can be used to reduce logistics costs and improve delivery efficiency in urban areas.

Finite Element Analysis of Natural Thawing Heat Transfer of Artificial Frozen Soil in Shield‐Driven Tunnelling

The technology of artificial horizontal freezing method is increasingly being used in the soil reinforcement of urban underground projects such as shield‐driven tunnelling. Compared with the freezing process, the thawing process is more complicated, and the thawing behavior of artificial frozen soil surrounding shield‐driven tunnels has not been well investigated in both the academic and industrial domains. This study, therefore, aims to investigate the natural thawing heat transfer behavior of artificial horizontal frozen soil in shield‐driven tunnelling using a three‐dimensional finite element method. The finite element modelling is based on the horizontal freezing reinforcement project of Chating Station to Jiqingmen Station Tunnel in the Nanjing Metro Line 2. Validation between finite element results and site measured results is firstly conducted. The natural thawing temperature field contours as well as the radial and longitudinal distributions of natural thawing temperature in the frozen soil surrounding the tunnel are then explicitly examined. Furthermore, sensitivity analysis of influencing factors such as the thermal conductivity, latent heat of phase change, ambient temperature inside tunnel, freezing time, and original ground temperature is carried out. The results and findings of this study may enrich the current limited database and enable a better understanding of natural thawing heat transfer behavior of artificial frozen soil in shield‐driven tunnelling.

Analysis of Space-Time Variation of Passenger Flow and Commuting Characteristics of Residents Using Smart Card Data of Nanjing Metro

The rapid development of cities has brought new challenges and opportunities to traditional traffic management. The usage of smart cards promotes the upgrading of intelligent transportation systems, and also produces considerable big data. As an important part of the urban comprehensive transportation system, Nanjing metro has more than 1 million inbound and outbound records of traffic smart cards used by residents every day. How to process these traffic data and present them visually is an urgent problem in modern traffic management. In this study, five working days with normal weather conditions in Nanjing were selected, and the swiping records of the smart cards were extracted, and the space–time characteristics were analyzed. In terms of time analysis, this research analyzed the 24-h fluctuation of daily average passenger flow, peak hour coefficient of passenger flow, 24-h fluctuation of passenger flow on different metro lines, passenger flow intensity on different metro lines and passenger flow comparison at different stations. In spatial analysis, this study uses thermodynamic charts to represent the inflow and outflow of passengers at different stations during early and evening peak periods. The analysis results and visualized images directly reflect the area where Nanjing metro congestion is located, and also shows the commuting characteristics of residents. It can solve the problem of urban congestion, carry out the rational layout of urban functional areas, and promote the sustainable development of people and cities.

Train operation optimization with adaptive differential evolution algorithm based on decomposition

The train operation is a multi‐objective optimization process including several operating indexes, such as safety, punctuality, precision stop, comfort, and low‐energy consumption. The speed profile and timetable for trains should be adjusted correspondingly to satisfy the passengers' demands while minimizing energy consumption. To solve this problem, we propose a multi‐objective optimization approach for train operation. First, we develop a single‐particle model of the train and a multi‐objective optimization model for the train operation, which is subject to the constraints such as safety requirement, passenger comfort, and low energy consumption. Second, to obtain the Pareto frontier of train operation, a uniform design multi‐objective adaptive differential evolution algorithm based on decomposition (UMADE/D) is studied and applied to solve the multi‐objective optimization model for the train operation. Finally, we present numerical examples based on the real‐life operation data from the Nanjing Metro Line 1 in Nanjing, China. Three searching methods, namely, the proposed UMADE/D, Non‐Dominated Sorting Genetic Algorithm, and Multi‐Objective Evolutionary Algorithm based on Decomposition, are implemented to find the Pareto frontier of train operation quickly and efficiently. The simulation results show the efficiency of the proposed UMADE/D algorithm, which can provide corresponding operation strategies and satisfy the multi‐objective demands when the train is in different operation state. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Transportation functionality vulnerability of urban rail transit networks based on movingblock: The case of Nanjing metro

This paper employs system science and complex network theory to abstract the topological structure and to analyze the connectivity of urban rail transit networks. Meanwhile, movingblock technology is applied to calculate the transportation functionality and to investigate the static and dynamic vulnerability based on transportation functionality of urban rail transit networks. Considering Nanjing metro network as example, the results show that the connectivity of Nanjing metro network is very poor. For static failures, Nanjing metro network is very vulnerable when suffering malicious attacks, and the highest load node-based attacks can result in more damages than the largest degree node-based attacks. For dynamic failures, the results show that the transportation functionality becomes larger and larger with the increase of the control parameter of load capacity, which illustrates that the reliability becomes higher and higher with the increase of the construction cost. Therefore, we can declare that there exists a tradeoff between the reliability and construction cost of urban rail transit networks.

Mining Public Opinion on Transportation Systems Based on Social Media Data

Public participation plays an important role of traffic planning and management, but it is a great challenge to collect and analyze public opinions for traffic problems on a large scale under traditional methods. Traffic management departments should appropriately adopt public opinions in order to formulate scientific and reasonable regulations and policies. At present, while increasing degree of public participation, data collection and processing should be accelerated to make up for the shortcomings of traditional planning. This paper focuses on text analysis using large data with temporal and spatial attributes of social network platform. Web crawler technology is used to obtain traffic-related text in mainstream social platforms. After basic treatment, the emotional tendency of the text is analyzed. Then, based on the probabilistic topic modeling (latent Dirichlet allocation model), the main opinions of the public are extracted, and the spatial and temporal characteristics of the data are summarized. Taking Nanjing Metro as an example, the existing problems are summarized from the public opinions and improvement measures are put forward, which proves the feasibility of providing technical support for public participation in public transport with social media big data.

Station-based average travel distance and its relationship with urban form and land use: An analysis of smart card data in Nanjing City, China

Few studies based on large sample data have examined mobility patterns from a travel distance perspective and investigated the potential influence of urban form and land use on people's daily travel distances. This paper provides additional empirical insights into spatiotemporal urban mobility patterns and their relationship with urban form and land use using station-based average travel distances (ATDs). Drawing on smart card data of the Nanjing metro system, land use data and open source points-of-interest (POIs) data, we apply exploratory spatial data and quantile regression analysis to examine distance patterns and explore the potential effects of urban form and land use calculated at different spatial scales (i.e. 800 m, 2 km and 5 km) on the ATDs. By comparing mobility patterns between weekdays and weekends and for different times of day, our findings highlight that ATDs are not uniformly nor randomly distributed in space. Positive spatial autocorrelation is found for different time segments. The results of OLS and quantile regression models show a positive and robust relationship between ATDs and distances to the city center (DCs). The models also prove that land use mix (especially measured at the 2 km and 5 km scale) significantly affects ATDs, supporting the importance of land use mix in decreasing daily travel distances. No significant relationship is found between ATDs and distances to the nearest subsidiary center (DSCs), while the employment/entertainment-residence balance has a marginal effect on ATDs at relatively large spatial scales (i.e. 2 km, 5 km). Consequently, with respect to reducing the ATDs, we recommend enhancing land use mix and reducing the imbalance between employment/entertainment and residence at larger spatial scales. Potential applications and future research directions are discussed. The findings in the present paper are helpful for guiding urban planning and policy making.

Comparison and Selection of Reinforcement Schemes for Shield Tunnelling Close Crossing High-speed Railway Viaduct Group

Numerical simulation is carried out of the group pile foundation project of the shield tunnel on Nanjing metro airport line which crossing Beijing-Shanghai high-speed railway. The paper analysed the characteristics of the horizontal displacement along bridge of the pile foundation during the whole crossing process. On this basis, the reinforcement effects of grouting reinforcement, longitudinal beam and cross bracing reinforcement, bored cast-in-place pile reinforcement are comparative analysed with the horizontal displacement alone bridge of pile as the evaluation index. Also, the feasible program of the shelter pile reinforcement could be determined by combing with the construction process and conditions.

A Flexible Architecture for Extracting Metro Tunnel Cross Sections from Terrestrial Laser Scanning Point Clouds

This paper presents a novel framework to extract metro tunnel cross sections (profiles) from Terrestrial Laser Scanning point clouds. The entire framework consists of two steps: tunnel central axis extraction and cross section determination. In tunnel central extraction, we propose a slice-based method to obtain an initial central axis, which is further divided into linear and nonlinear circular segments by an enhanced Random Sample Consensus (RANSAC) tunnel axis segmentation algorithm. This algorithm transforms the problem of hybrid linear and nonlinear segment extraction into a sole segmentation of linear elements defined at the tangent space rather than raw data space, significantly simplifying the tunnel axis segmentation. The extracted axis segments are then provided as input to the step of the cross section determination which generates the coarse cross-sectional points by intersecting a series of straight lines that rotate orthogonally around the tunnel axis with their local fitted quadric surface, i.e., cylindrical surface. These generated profile points are further refined and densified via solving a constrained nonlinear least squares problem. Our experiments on Nanjing metro tunnel show that the cross sectional fitting error is only 1.69 mm. Compared with the designed radius of the metro tunnel, the RMSE (Root Mean Square Error) of extracted cross sections’ radii only keeps 1.60 mm. We also test our algorithm on another metro tunnel in Shanghai, and the results show that the RMSE of radii only keeps 4.60 mm which is superior to a state-of-the-art method of 6.00 mm. Apart from the accurate geometry, our approach can maintain the correct topology among cross sections, thereby guaranteeing the production of geometric tunnel model without crack defects. Moreover, we prove that our algorithm is insensitive to the missing data and point density.

Anomaly Detection of Passenger OD on Nanjing Metro Based on Smart Card Big Data

Urban metro alleviates traffic pressure and also faces safety management problems. The metro AFC (Automatic Fare Collection System) records the OD (Origin-Destination) data of passengers’ daily trips. Many researches often neglect the pretreatment of data cleaning based on smart card data. Anomaly OD records also reflect the safety problems. How to use OD to identify anomalous data and passengers’ anomalous behavior is a research hotspot of metro big data. OD data of Nanjing metro were analyzed, and standard data cleaning processes were proposed including inbound records until the day before yesterday, inbound records of next days, negative records and overtime records. Then, using the data after cleaning, we analyze long-time records, short-time records, inbound and outbound records between the same stations, the swiping card records of more times, and carry out analysis. One day is chosen as an example to illustrate the analysis process, and then the OD records of several days are compared to summarize the classification of OD anomalies. Through analysis, OD anomalies can be classified into two categories: system anomalies and passenger behavior anomalies. System anomalies can be eliminated by upgrading. Abnormal passenger behavior reflects some potential safety problems. This research can effectively identify the abnormal behavior of passengers by tracking and comparing the appearing frequency of passenger cards. OD anomaly classification can be further refined, so that it has more practical value, can improve the level of metro safety management.

Site Measurement and Study of Vertical Freezing Wall Temperatures of a Large‐Diameter Shield Tunnel

When a large‐diameter shield tunnel boring machine enters or exits a tunnel, the newly exposed tunnel face is prone to instability and water seepage. In order to prevent collapse of the tunnel face, local ground improvement can be used until the permanent tunnel lining can be installed. The tunnel launching project of the Nanjing Metro Line 10 cross‐river tunnel had a high stability requirement for the entry and exit phases. To this end, this project used a combination of cement treatment and ground freezing methods. In this project, field measurement of the vertical freezing improvement of the large‐diameter shield tunnel was carried out. The temperature distribution and ground surface deformation of the vertical frozen soil wall at the end of the tunnel during the active freezing and maintenance freezing periods were analyzed in detail. The result shows that the surface settlement and seepage were successfully controlled by the combined cement treatment and ground freezing. On the other hand, the combination of cement treatment and ground freezing helps to control the freezing‐induced heaving. The hydration heat in improved ground leads to an increase in ground temperature and this leads to additional freezing duration. It was examined that the frozen soil wall and the enclosure structure were in a good cementation condition. These measured values provide guidance on the timing of the shield departure. The project results confirmed that instability and water permeation did not occur in the tunnel face during the subsequent excavation.

Parameter Selection and Evaluation of Robustness of Nanjing Metro Network Based on Supernetwork

Metro plays an important role in an urban public transport system. With the use of metro lines, the increasing flow of people has brought tremendous pressure to the operation of metro lines, resulting in different faults, thus affecting the travel of residents. How to qualitatively evaluate the robustness of the metro network after encountering faults is a problem worthy of attention. By 2018, ten metro lines have been opened in Nanjing, forming a radiation structure from the urban center to the surrounding suburbs. In this study, the metro faults in Nanjing in the past three years are counted and classified. The space L and space P models for the metro network are constructed. The robustness of a Nanjing metro network is measured by the three indicators: network connectivity efficiency, largest connected subgraph size, and average subgraph size. The concept of supernetwork is proposed, and the metro line is considered as a whole. The robustness changes of the Nanjing metro network caused by the attacks on the nodes and hyperedges of the metro network are analyzed. The results show that deliberate attack causes more damage than a random attack. When traffic hub stations and trunk lines are attacked, the performance of the metro network will decline sharply. The research conclusion has certain practical value to enhance the anti-fault ability of the metro network.

Deformation and Force Numerical Analysis of Deep Foundation Pit in Soil-Rock Dualistic Stratum

Based on the finite element calculation software Plaxis, the numerical simulation of the deep foundation pit of the Nanjing Metro Engineering Second-Bridge-Park Station was carried out. The calculation results were in good agreement with the monitoring values of the surface settlement 5m away from the foundation pit as well as two typical horizontal displacement of the pile, indicating the reliability of the model. The model was used to analyze the soil deformation, surface settlement, pile displacement and pile stress in the soil-rock combination stratum. The results showed that the pile deformation mainly occured in the soil part in the deep foundation pit of soil and rock combination stratum. Moreover, the maximum displacement was below the middle part of the soil part; the maximum surface settlement was located 0.35H away from the pile (H was of excavation depth); the sudden change of the pile body was basically at the boundary between the soil and the rock as well as the bottom part of the pit, which showed that the deformation of the foundation pit of the soil-rock combination stratum was closely related to the thickness of the soil layer and the excavation depth of the foundation pit. Numerical simulation using Plaxis software could provide a proof for the design and construction of foundation pits.

Assessment of metro ridership fluctuation caused by weather conditions in Asian context: Using archived weather and ridership data in Nanjing

This paper aims to assess metro ridership fluctuation caused by weather conditions in an Asian context (Nanjing, China) on metro single line and network levels. The daily ridership data utilized in the study is obtained from Nanjing Metro Agency, while meteorological data is from the Nanjing Meteorology Bureau. To address the main research questions of this paper, time-serials moving average method is extended and refined to define benchmark and to model ridership fluctuation (expressed as ridership residual). On the other hand, analyses of variance (ANOVAs) are introduced to examine meteorological events and temporal effects on ridership residuals. The data and result demonstrates that the impact of meteorological variables on daily ridership fluctuations generally results in a decrease in passengers on single lines and the travel network, especially on weekends. Precipitation related events produce more significant ridership fluctuations than temperature related events. Snowfall related events and large temperature deviations in winter account for the most dramatic changes in ridership. However, seasonality is not a significant factor in meteorological events-ridership residual relationship. This paper contributes to extending research on the weather-ridership relationship around the world especially to refining and extending the nine-term moving average method in this field. This could benefit metro operators by enabling them to add meteorological effects into their ridership prediction and budgeting work.