Comprehensive Transportation Hub Research Articles

Hub Traveler Guidance Signage Evaluation via Panoramic Visualization Using Entropy Weight Method and TOPSIS

Signage functions as guidance and distribution assistance, directly affecting the operational efficiency of traffic in and around the comprehensive transportation hubs. Among the elements of signage, the visual guidance effect is the key factor affecting the information conveyance, which should be evaluated during the design and optimization process. This study conducted field investigations and developed panoramic videos for multiple transportation hubs in China and designed a survey accordingly. Human subjects were recruited to watch panoramic videos via virtual reality (VR) and respond to the surveys. The results show that the degree of visual attention of travelers significantly affects the evaluation results of guidance signage, with the influence being inversely proportional. Key factors affecting visual attention include accurate legibility, obstruction and defacement rates, informativeness, and whether signage is set up in a hierarchical manner. In unfamiliar environments, travelers focus on the overall context and closely observe the interaction between directional signs and their surroundings. The prominence and visibility of signage are influenced by interactions within the spatial environment. Notably, simple and clear signs are more likely to attract travelers’ attention, and their directional information is more easily comprehended. Moreover, when the destination is clearly defined, visual attention significantly directs pedestrians’ wayfinding behavior.

A group decision-making model for architectural programming in megaprojects

PurposeDue to the complexity and diversity of megaprojects, the architectural programming process often involves multiple stakeholders, making decision-making difficult and susceptible to subjective factors. This study aims to propose an architectural programming methodology system (APMS) for megaprojects based on group decision-making model to enhance the accuracy and transparency of decision-making, and to facilitate participation and integration among stakeholders. This method allows multiple interest groups to participate in decision-making, gathers various perspectives and opinions, thereby improving the quality and efficiency of architectural programming and promoting the smooth implementation of projects.Design/methodology/approachThis study first clarifies the decision-making subjects, decision objects, and decision methods of APMS based on group decision-making theory and value-based architectural programming methods. Furthermore, the entropy weight method and fuzzy TOPSIS method are employed as calculation methods to comprehensively evaluate decision alternatives and derive optimal decision conclusions. The workflow of APMS consists of four stages: preparation, information, decision, and evaluation, ensuring the scientific and systematic of the decision-making process.FindingsThis study conducted field research and empirical analysis on a practical megaproject of a comprehensive transport hub to verify the effectiveness of APMS. The results show that, in terms of both short-distance and long-distance transportation modes, the decision-making results of APMS are largely consistent with the preliminary programming outcomes of the project. However, regarding transfer modes, the APMS decision-making results revealed certain discrepancies between the project's current status and the preliminary programming.Originality/valueAPMS addresses the shortcomings in decision accuracy and stakeholder participation and integration in the current field of architectural programming. It not only enhances stakeholder participation and interaction but also considers various opinions and interests comprehensively. Additionally, APMS has significant potential in optimizing project performance, accelerating project processes, and reducing resource waste.

Experiments and Numerical Simulations for the Intersecting Joints of the Steel Structure of Shenzhen Universiade Comprehensive Transportation Hub Station

Experiments and Numerical Simulations for the Intersecting Joints of the Steel Structure of Shenzhen Universiade Comprehensive Transportation Hub Station

Research on the Optimal Design of Retaining Piles of a Wide Metro Tunnel Foundation Pit Based on Deformation Control

Engineers pay more and more attention to the economic benefits of foundation pit engineering. At present, the optimal design of the foundation pit supporting structure mainly focuses on strength and functional design, and there is no mature theoretical design method for deformation control. In this paper, a method for calculating the overall deformation of a foundation pit supporting structure based on the principle of minimum potential energy is proposed. Based on this method, the optimal design of the foundation pit of Guangzhou Baiyun District Comprehensive Transportation Hub Metro Station is realized. The deformation calculation results and optimization design scheme are validated by finite element numerical simulation and field monitoring data. The results show that the proposed theoretical algorithm predicts the pile deformation curves better than the finite element method, suggesting the proposed theoretical method is reasonable and the optimization scheme of the retaining pile is feasible. In the optimized design, the deformation of the foundation pit retaining pile is controlled by its push-back effect. The proposed deformation calculation method can realize the overall deformation calculation of the foundation pit supporting structure.

Model for Intercity Railway Schedule Optimization Incorporating Metrorail Transfers

The promotion of multimodal coordination is of great significance for the joint development of diverse urban transportation systems. Focusing on a comprehensive urban passenger transport hub that converges both intercity modes and multiple inner-city modes, our study aims to incorporate intercity railway and Metrorail coordination into train scheduling optimization to enhance transfer efficiency and provide a seamless service for passengers in urban railway networks. By considering the variety of passenger demands in different transport modes (e.g., rail transit and traditional mainline railway), train loading capacity, and potential disruption scenarios, we specifically developed a mixed-integer nonlinear programming (MINLP) model to simultaneously generate the coordination strategies, arrival/departure times of trains at each station, and the number of carriages in service in the network. To enhance computational efficiency, we proposed several improvement strategies involving the model linearization to reformulate the MINLP model into a mixed-integer linear programming (MILP) model and the determination of appropriate big- M values. Finally, numerical experiments based on historical passenger data from a realistic urban railway network in China were implemented to verify the effectiveness of our approach. The results demonstrate that our intercity railway and Metrorail coordination strategies could, in practice, significantly improve passenger transfer efficiency by over 35% compared with the train schedule without coordination.

Mechanical Properties of Inclined Steel-Reinforced Concrete Column Structure of Shenzhen Huangmugang Comprehensive Transportation Hub

Mechanical Properties of Inclined Steel-Reinforced Concrete Column Structure of Shenzhen Huangmugang Comprehensive Transportation Hub

A study on eye movement test and visuospatial optimization of wayfinding perception in large-scale comprehensive transportation hubs

Abstract The integration of rail transit stations and the surrounding underground space presents volume scale and functional complexity, and it has gradually formed a complex integrated transportation hub. Wayfinding inside its space is also more difficult, and the behavioral phenomena of passengers stopping, wandering, and getting lost are common. This paper uses station A of a large transportation hub as an example. It combines target detection technology and the optical flow method, designs the traffic space guidance system, tests how well passengers can find their way by moving their eyes, and then looks at how the visual space can be improved in terms of color, comfort, and subjective comfort after getting feedback. The data from the passenger eye-movement test reveals that during the sub-processes of information perception and elevator path selection, the logo is the primary focus, with attention ratios of 72.35% and 61.28%. Orange, yellow, and green were the three colors that received the highest ratings for subjective spatial comfort from passengers, with ratings of 0.58, 0.55, and 0.35, respectively, which are data-supported for visuospatial optimization.

Study on the Influence of Excavation of Superlarge and Ultra-Deep Foundation Pits on the Pile Foundation of Existing Viaducts

The rapid development of urban above- and underground transportation has brought an increasing number of deep foundation pit projects that close to existing urban viaducts. Excavation of the deep foundation pit projects leads to soil movement around the pile foundation, which adversely affects the adjacent existing pile foundation and seriously threatens the operation safety of the adjacent existing viaduct. In this paper, the three-dimensional numerical model of foundation pit excavation, viaduct, and pile foundation was established by using the MIDAS GTS against the background of the basement foundation pit project in the new Guangzhou Baiyun Station comprehensive transportation hub building, production, and life complex, where the interaction between foundation pit excavation and viaduct pile foundation was simulated. The influence of various excavation-related factors and different parameters of the pile foundation on lateral displacements of the pile body adjacent to the existing pile foundation was analyzed. The variables controlled in the numerical model included the different excavation depths of the foundation pit, the distance between the excavation surface and the adjacent pile foundation, the spatial effect of different excavation sequences, the diameter of the pile that adjacent to the existing pile foundation, and the elastic modulus of the bored occlusal pile support structure. The results indicated that the lateral displacement of the pile body of the bridge pile foundation was significantly affected by the excavation of the deep foundation pit. The excavation depth exerted the greatest influence on the lateral displacement of the pile foundation, followed by the distance between the pile foundation and the excavation surface, the excavation sequence of the foundation pit, and the elastic modulus and the diameter of the bored occlusive pile support structure. Among them, the pile foundation located at the corner of the foundation pit was negligibly affected by these influencing factors. The findings in this study can provide valuable experiences for similar projects.

Dynamic Optimization of Construction Time-Cost for Deep and Large Foundation Pit Based on BIM Technology and Genetic Algorithm

With the increasingly fierce market competition, optimizing the construction time-cost of deep and large foundation pit construction projects has become one of the key factors for construction enterprises to remain invincible. By dynamically optimizing the time-cost, the optimal time corresponding to the lowest engineering cost can be found. Based on a comprehensive transportation hub project, considering the time value of capital and the reward and punishment of construction time, a time-cost dynamic optimization model is constructed. Relying on BIM technology, the feasibility of construction plan is analyzed from both qualitative and quantitative perspectives, and the project parameters and resource information is obtained accurately and quickly. Using the MATLAB program, time-cost optimization based on genetic algorithm is carried out, and the static and dynamic optimization results are compared. The results show that the dynamic optimization scheme reduces the total cost by 1.68% while reducing the total construction time by 8.47%. The dynamic optimization scheme extends the construction period by 2 days while reducing the total cost by 89,500 yuan compared to static optimization. The peak value of the fund demand curve before and after optimization has decreased from 128,000 yuan to 127,000 yuan. The time-cost dynamic optimization, considering the time value of capital is more in line with engineering reality, and the optimization results are more reliable and accurate. BIM technology can accurately and quickly obtain project parameters and resource information, solving problems such as complex processes in super deep excavation and huge engineering data statistics. The genetic algorithm can efficiently and accurately search for the optimal solution within the global domain. This study combines BIM technology with the genetic algorithm to solve the dynamic optimization problem of construction period cost for deep and large foundation pits. The research results of this study provide a theoretical reference for the optimization of schedule cost for similar projects.

Low-Carbon Emission Demolition of an Existing Urban Bridge Based on SPMT Technology and Full Procedure Monitoring

Due to the need for comprehensive transportation hub construction, an existing bridge in a bustling urban area with an operation duration of 25 years was required to be demolished. Based on Life Cycle Assessment (LCA), this paper proposes a scheme of "Self-propelled modular transporter (SPMT) technology + large segment cutting" to compare the carbon emissions of demolition schemes qualitatively and quantitatively. To ensure structural safety during demolition, the finite element analysis was used to simulate the entire demolishing process, and measuring points were set up to monitor the deformation of the main girder in real time under various demolition conditions. The results indicate that the scheme of SPMT has the lowest carbon emissions during the demolition stage. Additionally, the long-term prestress loss shall be considered when demolishing existing bridges; the suggested 25% proportional value for the long-term prestress loss of the Caitian Bridge is appropriate, which is determined by comparing the calculated results from various formulas. The values of the calculated and measured deformations of the main girder under different working conditions are in good agreement, with errors mostly within 10% and a maximum of no more than 14.7%. The demolition of the entire bridge was completed in a total of 28 h with little noise and pollution, and the impact on daily traffic was avoided, proving that the proposed “SPMT technology + large segment cutting” scheme is safe, efficient, and achieves the goal of green, environmentally friendly, and rapid demolition.

Feeder Bus Timetabling Optimization for High-Speed Railway Station with Uneven Departure Interval

This paper proposes a bus timetable with uneven departure interval, which is mainly used to optimize the bus timetable at high-speed railway stations. The railway comprehensive transportation hub is an important node for the connection between the internal and external transportation of the city. Efficient transfer efficiency can not only improve the travel satisfaction of passengers, but also enable public transport enterprises to retain passenger flow in the competition with rail enterprises. Therefore, this paper analyzes the travel time distribution law of railway passenger transfer to public transport, constructs a timetable optimization model that adapts to the passenger flow law, and uses genetic algorithm to solve it. The optimization results show that, without changing the departure frequency, the waiting time of passengers in peak hours using the uneven departure interval mode is reduced by 29.6%, and the waiting time in average peak hours is reduced by 16.2%. If the departure frequency is changed, the waiting time of passengers in the uneven departure interval mode will also be shorter than that in the equal time departure mode.

Forecast of Short-Term Passenger Flow in Multi-Level Rail Transit Network Based on a Multi-Task Learning Model

With the refinement of the urban transportation network, more and more passengers choose the combined mode. To provide better inter-trip services, it is necessary to integrate and forecast the passenger flow of multi-level rail transit network to improve the connectivity of different transport modes. The difficulty of multi-level rail transit passenger flow prediction lies in the complexity of the spatiotemporal characteristics of the data, the different characteristics of passenger flow composition, and the difficulty of research. At present, most of the research focuses on one mode of transportation or the passenger flow within the city, while the comprehensive analysis of passenger flow under various modes of transportation is less. This study takes the key nodes of the multi-level rail transit railway hub as the research object, establishes a multi-task learning model, and forecasts the short-term passenger flow of rail transit by combining the trunk railway, intercity rail transit and subway. Different from the existing research, the model introduces convolution layer and multi-head attention mechanism to improve and optimize the Transformer multi-task learning framework, trains and processes the data of trunk railway, intercity railway, and subway as different tasks, and considers the correlation of passenger flow of trunk railway, intercity railway, and subway in the prediction. At the same time, a new residual network structure is introduced to solve the problems of over-fitting, gradient disappearance, and gradient explosion in the training process. Taking the large comprehensive transportation hub in Guangzhou metropolitan area as an example, the proposed multi-task learning model is evaluated. The improved Transformer has the highest prediction accuracy (Average prediction accuracy of passenger flow of three traffic modes) 88.569%, and others methods HA, FC-LSTM and STGCN are 81.579%, 82.230% and 81.761%, respectively. The results show that the proposed multi-task learning model has better prediction performance than the existing models.

Assessment and mitigation of railway-induced environmental vibrations over underground comprehensive transportation hub

With the development of railway networks, a new infrastructure integrating the underground comprehensive transportation hub and building complex (UCTH&BC) is constructed in many metropolitan cities. However, there is no relevant research to analyse its railway-induced environmental vibrations and propose an appropriate mitigation measure for such a large structure. To have a comprehensive assessment and satisfying control of the potential environmental vibration problem during the life-cycle of UCTH&BC, a numerical study of a newly-built UCTH&BC was carried out through a time-frequency method based on transfer function theory. The ground and building vibrations were firstly evaluated to have a better understanding of vibration transmission and distribution characteristics. Furthermore, rubber mat floating slab tracks (RMFST) were optimised to propose a suitable mitigation measure. Results show that if adopting ordinary track structures, the ground vibrations in the regions where train-induced vibrations transmit directly through columns exceeded the standard limit seriously by more than 5 dB, while the nearby building vibrations were acceptable. The RMFST with the stiffness of 0.011 N/mm3 was recommended to efficiently reduce vibrations by more than 10 dB, ensuring environmental vibrations in the UCTH&BC satisfy the relevant standard requirement and provide a sufficient safety margin to deal with worse track conditions.

Construction of Risk Control Decision-Making Model Platform for Transportation Hub Projects under the Background of Message Technique

With the acceleration of urbanization, the construction and operation of comprehensive transportation hub have promoted the development of regional economy. However, due to its huge scale, high building density, and crowded public space, the safety status of the comprehensive transportation hub is worrying. As the node of various transportation modes, the efficient operation of the transportation system is closely related to it, but many potential risks threaten the operation safety of integrated transportation hub all the time. Therefore, risk management is an important work to ensure the safe operation of integrated transportation hub. With the deepening of technology application, the application scope of information technology has also been expanded to complete the analysis and simulation of technical scheme and construction organization process, find problems in time, and take preventive measures, so as to optimize the design scheme, reduce unnecessary losses, and speed up the construction progress. In this study, information technology is used to construct the risk control decision model of transportation hub project. According to the research, the change of the target value of the algorithm in this study is 29% better than that of the traditional algorithm, and it can get better results and get the optimal solution quickly when applied to the intelligent traffic dispatching management system.

Do passengers feel convenient when they transfer at the transportation hub?

Passengers’ perceptions play an important role in the evaluation of transfer efficiency for a transportation hub. However, there are many ways to transfer between hubs and urban traffic, and passengers who use different transfer modes may have different perceptions of the same hub. This paper adopts a case study of the Nanjing South Comprehensive Transport Hub in China to identify the main barriers to intermodal integration from a people-centered perspective. A total of 833 questionnaires were collected to reflect passengers' perceptions of interchange services. Combined with observational investigations, we mainly consider factors such as the comfort of the transfer process, the frequency of departures, the route to the ticket office, and the location of the entrances to different urban transportation modes. A Rasch model is established based on the perceptions of inconvenience in passenger transfers. The model comprehensively evaluates intermodal transport services between the hub and urban traffic from the perspective of passengers. According to the results, there are significant differences for different interchange modes, and the factors that cause these differences are heterogenous. In addition, the results show that transfer facilities for metro and cars urgently need improvement due to their greater ridership. Finally, recommendations are given to planners and policy makers by considering the transfer demands of different passenger groups.

Departure efficiency evaluation of a comprehensive transport hub based on Wi-Fi probe data and a multilayer hybrid model.

Evaluation of the passenger departure efficiency of a comprehensive transport hub is essential for traffic managers. Through the evaluation, security risks in the hub can be found in time to ensure the safe departure of passengers. The attention of existing studies has focused on the analysis of the overall situation of the hub, and the quantitative description of departure status in different connection areas inside the hub is insufficient. In this study, a multilayer hybrid model based on an analytic hierarchy process and entropy weight method was established. The data collected using Wi-Fi probe technology were clustered by a K-means algorithm. The first level of the model was divided according to the connection areas of the passenger hub, and the second level was based on the number of stranded people, wait time and departure time in each connection area. It was found that the SP index has the greatest impact on departure efficiency. In addition, the impact of passenger flow aggregation on each connection area is different, and the management department should treat it accordingly. The applicability of the proposed multilayer hybrid model was verified in the example of the Chongqing north railway station.

Strategic Learning and Knowledge Management of Technological Innovation in Safety Evaluation Planning of Construction Projects

The safety evaluation of construction projects is a very important problem. In the current study, the new smart methods especially for the complexity and variability of construction safety evaluation are absent. Combined with the engineering examples, this paper analyzes the sensitive factors that affect the construction project safety and makes discretizating of influencing factors based on expert and BIM technique. Based on BIM and Bayesian network, this paper established a new construction project safety evaluation model and presented the hybrid methods of strategic learning and knowledge management of technological innovation in construction project safety evaluation. Combined with the example of underground traffic engineering of Zhengzhou city comprehensive transportation hub, the Bayesian network was used to predict its security level. The probability of the safety level of the project in grade 3 is 0.614. Compared to other evaluation methods, presented hybrid method is more intelligent in strategic learning and knowledge management of technological innovation. Through the Bayesian network sensitivity analysis, we can know that the sensitivity factor of the construction project safety in the project is the construction risk, the continuous operation time, the protective measures, the material risk, and the number of maintenance. Presented detailed computational methods and steps in this paper can be used to improve the level of construction project safety effectively and help construction managers to take more effective control measures to prevent or reduce the occurrence of security incidents.

Two-Step Optimization of Urban Rail Transit Marshalling and Real-Time Station Control at a Comprehensive Transportation Hub

Urban rail transit connecting with a comprehensive transportation hub should meet passenger demands not only within the urban area, but also from outer areas through high-speed railways or planes, which leads to different characteristics of passenger demands. This paper discusses two strategies to deal with these complex passenger demands from two aspects: transit train formation and real-time holding control. First, we establish a model to optimize the multi-marshalling problem by minimizing the trains’ vacant capacities to cope with the fluctuation of demand in different periods. Then, we establish another model to control the multi-marshalling trains in real time to minimize the passengers’ total waiting time. A genetic algorithm (GA) is designed to solve the integrated two-step model of optimizing the number, timetable and real-time holding control of the multi-marshalling trains. The numerical results show that the combined two-step model of multi-marshalling operation and holding control at stations can better deal with the demand fluctuation of urban rail transit connecting with the comprehensive transportation hub. This method can efficiently reduce the number of passengers detained at the hub station as well as the waiting time without increasing the passengers’ on-train time even with highly fluctuating passenger flow.

Impact analysis of energy‐related carbon emission in Chongqing based on logarithmic mean division index

AbstractThe greenhouse effect has become the focus of global research attention in recent years. As a major carbon emitter, China has made great efforts to reduce carbon emissions. Chongqing, located in southwest China, is a comprehensive transportation hub in southwest China and the largest industrial and commercial hub in the west of the city and the Yangtze River economic belt. The purpose of the article is to investigate the impact analysis of the energy‐related carbon emission in Chongqing. And the logarithmic mean division index is employed to explore the contributor level of population, energy efficiency, energy structure and economic development to the total carbon emissions in Chongqing. The study reveals that economic development was the main driving factor affecting carbon emissions in Chongqing, and energy efficiency was the main factor in the decline of carbon dioxide emissions. Both factors increase over time. Population and energy structure have little effect on carbon emissions in Chongqing. Population factors have always played a driving role in carbon emissions, and the contribution of energy structure to carbon emissions is not obvious in the analysis of results. The findings of the study provide a valuable reference for the government to formulate related low policies and plans for carbon emissions mitigation.

Transportation organization design of Tangshan West Comprehensive Passenger Terminal

Tangshan West Comprehensive Passenger Terminal is an important passenger terminal of Tangshan West Railway Station. The purpose of this paper is to make a scientific and reasonable transportation organization design for Tangshan West Comprehensive Passenger Terminal Station, in order to improve the passenger travel service capacity of Tangshan West Comprehensive Passenger Terminal Station, and provide a good travel experience for the passengers. Based on the analysis and introduction of the internal structure of Tangshan West Comprehensive Transportation Hub Station, the paper designs the traffic organization of Tangshan West Comprehensive Transportation Hub Station according to the existing design scheme. The author through to the passenger flow and traffic flow, traffic flow data of field investigation, and analyzes the passenger’s behavior characteristics, and after consulting relevant literature, calculate and determine the passenger’s travel of the law on passenger station may arrived. At the end of the article, the passenger emergency evacuation plan is proposed and the specific implementation content is designed according to the corresponding situation.