Metro Transportation Research Articles

An Assessment of the Dubai Metro Service’s Performance Using SCOR Model and ARENA Simulation

Metro service operations have become challenging in modern urban environments due to the dynamics of population, service levels, accuracy and other operational issues. This research applies the supply chain operations reference (SCOR) model combined with the ARENA model simulation to examine the service performance in the Dubai Metro. The proposed approach takes into consideration the real-time flows of metro service operations and simulates the passengers’ service time in selected terminals. The researchers measure the actual time spent by passengers and estimate various possible scenarios as outcome. The researchers assessed the average time spent in the system and the performance improvement as a visualized outcome, with suggestions for improvements, such as: onboard card recharge, automatic checkout using radio-frequency identification (RFID) systems, integration of systems using the Internet of things (IOT) and blockchain and a dedicated lane system. The proposed recommendations have the potential to contribute to service performance improvement of the metro rail, as Dubai plans for its operational expansion process towards Expo 2020. This research methodology and these results can be extended to metro service operations of other urban centres, to better understand passengers’ behaviour in the future. In view of this, the research contributes to both the theory and practice of travel behaviour in the metro transportation service.

Deep learning based energy efficient optimal timetable rescheduling model for intelligent metro transportation systems

Due to the recent advances in intelligent transportation systems (ITS), Automatic Train System (ATS) gained significant attention among the research community. An effective ATS offers the whole railway network to operate in a safe, cost-effective and proficient manner against sudden disturbances like temporary platform blockages. Numerous Train Timetable Rescheduling (TTR) models have been presented for managing unforeseen events which might disturb the timetable. The main aim of an effective TTR model is to reduce power utilization by consuming the entire benefits of reproductive braking energy under a random situation. In this view, this paper presents a new TTR model to optimize the energy of metro systems by the incorporation of improved genetic algorithm (IGA) and long short term memory (LSTM) based recurrent neural network (RNN). The proposed method incorporates three different models, namely controller, timetable, and energy models. The proposed method requires minimum time to recompute a new schedule and offers effective solutions instantly after a random disturbance happens. The performance validation of the proposed IGSA-LSTM model is simulated using Chennai Metro Train Station. The proposed method significantly reduces the energy consumption of metro train and reaches to a minimum average energy utilization of 696 kWh.

Using differential pricing to mitigate the impact of congestion on metro: a big data study base on Shanghai metro

Metro, which is one of the most popular way of public transportation, has shown inability to withstand the high intensity of congestion presented in the first two decades of the new millennia. Despite the effort made by government which includes adding multiple metro line, the situation is still grievous. Unlike other form of transportation such as train or airplane, the ridership of metro wasn’t staggered and can be manipulated. In this paper, we employ differential pricing to alleviate traffic pressure on metro during the peak hours. As people have different elasticity of demand for metro transportation in different time interval, we can reduce the number of passengers who relatively treat metro transportation as unnecessary in specific time interval and place by setting up different price. Base on the data of shanghai metro, we show different aspects in our model in which we use system clustering, optimization model of social welfare and calculate an acceptable range of price using Ramsey pricing model. We validate our solution, using the agent simulation model, to be considerably capable at easing the traffic pressure of metro, whether comparably or statistically.

Public transport accessibility and the prices of nearby properties: the case of the first metro line in Warsaw

This paper identifies the relation between metro proximity and the prices of residential properties in Warsaw. The analysis is based on 2006-2013 AMRON-SARFiN data. The results show that metro has a positive impact on property prices if it is located at most 1.5 km from the property. The greatest increase in price of 8-13 per cent is observed when metro is located 400-800 meters from the property. The results indicate that when the metro transportation is poor, it causes a large increase in property prices, which is not comparable to the impact of other transports, such as bus or tram.

Mechanical Structure Design of Underground Logistics System Based on Passenger and Freight Transportation

Urban underground rail transit in China serves people, but at the same time, there is a problem of insufficient utilization of resources. To make more effective use of subway resources and alleviate traffic pressure, aiming at the problem of insufficient use of time and space resources in the process of Metro operation, this paper proposes a logistics system of underground railway based on the underground logistics system of passenger and freight co-transported. On this basis, the mechanical structure design of the system is carried out in the aspects of metro transportation and transformation of the Metro station. Firstly, the paper analyses the shortcomings in the current situation of Metro operation, discusses the underground logistics system of passenger and freight co-transportation, then focuses on the mechanical structure design of the system, and uses SolidWorks to simulate and analyze the mechanical structure to ensure the feasibility of the system and improve the utilization rate of Metro resources.

Establishment and Analysis of the Supernetwork Model for Nanjing Metro Transportation System

In recent years, many researchers have applied complex network theory to urban public transport network to construct complex network and analyze its network performance. The original analysis method generally uses the Space L and Space R model to establish a simple link between public sites but ignores the organic link between the overall network system and the line subsystem. As an important part of urban public transport system, subway plays an important role in alleviating traffic pressure. In this paper, a supernetwork model of Nanjing metro network is established by using the supernetwork method. Three parameters, node-hyperedge degree, hyperedge-node degree, and hyperedge degree, are proposed to describe the model. The model is compared with the traditional Space L and Space P models. The study on the supernetwork model of Nanjing metro complex network shows that the network density, network centrality, and network clustering coefficient are large, and the average network distance is small, which meets the requirements of traffic planning and design. In this study, the subway line is considered as a subsystem and further simplified as a node, so that the complex network analysis method can be applied to the new supernetwork model, expanding the thinking of complex network research.

Destination selection based on consensus-selected landmarks

This study aims at enhancing the destination look-up experience based on the fact that humans can easily recognize and remember images and icons of a destination instead of texts and numbers. Thus, this paper propose an algorithm to display buildings in hierarchical publicity and optimize the location distribution and orientation of each buildings. In the usual, the general navigation GPS include a lot of redundant information, and the necessary information always being drowned. Aimed to this point, we build the hierarchical structure according to their consensus-based publicity and spacial relationship to each other. The publicity is approximated by considering transportation importance and consensus visibility which reflects public consideration on metro transportation, opinions on popularity and famousness respectively. In addition to this, consensus-based optimal orientation of icon is optimized for easy recognition according to public preference estimated by clustering the view of public web photos. For the system evaluation, we perform four user studies to verify the effect of recognition and destination searching, and we all get positive response from these user studies.

PLANNING THE RAILS AND THEIR INTEGRATION IN THE CITY OF SALVADOR-BAHIA (2011-2016)

Este artigo analisa o planejamento dos trilhos (trem e metrô) na cidade de Salvador no período de 2011 a 2016 e sua relação com os outros sistemas de transporte. Para isso foi feita a seguinte pergunta: - Quanto foi feito do planejamento do transporte met

Social capital as a design parameter for product-service system design - Based on case study of the fare evasion problem in metro transportation -

Social capital as a design parameter for product-service system design - Based on case study of the fare evasion problem in metro transportation -