Search Results (11)

Dockless bike-sharing (DBS) plays a crucial role in solving the “last-mile” problem for metro trips. However, bike–metro transfer usage varies by time and transfer flows. This study explores the nonlinear relationship between the built environment and bike–metro transfer in Shenzhen, considering different times and transfer flows while incorporating spatial dependence to improve model accuracy. We integrated smart card records and DBS data to identify transfer trips and categorized them into four types: morning access, morning egress, evening access, and evening egress. Using random forest and gradient boosting decision tree models, we found that (1) introducing spatial lag terms significantly improved model accuracy, indicating the importance of spatial dependence in bike–metro transfer; (2) the built environment’s impact on bike–metro transfer exhibited distinct nonlinear patterns, particularly for bus stop density, house prices, commercial points of interest (POI), and cultural POI, varying by time and transfer flow; (3) SHAP value analysis further revealed the influence of urban spatial structure on bike–metro transfer, with residential and employment areas displaying different transfer patterns by time and transfer flow. Our findings underscore the importance of considering both built environment factors and spatial dependence in urban transportation planning to achieve sustainable and efficient transportation systems. Full article

The impressed current cathodic protection (ICCP) scheme is a more reliable and efficient method of corrosion prevention mechanism than the sacrificial method. Currently, the grid connected transformer rectifier units supported with a battery banks are used for the ICCP-based corrosion protection system in the desalination plant. This conventional method is entirely grid-dependent, more expensive, and suffers during prolonged grid failure. The present trend of industrialization is the application of multi-renewable energy sources based on a nanogrid to power the station’s auxiliary power supply. This paper introduces a concept of distributed energy resources (DERs) operated integrated nanogrid (ING) system to provide a stable power supply solution to the ICCP scheme. A 100-million-litter per day capacity-based seawater desalination plant (SWDP) in India has been chosen as the test station. The conceptual hardware design and operational logic details for smooth integration of the integrated nanogrid module into the ICCP scheme of the Desalination plant is proposed. This research aims to investigate the behaviour of DERs during on-grid, off-grid and switching over from one mode of operation to another and vice-versa by using the accelerated Gauss–Seidel method in ETAP software (version 16.0.0). The simulation results confirm that the ING suffers from a high-frequency change rate during islanded operation, and in some cases, a complete blackout occurs. A PLC-based Smart Versatile ING Controller has been suggested to overcome the blackout issue. Finally, it has been proven that the stability of an industrial power system can be improved further by introducing the ING module into it. Full article

One of the top concerns for travelers when choosing public transportation is whether they can reach their destination in limited time and monetary cost on the basis of ensured reliability. However, the existing literature shows no studies on how to evaluate bi-objective multimodal accessibility under travel time uncertainty. In order to fill this research gap, this paper creates a multimodal super network based on smart card data in which the transfers among taxi, bus, and subway modes are developed and applied. Next, we propose a two-stage opportunity accessibility model to calculate bi-objective multimodal accessibility under travel time uncertainty. Then we propose a multimodal reliability path finding model and a reliability boundary convergence algorithm to solve this problem. Finally, we conduct a large-scale real-world case study. It is found that the impedance heterogeneity between different modes is significant, and multimodal travel has better accessibility than a unimodal one. Although multimodal accessibility decreases as the reliability increases, the advantage of multimodal over unimodal accessibility increases with reliability, and it can be improved up to 14.61% by multimodal transfers. This model can effectively guide traffic management departments to improve traffic accessibility in terms of time and cost and advise commuters to choose living places. Full article

This article addresses timetable synchronization in public transportation, an important problem in modern smart cities, in order to guarantee a proper quality of service to citizens. Two variants of the bus timetabling synchronization problem considering extended transfer zones are studied: optimizing offsets and optimizing offsets and headways for each line. An exact mixed integer programming and an evolutionary algorithm are developed to solve both problem variants. The algorithms are evaluated on 45 instances of a real case study, the intelligent transportation system of Montevideo, Uruguay. Experimental results reported significant improvements over the current timetable implemented by the city administration. The number of successful synchronizations improved up to 66.6% and 179.9% for the first and second problem variant, respectively. The average waiting times for transfers improved, especially in tight problem instances (up to 57.8% and 158.3% for the first and second problem variant, respectively). The proposed planning methods are useful to help decision makers to configure public transportation systems. Full article

Seoul Metropolitan City’s buses cater to more than 50% of the average daily public transportation use, and they are the most important transportation mode in Korea, together with the subway. Since 2004, all public transportation records of passengers have been stored in Seoul, using smart transportation cards. This study explores the environmental and psychological factors in implementing a smart transportation system. We analyze the switching behavior of traffic users according to traffic congestion time and number of transfers based on public transportation data and show that bus-use behavior differs according to the traffic information of users and the degree of traffic congestion. Information-based switching behavior of people living near bus stops induces people to change routes during traffic congestion. However, in non-congested situations, the original routes are used. These results can guide the formulation of policy measures on bus routes. We made it possible to continuously change the routes for certain buses, which were temporarily implemented due to traffic congestion. Moreover, we added a service that posts the estimated arrival time to major stops while reflecting real-time traffic conditions in addition to the bus location and arrival time information through the global positioning system. Full article

With the introduction of the more electric aircraft, there is growing emphasis on improving overall efficiency and thus gravimetric and volumetric power density, as well as smart functionalities and safety of an aircraft. In future on-board power distribution networks, so-called high voltage DC (HVDC, typically +/−270VDC) supplies will be introduced to facilitate distribution and reduce the associated mass and volume, including harness. Future aircraft power distribution systems will also very likely include energy storage devices (probably, batteries) for emergency back up and engine starting. Correspondingly, novel DC-DC conversion solutions are required, which can interface the traditional low voltage (28 V) DC bus with the new 270 V one. Such solutions presently need to cater for a significant degree of flexibility in their power ratings, power transfer capability and number of inputs/outputs. Specifically, multi-port power-scalable bi-directional converters are required. This paper presents the design and testing of such a solution, addressing the use of leading edge wide-band-gap (WBG) solid state technology, especially silicon carbide (SiC), for use as high-frequency switches within the bi-directional converter on the high-voltage side. Full article

This study explores the relationship between the spatial distribution of relative transfer location (i.e., the location of the transfer point in relation to the trip origin and destination points) and the attractiveness of the transit service using smart card data. Transfer is an essential component of the transit trip that allows people to reach more destinations, but it is also the main factor that deters the smartness of the public transit. The literature quantifies the inconvenience of transfer in terms of extra travel time or cost incurred during transfer. Unlike this conventional approach, the new “transfer location” variable is formulated by mapping the spatial distribution of relative transfer locations on a homogeneous geocoordinate system. The clustering of transfer points is then quantified using grid-based hierarchical clustering. The transfer location factor is formulated as a new explanatory variable for mode choice modelling. This new variable is found to be statistically significant, and no correlation is observed with other explanatory variables, including transit travel time. These results imply that smart transit users may perceive the travel direction (to transfer) as important, in addition to the travel time factor, which would influence their mode choice. Travellers may disfavour even adjacent transfer locations depending on their relative location. The findings of this study will contribute to improving the understanding of transit user behaviour and impact of the smartness of transfer, assist smart transport planning and designing of new transit routes and services to enhance the transfer performance. Full article

A mismatch between staffing ratios and service demand leads to overcrowding of patients in waiting rooms of health centers. Overcrowding consequently leads to excessive patient waiting times, incomplete preventive service delivery and disgruntled medical staff. Worse, due to the limited patient load that a health center can handle, patients may leave the clinic before the medical examination is complete. It is true that as one health center may be struggling with an excessive patient load, another facility in the vicinity may have a low patient turn out. A centralized hospital management system, where hospitals are able to timely exchange patient load information would allow excess patient load from an overcrowded health center to be re-assigned in a timely way to the nearest health centers. In this paper, a machine learning-based patient load prediction model for forecasting future patient loads is proposed. Given current and historical patient load data as inputs, the model outputs future predicted patient loads. Furthermore, we propose re-assigning excess patient loads to nearby facilities that have minimal load as a way to control overcrowding and reduce the number of patients that leave health facilities without receiving medical care as a result of overcrowding. The re-assigning of patients will imply a need for transportation for the patient to move from one facility to another. To avoid putting a further strain on the already fragmented ambulatory services, we assume the existence of a scheduled bus system and propose an Internet of Things (IoT) integrated smart bus system. The developed IoT system can be tagged on buses and can be queried by patients through representation state transfer application program interfaces (APIs) to provide them with the position of the buses through web app or SMS relative to their origin and destination stop. The back end of the proposed system is based on message queue telemetry transport, which is lightweight, data efficient and scalable, unlike the traditionally used hypertext transfer protocol. Full article

The aim of this study is to develop a fast data fusion method for recognizing metro-to-bus transfer trips based on combined data from smart cards and a GPS system. The method is intended to establish station- and time-specific elapsed time thresholds for overcoming the limitations of one-size-fits-all criterion which is not sufficiently convincing for different transfer pairs and personal characteristics. Firstly, a data fusion method with bus smart card data and GPS data is proposed to supplement absent bus boarding information in the smart card data. Then, a model for identifying metro-to-bus interchange trips is derived based on two rules about maximal allowable transfer distance and elapsed transfer time threshold. Finally, in tests that used half-monthly field smart card data and GPS data from Shenzhen, China, the results recognized by the proposed method were more consistent with the actual surveyed group transfer time with a P value of 0.17 determined by Mann–Whitney U test. The comparison analysis showed that the proposed method can be widely applied to successfully identify and interpret metro-to-bus interchange behavior beyond a static transfer time threshold of 30 min. Full article

The primary objective of this study was to explore the factors that influence metro-bikeshare ridership from a spatial perspective. First, a reproducible method of identifying metro-bikeshare transfer trips was derived using two types of smart-card data (metro and bikeshare). Next, a geographically weighted Poisson regression (GWPR) model was established to explore the relationships between metro-bikeshare transfer volume and several types of independent variables, including sociodemographic, travel-related, and built-environment variables. Moran’s I statistic was applied to examine the spatial autocorrelation of each explanatory variable. The modeling and spatial visualization results show that riding distance is negatively correlated with metro-bikeshare transfer demand, and the coefficient values are generally lower at the edge of the city, especially in underdeveloped areas. Moreover, the density of bus, bikeshare, and other metro stations within 2 km of a metro station has different impacts on metro-bikeshare transfer volume. Travelers whose origin or destination is entertainment related tend to choose bikeshare as a feeder mode to metro if this trip mode is available to them. These results improve our understanding of metro-bikeshare transfer spatial patterns, and several suggestions are provided for improving the integration between metro and bikeshare. Full article

Understanding the relationship between short-term subway ridership and its influential factors is crucial to improving the accuracy of short-term subway ridership prediction. Although there has been a growing body of studies on short-term ridership prediction approaches, limited effort is made to investigate the short-term subway ridership prediction considering bus transfer activities and temporal features. To fill this gap, a relatively recent data mining approach called gradient boosting decision trees (GBDT) is applied to short-term subway ridership prediction and used to capture the associations with the independent variables. Taking three subway stations in Beijing as the cases, the short-term subway ridership and alighting passengers from its adjacent bus stops are obtained based on transit smart card data. To optimize the model performance with different combinations of regularization parameters, a series of GBDT models are built with various learning rates and tree complexities by fitting a maximum of trees. The optimal model performance confirms that the gradient boosting approach can incorporate different types of predictors, fit complex nonlinear relationships, and automatically handle the multicollinearity effect with high accuracy. In contrast to other machine learning methods—or “black-box” procedures—the GBDT model can identify and rank the relative influences of bus transfer activities and temporal features on short-term subway ridership. These findings suggest that the GBDT model has considerable advantages in improving short-term subway ridership prediction in a multimodal public transportation system. Full article