Measuring Crowdedness between Adjacent Stations in an Urban Metro System: a Chinese Case Study

Jiao, Liudan; Shen, Liyin; Shuai, Chenyang; Tan, Yongtao; He, Bao‐Jie

doi:10.3390/su9122325

Cited by 14 publications

(7 citation statements)

References 31 publications

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“…Along with Guangzhou's rapid economic growth, its urban rail network has been progressively constructed since 1993. By the end of 2013, the mileage of the Guangzhou Metro reached 250.11 km, serving most of the city's urban areas [4,40]. Foshan, located close to Guangzhou, is connected to its neighbor via highways and railways.…”

Section: Study Areamentioning

confidence: 99%

“…The concentration of population in urban regions creates increasing pressures on urban and regional traffic systems [3]. As a rapid and efficient form of transportation, rail transit (i.e., metro rail and light rail) played a significant role in alleviating traffic congestion and promoting sustainable development of urban traffic system [4][5][6][7]. Many large cities in China region.…”

Section: Introductionmentioning

confidence: 99%

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Spatial and Temporal Dynamics of Urban Expansion along the Guangzhou–Foshan Inter-City Rail Transit Corridor, China

et al. 2018

Sustainability

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Understanding the urban expansion process along inter-city rail transit corridors is critical to regional integration of city groups. Though numerous studies have considered the influences of rail transit on land use and urban form, most have focused on local station areas or intra-city urban structures. Few studies have examined the effects and dynamic process along inter-city rail transit corridors at a regional scale. In this study, multi-remote sensing images, landscape metrics and gradient analysis were combined to investigate the spatial and temporal dynamics of urban expansion and regional structural changes along the GuangFo inter-city Metro in the Pearl River Delta, south China. We introduced Thiessen Polygon into quadrat zoning for landscape gradient analysis, and clearly revealed the spatial variations of landscape changes along the metro transect. The regional expansion stage and inter-city structural changes were further detected based on the theoretical framework of diffusion-coalescence growth. This study revealed that during its construction the GuangFo Metro significantly impacted urban expansion at the urban fringes. Before construction the urban patches became irregular and fragmented as the gradient moved from city centers to city fringes. Influenced by the GuangFo Metro, the urban patches expanded and consequently coalesced into a homogenous urbanized area, which indicated that coalescence was the dominant expansion stage and the regional structure become more aggregated. This suggested that the inter-city rail transit has played an important role in promoting the integration of the GuangFo metropolitan region.

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Section: Study Areamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Dynamics of Urban Expansion along the Guangzhou–Foshan Inter-City Rail Transit Corridor, China

et al. 2018

Sustainability

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“…The Rapid Transit, or urban metro, System has been an extremely important component in urban infrastructures [8][9][10] and plays an essential role in the development of cities. According to statistics and prior studies, there are about 213 cities around the world that have deployed MRT Systems since the first line opened in 1863 in London [11].…”

Section: Literature Reviewmentioning

confidence: 99%

Mass Rapid Transit System Passenger Traffic Forecast Using a Re-Sample Recurrent Neural Network

Chiu

Hsieh

et al. 2019

Journal of Advanced Transportation

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In this study, we developed a model re-sample Recurrent Neural Network (RRNN) to forecast passenger traffic on Mass Rapid Transit Systems (MRT). The Recurrent Neural Network was applied to build a model to perform passenger traffic prediction, where the forecast task was transformed into a classification task. However, in this process, the training dataset usually ended up being imbalanced. To address this dataset imbalance, our research proposes re-sample Recurrent Neural Network. A case study of the California Mass Rapid Transit System revealed that the model introduced in this work could timely and effectively predict passenger traffic of MRT. The measurements of passenger traffic themselves were also studied and showed that the new method provided a good understanding of the level of passenger traffic and was able to achieve prediction accuracy upwards of 90% higher than standard tests. The development of this model adds value to the methodology of traffic applications by employing these Recurrent Neural Networks.

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“…Rapid urbanisation is accompanied by large pressure on environmental and social sustainability (Bibri & Krogstie, 2017; Neirotti, De Marco, Cagliano, Mangano, & Scorrano, 2014). As a large‐capacity and green means of transportation, urban rail transit systems play a significant role in alleviating traffic congestion and promoting sustainable urban systems (Cao & Schoner, 2014; Hurst & West, 2014; Jiao, Shen, Shuai, Tan, & He, 2017). Over the past decades, many developed countries have established a considerable scale of urban rail transit, and the rapidly growing developing nations' major cities are constructing urban rail transit systems to cope with urban traffic problems (Ingvardson & Nielsen, 2018).…”

Section: Introductionmentioning

confidence: 99%

Analysis of passenger flow characteristics and their relationship with surrounding urban functional landscape pattern

Liu

Tang

et al. 2020

Transactions in GIS

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The passenger flow characteristics of rail transit stations and their relationship with surrounding urban space play an important role in urban planning and transit‐oriented development policies. However, passenger flow data are high‐dimensional and complex, and corresponding characteristics are difficult to extract. Moreover, the integration of natural, social and economic factors in urban space may satisfactorily explain passenger flow characteristics. In this study, we clustered stations with passenger flow by using a dynamic time warping (DTW) distance‐based affinity propagation (AP) algorithm. We introduced the urban functional landscape to reveal the urban space surrounding the station by landscape metrics. Then, we explored the relationship between passenger flow characteristics and urban functional landscape pattern. The DTW distance‐based AP algorithm method identified passenger flow characteristics under total, inbound and outbound conditions, with cluster numbers of 3, 5 and 5, respectively. With the distance from the station, the proportion of natural landscape increased (from 26.11 to 36.62%), whereas that of socioeconomic landscape decreased (from 59.87 to 51.57%). The multivariate regression analysis indicated that types of urban functional landscape had significant influence on the passenger flow characteristics in different accessible areas of the station. These findings highlighted the effect of urban functional landscape pattern on passenger flow.

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Measuring Crowdedness between Adjacent Stations in an Urban Metro System: a Chinese Case Study

Cited by 14 publications

References 31 publications

Spatial and Temporal Dynamics of Urban Expansion along the Guangzhou–Foshan Inter-City Rail Transit Corridor, China

Spatial and Temporal Dynamics of Urban Expansion along the Guangzhou–Foshan Inter-City Rail Transit Corridor, China

Mass Rapid Transit System Passenger Traffic Forecast Using a Re-Sample Recurrent Neural Network

Analysis of passenger flow characteristics and their relationship with surrounding urban functional landscape pattern

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