How to design the metro network for maximal accessibility potential? A comparative analysis of Shanghai.

Abstract

In Shanghai, the high-capacity metro network has been proved to play an important role in the urban movement and urban morphology generating pattern. Previous studies on the metro network analysis such as London Underground network (Chiaradia, 2005) and Shanghai Metro network (Zhang, 2014) have shown that topological configuration of metro network can explain at least 50% of entry/exit movement at metro stations. The Shanghai metro network uses a core ring (Inner ring Line 4) to encircle a core of stations which are characterized by higher line connectivity. Branches radiate from the core and reach further areas of the urban system. However, the core lines and stations have over-congested especially at peak time, at the same time, the link mean distance doesn’t minimized because the inner ring core is not big enough for the ever growing metro network. How should the network be designed to achieve best accessibility potential? Through the use of sDNA (spatial design network analysis) and geographic information system, this paper compared current 2016 and planned 2020 Shanghai metro network (Fig 1). There was an increase of 23% in the metro station amount, however, the mean distance only decreased by 2.6%, and the line connectivity increased by 0.68%. Inspired by the Shanghai City Planning 2015-2040 which will reserve place for a ring-shaped metro line near mid-ring, and by the two orbital rail rings for the Greater Paris, we did a comparison between 4 network plans based on the 2016 network: a) a mid-ring line added; b)a mid-ring line & mid-ring express line added; c) two ellipse rings added; d) two ellipse rings & ellipse express lines added (Fig 2). The results showed that the plan D works best for minimizing mean distance and maximizing line connectivity, followed by plan C, plan B, and plan A. Two ellipse rings and express lines led to a reduction of more than 30% of network mean distance and an increase of 18.5% of line connectivity, corresponding to only 13% increase of the metro station amount. The proposed approach enables us to configurationally examine urban metro network accessibility potential and provides decision support for urban development.

Statistical Modeling of Traffic Flow in Commercial Clusters Based on a Street Network

“…Notably, sDNA can analyze the accessibility of street networks and calculate the potential of streets for pedestrian, bicycle, motor vehicle, and public transport use. This approach has been applied to different spatial networks, such as transit rail, urban street, and 3D pedestrian spaces [30,31]. This suggests that the use of SNA street networks is suitable for the study of socioeconomic attributes and transportation on the urban scale, and space syntax is suitable for the study of behavior triggered by human perceptions of the city on the urban mesoscopic scale, while sDNA has better potential for the study of urban micro-scale, three-dimensional spaces.…”