Bicycle–metro integration for the ‘last mile’: Visualizing cycling in Shanghai

Metro systems are often considered to be the most effective way to address the daily intra-city transport loads, especially in high-density cities. However, in big cities like Tokyo, Shanghai and Singapore, many residents live in the suburbs, where the metro stations are relatively sparse. The ‘last mile’ between homes and metro stations is a major factor influencing residents’ usage of metro systems (Zhao and Li, 2017).

Meanwhile, cycling is always considered to be one of the most popular daily traffic tools in cities due to its flexibility, convenience and low cost (Akar and Clifton, 2009; Parkes et al., 2013). Bicycle–metro integration is an effective solution for improving the accessibility of metro systems and facilitating green transportation (Zhao and Li, 2017). In recent years, dockless bike-sharing programmes have been launched in China at an impressive speed. These new common-usage bikes cover almost every street in Chinese big cities, and can be accessed via smartphone (Chinta and Sussan, 2018). Compared with traditional public bicycle systems with fixed docks, such as New York Citibike (Faghih-Imani and Eluru, 2016), this new bike-sharing system demonstrates the mobility and flexibility of cycling. People do not have to depart from or arrive at fixed docking stations; they may enjoy cycling from/to anywhere in the city. This design is effective in solving the ‘last mile’ problem, which is spreading across hundreds of cities around the world, including San Francisco, Seattle and London, by providing people with the transportation tools between public transport hubs and home.

OFO, as the first and one of the biggest dockless bike-sharing firms in China, provides the bicycle-sharing system with more than 700,000 bikes in Shanghai. This study randomly sampled the GPS coordinates of 80,000 OFO bikes in Shanghai, which represent the origin and destination points of cycling. The 80,000 cycling origin–destination (OD) lines were intercepted into 141,317 cycling directional lines, each with a length of no longer than 500 metres, which is generally considered as the basic service radius of metro stations. We mapped the cycling directional lines on an equal population cartogram of Shanghai (Figure 1) to distinguish overall patterns within the centre of Shanghai. The cycling directional lines are represented clearly as groups of radial lines from/to metro stations. Furthermore, with the help of the bicycle route navigation of Google Maps (www.maps.googleapis.com), each cycling trip was simulated by inputting coordinates of its start point and end point. Each street is assigned the number of starting and ending trips (no longer than 500 metres), which represents the cycling frequency. As is shown in Figure 2, most of the high-frequency cycling streets still centre around metro stations. The streets basically present a gradual decline from the metro stations to outlying areas in terms of cycling frequency, which indicates that bicycle–metro integration has already become the basic model for daily transport in Shanghai.

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Figure 1.

The spatial pattern of cycling and metro stations on an equal population cartogram of Shanghai.

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Figure 2.

The cycling frequency of each street on an equal population cartogram of Shanghai.