Plan pedestrian friendly environments around subway stations: lessons from Shanghai, China

Abstract

This research investigated pedestrians’ route directness, waiting time and satisfaction around subway stations in Shanghai, China. Twelve stations were selected from three different zones of the city. Six hundred questionnaires on people’s walking activities were collected. Results showed stations in the old city-centre had the best pedestrian route directness value and lowest waiting time followed by stations in the mid-ring and outer suburbs. Mid-ring stations had the best overall pedestrian satisfaction followed by stations in the old city centre and outer suburbs, which indicated there were other factors affecting pedestrians’ overall satisfaction other than walking directness and waiting time.

Introduction

Urban rail transit and walking have been well regarded as sustainable transportation modes and have regained their popularity across the world in the last few decades (Gehl and Gemzoe 1996; Hall and Hass-Klau 1985). The combination of urban rail transit and walking has been widely used to solve different transportation problems (O’Sullivan and Morrall 1996; Ewing 1999) as well as being catalysts for sustainable urban development (e.g. Transit Oriented Development –TOD) (Dittmar and Poticha 2004; Cervero and Day 2008). Creating sustainable and pedestrian friendly neighbourhoods has become an important goal for urban planners and designers in both academia and the professional world. However, most previous studies and practices have focused on residential neighbourhoods, but less is known about how pedestrian environments around transit stations might affect pedestrians’ behaviour (Sun et al. 2016) and their overall satisfaction (Weinstein et al. 2008; Deng and Li 2016). Investigating and understanding these questions would certainly benefit the knowledge development in urban planning, design and landscape architecture as well as improve people’s overall satisfaction about the transit service and promote more sustainable activities around stations.

During the last 30 years China has experienced a rapid urbanization process, where the overall urbanization rate jumped from 23.7% in 1985 to 53.7% in 2013 (He 2016). In order to meet the skyrocketing demand for transportation, local and central governments turned to urban rail transit as the ideal transportation solution (Liu 2012; Sun, Webster, and Chiaradia 2017). Shanghai metro has the world’s longest subway system by the total track length and the second largest system by the total ridership (ShanghaiMetroGroup 2016), and therefore offers a good case study to investigate the relationship between the pedestrian environment and people’s walking behaviour and satisfaction around urban rail stations. To better answer these questions, the research team selected 12 stations from three different urban zones in Shanghai (old city centre, mid-ring suburbs and outer suburbs) and collected 600 surveys in May and October 2012.

The final results showed that residents were generally but not excessively satisfied with the pedestrian environments around stations in these three city zones. Convenience measures (route directness and red light waiting time) had a major impact on pedestrian overall satisfaction. Pedestrian safety (traffic safety and neighbourhood security) and connectivity (bus transfer and directional signs) were also highly correlated with the overall pedestrian satisfaction. Compared to these factors, measures of comfort such as weather protection, sidewalk width and street lighting were weakly correlated with the overall pedestrian satisfaction.

Literature review

Rail transit and the pedestrian environment around stations

Urban rail transit (subway and light rail) is widely viewed as an important sustainable transportation mode across the world (Atash 1994; Park 2003; Schlossberg and Brown 2004; Cervero and Day 2008; Weinstein et al. 2008; Wey and Chiu 2013; Yang et al. 2013). The combination of walking, biking and transit services has been extensively studied to solve the last-mile problem in different cities, regions and countries (Cervero and Kockelman 1997; Pucher and Dijkstra 2000; Lee and Moudon 2006; Cervero and Day 2008; Lesh 2013).

In the 1960s, Sweden, Denmark, the Netherlands and Germany started to develop different urban rail transit systems and began to actively promote walking and biking in cities and around stations. At the end of the twentieth century, more cities started to pay attention to the urban pedestrian environment and promoted walking around subway stations. Toronto, Chicago, Boston and London all set up pedestrian friendly environment design guidelines within cities and around transit stations (Hall and Hass-Klau 1985; Burkhardt, McGavock, and Nelson 2002; Southworth 2005; Dittmar and Poticha 2004; Egan and Hyland 2008; Middleton 2009). Researchers started to investigate planning and design standards related to pedestrian experiences around transit stations. Loutzenheiser (1997) found that transit stations surrounded by high levels of retail activities and fewer parking areas attracted more walking trips to and from stations. Park (2003) found that street design and built environments significantly affect pedestrian accessibility around transit stations. Schlossberg and Brown (2004) analyzed the transit and pedestrian link for 11 TOD sites in Portland and found pedestrian-hostile streets have a negative influence on the pedestrian environment surrounding transit stations. Olszewski and Wibowo (2005) argued that on average people walked 608 metres (0.38 mile) to transit stations in Singapore and that physical barriers and traffic conflict significantly affect people’s mode choice and walking distance to transit stations. Agrawal and others (2008) surveyed pedestrians’paths to five rail stations in Portland, OR, and found on average people walked half a mile to transit stations. Minimizing time and distance were primary factors for route selection: secondary factors included traffic safety, route attractiveness, sidewalk quality and short waiting times at traffic lights. Rodríguez and others (2009) investigated built environments along street segments near transit stations in Bogota, Columbia, and found that wider and higher sidewalks, benches, garbage cans and bike paths were considered pedestrian friendly amenities. They found that more pedestrian activity occurred on segments with a higher development density, greater mix of land uses and more street crossing aids. Parsons Brinckerhoff (2010) analyzed the walking accessibility around nine types of rail transit stations in Washington DC, US, and found pedestrians used them differently based on their convenience and accessibility. Woldeamanuel and Kent (2015) found that sidewalk availability, quality and connectivity around transit stations affect people’s willingness to walk to transit stations in Los Angeles, US. Sidewalk availability and safety from crime were identified as important factors influencing people’s choice to walk to transit stations in Chicago (Tilahun and Li 2015).

One recent study identified that pedestrians’ walking experience around transit stations would significantly change the perceived walking time and further affect the size of the pedestrian catchment area around transit stations (Deng and Li 2016). Sun and others (2016) found that residents in newer neighbourhoods (e.g. Xiaoqu and Danwei) walked further to transit stations than residents in an older neighbourhood (e.g. Hutong) in China. Pedestrian friendly designs such as better street connectivity and more street-crossings might promote more walking activities around transit stations.

However, there is lack of systematic understanding of how detailed pedestrian environments around stations will affect pedestrians’ walking behaviour as well as their overall satisfaction. Creating a convenient, safe and comfortable pedestrian environment around transit stations is an effective way to promote walking around transit stations, which provides public health benefit for individuals as well as transportation and environmental benefits for cities.

Subway system in Shanghai

The rapid urbanization of Shanghai since the 1990s is evidenced by its changes in urban form. The urbanized area has been expanding outwards through the increased adoption of private cars and the construction of new street networks. Like a loose circle bleeding outwards, the city’s new suburbs differ significantly in urban form from the older, more compact concentric circles formed Shanghai in the 1980s and earlier (Figure 1). This intensive urbanization process, with its high energy and natural resource consumption, has caused severe social and environmental problems for the city. In order to mitigate these negative effects on growth, the government passed new urban planning guidelines and gave priority to public transit development.

Figure 1.

The urban expansion process of central Shanghai (1991–2008) (Chen and Gu 2012).

With government and policy support, the subway system has seen great success in Shanghai. Currently, Shanghai’s metro system is the world’s largest subway system by route length with 14 lines, 354 stations and 365 miles of track (Figure 2). It is the world’s second busiest metro system after the Beijing Subway. On an average workday, there are over 10 million daily riders, and 3.068 billion riders delivered in 2015. The Shanghai subway system presented a good case study to better understand how pedestrian environments around subway stations will affect riders’ walking behaviour and satisfaction.

Figure 2.

Shanghai Metro Map as of April 2016 (ShanghaiMetroGroup 2016).

Methodology

The following section introduces the research questions, conceptual measurements, case study area and data collection process related to the proposed pedestrian environment study.

Questions

Building upon previous studies, this research explores the relationship between detailed pedestrian environment variables and people’s walking behaviour and satisfaction around subway stations in Shanghai, China. The authors seek to answer two separate questions: (1) how do walking directness and waiting time vary around different subway stations? and (2) how do different pedestrian environment factors affect people’s satisfaction around subway stations? In order to better answer these two research questions, a pedestrian environment measurement framework will be introduced in the following section.

Conceptual measurements

In this study, pedestrian environment was measured by the following three factors:

(1). Pedestrian Route Directness

Pedestrian route directness (PRD) is a walking distance measure. It is the ratio between the network distance and the airline distance from the origin to the destination (Hess 1997). A ratio close to 1.00 indicates a direct route. Smaller PRD values indicate a more connected street network.

(2). Waiting Time Index

Waiting time index (WTI) is the ratio between the total waiting time at intersections and the total time used for walking to a metro station. The greater the WTI value, the lower the level of walking continuity.

(3). Pedestrian Satisfaction

Pedestrian satisfaction measures how pedestrians perceive and view their surrounding built environments along the walking path and around metro stations, which influences pedestrians’ psychology and further affects their perception of time and space.

Case study areas

In order to measure different pedestrian environments around stations in the city, researchers selected four subway stations from each of the three different urban zones: the old city centre, mid-ring suburbs and outer suburbs. These zones represent different urbanization periods in Shanghai. In total, 12 stations were selected (Figure 2). The old city centre mainly includes traditional Li-Nong neighbourhoods, mostly built between the early nineteenth-century and the mid-twentieth-century. The Li Nong neighbourhoods kept the traditional pedestrian street block characteristics such as mixed land uses and highly connected street systems. The mid-ring suburb zones are mainly factory workers’ living quarters built between the 1950s and the 1980s. Most of them are located on the fringes of the old city centre and are separated from the old city centre by major and secondary roads. Compared to the old city centre, there are fewer mixed-use developments in the mid-ring suburbs. The outer suburbs are mainly new residential neighbourhoods built in the 1990s that adopted the form of super street blocks with wide roads, centralized and internal commercial complexes and residential compounds enclosed by fences, walls or greenery.

Data collection

Land use, street network and other built environment data around each station were collected from the Shanghai Urban Planning Bureau and stored in GIS format. Walking time and satisfaction data were collected by Tongji University (Shanghai) during May 2012 and October 2012 to adjust for seasonal changes. Respondents were intercepted at subway station platforms and encouraged to fill out a five-minute survey while waiting for their trains. The survey was distributed in morning peak hours (6–9 am), night peak hours (5–8 pm), day non-peak hours (9 am–5 pm) and night (8 pm–6 am). At each station, surveyors were required to collect at least 12 questionnaires during each period and collect 50 questionnaires in total for each station. Once they finished the data collection at one station they moved on to the next station to repeat the process the next day. During the survey process, only 55 people declined the survey. In total, 600 questionnaires were collected and the response rate was 600/655 (91.6%).

Each questionnaire included basic demographic information (age, gender) and four questions about trip frequency, transportation modes to stations, overall stratification and the most important pedestrian environment factors around transit stations. It also included 14 detailed questions about different pedestrian environment factors around the transit station. These questions were presented on a Likert Scale with 5 being ‘strongly agree’ and 1 being ‘strongly disagree’ about the specific question. Overall the survey included slightly more female (51.7%) than male (48.3%) respondents and the maximum, mean and minimum ages of respondents were 78.2, 39.3 and 19.2, respectively. Seventy-six per cent of the respondents used their transit station of choice at least three days per week. Walking (65.8%) and taking a bus (21.7%) were the major transportation modes to the stations. More than half the respondents (54.1%) were satisfied with pedestrian environment around the stations, 40.5% respondents were neutral about the environment and only 5.4% respondents were not satisfied about the overall pedestrian environment around the stations. Detailed descriptive results about these survey questions can be found in Table 1.

Table 1.

Descriptive analysis results of the survey.

	Question	Descriptive results
	Age	Max (78.2), Mean (39.3), Min (19.2)
Number	Gender	Female (51.7%), Male (48.3%)
Q1	Travel frequency to the transit station	5 days (54.5%), 4 days (8.7%), 3 days (12.8%), 2 days (9.8%), 1 day (14.2%)
Q2	Travel mode to transit station	Walking (65.8%), Bike or motorcycle (6.8%), Bus (21.7%), Taxi (2.5%), Personal vehicle (3.2%)
Q3	Satisfaction of surrounding environment	Very satisfied (5.3%), Satisfied (48.8%), Neutral (40.5%), Dissatisfied (4.2%), Very dissatisfied (1.2%)
Q4	Top five most important pedestrian environment factors around transit station	Good pedestrian network to stations (21.3%) Convenient pedestrian crosswalk (11.7%) Good directional signs to transit stations (10.2%) Good personal security (9%), Ease of bus connections (7.8%)
Q5	Direct pedestrian route	Max(3.88), Mean(3.64), Min(3.30)
Q6	Pedestrian traffic safety	Max(3.80), Mean(3.61), Min(3.26)
Q7	Perceived personal security	Max(4.06), Mean(3.71), Min(3.36)
Q8	Sidewalk width	Max(3.74), Mean(3.37), Min(3.02)
Q9	Street crossing	Max(3.74), Mean(3.52), Min(3.23)
Q10	Environmental quality (landscaping, air, noise)	Max(3.58), Mean(3.22), Min(2.92)
Q11	Sidewalk clean and sanitation level	Max(3.76), Mean(3.48), Min(3.02)
Q12	Quality of shops along street	Max(3.92), Mean(3.40), Min(3.04)
Q13	Directional signs	Max(4.00), Mean(3.81), Min(3.63)
Q14	Ease of bus transfer	Max(4.18), Mean(3.60), Min(3.18)
Q15	Street lighting	Max(3.92), Mean(3.54), Min(3.25)
Q16	Visual scene	Max(3.70), Mean(3.41), Min(3.00)
Q17	Weather protection	Max(3.33), Mean(3.07), Min(2.63)
Q18	Unauthorized vending and parking	Max(3.54), Mean(2.99), Min(2.63)

Analysis

Pedestrian route directness (PRD)

Pedestrian route directness (PRD) was calculated within the 500 metre (0. 31mile) and 1000 metre (0.62 mile) buffers around the rail transit station (O’Sullivan and Morrall 1996; Hess 1997; Olszewski and Wibowo 2005; Weinstein et al. 2008). Each individual buffer was divided into eight concurrent circles. City streets intersected with these circles to form a node on each circle. These nodes will be treated as different destinations. Starting from each station, the shortest walking distance to each destination was recorded (${\mathrm{L}}_1,{\mathrm{L}}_2,\dots {\mathrm{L}}_8$) as links. The average link length within the 500 metre and 1000 metre buffers was calculated. Researchers then divided the average link length by 500 metres and 1000 metres as the PRD values of these two buffers (Figure 3).

Figure 3.

Typical urban form characteristics around stations in different zones.

Other related urban form variables such as the average street block length, intersection density (the number of intersections per study area) and link-node-ratio (the ratio between the number of road segments and the total of street intersections) were also measured and compared in this analysis (Table 2). R statistical software was used to test the correlation between PRD values and these three variables within the 500 metre and 1000 metre buffers.

Table 2.

Street network characteristics around transit stations.

	1000 m buffer (0.62mile)				500 m buffer (0.31mile)
Location	PRD	Street block length (m)	Intersection density index(/km2)	Link- node-ratio	PRD	Street block length (m)	Intersection density index(/km2)	Link- node-ratio
Old city centre	1.167	175	39.31	1.639	1.141	150	42.62	1.468
Mid-ring suburbs	1.274	348	9.55	1.45	1.261	343	7.86	1.262
outer suburbs	1.4	390	6.36	1.33	1.33	380	6.34	1.2

Pedestrian waiting time index

A pedestrian friendly environment around transit stations means less waiting time at red lights and better access to and from stations. The Waiting Time Index (WTI) developed by (Gehl and Gemzoe 1996) was adopted to measure the overall waiting time around each individual station. Based on the survey results, the three most commonly used walking routes around each station were selected. Volunteers were assigned to retrace these routes from the station entrances to the edge of the 500 metre buffers and then return to the departure point. For each individual trip, the total walking time (T) and red light waiting time at each intersection ($t_n$) were recorded. For each station, the average walking time index was calculated as follows.

$$\text{WTI}=t_1+t_2+t_3+\dots +t_n∕T$$

where: $t_n$ is the red light waiting time at each intersection and $T$ is the total walking time during that trip. The smaller the WTI values the less waiting time at intersections. The results showed WTI values significantly differ among these 12 selected stations. The average WTI in the old city centre, mid-ring suburbs and other suburbs was 9.7, 11.1 and 17.1%, respectively. This indicated that the average red light waiting time in the outer suburbs is much longer than that of the old city centre. Assuming people’s walking speeds are similar, the WTI value around each station will be only related to the total number of intersections (n) and red light waiting time at each intersection ($t_n$) in that zone. The more intersections there are, the longer total red lights waiting time, resulting in a higher WTI. During the survey, the investigators also included the number of red light stops during each walking trip and the number of stops with longer than 60 seconds waiting time (Table 3).

Table 3.

Waiting time and other related measures around transit stations.

	500 m buffer (0.31mile)
Location	WTI	Total no. of intersections	Total no. of red light waiting times	Total no. of red lights with longer than 60s waiting time
Old city centre	9.70%	8	2.5	0.33
Mid-ring suburbs	11.10%	4.25	2	0.75
Outer suburbs	17.10%	3.5	2	1.59

Pedestrian satisfaction

Pedestrian satisfaction measured how people perceive the surrounding built environments around stations while walking. Intangible perceptions such as sense of security and comfort will affect pedestrians’ perception of the surrounding environments (Alfonzo et al. 2008; Wang et al. 2011). The convenience and comfort level of the pedestrian environment near a subway station may also affect residents’ travel choices (Liu 2012; Deng and Li 2016). In this research, pedestrians’ built environment perceptions were measured from six sub-categories and with 14 indexes (Table 1):

1. Convenience: (a) direct route;

2. Connectivity: (b) street crossing, (c) the ease of bus transfer;

3. Safety: (d) personal safety, (e) traffic safety, (f) street lighting;

4. Conspicuousness: (g) directional signs;

5. Comfort: (h) shops along streets, (i) weather protection, (j) environmental quality (air, greenery and noise), (k) sidewalk width, (l) unauthorized vending and parking;

6. Pleasantness: (m) sidewalk cleanliness and sanitary level, (n) visual scene

Satisfaction level evaluation was measured on a Likert Scale with five categories as ‘excellent’, ‘satisfactory’, ‘acceptable’, ‘unsatisfactory’ and ‘very unsatisfactory’, which corresponds to the values of 5, 4, 3, 2 and 1 (Tables 1, 4).

Table 4.

General and individual satisfaction level of pedestrian environment.

		Old City Centre	Mid-ring Suburbs	Outer Suburbs
General satisfaction value		3.55	3.63	3.40
Convenient	Direct pedestrian route	3.70	3.71	3.51
Connected	Street crossing	3.58	3.53	3.46
	The ease of bus transfer	3.57	3.86	3.37
Safety	Perceived personal security	3.90	3.71	3.52
	Perceived traffic safety	3.65	3.69	3.49
	Street lighting	3.69	3.51	3.42
Conspicuousness	Directional signs	3.78	3.92	3.73
Comfort	Quality of shops along streets	3.50	3.40	3.32
	Weather protection	3.22	3.06	2.92
	Environmental quality	3.11	3.29	3.20
	Sidewalk width	3.26	3.33	3.52
	Unauthorized vending and parking	3.23	2.97	2.76
Pleasantness	Sidewalk clean and sanitation level	3.48	3.52	3.43
	Visual scene	3.51	3.28	3.44

Results

Pedestrian route directness

The results showed there was no significant PRD difference within the 500 metres and 1000 metres buffers. The PRD values of the 12 study areas were between 1.080 and 1.447 (Table 2). In the old city centre the PRD values were the smallest, ranging from 1.080 to 1.200. In the mid-ring suburbs the average PRD values ranged from 1.216 to 1.364. The outer suburbs had the highest PRD values (1.280 to 1.447). These results confirmed Hess’ findings (1997), which showed that PRD values in residential areas of the old central city with small blocks were generally around 1.2.

The results also showed that PRD was strongly and positively correlated, with the average street block length (0.763, p = 0.01) in both buffers. PRD were also negatively correlated with intersection density index (−0.503, p = 0.05) and link-node-ratio (−0.447, p = 0.05) in both buffers. This means that in the station zone, the longer the average street block length, the smaller the intersection density and the greater the detour level. In the related studies focusing on North American cities, where many zones adopted a hierarchical road system (suitable for low density community development), there are more cul-de-sac roads and curved roads. Therefore, link-node-ratio and intersection density often become the key indexes to quantify the street networks. In the new construction zones in Chinese cities, street networks were built to lease or sell plots, so cities often adopted a highly connected grid network.

However, there are clear differences in terms of street block length and intersection density between the outer suburb and the old city centre. For example, the average block length and intersection density within a 500 metre and 1000 metre buffer in the old city centre is 150/175 metres and 42.6/39.3, in contrast to 380/390 metres and 6.34/6.36 for the outer suburbs. This indicated that the outer suburbs had significantly larger blocks than those of the old city centre. There was no significant difference in terms of average block length and intersection density between the mid-ring suburbs and outer suburbs within both 500 metres and 1000 metres buffers (Table 2), which indicated a similar development pattern and urban form between the mid-ring suburbs and outer suburbs.

Pedestrian waiting time

The results showed that the WTI was not correlated with the number of intersections within either station buffer (500 metres, 1000 metres). However, WTI was positively correlated with the number of red light stops and the number of red light stops with longer than 60 seconds waiting time. Although the number of intersections around metro stations in the outer suburbs was less than 50% of that in the old city centre, the number of red lights with longer than 60 seconds waiting time was nearly five times that of the old city centre. Mid-ring suburban stations had a similar WTI to the old city centre, a similar number total intersections to the outer suburbs, but significantly fewer 60 seconds red light waiting times than outer suburbs. It indicated the street network and signal system in the outer suburbs and the old city centre were planned to serve motorized transportation and non-motorized transportation, respectively. Mid-ring blocks were designed to serve both motorized transportation and non-motorized transportation with significantly fewer long red lights waiting periods. The outer suburbs’ street network and signal design had serious adverse effects on walking activities around suburban stations. In addition, due to construction convenience, suburban stations often utilized the spaces of the major roads, meaning that their stations are adjacent to the main roads where walking conditions could be worse.

Pedestrian satisfaction

The results showed that all 14 different environment measures were positively correlated with the overall pedestrian satisfaction, but the impacts were different. Among them, direct pedestrian route (0.387) had the strongest correlation with pedestrians’ general satisfaction, followed by perceived traffic safety and security (0.284 and 0.281), good street crossing and easy bus transfer (0.282 and 0.268), visual scene and sidewalk cleanliness (0.277 and 0.273), and environmental quality (0.253). In total, there were eight different factors with a positive correlation to overall pedestrian satisfaction larger than 0.250. However, many individual comfort measures had low correlation with the overall pedestrian satisfaction (e.g. sidewalk width 0.176, weather protection 0.201, unauthorized vending and parking 0.217). Street lighting (0.167) and directional signs (0.233) also had low correlation with pedestrian satisfaction in the survey (Table 5). This suggested that pedestrians cared more about the utility and safety of the built environment around stations and less about the comfort of the environment and along routes. These findings regarding walking convenience were also confirmed by the questionnaire, which reported that 70.9% of respondents chose ‘convenient walk, no detour’ as the most important factor for a good walking environment. Similar findings were reported in previous studies (O’Sullivan and Morrall 1996; Olszewski and Wibowo 2005; Weinstein et al. 2008).

Table 5.

Correlations between overall pedestrian satisfaction and individual measures.

Performance index	Individual factor indexes	General satisfaction
Convenience	Direct pedestrian route	.387**
Connection	Street crossing	.282**
	Ease of bus transfer	.268**
Safety	Perceived personal security	.281**
	Perceived traffic safety	.284**
	Street lighting	.167**
Conspicuousness	Directional signs	.233**
Comfort	Quality of shops along streets	.227**
	Weather protection	.201**
	Environmental quality	.253**
	Sidewalk width	.176**
	Unauthorized vending and parking	.217**
Pleasantness	Sidewalk clean and sanitation level	.273**
	Visual scene	.277**

^**p < 0.01

The results showed the stations in the mid-ring suburbs had the highest overall pedestrian satisfaction (3.63) followed by the old city centre (3.55). The outer suburbs had the lowest general pedestrian satisfaction value (3.40). These results were a little different with the results of the PRD and WTI, which indicated that apart from walking distance and time factors, there were other factors which influenced pedestrians’ satisfication (Weinstein et al. 2008). Further analysis examined the satisfication values regarding different factors in three city zones as well as their correlations to pedestrians’ overall environment satisfaction values (Table 5).

Stations in the old city centre and mid-ring suburbs scored higher in different environment measures. For the 14 individual measures, stations in the old city centre ring suburbs scored highest for seven measures, including street crossing, street lighting, perceived personal security, weather protection, quality of shops along the road, visual scene, and unauthorized vending and parking. Stations in mid-ring suburbs scored well in several important utility and safety measures such as: route directness, the ease of bus transfer, perceived traffic safety, directional signs, sidewalk cleanliness and sanitation, and overall environmental quality. Compared to the old city centre, it was clear that the mid-ring suburbs had been developed more recently and were equipped with more convenient pedestrian networks (e.g. direct pedestrian route, easier bus transfer) and better facilities (clean sidewalk and directional signs).

The outer suburbs scored low in almost all individual measures. They only scored the highest value for the sidewalk width measure. Among the 14 individual environment measures, outer suburbs stations were the lowest for 11 measures such as the directness of the route and street crossing, perceived personal security, perceived traffic safety, street lighting and unauthorized vending and parking. This indicated that the current urban development trends in outer suburbs mainly focused on automobile transportation and seriously neglected pedestrians’ travel demands in these areas.

Although the development pattern and urban form were quite different in these three urban zones, the residents were generally satisfied with the overall pedestrian environment in these areas. The authors believe the reasons might result from the fact that unlike many urban development projects in the US, which are completely automobile oriented and lack complete sidewalk systems (Elias 2011), even the newest suburban developments in Chinese cities still have a relatively good pedestrian network with complete sidewalks, crosswalks and directional signs which meet pedestrians’ basic travel needs (Sun, Webster, and Chiaradia 2017). On the other hand, although stations in all three city zones provided basic pedestrian facilities for its residents, none of them scored very high (e.g. above 4 on a Likert Scale) (Table 4) for any individual environmental measure, which might explain why residents were generally but not excessively satisfied with the pedestrian environments around stations in these three different city zones.

Discussion and conclusion

Using 600 surveys collected from 12 subway stations in Shanghai, China, the authors investigated pedestrians’ route directness, waiting times and the overall satisfaction around subway stations in three different city zones (old city centre, mid-ring suburbs, and outer suburbs) in Shanghai, China.

The results showed that the pedestrian environments around these stations were significantly different. People were generally satisfied with the pedestrian environment around subway stations in the older city centre and mid-ring suburbs but less satisfied with stations in the outer suburbs. Among them, old city centre stations had the best pedestrian route directness value and lowest waiting time followed by stations in the mid-ring and outer suburbs. Mid-ring stations had the best overall satisfaction level, closely followed by old city centre stations. In terms of detailed pedestrian environment measures, stations in the city centre and mid-ring suburbs scored highest in seven and six individual measures, respectively. Outer suburbs, characterized by super blocks and automobile oriented streets, had the worst pedestrian environments around subway stations and only scored highest in one measure (sidewalk width), indicating a lack of attention to pedestrian travel in these newly developed areas.

The results showed that the pedestrian route directness (PRD) is the primary concern for pedestrians who choose to walk to a metro station. PRD was positively correlated with street block length and negatively correlated with intersection density index and link-node-ratio. This suggests that in station zones the longer the average street block length, the smaller the intersection density and the greater pedestrian detour. Among the existing studies, Ewing (1999) proposed that 300 feet (91 metres) is an ideal side length for a pedestrian-friendly street block, with 400 to 500 feet (122 to 152 metres) being an acceptable length. The American Public Transportation Association (2012) recommends that a street block around transit stations should be 90 to 150 metres. This value is similar to the street dimensions in the old Shanghai city centre but shorter than the block length in the mid-rings, which received the highest overall satisfaction rating. This implied that other factors would also affect pedestrians’ overall satisfaction

Red light waiting time is another important factor affecting pedestrians’ overall satisfaction with the environment. Longer red light waiting time will significantly affect walking time to and from subway stations. Previous studies in Japan, America and European countries showed that if the waiting time to cross the street is longer than 45 seconds, the rate of pedestrian motor vehicle accidents will significantly increase (Martin 2006; Guo et al. 2012). Several countries have introduced a regulation that the waiting time to cross any street will be no longer than 90 seconds (Xiong, Chen, and Xian-biao 2009). In this study, researchers found that some red light waiting times in the outer suburbs were even longer than 120 seconds, which might explain the low pedestrian satisfaction around the outer suburbs stations.

Besides route directness and red light waiting time, pedestrian safety (traffic safety and neighbourhood security) and connectivity (bus transfer and directional signs) were also highly correlated with the overall pedestrian satistification. Stations in the mid-ring suburbs offered the best bus transfer system and directional signs, which could have significantly increased overall pedestrian satisfication in these areas. Interestingly, compared to other convenience and safety mesaures, pedestrian comfort measures, such as weather protection, sidewalk width, street lighting and quality of shops along streets, had a relatively low correlation with the overall satisficaition rating. Again, this confirmed the importance of convenience and safety in pedestrians’ travel decision-making processes (Zacharias 2001; Kelly et al. 2011).

The findings of this study have several implications for urban design. The results show that route directness and red light waiting times are primary concerns for pedestrian travel to and from subway stations. Pedestrian safety (traffic and neighbourhood security) and connectivity (the ease of bus transfer and directional signs) are equally important environmental factors for pedestrian travel. Some physical environmental variables such as sidewalk width, street lighting and weather protection facilities played less important roles in pedestrians’ decision-making processes. Improving pedestrian environments around transit stations is a powerful method to promote and improve public transportation usage. A good pedestrian environment around transit stations will encourage people to walk to a station instead of driving there, which is beneficial to individual health outcomes as well as positively impacting the transportation and environmental landscape of cities.