# Comparative Study on Characteristics of Urban Road Network in Station Catchment Area between China and Other Countries for Station-City Integration

Authors: Yi-Zheng Dai; Chen-Yang Zhang
Journal: Journal of Advanced Transportation
 (2022)

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## Abstract

The urban road network is one of the most important factors affecting urban traffic operation in station catchment areas, as well as the main factor in station-city integration. China’s high-speed railway has developed rapidly, and station catchment areas encompassed by station-city integration have emerged as city planning and urban design aims. However, the differences in urban road network characteristics in the station catchment area between China and other countries have not been adequately researched yet. Considering 20 station catchment areas encompassed by the station-city integration as examples, this study analyzes the intersection quantity and network density in station catchment areas to compare the characteristics of urban road networks in China with those in Europe, North America, and Japan. Combined with the square block model calculation, we found the following. (1) The network density in non-China cases is concentrated in 16–22 km/km2. The Honkong West Kowloon Station and Shapingba Station approach this range, while the Shanghai Hongqiao Station and Hangzhou East Station feature considerably lower values than this range. (2) The intersection quantity in non-China cases is concentrated in 225 pcs/km2. Except for that of the Honkong West Kowloon Station, the values for the Shapingba Station, Shanghai Hongqiao Station, and Hangzhou West Station are lower than this range. (3) Developing small-scale blocks by gridding has an optimal effect on station catchment areas within the side-length range of 47.1–97.5 m. (4) The current situation of the entire urban road network and the specifications for the design codes of the road network exhibit a certain correlation with the road network characteristics of the station catchment areas.


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## Body

## 1. Introduction

With the cities in Europe, North America, and East Asia paying increasing attention to the sustainability of railway construction and urban development, the implementation of station-city integration has emerged as a common share of city planning and urban design aims. Along with the ideals of station-city integration, the urban network characteristics of these areas, particularly, station catchment areas, are being reshaped. Over the past decade, China’s high-speed railway has developed rapidly. The total mileage of high-speed railways has reached 35000 km, and 1500 railway stations have been built by the end of 2019.Road networks have been found to remain central in the spatial organization of urban areas over time across significant political, economic, environmental, demolition, and reconstruction changes that are considered important for station-city integration [1, 2]. In conjunction with the respective features within a city, such as land usage or traffic, road networks may determine the important functional, social, and perceptual properties of urban settlements, such as the efficiency of transportation and space utilization, social residential segregation, and way-finding [3]. Optimizing the road network for station-city integration will enable planners understand and optimize the status quo of intensive land use between railway stations and surrounding regions to save further travel time, space consumption, and urban energy. Simultaneously, it can enhance the vitality of station catchment areas and establish a suitable connection with the environment. Although traffic accessibility and pedestrian movement in station catchment areas are related to the matching of land use form and transport systems [4, 5], the road network characteristics of station catchment areas have not been adequately researched yet.Investigating the characteristics of road networks is an important research direction based on inspection of the distribution of the different features across the road network and correlation with the geometric and other properties of road segments [6]. In a study specifically addressing road network measures, four groups of connectivity measures for road networks were classified as typological distinctions, data differences, particular locations, and space syntax [7]. Intersection quantity and network density are reliable indicators of road network characteristics [8], and the typical unit is often a square mile. “Intersection quantity” is typically measured by the number of intersections per unit area. “Network density” is equal to the ratio of the total length of all roads in a calculated area to the total area [9]. A better understanding of the intersection quantity and network density in cities would facilitate engineering solutions and improve management and planning [10]. Most empirical studies are based primarily on the analysis of a single case for urban planning or urban design, but they are inadequate. Existing research has focused considerably on the properties of road networks, and there has been only limited investigation of the differences between China and other countries.This study addresses the following question. How are the characteristics of road networks suitable for station catchment areas? Do the road network characteristics of station catchment areas vary consistently across different countries and regions? In this study, we extend this research by analyzing the intersection quantity and network density in station catchment areas to compare the characteristics of road networks in China with those in Europe, North America, and Japan. These countries have implemented station-city integration that is expected in China as well. Investment in construction and operation can have a profound impact on social and economic activities [11]. The study framework involves four steps: study area and case selection, network density sampling, intersection quantity sampling, and quantitative analysis with the block model.


## 2. Methodology

To determine the intersection quantity and network density, we derived them using the BaiduMap database that contains data on the road networks with attribute information. BaiduMap API is a Python-based research tool that easily downloads BaiduMap data for any place name, address, or polygon in the world and, thereafter, constructs it into a spatially embedded graph-theoretic object for analysis and visualization.


### 2.1. Study Area and Case Selection

A station catchment area is a geographic space around a station that offers physical proximity to people to access transit services. The size of the station areas typically varies according to the transit service and mobility options of transit users. Nevertheless, many guidelines suggest ideal distances of 400 m (1/4 mi) to 800 m (1/2 mi) from a station [12]. Of the residents queried in one study, 93.7% accepted a maximum walking distance between 732 and 762 m, equivalent to a 10-min walk with an average walking speed of 1.22–1.27 m/s [13]. A large proportion of people (75%) are willing to walk up to 800 m for rail services [14]. The results from these studies provide us credence to consider 800 m as the radius in the definition of station catchment areas for this study (Figure 1).Figure 1
Overview of the study area: schematic of Yokohama station.To compare the characteristics of road networks in China with those in Europe, North America, and Japan, we employed 20 station catchment areas as our empirical case study, including 16 non-China cases and 4 cases of China (Table1). These were selected based on the following three factors:(i)
Urban environment setting of station-city integration(ii)
Access to comprehensive and high-quality data of the present road network(iii)
Accounting for different countries and regionsTable 1
Twenty station catchment areas for the current empirical case study.
Name of railway stationLocationName of railway stationNetwork densityOsaka-Umeda stationJapanHangzhou west stationChinaShanghai Hongqiao stationChinaYokohama stationJapanKyoto stationJapanOslo central stationNorwayNagoya stationJapanUtrecht central stationNetherlandsMontparnasse stationFranceBirmingham new road stationEnglishKing’s Cross-St. PancrasEnglishHakata stationJapanTokyo stationJapanSendai stationJapanLille-Europe stationFranceShibuya stationJapanToronto union stationCanadaShapingba stationChinaHongkong West Kowloon stationChinaFutako-Tamagawa stationJapanThe existence of railways has been deeply integrated into the lives of the residents in the city corresponding to these cases. In particular, East Asian metropolitan areas have developed railway networks and improved the transportation facilities [15].


### 2.2. Network Density Sampling

Network density is defined as the number of roads per unit area. In conventional traffic engineering definitions, network density is usually measured as meters of road (length) per square meter of ground area (surface). The unit of the outcome is the meter of network per square meter of unit area (km/km2) given by the following expression:(1)D=LcaSca,where Sca is the station catchment area and Lca is the total length of the road network.Network density is the limit of the developmental relationship between road length and land use that is an important factor affecting traffic accessibility and pedestrian movement in station catchment areas. Theoretically, in a certain district, when the density of the road network increases, the traffic capacity should increase owing to increase in road supply, thus allowing more motor vehicles to pass. However, when the road network becomes denser, the intersections become disadvantageous for motor vehicles; in other words, traffic capacity declines [16].The network density of station catchment areas obtained from the BaiduMap database for the 20 cases is shown in Table2 and Figure 2.Table 2
Data of road network density obtained from the BaiduMap database.
Name of railway stationNetwork densityName of railway stationNetwork densityOsaka-Umeda station20.63040233Hangzhou west station6.526844745Shanghai Hongqiao station6.184661618Yokohama station20.82194279Kyoto station20.88112854Oslo central station17.5319117Nagoya station21.57675201Utrecht central station16.05773904Montparnasse station17.01963173Birmingham new road station20.15846562King’s Cross-St. Pancras20.97190941Hakata station20.44544188Tokyo station19.41418722Sendai station16.73414755Lille-Europe station17.64800423Shibuya station23.01330742Toronto union station12.07588131Shapingba station14.85960074Hongkong West Kowloon station14.01359274Futako-Tamagawa station17.71394517Figure 2
Network density sampling.The Toronto Union Station, Hongkong West Kowloon Station, and Futako-Tamagawa Station are built near a river or sea, resulting in lack of consistency of study area with other cases; thus, the network density needs to be corrected. The correction factor is the ratio of total area with a radius of 800 m to the land use. The correction factor of the Toronto Union Station is 1.2000, the Hongkong West Kowloon Station is 1.2082, and the Futako-Tamagawa Station is 1.2645. The corrected road network density is 14.49105757 km/km2 at the Toronto Union Station, 16.93122275 km/km2 at the Hongkong West Kowloon Station, and 22.39928367 km/km2 at the Futako-Tamagawa Station. The corrected data of road network density are shown in Figure 3.Figure 3
Corrected data of road network density comparison.


### 2.3. Intersection Quantity Sampling

An intersection is the node of the road networks. In addition to network density, intersection quantity is also an indicator of traffic accessibility and pedestrian movement. There is an inverse relationship between intersection density and intersection spacing. An increase in one factor leads to a decrease in another factor. “Intersection quantity” is typically measured by the number of intersections per unit area (pcs/km2), given by the following expression:(2)Q=NcaSca,where Sca is the station catchment area and Nca is the number of intersections of the road network.All types of vehicles and pedestrians on the road should be able to gather, turn, and pass through the intersection; thus, potential traffic congestion is expected. The higher the intersection density, the lower the traffic flow at the intersection that reduces the congestion at the intersection. As shown in Figure4, from A to B at the same block size, the road network structure composed of widely spaced large roads can afford turning at seven intersections, and the road network structure composed of dense small-scale roads can afford turning at 23 intersections. However, when an intersection becomes denser, it is disadvantageous for motor vehicles. In principle, under a specific demand pattern, there should be an intersection value of road networks that maximizes the traffic capacity.Figure 4
The road network structure.The data of intersection quantity of road networks obtained from the BaiduMap database for the 20 station areas are shown in Table3 and Figure 5. The correction cases and correction factors are the same as those described in Section 2.2. The corrected intersection quantity is 82.3627 pcs/km2 at the Toronto Union Station, 146.6219 pcs/km2 at the Hongkong West Kowloon Station, and 200.6225 pcs/km2 at the Futako-Tamagawa Station. The corrected data for the intersection quantity of the road networks are shown in Figure 6.Table 3
Data of intersection quantity of road networks obtained from the BaiduMap database.
Name of railway stationIntersection quantityName of railway stationIntersection quantityOsaka-Umeda station204.7319109Hangzhou west station21.88380468Shanghai Hongqiao station10.94190234Yokohama station186.0123398Kyoto station211.3776588Oslo central station134.2869833Nagoya station223.9872745Utrecht central station232.7641043Montparnasse station129.3133913Birmingham new road station204.4146301King’s Cross-St. Pancras209.7905659Hakata station171.588923Tokyo station171.785249Sendai station117.8741297Lille-Europe station176.9768193Shibuya station260.1188602Toronto union station68.63556922Shapingba station102.4559946Hongkong West Kowloon station121.3556441Futako-Tamagawa station158.6575839Figure 5
Intersection quantity sampling.Figure 6
Corrected data of intersection quantity of road networks.


## 2.1. Study Area and Case Selection

A station catchment area is a geographic space around a station that offers physical proximity to people to access transit services. The size of the station areas typically varies according to the transit service and mobility options of transit users. Nevertheless, many guidelines suggest ideal distances of 400 m (1/4 mi) to 800 m (1/2 mi) from a station [12]. Of the residents queried in one study, 93.7% accepted a maximum walking distance between 732 and 762 m, equivalent to a 10-min walk with an average walking speed of 1.22–1.27 m/s [13]. A large proportion of people (75%) are willing to walk up to 800 m for rail services [14]. The results from these studies provide us credence to consider 800 m as the radius in the definition of station catchment areas for this study (Figure 1).Figure 1
Overview of the study area: schematic of Yokohama station.To compare the characteristics of road networks in China with those in Europe, North America, and Japan, we employed 20 station catchment areas as our empirical case study, including 16 non-China cases and 4 cases of China (Table1). These were selected based on the following three factors:(i)
Urban environment setting of station-city integration(ii)
Access to comprehensive and high-quality data of the present road network(iii)
Accounting for different countries and regionsTable 1
Twenty station catchment areas for the current empirical case study.
Name of railway stationLocationName of railway stationNetwork densityOsaka-Umeda stationJapanHangzhou west stationChinaShanghai Hongqiao stationChinaYokohama stationJapanKyoto stationJapanOslo central stationNorwayNagoya stationJapanUtrecht central stationNetherlandsMontparnasse stationFranceBirmingham new road stationEnglishKing’s Cross-St. PancrasEnglishHakata stationJapanTokyo stationJapanSendai stationJapanLille-Europe stationFranceShibuya stationJapanToronto union stationCanadaShapingba stationChinaHongkong West Kowloon stationChinaFutako-Tamagawa stationJapanThe existence of railways has been deeply integrated into the lives of the residents in the city corresponding to these cases. In particular, East Asian metropolitan areas have developed railway networks and improved the transportation facilities [15].


## 2.2. Network Density Sampling

Network density is defined as the number of roads per unit area. In conventional traffic engineering definitions, network density is usually measured as meters of road (length) per square meter of ground area (surface). The unit of the outcome is the meter of network per square meter of unit area (km/km2) given by the following expression:(1)D=LcaSca,where Sca is the station catchment area and Lca is the total length of the road network.Network density is the limit of the developmental relationship between road length and land use that is an important factor affecting traffic accessibility and pedestrian movement in station catchment areas. Theoretically, in a certain district, when the density of the road network increases, the traffic capacity should increase owing to increase in road supply, thus allowing more motor vehicles to pass. However, when the road network becomes denser, the intersections become disadvantageous for motor vehicles; in other words, traffic capacity declines [16].The network density of station catchment areas obtained from the BaiduMap database for the 20 cases is shown in Table2 and Figure 2.Table 2
Data of road network density obtained from the BaiduMap database.
Name of railway stationNetwork densityName of railway stationNetwork densityOsaka-Umeda station20.63040233Hangzhou west station6.526844745Shanghai Hongqiao station6.184661618Yokohama station20.82194279Kyoto station20.88112854Oslo central station17.5319117Nagoya station21.57675201Utrecht central station16.05773904Montparnasse station17.01963173Birmingham new road station20.15846562King’s Cross-St. Pancras20.97190941Hakata station20.44544188Tokyo station19.41418722Sendai station16.73414755Lille-Europe station17.64800423Shibuya station23.01330742Toronto union station12.07588131Shapingba station14.85960074Hongkong West Kowloon station14.01359274Futako-Tamagawa station17.71394517Figure 2
Network density sampling.The Toronto Union Station, Hongkong West Kowloon Station, and Futako-Tamagawa Station are built near a river or sea, resulting in lack of consistency of study area with other cases; thus, the network density needs to be corrected. The correction factor is the ratio of total area with a radius of 800 m to the land use. The correction factor of the Toronto Union Station is 1.2000, the Hongkong West Kowloon Station is 1.2082, and the Futako-Tamagawa Station is 1.2645. The corrected road network density is 14.49105757 km/km2 at the Toronto Union Station, 16.93122275 km/km2 at the Hongkong West Kowloon Station, and 22.39928367 km/km2 at the Futako-Tamagawa Station. The corrected data of road network density are shown in Figure 3.Figure 3
Corrected data of road network density comparison.


## 2.3. Intersection Quantity Sampling

An intersection is the node of the road networks. In addition to network density, intersection quantity is also an indicator of traffic accessibility and pedestrian movement. There is an inverse relationship between intersection density and intersection spacing. An increase in one factor leads to a decrease in another factor. “Intersection quantity” is typically measured by the number of intersections per unit area (pcs/km2), given by the following expression:(2)Q=NcaSca,where Sca is the station catchment area and Nca is the number of intersections of the road network.All types of vehicles and pedestrians on the road should be able to gather, turn, and pass through the intersection; thus, potential traffic congestion is expected. The higher the intersection density, the lower the traffic flow at the intersection that reduces the congestion at the intersection. As shown in Figure4, from A to B at the same block size, the road network structure composed of widely spaced large roads can afford turning at seven intersections, and the road network structure composed of dense small-scale roads can afford turning at 23 intersections. However, when an intersection becomes denser, it is disadvantageous for motor vehicles. In principle, under a specific demand pattern, there should be an intersection value of road networks that maximizes the traffic capacity.Figure 4
The road network structure.The data of intersection quantity of road networks obtained from the BaiduMap database for the 20 station areas are shown in Table3 and Figure 5. The correction cases and correction factors are the same as those described in Section 2.2. The corrected intersection quantity is 82.3627 pcs/km2 at the Toronto Union Station, 146.6219 pcs/km2 at the Hongkong West Kowloon Station, and 200.6225 pcs/km2 at the Futako-Tamagawa Station. The corrected data for the intersection quantity of the road networks are shown in Figure 6.Table 3
Data of intersection quantity of road networks obtained from the BaiduMap database.
Name of railway stationIntersection quantityName of railway stationIntersection quantityOsaka-Umeda station204.7319109Hangzhou west station21.88380468Shanghai Hongqiao station10.94190234Yokohama station186.0123398Kyoto station211.3776588Oslo central station134.2869833Nagoya station223.9872745Utrecht central station232.7641043Montparnasse station129.3133913Birmingham new road station204.4146301King’s Cross-St. Pancras209.7905659Hakata station171.588923Tokyo station171.785249Sendai station117.8741297Lille-Europe station176.9768193Shibuya station260.1188602Toronto union station68.63556922Shapingba station102.4559946Hongkong West Kowloon station121.3556441Futako-Tamagawa station158.6575839Figure 5
Intersection quantity sampling.Figure 6
Corrected data of intersection quantity of road networks.


## 3. Quantitative Analysis and Results

### 3.1. Model Formulation

The road network structure composed of dense small-scale roads is well known for its convenience for nonmotorists; dense small-scale roads offer more direct road choices for pedestrians and cyclists; small-scale roads and intersections enable smooth crossing by pedestrians and cyclists. Nevertheless, while aspiring to these benefits, the specific design parameters of dense small roads for station catchment areas must be addressed. In cities, dense small-scale roads may lead to a rapid increase in road area ratio. A high road area ratio implies that land for nontraffic functions is reduced which is a significant challenge in the development of urban construction. The road area ratio is calculated as follows:(3)R=AcaSca,where R is the road area ratio, Sca is the station catchment area, and Aca is the road area.The block is the smallest urban unit surrounded by roads. Blocks with different functions are the basis for the formation of a diversified urban space. Blocks based on different scales are closely related to the intersection quantity and network density. A square block model was developed in this study to analyze the corresponding road network density and road intersection quantity under different block-scale planning in the station catchment area. This model is represented as follows:(4)B=∫D,Q,R,where B is the road network characteristics of the square block model, D is the network density, Q is the intersection quantity, and R is the road-area ratio. The square block model was set as a standard grid road network arranged at equal intervals with a side length of 1 km and a coverage area of 1 km 2. The square block model implies that the number of horizontal and vertical roads in the road network is the same, the number of lanes of each road is the same and arranged at equal intervals, and the road sections are two-way traffic comprising 60 m arterial road, 40 m secondary trunk road, and 20 m branch roads with red-line width.Different road network characteristics can yield different values, including the network density, intersection quantity, and road area ratio. To be consistent with the data obtained in the sample cases shown in Figure7, the square block model continuously sets 15 numerical intervals and their corresponding structure types, as shown in Table 4 and Figure 8.Figure 7
Simulation data of the square block model.Table 4
Fifteen numerical intervals set by the square block model.
NameDivided blockThe side length (m)Proportion of areaNetwork density (km/km2)Intersection quantity (pcs/km2)A011940.05.824A024450.0949A039293.313.4616A0416215.017.8825A0525168.022.21036A0636135.026.61249A0749114.3311464A086497.535.41681A098184.439.818100A1010074.044.220121A1112165.548.622144A1214458.35324169A1316952.357.426196A1419647.161.828225A1522542.666.230256Figure 8
Fifteen types of road network structure continuously set by the square block model.


### 3.2. Comparative Analysis of Network Density

Figure3 shows that the road network density in all cases is in the range of 5–25 km/km2 that can be divided into five sections based on the distribution characteristics of the data. There are two cases corresponding to the 5–10 km/km2 range, two cases corresponding to the 10–15 km/km2 range, seven cases corresponding to the 15–20 km/km2 range, and nine cases corresponding to the 20–25 km/km2 range.The standard deviation (STDEV) is a measure of how widely the values are dispersed from the average value (mean) that is used to calculate the dispersion of the interval value of the sample case. The formula used is as follows:(5)a=∑i=1nXi−X2n−1,where X is the average of all sample cases.For the non-China cases, the interval value dispersion of 16 cases is 2.8466, reflecting that the difference in road network density in the above cases is small under station-city integration, with an average value of 18.7746 km/km2. According to the network density clustering shown in Table 5, the road network density of non-China cases is mainly concentrated in A08–A11, and the road area ratio corresponds to 35.4–48.6%.Table 5
Network density clustering.
Name of railway stationNetwork densityName of railway stationNetwork density(1) Osaka-Umeda stationA10-A11(11) Hangzhou west stationA03-A04(2) Shanghai Hongqiao stationA03-A04(12) Yokohama stationA10-A11(3) Kyoto stationA10-A11(13) Oslo central stationA08-A09(4) Nagoya stationA10-A11(14) Utrecht central stationA08-A09(5) Montparnasse stationA08-A09(15) Birmingham new road stationA10-A11(6) King’s Cross-St. PancrasA10-A11(16) Hakata stationA10-A11(7) Tokyo stationA09-A10(17) Sendai stationA08-A09(8) Lille-Europe stationA08-A09(18) Shibuya stationA11-A12(9) Toronto union stationA06-A07(19) Shapingba stationA07-A08(10) Hongkong West Kowloon stationA07-A08(20) Futako-Tamagawa stationA08-A09For the case of China, the Honkong West Kowloon Station (16.93 km/km2) is in the range of 15–20 km/km2. The Shapingba Station (14.86 km/km2) and Toronto Union Station (14.49 km/km2) are in the range of 10–15 km/km2 that is not ideal. The road network density for the Shanghai Hongqiao Station (6.18 km/km2) and Hangzhou West Station (6.53 km/km2) is much lower than that in other cases that objectively reflects the insufficiency of traffic accessibility and pedestrian movement. Furthermore, all the four cases of China feature values below the average value of 18.7746 km/km2.


### 3.3. Comparative Analysis of Intersection Quantity

Figure5 shows that the intersection quantity for all cases is in the range of 0–300 pcs/km2 and is divided into six sections. There are two cases corresponding to the intersection quantity of 0–50 pcs/km2, one case corresponding to 50–100 pcs/km2, five cases corresponding to 100–150 pcs/km2, four cases corresponding to 150–200 pcs/km2, seven cases corresponding to 200–250 pcs/km2, and one case corresponding to 250–300 pcs/km2.For the non-China case, the interval value dispersion of the 16 cases was 35.8647, according to equation (5), and the average value of road intersection quantity was 181.4766 pcs/km2. However, average value of road intersection quantity the Toronto Union Station was only 82.36 pcs/km2. According to the intersection quantity clustering shown in Table 6, the intersection quantity of the non-China cases is mainly concentrated in A10–A14, and the road area ratio is 44.2–61.8%.Table 6
The intersection quantity clustering.
Name of railway stationIntersection quantityName of railway stationIntersection quantity(1) Osaka-Umeda stationA13-A14(11) Hangzhou west stationA03-A04(2) Shanghai Hongqiao stationA02-A03(12) Yokohama stationA12-A13(3) Kyoto stationA13-A14(13) Oslo central stationA10-A11(4) Nagoya stationA13-A14(14) Utrecht central stationA14-A15(5) Montparnasse stationA10-A11(15) Birmingham new road stationA13-A14(6) King’s Cross-St. PancrasA13-A14(16) Hakata stationA12-A13(7) Tokyo stationA12-A13(17) Sendai stationA09-A10(8) Lille-Europe stationA12-A13(18) Shibuya stationA15-A16(9) Toronto union stationA07-A08(19) Shapingba stationA09-A10(10) Hongkong West Kowloon stationA10-A11(20) Futako-Tamagawa stationA11-A12In the cases of China, the Shanghai Hongqiao Station (10.94 pcs/km2) and Hangzhou West Station (21.88 pcs/km2) are in the range of 0–50 pcs/km2. The Hongkong West Kowloon Station (146.62 pcs/km2) and Shapingba Station (102.45 pcs/km2) are in the range of 100–150 pcs/km2. All the four China cases feature values below the average value of 181.4766 pcs/km2.


## 3.1. Model Formulation

The road network structure composed of dense small-scale roads is well known for its convenience for nonmotorists; dense small-scale roads offer more direct road choices for pedestrians and cyclists; small-scale roads and intersections enable smooth crossing by pedestrians and cyclists. Nevertheless, while aspiring to these benefits, the specific design parameters of dense small roads for station catchment areas must be addressed. In cities, dense small-scale roads may lead to a rapid increase in road area ratio. A high road area ratio implies that land for nontraffic functions is reduced which is a significant challenge in the development of urban construction. The road area ratio is calculated as follows:(3)R=AcaSca,where R is the road area ratio, Sca is the station catchment area, and Aca is the road area.The block is the smallest urban unit surrounded by roads. Blocks with different functions are the basis for the formation of a diversified urban space. Blocks based on different scales are closely related to the intersection quantity and network density. A square block model was developed in this study to analyze the corresponding road network density and road intersection quantity under different block-scale planning in the station catchment area. This model is represented as follows:(4)B=∫D,Q,R,where B is the road network characteristics of the square block model, D is the network density, Q is the intersection quantity, and R is the road-area ratio. The square block model was set as a standard grid road network arranged at equal intervals with a side length of 1 km and a coverage area of 1 km 2. The square block model implies that the number of horizontal and vertical roads in the road network is the same, the number of lanes of each road is the same and arranged at equal intervals, and the road sections are two-way traffic comprising 60 m arterial road, 40 m secondary trunk road, and 20 m branch roads with red-line width.Different road network characteristics can yield different values, including the network density, intersection quantity, and road area ratio. To be consistent with the data obtained in the sample cases shown in Figure7, the square block model continuously sets 15 numerical intervals and their corresponding structure types, as shown in Table 4 and Figure 8.Figure 7
Simulation data of the square block model.Table 4
Fifteen numerical intervals set by the square block model.
NameDivided blockThe side length (m)Proportion of areaNetwork density (km/km2)Intersection quantity (pcs/km2)A011940.05.824A024450.0949A039293.313.4616A0416215.017.8825A0525168.022.21036A0636135.026.61249A0749114.3311464A086497.535.41681A098184.439.818100A1010074.044.220121A1112165.548.622144A1214458.35324169A1316952.357.426196A1419647.161.828225A1522542.666.230256Figure 8
Fifteen types of road network structure continuously set by the square block model.


## 3.2. Comparative Analysis of Network Density

Figure3 shows that the road network density in all cases is in the range of 5–25 km/km2 that can be divided into five sections based on the distribution characteristics of the data. There are two cases corresponding to the 5–10 km/km2 range, two cases corresponding to the 10–15 km/km2 range, seven cases corresponding to the 15–20 km/km2 range, and nine cases corresponding to the 20–25 km/km2 range.The standard deviation (STDEV) is a measure of how widely the values are dispersed from the average value (mean) that is used to calculate the dispersion of the interval value of the sample case. The formula used is as follows:(5)a=∑i=1nXi−X2n−1,where X is the average of all sample cases.For the non-China cases, the interval value dispersion of 16 cases is 2.8466, reflecting that the difference in road network density in the above cases is small under station-city integration, with an average value of 18.7746 km/km2. According to the network density clustering shown in Table 5, the road network density of non-China cases is mainly concentrated in A08–A11, and the road area ratio corresponds to 35.4–48.6%.Table 5
Network density clustering.
Name of railway stationNetwork densityName of railway stationNetwork density(1) Osaka-Umeda stationA10-A11(11) Hangzhou west stationA03-A04(2) Shanghai Hongqiao stationA03-A04(12) Yokohama stationA10-A11(3) Kyoto stationA10-A11(13) Oslo central stationA08-A09(4) Nagoya stationA10-A11(14) Utrecht central stationA08-A09(5) Montparnasse stationA08-A09(15) Birmingham new road stationA10-A11(6) King’s Cross-St. PancrasA10-A11(16) Hakata stationA10-A11(7) Tokyo stationA09-A10(17) Sendai stationA08-A09(8) Lille-Europe stationA08-A09(18) Shibuya stationA11-A12(9) Toronto union stationA06-A07(19) Shapingba stationA07-A08(10) Hongkong West Kowloon stationA07-A08(20) Futako-Tamagawa stationA08-A09For the case of China, the Honkong West Kowloon Station (16.93 km/km2) is in the range of 15–20 km/km2. The Shapingba Station (14.86 km/km2) and Toronto Union Station (14.49 km/km2) are in the range of 10–15 km/km2 that is not ideal. The road network density for the Shanghai Hongqiao Station (6.18 km/km2) and Hangzhou West Station (6.53 km/km2) is much lower than that in other cases that objectively reflects the insufficiency of traffic accessibility and pedestrian movement. Furthermore, all the four cases of China feature values below the average value of 18.7746 km/km2.


## 3.3. Comparative Analysis of Intersection Quantity

Figure5 shows that the intersection quantity for all cases is in the range of 0–300 pcs/km2 and is divided into six sections. There are two cases corresponding to the intersection quantity of 0–50 pcs/km2, one case corresponding to 50–100 pcs/km2, five cases corresponding to 100–150 pcs/km2, four cases corresponding to 150–200 pcs/km2, seven cases corresponding to 200–250 pcs/km2, and one case corresponding to 250–300 pcs/km2.For the non-China case, the interval value dispersion of the 16 cases was 35.8647, according to equation (5), and the average value of road intersection quantity was 181.4766 pcs/km2. However, average value of road intersection quantity the Toronto Union Station was only 82.36 pcs/km2. According to the intersection quantity clustering shown in Table 6, the intersection quantity of the non-China cases is mainly concentrated in A10–A14, and the road area ratio is 44.2–61.8%.Table 6
The intersection quantity clustering.
Name of railway stationIntersection quantityName of railway stationIntersection quantity(1) Osaka-Umeda stationA13-A14(11) Hangzhou west stationA03-A04(2) Shanghai Hongqiao stationA02-A03(12) Yokohama stationA12-A13(3) Kyoto stationA13-A14(13) Oslo central stationA10-A11(4) Nagoya stationA13-A14(14) Utrecht central stationA14-A15(5) Montparnasse stationA10-A11(15) Birmingham new road stationA13-A14(6) King’s Cross-St. PancrasA13-A14(16) Hakata stationA12-A13(7) Tokyo stationA12-A13(17) Sendai stationA09-A10(8) Lille-Europe stationA12-A13(18) Shibuya stationA15-A16(9) Toronto union stationA07-A08(19) Shapingba stationA09-A10(10) Hongkong West Kowloon stationA10-A11(20) Futako-Tamagawa stationA11-A12In the cases of China, the Shanghai Hongqiao Station (10.94 pcs/km2) and Hangzhou West Station (21.88 pcs/km2) are in the range of 0–50 pcs/km2. The Hongkong West Kowloon Station (146.62 pcs/km2) and Shapingba Station (102.45 pcs/km2) are in the range of 100–150 pcs/km2. All the four China cases feature values below the average value of 181.4766 pcs/km2.


## 4. Discussion

Here, a comparative study has been conducted on the road network characteristics of station catchment areas encompassed by station-city integration between China and other countries to support design practices. Based on the results of data analysis and comparison, we consider the following aspects worthy of further discussion.


### 4.1. Importance of Setting Planning Standards and Design Codes

As per the survey results, first, the average road network density of non-China cases was 18.7746 km/km2, mainly concentrated in A08–A11 (16–22 km/km2). The Shanghai Hongqiao Station and Hangzhou West Station were in A03–A04 (6–8 km/km2), and the Hongkong West Kowloon Station and Shapingba Station were in A07–A8 (14–16 km/km2). Second, the average road intersection quantity of non-China sample cases was 181.4766 pcs/km2, mainly concentrated in A10–A14 (121–225 pcs/km2). The Shanghai Hongqiao Station and Hangzhou West Station were located in A2–A4 (9–25 pcs/km2), and the Hongkong West Kowloon Station and Shapingba Station were in A9–A11 (100–144 pcs/km2). Third, the average road area ratio of the non-China cases was greater than that of the cases of China.However, it is surprising to note that the road network characteristics of the cases of China meet the current specifications.(i)
《Code for transport planning on urban road GB 50220-95》stipulates that the road density should be 5.3–7.1 km/km2 in large cities, 5.2–6.6 km/km2 in medium-sized cities, and 6–14 km/km2 in small cities.(ii)
《Standard for urban comprehensive transport system planning GB/T 51328-2018》proposes requirements for road network density for different types of functional areas from the perspectives of block scale and road network density. The standard requires the road network density of residential functional areas to be 7–15 km/km2 and that of business functional areas to be 10–20 km/km2.(iii)
《Code for Classification of Urban Land Use and Planning Standards of Development Land GB 50137-2011》stipulates that the proportion of road area should be 10–25%.As the implementation of station-city integration has started only recently in China, there are no absolute specifications for the planning standards and design codes of the road network in station catchment areas in China. It is necessary to comprehensively understand the characteristics of road networks in station catchment areas for station-city integration and to advance the setting of planning standards and design codes conducive to rapid development in the later stages.


### 4.2. Entire Urban Road Network Correlation

It should be noted that there are significant differences in the characteristics of road networks across different cities. The road network of station catchment areas is a part of the entire urban road network; therefore, it is also affected by the entire urban road network.Table7 presents the overall urban road network density for the corresponding station catchment areas. Figure 9 shows the correspondence of two groups of data: the entire urban road network density and the corresponding road network of the station catchment areas. It can be observed that the two groups of data are the same. The correspondence analysis illustrates the implicit feature that the sample case does not deliberately enhance the road network density of station catchment areas; it is merely an extension of the characteristics of the entire urban road network density. Thus, the judgement of road network density of road network in station catchment areas involves the entire urban road network. This also indirectly shows that station-city integration is based on a higher level of urban development.Table 7
Entire urban road network density with the corresponding station catchment areas.
Name of railway stationUrban road network densityName of railway stationUrban road network densityOsaka-Umeda station23.99Hangzhou West station6.98Shanghai Hongqiao station7.15Yokohama station23.22Kyoto station21.19Oslo central station18.6Nagoya station25.08Utrecht central station16.3Montparnasse station15.4Birmingham new road station17.9King’s Cross-St. Pancras18.1Hakata station22.4Tokyo station19.92Sendai station5.10Lille-Europe station17.78Shibuya station19.92Toronto union station23.74Shapingba station6.49Hongkong West Kowloon station22.9Futako-Tamagawa station19.92Figure 9
Correspondence of two groups of data.


### 4.3. Development of Small-Scale Blocks

The square block model shows that the road area ratio is closely related to the road network density and road intersection quantity. Figure8 shows that small-scale blocks may lead to a rapid increase in the road-area ratio by more than 50%. The development of station catchment areas is not entirely spontaneous, but entails conscious spatial guidance to adapt to station-city integration; the development of small-scale blocks is the primary starting point. Increased number of road intersections is generally associated with increased walking and biking [17].Based on the results of the comparative analysis, non-China cases were concentrated in A08–A14, and the corresponding road area ratio was 35.4–61.8%. Based on the above interval, the side length of the block was 47.1–97.5 m. In contrast, the Shanghai Hongqiao Station and Hangzhou West Station were “large blocks,” with a side length of 215.0–293.3 m. The larger the blocks are, the smaller and narrower is the road space available for external public transport. Traffic flow can only be concentrated on a limited number of roads that are prone to congestion and affects public interests.Although the connectivity of the station catchment areas was improved in the small-scale blocks, it would incorporate more road intersections and T-shaped roads to the block, increasing the complexity of traffic flow and increasing the travel time. Therefore, developing small-scale blocks by gridding had an optimal effect on station catchment areas within a side-length range of 47.1–97.5 m.


### 4.4. Limits and Prospects

Overall, the conclusions of this study convey the differences in road network characteristics in station catchment areas between China and other countries from three aspects: road network density, road intersection quantity, and road area ratio. Nonetheless, the study has the following limitations: First, owing to the limited number of samples, the applicability of the conclusions drawn by the study to other regions is still to be explored. Second, the study did not analyze the appropriate grade proportion of road networks in the station catchment areas. Third, in the sample case, the rationality of the road network in the station catchment areas depends partly on synthetic judgement.Despite these deficiencies, this study still makes a significant contribution. Through an investigation of a series of cases, the characteristics of road networks in station catchment areas were compared by rational quantitative means. To compensate for these shortcomings, future research needs to be combined with new technical means and methods for expansion. (1) Computer science, particularly, the application of simulation tools, would provide a fast evaluation method for the performance of road network. (2) The synergetic method can clarify the correlation between transportation exchange centers and road networks in station catchment areas.


## 4.1. Importance of Setting Planning Standards and Design Codes

As per the survey results, first, the average road network density of non-China cases was 18.7746 km/km2, mainly concentrated in A08–A11 (16–22 km/km2). The Shanghai Hongqiao Station and Hangzhou West Station were in A03–A04 (6–8 km/km2), and the Hongkong West Kowloon Station and Shapingba Station were in A07–A8 (14–16 km/km2). Second, the average road intersection quantity of non-China sample cases was 181.4766 pcs/km2, mainly concentrated in A10–A14 (121–225 pcs/km2). The Shanghai Hongqiao Station and Hangzhou West Station were located in A2–A4 (9–25 pcs/km2), and the Hongkong West Kowloon Station and Shapingba Station were in A9–A11 (100–144 pcs/km2). Third, the average road area ratio of the non-China cases was greater than that of the cases of China.However, it is surprising to note that the road network characteristics of the cases of China meet the current specifications.(i)
《Code for transport planning on urban road GB 50220-95》stipulates that the road density should be 5.3–7.1 km/km2 in large cities, 5.2–6.6 km/km2 in medium-sized cities, and 6–14 km/km2 in small cities.(ii)
《Standard for urban comprehensive transport system planning GB/T 51328-2018》proposes requirements for road network density for different types of functional areas from the perspectives of block scale and road network density. The standard requires the road network density of residential functional areas to be 7–15 km/km2 and that of business functional areas to be 10–20 km/km2.(iii)
《Code for Classification of Urban Land Use and Planning Standards of Development Land GB 50137-2011》stipulates that the proportion of road area should be 10–25%.As the implementation of station-city integration has started only recently in China, there are no absolute specifications for the planning standards and design codes of the road network in station catchment areas in China. It is necessary to comprehensively understand the characteristics of road networks in station catchment areas for station-city integration and to advance the setting of planning standards and design codes conducive to rapid development in the later stages.


## 4.2. Entire Urban Road Network Correlation

It should be noted that there are significant differences in the characteristics of road networks across different cities. The road network of station catchment areas is a part of the entire urban road network; therefore, it is also affected by the entire urban road network.Table7 presents the overall urban road network density for the corresponding station catchment areas. Figure 9 shows the correspondence of two groups of data: the entire urban road network density and the corresponding road network of the station catchment areas. It can be observed that the two groups of data are the same. The correspondence analysis illustrates the implicit feature that the sample case does not deliberately enhance the road network density of station catchment areas; it is merely an extension of the characteristics of the entire urban road network density. Thus, the judgement of road network density of road network in station catchment areas involves the entire urban road network. This also indirectly shows that station-city integration is based on a higher level of urban development.Table 7
Entire urban road network density with the corresponding station catchment areas.
Name of railway stationUrban road network densityName of railway stationUrban road network densityOsaka-Umeda station23.99Hangzhou West station6.98Shanghai Hongqiao station7.15Yokohama station23.22Kyoto station21.19Oslo central station18.6Nagoya station25.08Utrecht central station16.3Montparnasse station15.4Birmingham new road station17.9King’s Cross-St. Pancras18.1Hakata station22.4Tokyo station19.92Sendai station5.10Lille-Europe station17.78Shibuya station19.92Toronto union station23.74Shapingba station6.49Hongkong West Kowloon station22.9Futako-Tamagawa station19.92Figure 9
Correspondence of two groups of data.


## 4.3. Development of Small-Scale Blocks

The square block model shows that the road area ratio is closely related to the road network density and road intersection quantity. Figure8 shows that small-scale blocks may lead to a rapid increase in the road-area ratio by more than 50%. The development of station catchment areas is not entirely spontaneous, but entails conscious spatial guidance to adapt to station-city integration; the development of small-scale blocks is the primary starting point. Increased number of road intersections is generally associated with increased walking and biking [17].Based on the results of the comparative analysis, non-China cases were concentrated in A08–A14, and the corresponding road area ratio was 35.4–61.8%. Based on the above interval, the side length of the block was 47.1–97.5 m. In contrast, the Shanghai Hongqiao Station and Hangzhou West Station were “large blocks,” with a side length of 215.0–293.3 m. The larger the blocks are, the smaller and narrower is the road space available for external public transport. Traffic flow can only be concentrated on a limited number of roads that are prone to congestion and affects public interests.Although the connectivity of the station catchment areas was improved in the small-scale blocks, it would incorporate more road intersections and T-shaped roads to the block, increasing the complexity of traffic flow and increasing the travel time. Therefore, developing small-scale blocks by gridding had an optimal effect on station catchment areas within a side-length range of 47.1–97.5 m.


## 4.4. Limits and Prospects

Overall, the conclusions of this study convey the differences in road network characteristics in station catchment areas between China and other countries from three aspects: road network density, road intersection quantity, and road area ratio. Nonetheless, the study has the following limitations: First, owing to the limited number of samples, the applicability of the conclusions drawn by the study to other regions is still to be explored. Second, the study did not analyze the appropriate grade proportion of road networks in the station catchment areas. Third, in the sample case, the rationality of the road network in the station catchment areas depends partly on synthetic judgement.Despite these deficiencies, this study still makes a significant contribution. Through an investigation of a series of cases, the characteristics of road networks in station catchment areas were compared by rational quantitative means. To compensate for these shortcomings, future research needs to be combined with new technical means and methods for expansion. (1) Computer science, particularly, the application of simulation tools, would provide a fast evaluation method for the performance of road network. (2) The synergetic method can clarify the correlation between transportation exchange centers and road networks in station catchment areas.


## 5. Conclusion

The road network is one of the most important factors affecting urban traffic operation in station catchment areas as well as the main factor of station-city integration. Based on 20 sample cases, this study compares the performance of road networks in China with those in Europe, North America, and Japan and draws the following conclusions:(1)
Through a comparative analysis of road network density, it is found that the road network density of the station catchment areas is concentrated in 16–22 km/km2. The Honkong West Kowloon Station and Shapingba Station approach this range, while the Shanghai Hongqiao Station and Hangzhou West Station exhibit values considerably lower than this range.(2)
Through a comparative analysis of road intersection quantity, it is found that the road intersection quantity of station catchment areas is concentrated in 121–225 pcs/km2. Except for the Honkong West Kowloon Station, the Shapingba Station, Shanghai Hongqiao Station, and Hangzhou West Station exhibit lower values than this range.(3)
According to the calculation results of the square block model, the road area ratio is 44.2–61.8%, and the side length of block is 47.1–97.5 m. Small-scale blocks in station catchment areas could be developed based on the aforementioned range.(4)
It is found that the current situation of the entire urban road network and specific specifications for the design codes of the road network are correlated with the road network characteristics of the station catchment areas.



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*Source: 1910404-2022-05-11.xml*