An improved potential-based approach to measuring the daily accessibility of HSR
Introduction
High speed rail (HSR) has grown popular in many countries due to its fast speed, safety, and low energy consumption. HSR has not only become the focus of world railway modernization but also been an important symbol of modern society (Arduin and Ni, 2005). At the same time, HSR shortens distances in space and time and has significantly improved accessibility in cities, thus playing an important role in intercity passenger transport (Zhang et al., 2016, Wan et al., 2016, Gutiérrez, 2001, Ureña et al., 2009, Shaw et al., 2014, Mota et al., 2017). HSR thus in turn promotes the mobility of individuals and economic exchanges between different cities (Zhang et al., 2016, Yu and Fan, 2018, Amidi and Majidi, 2020) and improves regional cohesion. Daily accessibility, defined as intercity around-trip travel that can be completed in the daytime within the threshold of a 4-hours one-way journey (Martín et al., 2004), significantly extends the reach of human travel and economic activities performed in a day. Thus, the resulting impacts on economic exchanges among cities are substantial. Rather, daily accessibility has redefined what a business trip is and has become an important measure of decision making in urban or transport network planning (Shaw et al., 2014). Therefore, daily accessibility improvements and their effects have increasingly become the focus of scholars' attention. The measurement of daily accessibility achieved by HSR has thus become an important issue.
Accessibility is defined in several ways in the literature (Chang and Lee, 2008, Geurs and Wee, 2004, Gutiérrez, 2001, Páez et al., 2012, Martín et al., 2004, L’Hostis, 2009, Cao et al., 2013, Monzón et al., 2013; Shaw et al., 2014, Jiao et al., 2014, Moyano et al., 2018). In practical studies, many scholars make use of two or more approaches to analyze the accessibility of HSR (Gutiérrez, 2001, Chen et al., 2014, Jiang and Chu, 2017). In general, approaches to measuring accessibility can be classified into three basic types: utility-based accessibility approaches, time-based (or location-based) accessibility approaches, and potential-based (or gravity-based) accessibility approaches. Utility-based accessibility approaches refer to the benefits that people derive from accessing spatially distributed activities by transport as the outcome of a set of transport choices (Geurs and Wee, 2004). This type of approach is largely focused on transport costs and adopts a person-based measure that depends on the amount and spatial distribution of supplied opportunities and is often used in microlevel accessibility analyses, such as those focused on job and medical accessibility. The method’s major advantage relates to its usability in the economic evaluation and its convenience in assessing the improvement in accessibility for individuals. The method’s disadvantage is rooted in the fact that it is often used for within city measurements of accessibility. Collecting the needed data at the individual level to measure this type of accessibility is often difficult.
The time-based (or location-based) accessibility approach is based on the locations of HSR stations and determines accessibility by calculating travel time between different HSR stations in an HSR network. Three measures of travel time are adopted: the minimum time, average time and total time. The first two measures of travel time mainly refer to the time take to travel between nodes (the origin station in one city to the destination station in another city), which is also referred to as intercity time. The total time includes intercity time and the time taken to travel from an HSR station to an office or home (i.e., intracity time) within an urban agglomeration (Wang et al., 2013). Therefore, the identification of travel time plays a decisive role in this approach. For example, if we consider access and egress times for high-speed rail stations, it will help to determine the details of spatiotemporal accessibility and make more sense to apply this method to stations located along a high-speed line outside of a city or in the large metropolitan area, which tend to be characterized by heavy traffic or low quality urban transport systems (Moyano et al., 2018). Additionally, if we only consider the time taken to travel between two transport nodes, this method reflects time–space convergence or contraction in HSR networks (L’Hostis, 2009). In general, this kind of approach is very simple and clearly illustrates accessibility changes created by an HSR line or network and shows improvements in accessibility due to HSR. This method is widely used in research on high-speed rail accessibility. For example, Gutiérrez (2001) and Martín et al. (2004) used the minimum time and GDP to evaluate accessibility impacts, while López et al. (2008), Cao et al., 2013, Jiang and Chu, 2017, Yu and Fan, 2018 used the average weighted time and GDP (or the population or both) to measure accessibility. Wang et al. (2013) used the whole time to evaluate time savings and to investigate the user friendliness of HSR. However, this type of approach only considers the physical distance (in travel time) between the origin and destination without considering train frequencies. It is well known that train frequency is an important characteristic of HSR services and a critical factor in determining whether an individual chooses to take an HSR train. Thus, this variable should be considered, particularly in measuring daily accessibility.
Potential-based (or gravity-based) accessibility approaches are based on the potential opportunities provided by HSR services and take the distance–decay function as a plausible weight to measure accessibility (Martín et al., 2004, López et al., 2008, Cao et al., 2013, Monzón et al., 2013, Jiang and Chu, 2017). This method is positively related to the mass of the destination (e.g., population and GDP), and inversely proportional to a power of distance or travel time between the two HSR stations considered (Geurs and Wee, 2004). Distance here not only refers to spatial distance but also to temporal distance. The outcome of this type of approach is that closer to a high-speed railway station, accessibility levels are higher (Kim and Sultana, 2015). Relating accessibility to city or regional economic conditions has practical advantages for the spatial-economic evaluation of transport projects. Thus, this approach is widely used in accessibility studies (Gutiérrez, 2001). For example, Monzón et al. (2013) used this approach to evaluate the efficiency and spatial equity impacts of high-speed rail extensions in urban areas. Jiang and Chu (2017) used the indicator to evaluate spatial patterns and differences in the economic potential of HSR networks in China. The main advantage of this approach is that it focuses on the conditions found in destinations and contributes to the analysis of relationships between destination and departure cities. While this approach considers economic factors, it does not consider the train frequency and thus has the same deficiencies as time-based approaches in analyzing the daily accessibility.
From the above analysis, we found that these accessibility measures do not consider train frequency or daily schedules; even though some studies mention frequency, they provide only simple descriptions and do not include frequency in the measurement of accessibility (Shaw et al., 2014, Wang, 2018). However, in measuring daily accessibility, it is extremely important to consider train frequency because daily trips between two cities need to be planned very accurately if one needs to return to one’s home city on the same day. In addition, an important characteristic of HSR concerns its frequent services between two cities provided in a day. Thus, studies on the daily accessibility provided by HSR must consider train frequency. In addition, we found that accessibility has much to do with the mass of the destination and depends on GDP and population. This is the case because high-speed transport at first passes through densely populated and economically developed regions (Wang et al., 2017). In addition, the area of the destination is not included in the mass of the destination, while area is an important factor in analyzing the scope of accessible regions. Thus, studies on daily accessibility provided by HSR should consider the area of the destination.
The main purpose of this paper is to construct an improved approach for providing a more fine-grained understanding of daily accessibility by considering train frequency. The potential-based accessibility approach ties accessibility to economic potential and is a widely used approach. We use this approach as a basis to illustrate the effectiveness of incorporating train frequency and area into daily accessibility. The rest of this paper is structured as follows. The second section introduces the improved potential-based accessibility approach; the third section describes our study area and data sources; the fourth section lists the results of the improved potential-based approach and a discussion; and the fifth section concludes.
Section snippets
Determination of train frequency from train schedules
To incorporate train schedules into the daily accessibility measure, train schedules need to be converted into train frequency. For this purpose, we divided the travel time of a day into 5 time intervals by travel time, 0–30 min, 30 min – 1 h, 1–2 h, 2–3h and 3–4 h, applying the upper limit of a 4-hour one-way journey (a round-trip journey can be completed in one day). The train frequencies of different intervals refer to the number of trains travelling between city i station and destination j
Study area
Shandong Province, located in eastern China between Beijing and Shanghai (Fig. 1), includes 16 prefecture-level cities and covers an area of 158,000 km2 with a population of 100.09 million (by the end of 2017). Shandong Province is the second largest province in population and the third largest province in GDP in China. HSR and non-HSR cities coexist in the province, and a comparative analysis can thus be performed on HSR and Non-HSR accessibility in the same province. In addition, the province
Correlation between accessibility and GDP
As we know, many factors affect the accessibility of HSR, including levels of economic development, population, network effects and service structures. GDP is the most useful indicator of the economic status of a region, and the daily accessibility of one region should be correlated with its local economic development. In comparing the correlations between the accessibility index (calculated by Equations (1), (2), (3), (4), (5), (6)) and GDP for the improved and original approaches, we can
Discussions and conclusions
From the above comparative analysis and discussion, we find that the improved potential-based accessibility approach offers the advantages of more accurately reflecting changes or improvements in daily accessibility by HSR. In other words, it is appropriate and scientific to consider train frequency when evaluating the accessibility of HSR.
First, from our correlation analysis between the accessibility of different time intervals and local economic development (GDP), we find that the improved
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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