As the world is getting smaller, more and more people are living in cities. By 2050, two thirds of the world’s population will live in cities (United Nations, 2018). These changes, together with a pressing need to reduce carbon emission, clearly underline the importance of public transport. But how can the quality of public transport be measured? This question is not only relevant to city planners, but also to consumers, particularly people moving, who may wonder which location may suit their transit needs the best.
There are several measures of the quality of public transport that vary in their approach and complexity. We will briefly give an overview of the most important ones and how to implement them in an urban environment.
Access to public transport
The simplest measure of quality of public transport is the access to public transport. Access to public transport includes measures of temporal availability, e.g. how often is a bus station served per hour and how many hours in a day is a transit station being served (Barker et al., 2003; Poelman & Dijkstra, 2015). In this context, it is also important to consider which area a particular transit station serves. Taking into account the different travel speeds and susceptibility to congestion of the different modes of transport, such as trains, metros, busses and trams, it makes sense to calculate their service area differently. Thus, trains and metros include a service area of 10 walking minutes while trams and bus station include a service area of 5 walking minutes (Poelman & Dijkstra, 2015). With this information, we can calculate how good a particular address’s access to public transport is.
An advantage of measuring access to public transport is that it’s intuitive and allows for a good estimate of the quality of public transport at a quick glance. For example, city planners can use this measure to identify areas that lack access easily. A disadvantage of this kind of measure is that its informative value is limited. For example, these measures are only relevant locally, they do not consider the broader network or the locations that can be reached from the transit stations. Moreover, these measures are not suited to assess a location’s car dependency which is an important indicator of sustainability (Rubulotta, Ignaccolo, Inturri, & Rofé, 2013; Siedentop, Roos, & Fina, 2013).
Another approach to measure the quality of urban public transit is rooted in network analysis. In this approach, the city is seen as a network, consisting of individual nodes (i.e. transit stations) that are connected via edges (i.e. routes). By considering the location and the connections of each node, the importance of a transit station can be assessed. There are different ways to measure this. The simplest measure is degree centrality. Degree centrality indicates how many connections a transit station has. In the context of public transport, this indicates how many routes a bus station serves. A bit more sophisticated is closeness centrality. This measure indicates how close a node or transit station is to all other nodes in the network. The most important measure related to public transport is betweenness centrality. It measures whether a node functions as a bridge towards other nodes. Thus, a public transport station with a high betweenness centrality serves as an important transfer point or connector to many regions within the network (Scheurer, Curtis, & Porta, 2007).
The advantages of network-based measures are that they give a good quantitative estimation about the importance of a node in a network that is otherwise difficult to assess. Research shows that public transport performs better in areas with higher centrality (Scheurer et al., 2007). The disadvantages of network-based measures are that the calculations become increasingly complex with the size of the network and that centrality is a rather abstract concept which may be rather difficult to comprehend.
A more intuitive measure of quality of public transport is accessibility. Accessibility measures how easily certain locations can be reached by foot and/or public transport. It not only takes the spatial configuration of places into account, but also which services can be reached (Farber, Morang, & Widener, 2014).
For example, common measures are supermarket accessibility (Farber et al., 2014; Widener, Farber, Neutens, & Horner, 2015) or job accessibility (Fan, Guthrie, & Levinson, 2012). There are different ways to assess accessibility (Boisjoly & El-Geneidy, 2016). The simplest assessment is to measure access at a certain day time (e.g., 8am) and to see how many opportunities can be reached within certain time frames (e.g., 10, 20 min). The drawback of this simple measures is that accessibility can change quite rapidly. For example, if a less well-connected place has good accessibility one min before a bus comes, it has much worse accessibility one min after the bus left. This is why accessibility is sometimes measured by taking the average of min by min accessibility (Farber et al., 2014). While this may give a good estimation, it is also quite heavy to compute.
In general, accessibility is a meaningful and intuitive measure of public transport. It enables city planners to spot places which lack certain services (e.g., food deserts, places which do not have sufficient access to supermarkets). Displaying accessibility to different services is important as individual transportation needs vary (El-Geneidy & Levinson, 2006). Unfortunately, however, similar to measuring centrality, the bigger the network, the more complex computations become.
This brief overview shows that there are various measures of the quality of public transport that vary in complexity. While access to public transport is relatively easily measured, accessibility and network-based centrality measures are more sophisticated. When choosing a measure, it’s important to make sure that the measure is transparent and easy to grasp for city planners and consumers alike. This is especially important for data-driven policy (TNO, 2020). From this standpoint, concrete rather than abstract measures seem the best option. Implementing measures of access to public transport can help to identify well-connected areas without making any heavy computational demands. These basic measures can be expanded to include accessibility measures. Here it is important to include the most basic services (e.g., supermarkets, GPs) before expanding to services that may be especially important to subgroups (e.g., schools).
Measures of the quality of public transport are not only important for data driven policy making but also for the evaluation of real estate and for making location-based decisions. For example, accessibility to jobs is correlated with housing prices (El-Geneidy & Levinson, 2006). Moreover, accessibility measures can help to decide where to locate new service providers, such as supermarkets.
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