Multi-dimensional accessibility metrics for evaluating investments in cycling infrastructure

Numerical indicators play a big role in the evaluation of proposals for political interventions in our living environment. Decision makers love to see numbers that can easily be understood and compared, in order to define which alternative is best. In the big data era, this form of planning is known as evidence-based planning. Each decision needs to be supported by objective, quantitative information, usually produced by models that process data from various sources.

For a long time, and still today, mobility-based indicators have been the most common type of indicators used in transport planning. These indicators are focused on the efficiency of the transport network itself. The further and faster people can move, the better it is, according to this paradigm. Over the years, critiques of this approach have advocated the usage of accessibility-based indicators. These indicators represent the idea that it is not necessarily the movement itself that is important, but the opportunities that you can reach by the act of moving.

Although various types of accessibility-based indicators exist, most of them are the result of a focus on the same thought: reaching more opportunities within a shorter amount of time leads to a higher accessibility. That is, using accessibility-based indicators still promotes the speed of movement as a key measure to be optimized. This is especially true in transport infrastructure interventions, that do not affect the land-use component. Given a fixed land-use, you can reach more opportunities (or at least the same amount) within less time if you move faster, thus improving accessibility. This favors investments focused on the fastest mode of transport. In most cases this is the car, especially on larger scales, and when routing algorithms do not account for congestion or time spent looking for a parking spot. This makes it complicated for investments in cycling infrastructure, as well as investments in any infrastructure intervention that actually slows down the speed of movement (e.g. shared-space or car-free streets), to be prioritized.

To promote cycling, and a people-centered living environment as a whole, we need to redefine what accessibility actually means to people. The term accessibility is still rather vaguely defined in the academic literature, often something along the lines of “the ease with which you can reach opportunities”. Automatically, this seems to be translated into “the speed at which you can reach opportunities”. But should it be that way? Is a place more accessible when you can get there faster? Or is it maybe more accessible when you can get there happier? Or healthier? Or safer? Accessibility is a multi-dimensional concept, and we need metrics that reflect that. Some of its dimensions may be hard to quantify, especially since they are valued differently by different people. However, with the increasing amount of available data and tools, spatial data science techniques may be able to at least approximate them.

In our presentation, we’d like to discuss the concept of people-centered, multi-dimensional accessibility, and its implications for cycling-oriented planning, in an interactive way. We will bring in our own views on the topic, and hope to gather ideas, experiences, and critical feedback. What are the dimensions of accessibility, and what are the changes that we can actually quantify them in a way that remains transparent and understandable? Or, should we drop the focus on numerical indicators and evidence-based planning altogether?