Happiness is in the journey: A different view on measuring accessibility in human-centred cities

Research output: Contribution to conferenceAbstractpeer-review

Abstract

Accessibility-oriented planning is based on the idea that the ultimate goal of the
transport system is not to provide people the ability to move per se, but rather
the ability to access their desired destinations. Prioritising accessibility is widely
regarded to enhance sustainability and social equality in cities, and promote the
uptake of active transport modes.

However, in the way we currently measure accessibility, the trip towards
the destination has no value in itself. It is just a demand derived from the
need to reach the destination. A cost that should be minimised. This cost is
usually expressed in terms of travel time. Other approaches have started to
include different types of monetary, societal and/or environmental costs as well,
but even in these cases, the focus remains on the negative effects of mobility.
It is still seen as a disutility. Recent research has challenged this dominating
view of mobility as a disutility, and proposed alternative narratives that instead
underpin the benefits of mobility, and active mobility in particular: a way to
experience positive mental states, to socially interact, to develop senses of place
and belonging, and to increase well-being. Hence, mobility is something that has
value in itself, and can provide us with many different pleasurable experiences.
We believe that these alternative narratives should be integrated in the way
we think about accessibility, and how we measure it. Our hypothesis is that
pleasurable experiences during the trip to the desired destination can make the
destination itself be perceived as more accessible. If this holds true, we can
improve accessibility by designing streets in a way that fosters such experiences
(e.g. through green, shared spaces with many possibilities for social interactions),
even if this means that the estimated cost to reach the desired destinations
is higher than if we would design the street in a way that prioritises fast and
efficient travel (e.g. bicycle highways). This may shift the focus of urban planning
practices towards designing liveable streets that connect people to the places they
move through.

Ongoing developments in spatial data science have made it a realistic goal
to integrate these alternative views into quantitative frameworks that assess ac-
cessibility. For example, with LiDAR scanning techniques we can digitally rep-
resent different environments people move through from a human perspective.
By combining quantitative emotion sensing with qualitative questionnaires in
mixed-method approaches, we are able to measure how people experience these
environments. Augmented reality can extend this into computer-generated envi-
ronments that do not yet exist in the real world. Furthermore, with bottom-up
simulation models of human movement we may assess how different street de-
signs are fostering social interactions. In a next step, automated interpretation of
(generated) imagery through GeoAI can help us to evaluate planning scenarios
based on the developed insights.

Considering the above, we hope to spark a fruitful discussion on what acces-
sibility really means to people, and how spatial data science can address this.
Original languageEnglish
Publication statusPublished - 12 Sept 2023
EventGIScience 2023: The 12 International Conference on Geographic Information Science. - University of Leeds, Leeds, United Kingdom
Duration: 12 Sept 202315 Sept 2023
Conference number: 12
https://giscience2023.github.io

Conference

ConferenceGIScience 2023
Abbreviated titleGIScience
Country/TerritoryUnited Kingdom
CityLeeds
Period12/09/2315/09/23
Internet address

Keywords

  • sustainable mobility
  • accessibility
  • human-centred data science
  • urban geoinformatics
  • spatial data science
  • urban planning

Fields of Science and Technology Classification 2012

  • 102 Computer Sciences
  • 507 Human Geography, Regional Geography, Regional Planning

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