"...when you're a stranger": Evaluating safety perceptions of (un)familiar urban places

Martin Traunmueller, Paul Marshall, Licia Capra

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

9 Citations (Scopus)

Abstract

What makes us feel safe when walking around our cities? Previous research has shown that our perception of safety strongly depends on characteristics of the built environment; separately, research has also shown that safety perceptions depend on the people we encounter on the streets. However, it is not clear how the two relate to one another. In this paper, we propose a quantitative method to investigate this relationship. Using an online crowd-sourcing approach, we collected 5452 safety ratings from over 500 users about images showing various combinations of built environment and people inhabiting it. We applied analysis of covariance (ANCOVA) to the collected data and found that familiarity of the scene is the single most important predictor of our sense of safety. Controlling for familiarity, we identified then what features of the urban environment increase or decrease our safety perception.

Original languageEnglish
Title of host publicationUrb-IoT 2016 - 2nd International Conference on IoT in Urban Space, Conference Proceedings
PublisherAssociation for Computing Machinery (ACM)
Pages71-77
Number of pages7
Volume24-25-May-2016
ISBN (Electronic)9781450342049
DOIs
Publication statusPublished - 24 May 2016
Event2nd International Conference on IoT in Urban Space, Urb-IoT 2016 - Tokyo, Japan
Duration: 24 May 201625 May 2016

Conference

Conference2nd International Conference on IoT in Urban Space, Urb-IoT 2016
CountryJapan
CityTokyo
Period24/05/1625/05/16

Keywords

  • Crowdsourcing
  • Environment
  • Perception
  • Safety
  • Urban

Cite this

Traunmueller, M., Marshall, P., & Capra, L. (2016). "...when you're a stranger": Evaluating safety perceptions of (un)familiar urban places. In Urb-IoT 2016 - 2nd International Conference on IoT in Urban Space, Conference Proceedings (Vol. 24-25-May-2016, pp. 71-77). [2962761] Association for Computing Machinery (ACM). https://doi.org/10.1145/2962735.2962761