| Id | 2828 | |
| Author | Gössling S.; McRae S. | |
| Title | Subjectively safe cycling infrastructure: New insights for urban designs | |
| Reference | Gössling S.; McRae S. Subjectively safe cycling infrastructure: New insights for urban designs,Journal of Transport Geography 101 |
|
| Keywords | Germany; cycle transport; infrastructural development; traffic congestion; transportation development; transportation planning; transportation safety; urban design; urban development; urban transport |
|
| Link to article | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128162794&doi=10.1016%2fj.jtrangeo.2022.103340&partnerID=40&md5=6971cd495eb80ecda39e131dd4d9ff13 |
|
| Abstract | Transportation infrastructure that accommodates the needs of active mode users is an essential element of sustainable and just urban mobility transitions. Safety is a major factor influencing bicyclist behavior, and understanding how safety is perceived by traffic participants can support urban designs that will attract greater shares of active travelers. This paper evaluates the stated preferences of motorists, cyclists, and pedestrians for safe transport infrastructures. It relies on data collected by the non-governmental organization FixMyBerlin in cooperation with a German newspaper, Berliner Tagesspiegel. 21,401 participants assessed a total of 1900 different traffic situations, generating a sample of 468,379 opinions on street design elements including major streets, side streets and pavements. Results point at the importance of wide bicycle tracks and the separation of cyclists from motorized and pedestrian traffic. The removal of parking next to bicycle lanes also has great importance for improving perceptions of safety. The data offers detailed insight into key elements of urban safety design characteristics, which are remarkably similar irrespective of mode type preference. The study concludes that subjective safety is a novel starting point for urban transport designs. © 2022 |
|
| Metodology | Technique |
Find research methods used
Show Candidate Transition Variables for article (AI method)
Find category for article (AI method)
Find social impact for article (AI method)
Show WordCloud from article (AI method)
Find semantically similar articles (Semantic search)
