The Bike Path Radar: A Dashboard to Provide New Information About Bicycle Infrastructure Quality

Michael Birke (), Florian Dyck (), Mukhran Kamashidze (), Malte Kuhlmann (), Malte Schott (), Richard Schulte (), Alexander Tesch (), Johannes Schering (), Pascal Säfken (), Jorge Marx Gómez (), Kathrin Krienke () and Peter Gwiasda ()
Additional contact information
Michael Birke: Carl von Ossietzky Universität Oldenburg
Florian Dyck: Carl von Ossietzky Universität Oldenburg
Mukhran Kamashidze: Carl von Ossietzky Universität Oldenburg
Malte Kuhlmann: Carl von Ossietzky Universität Oldenburg
Malte Schott: Carl von Ossietzky Universität Oldenburg
Richard Schulte: Carl von Ossietzky Universität Oldenburg
Alexander Tesch: Carl von Ossietzky Universität Oldenburg
Johannes Schering: Carl von Ossietzky Universität Oldenburg
Pascal Säfken: Carl von Ossietzky Universität Oldenburg
Jorge Marx Gómez: Carl von Ossietzky Universität Oldenburg
Kathrin Krienke: Planungsbüro VIA eG
Peter Gwiasda: Planungsbüro VIA eG

A chapter in Advances and New Trends in Environmental Informatics 2023, 2024, pp 95-113 from Springer

Abstract: Abstract Data can support the decision making process in bicycle infrastructure planning. Dashboards may make a positive contribution to learn more about infrastructure shortcomings if these provide relevant Key Performance Indicators (KPIs) and visualizations. Existing dashboards do not reflect the perspective of different types of users, only provide limited data sources and do not provide much information about bike path damages. The Bike Path Radar (Radweg Radar) should fill this research gap by providing relevant information about cycling infrastructure. The frontend enables the end user to create different KPIs regarding cycling accidents, citizen reportings, traffic volume etc. of highest interest. A role concept enables the provision of a suitable degree of information traffic planning experts and citizens. The most important KPIs were identified based on expert interviews. The dashboard is connected to a database in the background that includes heterogeneous cycling and bicycle infrastructure data by an API. In addition to that, the dashboard gives new opportunities for citizen engagement. Users can upload images of bike path damages in a reporting tool. The images will be processed by an object detection algorithm. The detected damages will be displayed on a map by a marker to find locations with surface shortcomings. This contribution will give a short overview about the current state of development of the Bike Path Radar. The outlook provides some additional information about the forthcoming working steps.

Keywords: Dashboard; Cycling planning; KPIs; Times series data; Object detection; Road damages; Machine learning; AI (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:prochp:978-3-031-46902-2_6

Ordering information: This item can be ordered from
http://www.springer.com/9783031469022

DOI: 10.1007/978-3-031-46902-2_6

Access Statistics for this chapter

More chapters in Progress in IS from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().