Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/3009912.3009913acmconferencesArticle/Chapter ViewAbstractPublication PagesmiddlewareConference Proceedingsconference-collections
research-article

Increasing Bicycle Usage in Smart Cities

Published: 12 December 2016 Publication History

Abstract

The emergence and market uptake of technologies for mobile and ubiquitous computing is opening a window of opportunities for innovative applications that promote cycling and walking in new forms. These technologies allow affordable and accessible ways of tracking the walking and cycling of individuals which, when combined with new community-centric applications, promise to unleash the behavior-change potential to unprecedented levels.
A particular synergy is between local businesses, who are interested in segmenting their customer base to attract new clients who arrive by bicycle or on foot; and potential customers, interested in obtaining discounts. Likewise, cities and governments are interested in attributing benefits to people choosing to cycle or walk. However, achieving so requires applications that are able to trace individual mobility choices, at the same time respecting both technical and social requirements.
This paper sheds some new light on the delicate balance between the the social and technical requirements that determine the actual outcome of behavior change towards more sustainable mobility in smart cities. We focus on a particular application, called Cycle-to-Shop, which is under development in the context of the TRACE H2020 project.

References

[1]
S. Bamberg, S. Fujii, M. Friman, and T. Garling. Behaviour theory and soft transport policy measures. Transport Policy, 18(1):228--235, 2011.
[2]
. C. J. Buningh S., Martijnse-Hartikka R. Mobi - modal shift through gamification. Transport Research Arena, pages 1--8, 2014.
[3]
E. Commission. Together towards competitive and resource-efficient urban mobility. https://ec.europa.eu/transport/sites/transport/files/themes/urban/doc/ump/com%282013%29913_en.pdf, 2013.
[4]
D. A. Faludi and B. Waterhout. Introducing evidence-based planning. disP - The Planning Review, 42(165):4--13, 2006.
[5]
M. Flamm and V. Kaufmann. Combining person based gps tracking and prompted recall interviews for a comprehensive investigation of travel behaviour adaptation processes during life course transitions. 11th World Conference on Transport Research, 2007.
[6]
P. B. Goodwin. How easy is it to change travel behaviour? Fifty Years of Transport Policy: Successes, Failures and New Challenges (European Conference of Ministers of Transport), pages 49--73, 2003.
[7]
M. B. Kjærgaard, J. Langdal, T. Godsk, and T. Toftkjær. Entracked: Energy-efficient robust position tracking for mobile devices. In Proceedings of the 7th International Conference on Mobile Systems, Applications, and Services, MobiSys '09, pages 221--234, New York, NY, USA, 2009. ACM.
[8]
A. Repenning and A. Ioannidou. Mobility agents: Guiding and tracking public transportation users. In Proceedings of the Working Conference on Advanced Visual Interfaces, AVI '06, pages 127--134, New York, NY, USA, 2006. ACM.
[9]
Y. Zheng. Trajectory data mining: An overview. ACM Transaction on Intelligent Systems and Technology, September 2015.

Cited By

View all
  • (2021)detectBiklioProceedings of the 36th Annual ACM Symposium on Applied Computing10.1145/3412841.3441965(900-907)Online publication date: 22-Mar-2021

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
SmartCities '16: Proceedings of the 2nd International Workshop on Smart
December 2016
55 pages
ISBN:9781450346672
DOI:10.1145/3009912
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 December 2016

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. Smart cities
  2. behavior change
  3. mobile sensing
  4. tracking
  5. urban planning

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Conference

Middleware '16
Sponsor:
  • ACM
  • USENIX Assoc

Upcoming Conference

MIDDLEWARE '24
25th International Middleware Conference
December 2 - 6, 2024
Hong Kong , Hong Kong

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)12
  • Downloads (Last 6 weeks)1
Reflects downloads up to 06 Oct 2024

Other Metrics

Citations

Cited By

View all
  • (2021)detectBiklioProceedings of the 36th Annual ACM Symposium on Applied Computing10.1145/3412841.3441965(900-907)Online publication date: 22-Mar-2021

View Options

Get Access

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media