CycleSafe: Safe Route Planning for Urban Cyclists

  • Mehdi Shah
  • Tianqi Liu
  • Sahil Chauhan
  • Lianyong Qi
  • Xuyun ZhangEmail author
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 322)


Cyclist numbers in major cities are constantly increasing whilst traffic conditions continue to worsen. This poses a major issue for cyclists who attempt to share congested roads with motor vehicles. This paper shows that there is not enough work being done to improve the safety of cyclists on the road, and proposes a solution to this problem in the form of a route planning application. Current cyclist route planning applications do not take safety factors like traffic, rain or visibility into account when providing cycle routes. We use Auckland city as a case study to explore our solution. The traffic and weather data in Auckland are acquired by using Google, Bing and Wunderground APIs. An evaluation of our solution shows that our system successfully implements a route planning application that routes users away from unsafe traffic conditions, thus improving cyclist safety.


Traffic data fusion and analytics Mobile computing Cloud services 



This work was supported in part by the New Zealand Marsden Fund under Grant No. 17-UOA-248, and the UoA FRDF fund under Grant No. 3714668.


  1. 1.
  2. 2.
    Jain, V., Sharma, A., Subramanian, L.: Road traffic congestion in the developing world. In: Proceedings of the 2nd ACM Symposium on Computing for Development, p. 11. ACM (2012)Google Scholar
  3. 3.
    Machay, J.: How does google detect traffic congestion?.
  4. 4.
    Auckland Transport: The auckland cycling account.
  5. 5.
    Auckland Transport: Traffic counts 2012 to 2018.
  6. 6.
    Ministry of Transport: Ministry of transport - cyclist crash facts 2017.
  7. 7.
    Weinstock, Z.: Flattest route.
  8. 8.
    OpenStreetMap Wiki: Open cycle map.
  9. 9.
    Xu, L., Yue, Y., Li, Q.: Identifying urban traffic congestion pattern from historical floating car data. Procedia Soc. Behav. Sci. 96, 2084–2095 (2013)CrossRefGoogle Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2020

Authors and Affiliations

  • Mehdi Shah
    • 1
  • Tianqi Liu
    • 2
  • Sahil Chauhan
    • 1
  • Lianyong Qi
    • 3
  • Xuyun Zhang
    • 1
    Email author
  1. 1.Department of Electrical, Computer and Software EngineeringUniversity of AucklandAucklandNew Zealand
  2. 2.Northeastern UniversityBostonUSA
  3. 3.Qufu Normal UniversityJiningChina

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