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A forward Markov model for predicting bicycle speed

  • Petter ArnesenEmail author
  • Olav Kåre Malmin
  • Erlend Dahl
Article
  • 18 Downloads

Abstract

Speed prediction of different transport modes is important in applications such as route planning, transport modelling and energy calculations. In this paper we model bicycle speed as a function of slope and horizontal curvature. We developed two models, one with dependence between subsequent observations (a forward Markov model) and one without such a dependence (a generalised linear model). We show through prediction on out-of-sample data that the model including dependence between observations outperforms the model without. To estimate and evaluate our models we use a data set collected using a smart phone application. The data collected includes different sources of error, and therefore we introduce various filtering methods to make the data more appropriate for statistical analysis and model estimation.

Keywords

Bicycle speed modelling GLM GPS data Markov model 

Notes

Author contributions

The authors confirm contribution to the paper as follows: literature review: Petter Arnesen and Olav Kåre Malmin; app development and data collection: Erlend Dahl; filtering and data preperation: Erlend Dahl and Petter Arnesen; model development and estimation: Petter Arnesen; analysis and interpretation of results: Petter Arnesen, Olav Kåre Malmin and Erlend Dahl; draft manuscript preparation: Petter Arnesen, Erlend Dahl and Olav Kåre Malmin. All authors reviewed the results and approved the final version of the manuscript.

Compliance with ethical standards

Conflicts of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Mobility and EconomicsSINTEFTrondheimNorway

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