A forward Markov model for predicting bicycle speed

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.