Large-Scale Bicycle Flow Experiment: Setup and Implementation

Abstract

Cycling research at the operational behavioral level is limited, mainly because of the lack of empirical data. To overcome this data shortage, we performed a controlled, large-scale cycling experiment in the Netherlands. In this paper we describe the methodology for setting up and implementing such an experiment, from the motivation of its design using a conceptual model describing cyclist behavior to adjustments that were required during the experiment. The main contribution of this paper is, therefore, to be used as a guide in future experimental data collections. Moreover, we present the characteristics of the participants and their bicycles, and provide a qualitative description of phenomena observed during the experiment. Finally, we elaborate on the potential that the collected dataset holds for future research into understanding and modeling operational cycling behavior.

Modelling cyclist queue formation using a two-layer framework for operational cycling behaviour

“…This is the lower operational layer which we name 'operational physical' layer. Given this definition, we build upon the conceptual model of Gavriilidou et al (2019a), shown in Figure 2, which describes cycling behaviour at the operational level, and we fit the two proposed layers within the individual behaviour, as visualised in Figure 3. (Gavriilidou et al 2019a).…”

“…We hypothesise that these choices depend on a set of attributes that need to be taken into account by the models. The attributes displayed in Figure 3 for the decisions to overtake, yield, and stop at a red traffic light are the outcome of a stated preference survey we conducted in the Netherlands, discussed in (Gavriilidou et al 2019a). They still need to be validated with field data, but give good insights into the behavioural attributes.…”

“…The choice in the mental layer determines the choices within the operational physical layer (coloured in blue). The elements that go beyond the scope of this paper are coloured in gray, while the scope of the model application in this paper is framed within the green box (built upon (Gavriilidou et al 2019a)).…”

“…These models can then be used in microsimulations and to update the model attributes in the framework. A challenge in this process has been the shortage of cyclist trajectory data which we will tackle in future work thanks to the dataset collected through our controlled large-scale cycling experiment (Gavriilidou et al 2019a).…”

Voronoi Densities for Bicylists: Adaptation for Finite Object Size and Speed

“…For this, simplified the cost functions and bike sizes are being assumed. Having said so, we do illustrate the ideas presented here with realworld data, collected in an experiment with cyclists [2]. From the data, we use the position of the head, as well as the heading direction and the speed; we use average size of a bike, and simplify its shape to a cross.…”