Simulating Spatio-Temporal Patterns of Bicycle Flows with an Agent-Based Model

Abstract

Transport planning strategies regard cycling promotion as a suitable means for tackling problems connected with motorized traffic such as limited space, congestion, and pollution. However, the evidence base for optimizing cycling promotion is weak in most cases, and information on bicycle patterns at a sufficient resolution is largely lacking. In this paper, we propose agent-based modeling to simulate bicycle traffic flows at a regional scale level for an entire day. The feasibility of the model is demonstrated in a use case in the Salzburg region, Austria. The simulation results in distinct spatio-temporal bicycle traffic patterns at high spatial (road segments) and temporal (minute) resolution. Scenario analysis positively assesses the model’s level of complexity, where the demographically parametrized behavior of cyclists outperforms stochastic null models. Validation with reference data from three sources shows a high correlation between simulated and observed bicycle traffic, where the predictive power is primarily related to the quality of the input and validation data. In conclusion, the implemented agent-based model successfully simulates bicycle patterns of 186,000 inhabitants within a reasonable time. This spatially explicit approach of modeling individual mobility behavior opens new opportunities for evidence-based planning and decision making in the wide field of cycling promotion

Bicycle Traffic Model for Sustainable Urban Mobility Planning

“…The presented methodology of development of the model allows the analysis of the influence of the development of the public transport system, or individual motorised transport, on the transport behaviour of inhabitants in terms of a change in the probability of choosing bicycles for travel; it also takes into account the characteristics of the infrastructure of the transport system, which can determine the choice of cycling as an alternative to other modes of transport. An alternative approach to comprehensive modelling of travel demand and transport networks could be agent-based modelling [22,162]; however, the range of data available for modelling led the authors of this paper to use a four-stage approach. The availability of data can determine the choice of the modelling method.…”

“…In [22,162], the results of agent-based modelling are presented to simulate cycling in the city of Salzburg. The model mainly aimed to test the role of the surrounding Salzburg area for inner-city cycle traffic.…”

“…Thus far, cities use transport models to a very limited extent, and very rarely-especially when modelling active travel and its influence on motor vehicle trips and trips made via public transport. One of the reasons for this is the scarcity of reliable, integrated, and comprehensive tools to model the transport system while taking into account cycling traffic at the macroscopic level [19][20][21][22]. The tools used for transport modelling most often include the functioning of motor vehicle road transport and public transport, excluding cyclists or treating them as a factor disrupting traffic conditions.…”

“…From the opinions of the respondents presented in Section 4.2, it also appears that the pavement indicated by cyclists as the most attractive is a smooth, even surface (asphalt and, to a lesser extent, smooth concrete blocks). Many previous studies indicate that the type of surface is a factor that determines the choice of route by a cyclist [22,129,130,163,215,216]; however, it is difficult to find direct research results on cyclist preferences with regard to this issue [217,218]. One of the few works that unambiguously states that the quality of the surface is an important decision factor for cyclists when choosing a cycling route is the study by Landis et al [219].…”

“…There are very few reliable, integrated, and comprehensive tools for modelling the transport system that take into account bicycle traffic at the macroscopic level [19][20][21][22]. Most existing urban transport modelling tools inaccurately or incompletely take into account the influence of cycling on the functioning of the transport network.…”