Enhancing Car-Following Models with Bike Dynamics for Improved Traffic Simulation
Road traffic simulations are crucial for establishing safe and efficient traffic environments. They are used to test various road applications before real-world implementation. SUMO (Simulation of Urban MObility) is a well-known simulator for road networks and intermodal traffic, often used in conjunction with other tools to test various types of applications. Realistic simulations require accurate movement models for different road users, such as cars, bicycles, and buses. While realistic models are already implemented for most vehicle types, bicycles, which are essential for achieving safe and efficient traffic, can only be modeled as slow vehicles or fast pedestrians at present. This paper introduces the Realistic Bicycle Dynamics Model (RBDM), the first dedicated bicycle model for SUMO, addressing this significant gap. Leveraging real-world bicycle data from the SimRa dataset, the RBDM implements realistic speed, acceleration, and deceleration behaviors of bicycles in urban scenarios. The evaluation is conducted using the Monaco SUMO traffic scenario (MoST) and a newly generated Berlin scenario in SUMO. The RBDM significantly outperforms the existing slowvehicle approximation in SUMO, aligning more closely with realworld data across distribution, median, and interquartile range metrics. These results underscore the necessity of a realistic bicycle movement model for accurate simulations, given the significant differences in the movement profiles of bicycles, cars, and pedestrians. Furthermore, the model is tested for its ability to generalize to disparate scenarios and urban topologies, which is dependent on the manner and geographical region in which the SimRa data were gathered. In addition, recommendations are provided for how it could be adapted for use in different city topologies. The enhanced realism of the RBDM is essential for accurately simulating and evaluating applications such as Vehile-to-X communication and urban planning systems that depend on precise bicycle movement representation.
Authors
- Keno Garlichs (ORCID: https://orcid.org/0000-0002-5874-6417)
- Lars Wolf (ORCID: https://orcid.org/0000-0001-9782-7765)
- Nico Ostendorf
Institutions
- Robert Bosch (Germany) (DE)
- Technische Universität Braunschweig (DE)
Publication Details
- Published
- 2025-05-04
- DOI
- https://doi.org/10.1109/most65065.2025.00023
- Citations
- 3
- Primary Topic
- Traffic control and management
- Type
- article
- Field-Weighted Citation Impact
- 3.64