An operational simulation framework for modelling the multi-interaction of two-wheelers on mixed-traffic road segments

Ying, Nie; Li, Yixin; Yuan, Yufei; Sun, Jian

doi:10.1016/j.physa.2022.128441

Cited by 9 publications

(1 citation statement)

References 97 publications

(149 reference statements)

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“…Other researchers improve the cycling characteristics by adding path-planning modules (Rinke et al, 2017) oor anisotropic characteristics to the repulsive force fields of other road users (Yuan et al, 2019;Dias et al, 2018). Lastly, researchers add complex tactical layers to the social force model that explicitly model different behaviors and preferences depending on a cyclist's surroundings (Ni et al, 2023;Liang et al, 2018;Rinke et al, 2017). While all these innovations improve the capabilities of the social force model to simulate bicycling, we have not found work that introduces the physical constraints of riding a two-wheeled bicycle into the framework.…”

Section: Introductionmentioning

confidence: 99%

Essential Bicycle Dynamics for Microscopic Traffic Simulation: An Example Using the Social Force Model

Schmidt,

Dabiri,

Schulte

et al. 2023

The Evolving Scholar - BMD 2023, 5th Edition

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Microscopic simulation is an established tool in traffic engineering and research, where aggregated traffic performance measures are inferred from the simulation of individual agents. Additionally, measures describing the safety and efficiency of road user interactions gain importance for recent developments such as automated vehicles and urban cycling. However, current simulation frameworks model interactions including cyclists only with limited realism. To address this issue, we propose to bring bicycle dynamics to traffic simulation. We demonstrate that a novel reformulation of the social force framework can create input signals for a controlled inverted pendulum bicycle model and thereby enable a fully two-dimensional open space simulation of cyclist interactions. The inverted pendulum model introduces the need to stabilize the bicycle as a constraint to the reactive behavior of simulated cyclists. Furthermore, it enables the simulation of countersteering and weaving for stabilization. Our cyclist social forces have anisotropic force fields with respect to relative interaction position and orientation to describe the varying interaction constellations in open space. With these models, we simulate five single- and multi-cyclist test cases and show that the generated trajectories notably differ from results obtained from a 2D bicycle model without lean angle simulation. Measurements of the maximum lateral path deviation and post-encroachment time show that these differences are relevant for typical applications. Our work demonstrates the potential of introducing physics-based realistic bicycle dynamics to the microscopic simulation of individual road user interactions and the fundamental capability of our reformulated cyclist social forces to do so. Going further, we plan to calibrate and validate our model based on naturalistic cycling data to support the initial results of this work.

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