Modeling of Shared Space with Multi-modal Traffic using a Multi-layer Social Force Approach

Pascucci, Federica; Rinke, Nils; Schiermeyer, Chris; Friedrich, Bernhard; Berkhahn, Volker · 2015 · OpenAlex-citations

DOI: 10.1016/j.trpro.2015.09.081

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Summary

This paper addresses the lack of appropriate micro-simulation tools for evaluating shared space designs, where motorized and non-motorized traffic coexist without strict separation. The authors aim to develop a simulation framework capable of modeling the complex interactions and conflict resolutions inherent in these environments to assess performance indicators such as efficiency, safety, and environmental impact. The research is motivated by the need to move beyond traditional separation-based traffic models, which fail to capture the negotiated priority and high interaction levels characteristic of shared spaces. The study employs a multi-layer Social Force Model (SFM) enhanced to handle mixed traffic modes. The methodology is grounded in observational data collected from a pedestrian-friendly intersection in Braunschweig, Germany, involving pedestrians, cyclists, and vehicles. The simulation framework is structured into three layers: a Free-Flow (FF) layer, a Long-Range Collision Avoidance (LRCA) layer, and a Short-Range Collision Avoidance (SRCA) layer. The FF layer generates trajectories using visibility graphs and clothoid estimations to ensure smooth, obstacle-avoiding paths. The LRCA layer introduces a new force term to the classical SFM equation, allowing users to predict and avoid conflicts based on extrapolated trajectories of other users within their field of vision. Conflict detection relies on a distance function comparing the ego-user’s free-flow trajectory with the predicted spatiotemporal trajectory of competitive users. The results demonstrate the model’s ability to replicate observed behaviors in two specific scenarios: pedestrian-pedestrian conflicts and car-pedestrian conflicts. In pedestrian-pedestrian interactions, the simulation correctly reproduced the behavior of one pedestrian deviating from their path to allow another to pass, though the simulated deviation was slightly more pronounced than observed. In car-pedestrian scenarios, the model accurately simulated the deceleration of vehicles and the timing of pedestrian crossings, reflecting the prudent behavior observed in reality. The simulation successfully captured the dynamic recalculation of trajectories and the acceleration/deceleration processes required to resolve conflicts. The significance of this work lies in providing a foundational micro-simulation tool that specifically accounts for the unique dynamics of shared spaces, such as negotiated priority and long-range collision avoidance. The authors conclude that while the current model effectively represents simple conflict situations, future research must focus on calibrating parameters using genetic algorithms, extending the model to include bicycles and public transport, and handling multiple simultaneous conflicts. Ultimately, this framework aims to enable the calculation of performance indicators like Level of Service and safety metrics, facilitating the design and evaluation of shared space infrastructure.

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• mental model of traffic