On Intercultural Transferability and Calibration of Heterogeneous Shared Space Motion Models

TL;DR

This paper enhances a social force model for shared space traffic simulation with automated calibration and investigates its transferability across different cultural environments, showing that incorporating local social norms improves accuracy.

Contribution

It introduces a generic automated calibration method for the Game-Theoretic Social Force Model and evaluates its transferability between German and Chinese shared space environments.

Findings

Automated calibration improves model accuracy.

Adding social norms enhances transferability.

Model faces challenges in cross-cultural replication.

Abstract

Modelling and simulation of mixed-traffic zones is an important tool for transportation planners to assess safety, efficiency, and human-friendliness of future urban areas. This paper addresses problems of calibration and transferability of existing shared space models when applied to scenarios that differ in terms of cultural aspects, traffic conditions, and spatial layout. In particular, the first contribution of this work is an enhancement of the Game-Theoretic Social Force Model (GSFM) by a generic methodology for largely automated model calibration; we illustrate the use of the calibration method for a shared space environment in Germany. The second contribution is an investigation into transferability of shared space models. We define criteria for model transferability and present a case study, in which we analyse and evaluate transferability of the model we constructed based on the ``German dataset'' to a different shared space environment from China. Our results indicate that although -- as to be expected -- the model faces difficulties to replicate the movement behaviours of road users from a new environment, by adding social norms (derived through analysis) of that environment to our model, satisfactory improvement of model accuracy can be obtained with limited effort.