A heterogeneous Social Force Model for Personal Mobility Vehicles on futuristic sidewalks

Alireza Jafari, Yen Chen Liu

研究成果: Article同行評審

摘要

Electric scooters are becoming popular in public spaces, and autonomous robots will join soon. However, integrating these Personal Mobility Vehicles (PMV) without proper provisions challenges the safety and comfort of all users. While Social Force Model (SFM) commonly replicates pedestrians’ movements, directly applying it to PMVs is challenging and inaccurate. We propose a heterogeneous SFM considering the dynamic personal spaces of various agents on futuristic sidewalks, addressing the impracticalities of SFM. Additionally, subjective safety estimation relaxes the constant desired-velocity assumption, and the influence weight reduces the complexity by omitting pairwise calibration. Experiments calibrate the model for e-scooters, validating it in realistic scenarios with multiple e-scooters passing through pedestrians. The proposed model has higher accuracy than previous models regarding behavioral naturalness metrics. In addition, the models’ performance in replicating experimental observations is analyzed. This research contributes to safer and more efficient transportation with PMVs, particularly e-scooters, and provides a novel approach to modeling multi-type agents on heterogeneous sidewalks.

原文English
文章編號102879
期刊Simulation Modelling Practice and Theory
131
DOIs
出版狀態Published - 2024 2月

All Science Journal Classification (ASJC) codes

  • 軟體
  • 建模與模擬
  • 硬體和架構

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