提出通用物理模型GM3，精准模拟微型交通工具的轮胎滑移与倾角动态。
GM3: A General Physical Model for Micro-Mobility Vehicles
- 基于轮胎刷子模型，支持任意轮组布局的统一动力学建模。
- 在斯坦福无人机数据集上验证，对骑行者、滑板者和手推车类均有效。
- 提供可交互仿真框架，适合自动驾驶与城市交通模拟研究者使用。
微移动车辆（MMV）动力学建模对自动驾驶系统训练和城市交通仿真日益重要。然而，主流工具依赖于运动学自行车模型（KBM）或特定模式的物理模型，忽略了轮胎滑移、载荷转移和骑手/车辆倾斜等关键因素。据我们所知，尚无统一的物理基础模型能覆盖常见MMV及其轮组布局的全范围动态。本文提出“通用微移动模型”（GM3），基于轮胎刷子表示法，支持单轨/双轨及多轮平台的任意轮组配置。设计了一个模型无关的交互式仿真框架，将车辆/布局定义与动力学解耦，包含固定步长的RK4积分、人机协同与脚本控制、实时轨迹追踪与日志记录，用于分析对比GM3与KBM及其他模型。还在斯坦福无人机数据集的deathCircle（环形路口）场景中，对骑行者、滑板者和手推车类别进行了实证验证。
原文摘要 · Abstract (English)
Modeling the dynamics of micro-mobility vehicles (MMV) is becoming increasingly important for training autonomous vehicle systems and building urban traffic simulations. However, mainstream tools rely on variants of the Kinematic Bicycle Model (KBM) or mode-specific physics that miss tire slip, load transfer, and rider/vehicle lean. To our knowledge, no unified, physics-based model captures these dynamics across the full range of common MMVs and wheel layouts. We propose the "Generalized Micro-mobility Model" (GM3), a tire-level formulation based on the tire brush representation that supports arbitrary wheel configurations, including single/double track and multi-wheel platforms. We introduce an interactive model-agnostic simulation framework that decouples vehicle/layout specification from dynamics to compare the GM3 with the KBM and other models, consisting of fixed step RK4 integration, human-in-the-loop and scripted control, real-time trajectory traces and logging for analysis. We also empirically validate the GM3 on the Stanford Drone Dataset's deathCircle (roundabout) scene for biker, skater, and cart classes.
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