意图-等待-交叉：面向真实行人过街行为建模
Intend-Wait-Cross: Towards Modeling Realistic Pedestrian Crossing Behavior
摘要：
提出了一种基于Agent的行人微观行为模型Intend-Wait-Cross。该模型由将行人行为表示为一系列决策的规则组成，这些决策取决于行人的个人特征（例如，人口统计数据，步行速度，遵守法律）和环境条件（例如，交通流量，道路结构）。该模型的主要重点是生成现实的交叉决策模型，其中包括一个改进的制定时间碰撞（TTC）计算占上下文，车辆动力学和感知噪声。我们的模型生成了一个不同的人口代理在一个高度可配置的环境中行事。所有的模型组件，包括行人的个人特征，他们所做的决定的类型，和环境因素，是由行人交通行为的研究。模型参数校准使用的自然驾驶数据和估计从文献中最大限度地模拟行为的现实主义的组合。大量的实验验证了模型的各个方面，如行人过街模式，行人的个人特征。
英文摘要：
In this paper, we present a microscopic agent-based pedestrian behavior model Intend-Wait-Cross. The model is comprised of rules representing behaviors of pedestrians as a series of decisions that depend on their individual characteristics (e.g. demographics, walking speed, law obedience) and environmental conditions (e.g. traffic flow, road structure). The model's main focus is on generating realistic crossing decision-model, which incorporates an improved formulation of time-to-collision (TTC) computation accounting for context, vehicle dynamics, and perceptual noise. Our model generates a diverse population of agents acting in a highly configurable environment. All model components, including individual characteristics of pedestrians, types of decisions they make, and environmental factors, are motivated by studies on pedestrian traffic behavior. Model parameters are calibrated using a combination of naturalistic driving data and estimates from the literature to maximize the realism of the simulated behaviors. A number of experiments validate various aspects of the model, such as pedestrian crossing patterns, and individual characteristics of pedestrians.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
