身体与心智：通过耦合力学过程与决策过程解码行人动力学及智能手机分心的影响
Body and mind: Decoding the dynamics of pedestrians and the effect of smartphone distraction by coupling mechanical and decisional processes
AI总结：
本研究提出耦合决策层与力学层的连续智能体模型ANDA，仅含少量可通过实验拟合的参数，可复现多类行人场景及智能手机分心导致的流动混乱性增强现象，为行人动力学与活性物质研究提供透明框架。
摘要：
行人具备预判能力，这一特性让他们在避开碰撞、在拥挤空间中通行时更具优势。然而，智能手机带来的数字分心会削弱这些能力，这一问题已成为日益严峻的安全隐患。为捕捉这些特征，我们提出了一种基于连续智能体的模型（命名为ANDA），该模型核心在于清晰划分两个层面：一是决策过程，即选择期望速度作为感知成本的最优解；二是处理接触与碰撞的力学层。整体而言，该模型的参数不足12个，其中许多参数通过独立实验数据拟合得到。我们通过数值模拟验证了ANDA的通用性，它能成功复现极广泛场景下的实证观测结果。这些场景涵盖单个、两个及更多智能体的避碰行为，单向与双向环境中的集体流动特性，以及瓶颈处的疏散动力学——在此场景中可直接获取接触力。值得注意的是，该模型通过降低决策更新频率，复现了数字分心效应，能够重现实验中观测到的“边走路边用手机”行人流动混乱性增强的现象。该模型的概念透明性便于明确其当前局限性的根源，也有助于厘清行人群体在活性物质系统中的独特定位。
英文摘要：
Pedestrians are able to anticipate, which gives them an edge in avoiding collisions and navigating in cluttered spaces. However, these capabilities are impaired by digital distraction through smartphones, a growing safety concern. To capture these features, we put forward a continuous agent-based model (dubbed ANDA) hinging on a transparent delineation of a decision-making process, wherein a desired velocity is selected as the optimum of a perceived cost, and a mechanical layer that handles contacts and collisions. Altogether, the model includes less than a dozen parameters, many of which are fit using independent experimental data. The versatility of ANDA is demonstrated by numerical simulations that successfully replicate empirical observations in a very wide range of scenarios. These scenarios vary from collision avoidance involving one, two, or more agents, to collective flow properties in unidirectional and bidirectional settings, and to the dynamics of evacuation through a bottleneck, where contact forces are directly accessible. Remarkably, the model is able to replicate the enhanced chaoticity of the flow observed experimentally in 'smartphone-walking' pedestrians, by reducing the frequency of decisional updates, replicating the digital distraction effect. The conceptual transparency of the model makes it easy to pinpoint the origin of its current limitations and to clarify the singular position of pedestrian crowds amid active-matter systems.
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。
