AMC-SS Stochastic Modeling and Simulation for Traffic Flow

提案ID：0606807PI：Alexandros Sopasakis机构：马萨诸塞大学AMHERST题目：AMC-SS交通流随机建模和仿真摘要复杂动力系统，如交通流，具有不同时间尺度上共存阶段的特征。此外，随机扰动虽然很小，但可能会对整个系统行为产生重大影响。虽然许多物理现象是由大量变量的相干但先验未知的运动引起的，但目前的大多数模型都要求求解粒子的单个运动。这种方法导致难以获得可靠或及时的预测。我们提出了一种交通流模型的层次结构，它可以提供一种更好的预测交通流观测值的方法。具体地说，我们采用了一种新颖的、能量驱动的随机噪声模型来描述车辆交通流的不同复杂阶段。该模型将能够再现较高浓度区交通流的混沌和难以分解。对车辆交通流的行为进行建模是一个具有挑战性的、当前和亟待解决的开放问题。所提出的交通流模型可以对包含大量交互车辆的真实交通流进行更准确且可能更快的模拟，从而成为多个跨学科交通相关研究领域的突破。对交通的连贯描述可以带来更好的预测策略，在我们的能源、环境和安全问题上直接和间接地受益。

Proposal ID: 0606807PI: Alexandros SopasakisInstitution: University of Massachusetts AmherstTitle: AMC-SS Stochastic Modeling and Simulation for Traffic FlowAbstractComplex dynamical systems, such as traffic flow, are characterized by coexisting phases acting at different temporal scales. Further, random perturbations, although small, can have dramatic effects on the overall system behavior. While many physical phenomena result from the coherent but a priori unknown motion of a large number of variables most of the current models require that individual motion of the particles is resolved. Such approaches lead to difficulties in obtaining predictions that are dependable or timely. We propose a hierarchy of traffic flow models that can provide a better way of predicting traffic flow observables. Specifically we employ a novel, energy driven, stochastic noise model in order to describe the different complex phases of vehicular traffic flow. The model will be capable of reproducing the flow of traffic for the chaotic and difficult to resolve higher concentration regime.Modeling the behavior of vehicular traffic flow is a challenging, current and open problem demanding an immediate solution. The proposed traffic flow model can be a breakthrough for several cross-disciplinary traffic related research areas by enabling much more accurate and potentially faster simulation of realistic traffic streams containing a large number of interacting vehicles. The coherent description of traffic can lead to better prediction strategies with direct and indirect benefits in our energy resources, environmental and safety issues.