A flexible traffic stream model and its three representations of traffic flow

A flexible traffic stream model and its three representations of traffic flow
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灵活的交通流模型及其三种交通流表示

DOI:
10.1016/j.trc.2016.12.006
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发表时间:
2017-02
期刊:
Transportation Research Part C
影响因子:
--
通讯作者:
He Tian
He Tian
中科院分区:
其他
文献类型:
--
作者:
Zheng Liang;He Zhengbing;He Tian

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为了将微观驾驶行为与宏观对应(即,的基本图),本研究提出了一种灵活的交通流模型,这是来自一个新的车辆跟驰模型在稳态条件下。它的四个与驾驶行为相关的参数,即,反应时间、平静参数、速度和空间相关的敏感性在形成基本图中具有明显的效果。详细分析了该模型的边界条件和齐次情况,并与其它两种模型(即,纵向控制模型和智能驾驶员模型)。特别是拉格朗日坐标系下的交通流模型公式和性质为重新审视交通流提供了一个新的视角,并与欧拉坐标系下的交通流模型进行了补充。一个校准方法,采用猴子算法与动态适应校准这个模型,从广泛的位置的真实数据的基础上。结果表明,该模型具有良好的灵活性,以适应这些交通数据,并表现出优于其他九个模型。最后,设计了一个具体的交通应用实例,其中三个关键参数对车辆轨迹和冲击波的影响有三种表示(即,分别定义在x-t,n-tan和x-n坐标下),冲击波的宏观解和微观解彼此吻合得很好。综上所述,该交通流模型具有灵活性和高效性的优点,在服务水平分析和交通规划方面具有良好的应用潜力。
To connect microscopic driving behaviors with the macro-correspondence (i.e., the fundamental diagram), this study proposes a flexible traffic stream model, which is derived from a novel car-following model under steady-state conditions. Its four driving behavior-related parameters, i.e., reaction time, calmness parameter, speed- and spacing-related sensitivities, have an apparent effect in shaping the fundamental diagram. Its boundary conditions and homogenous case are also analyzed in detail and compared with other two models (i.e., Longitudinal Control Model and Intelligent Driver Model). Especially, these model formulations and properties under Lagrangian coordinates provide a new perspective to revisit the traffic flow and complement with those under Eulerian coordinate. One calibration methodology that incorporates the monkey algorithm with dynamic adaptation is employed to calibrate this model, based on real-field data from a wide range of locations. Results show that this model exhibits the well flexibility to fit these traffic data and performs better than other nine models. Finally, a concrete example of transportation application is designed, in which the impact of three critical parameters on vehicle trajectories and shock waves with three representations (i.e., respectively defined inx-t,n-tandx-ncoordinates) is tested, and macro- and micro-solutions on shock waves well agree with each other. In summary, this traffic stream model with the advantages of flexibility and efficiency has the good potential in level of service analysis and transportation planning.
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