复杂路网内大规模车辆运动的仿真

发布时间：2018-02-20 16:13

本文关键词： 大规模车辆复杂路网层次语义模型车辆换道行为宏观流模型虚拟现实　出处：《计算机学报》2017年11期 　论文类型：期刊论文

【摘要】：为仿真现实生活中由纵横交错的道路路网、大规模的车辆及其运动组成的交通场景,文中提出一种复杂路网内大规模车辆运动的仿真技术.首先设计一种层次路网语义模型,根据输入的路网车道线矢量数据,通过语义建模,从几何、拓扑等不同层次描述错综复杂的交通路网.其次,由于现有的车辆运动仿真方法中基于个体的微观方法针对大规模车辆运动计算效率较低,而基于流的宏观方法无法仿真复杂的交通现象,提出了一组新的宏观流方程来描述路网内车辆的运动,使得宏观流模型能够与车辆换道行为模型有机地进行结合,从而逼真地描述各种复杂的交通现象.实验结果表明,文中方法在实现复杂路网内车辆运动高细节模拟的前提下,其计算效率与一般宏观流模型保持在同一数量级.通过在实际应用中对真实交通路网进行虚拟现实建模,并在其上进行大规模车辆运动仿真,进一步验证了方法的有效性.
[Abstract]:In order to simulate the traffic scene composed of crisscross road network, large-scale vehicles and their movement in real life, this paper presents a simulation technique of large-scale vehicle movement in complex road networks. Firstly, a hierarchical network semantic model is designed. According to the input vector data of road network lane line, the complicated traffic network is described from geometry, topology and other different levels through semantic modeling. Secondly, In the existing methods of vehicle motion simulation, the microscopic method based on individual is less efficient for large-scale vehicle motion calculation, but the macroscopic method based on flow can not simulate the complex traffic phenomenon. A new set of macroscopic flow equations is proposed to describe the movement of vehicles in the road network. The macroscopic flow model can be combined organically with the vehicle changing behavior model, and the complex traffic phenomena can be described realistically. In this paper, on the premise of realizing the high-detail simulation of vehicle movement in complex road network, the computational efficiency is the same as that of the general macroscopic flow model. The virtual reality model of the real traffic network is built in the practical application. A large scale vehicle motion simulation is carried out on it, which further verifies the effectiveness of the method.
【作者单位】：中国科学院计算技术研究所移动计算与新型终端北京市重点实验室;郑州轻工业学院计算机与通信工程学院;郑州大学信息工程学院;
【基金】：国家“八六三”高技术研究发展计划项目基金(2013AA013902) 公益行业科研专项课题(2013467058) 国家自然科学基金(61472370)、国家自然科学基金青年基金(61402269)资助
【分类号】：TP391.9;U491

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