面向城市交通通道仿真的交通流建模与组织优化

项目名称： 面向城市交通通道仿真的交通流建模与组织优化

项目编号： No.51508505

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 建筑科学

项目作者： 陈喜群

作者单位： 浙江大学

项目金额： 20万元

中文摘要： 本项目面向城市交通通道综合管控协调性不足的问题，研究随机交通流建模仿真和综合管控策略组织优化方法，通过基于仿真的优化方法完善交通通道的综合控制策略、事件管理策略、需求管理策略、以及多种不同管控策略的整合，弥补当前单一策略优化与评估模式的不足，最终提升城市交通通道整体通行效率。本项目从四个方面开展研究工作：微观和宏观相结合的随机交通流理论、基于全路网动态仿真的多目标建模与元模型优化算法、基于多源异构数据的常态和非常态宏观基本图特征、基于开源动态交通分配程序包的可视化仿真平台。重点构建面向大规模网络应用的随机交通流模型，克服现有研究在路段基本图关键参数随机性计算中的局限性；开发能够处理随机仿真的元模型优化算法，兼顾估计准确性和计算高效性；深入挖掘和融合多源异构交通大数据，解决宏观基本图的构建和特征演化问题。本项目提出的元模型仿真优化方法具有可扩展性，可应用到其他综合交通管控组织优化问题。

中文关键词： 城市交通通道；随机交通流；基于仿真的优化；多源异构数据

英文摘要： The project aims to solve the coordination problem of integrated management and control for urban transportation corridors, studies stochastic traffic flow models and simulations, and the simultaneous optimization method of integrated corridor management. It compromises the previous optimization and evaluation of individual strategies via simulation-based optimization (SBO) for comprehensive control strategies, traffic incident management, demand management, as well as a variety of combinations, and ultimately improves the overall efficiency urban transportation corridors. The project carries out research work in four areas: development of integrated micro/macro-scopic stochastic traffic flow theory, multi-objective formulation and meta-modeling based on dynamic simulation of the whole road network, macroscopic fundamental diagram (MFD) under both normal and abnormal situations characterized by multi-source heterogeneous data, visual simulation platform based on open-source dynamic traffic assignment package. This project focuses on developing stochastic traffic flow models for large-scale network applications, overcoming the limitation of deterministic fundamental diagram parameters in the existing research. Surrogate-based optimization algorithms are developed to handle stochastic simulation responses and take into account the accuracy and computational efficiency. The MFD construction and evolution features can be analyzed based on multi-source heterogeneous data. The proposed meta-modeling in this project is scalable, and can be applied to other comprehensive traffic control problems.

英文关键词： Urban transportation corridor;stochastic traffic flow;simulation-based optimization (SBO);multi-source heterogeneous data