The broad Urban Traffic Management System is composed of Traffic Control and Vehicle Route Guidance System.
广义城市交通管理系统由交通控制和车辆诱导系统组成。
Multisource traffic information processing is the key to cooperation between urban traffic control and dynamic route guidance.
多源交通信息处理是交通控制与交通诱导实现协同的基础和关键。
The identification of chaos in the real traffic flow can provide theoretical guidance for forecasting and control of real traffic flow.
通过对实测交通流进行混沌判别，可以为实际交通流的预测和控制提供理论指导。
The identification of chaos in traffic flow can provide theoretical guidance for forecasting and control of real traffic flow.
对交通流进行混沌判别，可以为实际交通流的预测和控制提供理论指导。
Urban Traffic Signal Control System and Urban Traffic Flow Guidance System were the important part of ITS.
城市交通信号控制系统和城市交通流诱导系统是智能交通系统的重要组成部分。
The accurate real-time forecast of traffic volume is the premise and basement of the dynamic traffic control and guidance.
实时、准确的交通量预测是实现动态交通流控制及诱导的前提和基础。
Dynamic traffic assignment is the key to this problem, and it plays an important role in the traffic control and guidance.
动态交通分配为解决此问题提供了思路，其在交通控制与诱导中发挥着重要作用。
Based on the double object-function constraints of parking guidance and traffic flow control, optimization model of parking guidance coordinated with traffic flow control was constructed.
在停车诱导和交通流控制双重目标函数约束下，建立了停车诱导与交通流控制协同优化模型。
Traffic signal control and route guidance are the two main ways of online administration for urban traffic.
交通信号控制系统与车辆路线诱导系统是城市交通流在线管理的两种主要方式。
UTCS (urban traffic Control System) and UTGS (urban traffic Guidance System) are the core parts of ITS (Intelligence Transportation System) in the Real-time management of urban traffic.
城市交通控制系统(utcs)和城市交通诱导系统(utgs)是智能交通系统(its)对道路交通进行在线实时管理的核心部分。
The thesis introduced research status of Urban Traffic Control and Route Guidance System, analyzed necessity of Urban Traffic Control and Route Guidance System collaboration research.
本文简要地介绍了城市交通控制与诱导系统的研究现状，分析了控制与诱导一体化研究的必要性。
The intelligent collaboration between urban traffic control and dynamic route guidance is studied after the relationship of them is analyzed.
交通信号控制和动态交通诱导是城市交通管理的两个主要手段，两者智能协作能提高城市交通管理效率。
Traffic control and traffic guidance can learn from each other, give full play to their strengths, also can play its collaboration features. It has great role to solve traffic jam problems.
交通控制与交通诱导的结合能取长补短，充分发挥各自的优势，又能发挥其合作的特点，对解决交通拥挤问题有很大的作用。
Traffic signal control and dynamic route guidance are two main means of urban traffic management. Intelligent collaboration between them can improve the traffic management efficiency.
交通信号控制和动态交通诱导是城市交通管理的两个主要手段，两者智能协作能提高城市交通管理效率。
The interaction of traffic control and traffic flow guidance was analyzed.
分析了交通控制和交通诱导的相互影响与相互作用。
To improve the traffic throughout and reduce the total vehicle travel time, the control and guidance method for expressway communication management are put forward in this research.
本文围绕提高高速公路的交通流量，解决交通拥堵的问题，提出了高速公路交通控制与诱导的方法。
A multiagent simulation system was established for the synergy study of the traffic signal control and the route guidance.
设计了交通信号控制与路径诱导协同研究的多智能体模拟系统。
Short—term traffic flow prediction is the basis of dynamic traffic control and guidance.
短时交通流预测是动态交通控制和诱导的前提。
The article sets up system Equilibrium and User Equilibrium coordination module regarding on the allocation and guidance problems existing in the traffic control system and traffic guidance system.
针对控制与诱导系统一体化中分配、控制与诱导的问题，本文建立了用户最优-系统最优协调模型。
The simulation results are encouraging and the synergy of the traffic signal control and the route guidance leads to saving in the total travel time up to 41.4%.
模拟的结果是令人鼓舞的，交通信号控制和路线指引的协同效应导致的总旅行时间节省高达41.4%。
Urban Intelligent Transportation system consists of several subsystems, and urban traffic control system and traffic guidance system are the key ones.
城市智能交通系统包括多个子系统，其中交通控制系统和交通诱导系统都是关键的子系统。
The prediction results will have direct effect on traffic control and traffic guidance. A traffic flow prediction model using support vector machines(SVMs) based method is proposed.
提出一种基于支持向量机的交通流量实时预测模型，通过采用序贯最小优化算法，能够实现对交通流量的有效预测。
The prediction results will have direct effect on traffic control and traffic guidance. A traffic flow prediction model using support vector machines(SVMs) based method is proposed.
提出一种基于支持向量机的交通流量实时预测模型，通过采用序贯最小优化算法，能够实现对交通流量的有效预测。
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