受控路网条件下动态交通分配研究
发布时间：2018-07-13 17:41
【摘要】：智能交通系统(ITS)作为一种现在全世界公认有效的交通需求管理方式,对缓解城市交通拥堵问题具有相当显著的作用。基于智能交通系统技术的受控路网正逐渐显露出来。受控路网为交通流运行方式基于网络平台的重建提供了现实基础。本文根据受控路网的特点构建了受控路网条件下的动态交通分配模型,将控制思想融入动态交通分配中,且不同于传统动态交通分配模型最终得到的唯一最优状态,论文实现了在受控路网下对道路流量进行有控制的分配的目标,使得路网可以按照管理者的意愿或路网的实际情况进行更为合理的动态配流,完成了对路网流量的定时定量控制。并通过路段流量控制达到改善路网均衡状态、减少局部交通拥堵、提高城市交通系统运行效率的目的。本文首先结合智能交通技术对受控路网进行了全面的介绍和分析,包括其网络特性和对动态交通分配的影响,确定了受控路网条件下的路径选择及其分配方法。然后对影响路网整体运行效率的关键路段进行分析,根据其在路网中的地位和动态交通分配中的作用给出了其识别步骤。其次,针对受控路网条件下关键路段流量的控制,考虑到流量分配的延时性,即分配后流量在路段上会有一段运行时间,本文提出一种预控制方式即提前控制将要到达关键路段上的流量,使得流量在任意时刻都不会超过限定值。据此利用BP神经网络对受限路段上的流量进行预测,得到流量达到饱和值的时刻然后根据走行时间进行逆推得到应该进行控制的时刻。最后,结合以上分析,以系统最优为目标,基于最优控制理论建立了受控路网条件下的动态交通分配模型。分析了模型的最优解条件并阐述了模型的求解算法。以一较大网络作为路网算例,进行了不同OD需求下以及有无流量限制的分配,最后分配结果表明在对关键路段进行流量控制的情况下关键路段流量能够合理分流到其他路段上,路段的运行效率能够维持在一个比较稳定的水平,有效地避免了局部交通拥堵和潜在的网络格锁。
[Abstract]:Intelligent Transportation system (its), as an effective way of traffic demand management, plays a significant role in alleviating urban traffic congestion. The controlled road network based on Intelligent Transportation system (its) technology is gradually emerging. The controlled road network provides a practical basis for the reconstruction of traffic flow operation mode based on network platform. According to the characteristics of the controlled road network, this paper constructs the dynamic traffic assignment model under the condition of the controlled road network, and integrates the control idea into the dynamic traffic distribution, which is different from the only optimal state finally obtained by the traditional dynamic traffic assignment model. The paper realizes the goal of the controlled distribution of the road flow under the controlled road network, which makes the road network more reasonable dynamic flow allocation according to the wishes of the manager or the actual situation of the road network. The timing and quantitative control of network flow is completed. The road flow control can improve the equilibrium state of the road network, reduce the local traffic congestion and improve the efficiency of the urban traffic system. This paper first introduces and analyzes the controlled road network with intelligent transportation technology, including its network characteristics and its influence on dynamic traffic allocation, and determines the route selection and its allocation method under the condition of controlled road network. Then the key sections which affect the overall operation efficiency of the road network are analyzed and the identification steps are given according to their position in the road network and the role of dynamic traffic assignment. Secondly, considering the delay of flow distribution, that is to say, the flow will have a period of running time in the road section after the flow distribution is considered for the control of the critical road flow under the condition of controlled road network. In this paper, a precontrol method is proposed, that is, the flow will reach the critical section in advance, so that the flow will not exceed the limited value at any time. The BP neural network is used to predict the flow on the restricted road, and the time when the flow reaches saturation value is obtained, and then the time of control is obtained according to the travel time. Finally, based on the optimal control theory, the dynamic traffic assignment model under the condition of controlled road network is established based on the above analysis. The optimal solution condition of the model is analyzed and the algorithm of solving the model is described. Taking a large network as an example, the assignment of different OD demand and no flow restriction is carried out. The results show that the flow of key sections can be reasonably diverted to other sections under the condition of controlling the flow of critical sections. The operation efficiency of road sections can be maintained at a relatively stable level, effectively avoiding local traffic jams and potential network latches.
【学位授予单位】：西南交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U491
本文编号：2120209
[Abstract]:Intelligent Transportation system (its), as an effective way of traffic demand management, plays a significant role in alleviating urban traffic congestion. The controlled road network based on Intelligent Transportation system (its) technology is gradually emerging. The controlled road network provides a practical basis for the reconstruction of traffic flow operation mode based on network platform. According to the characteristics of the controlled road network, this paper constructs the dynamic traffic assignment model under the condition of the controlled road network, and integrates the control idea into the dynamic traffic distribution, which is different from the only optimal state finally obtained by the traditional dynamic traffic assignment model. The paper realizes the goal of the controlled distribution of the road flow under the controlled road network, which makes the road network more reasonable dynamic flow allocation according to the wishes of the manager or the actual situation of the road network. The timing and quantitative control of network flow is completed. The road flow control can improve the equilibrium state of the road network, reduce the local traffic congestion and improve the efficiency of the urban traffic system. This paper first introduces and analyzes the controlled road network with intelligent transportation technology, including its network characteristics and its influence on dynamic traffic allocation, and determines the route selection and its allocation method under the condition of controlled road network. Then the key sections which affect the overall operation efficiency of the road network are analyzed and the identification steps are given according to their position in the road network and the role of dynamic traffic assignment. Secondly, considering the delay of flow distribution, that is to say, the flow will have a period of running time in the road section after the flow distribution is considered for the control of the critical road flow under the condition of controlled road network. In this paper, a precontrol method is proposed, that is, the flow will reach the critical section in advance, so that the flow will not exceed the limited value at any time. The BP neural network is used to predict the flow on the restricted road, and the time when the flow reaches saturation value is obtained, and then the time of control is obtained according to the travel time. Finally, based on the optimal control theory, the dynamic traffic assignment model under the condition of controlled road network is established based on the above analysis. The optimal solution condition of the model is analyzed and the algorithm of solving the model is described. Taking a large network as an example, the assignment of different OD demand and no flow restriction is carried out. The results show that the flow of key sections can be reasonably diverted to other sections under the condition of controlling the flow of critical sections. The operation efficiency of road sections can be maintained at a relatively stable level, effectively avoiding local traffic jams and potential network latches.
【学位授予单位】：西南交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U491
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