Modeling an Elastic-Demand Bimodal Transport Network with Park-and-Ride Trips

This paper presents a network equilibrium formulation for modeling commuters＇ travel choices in a bimodal transport system with park-and-ride （P＆R） trips while the total demand is elastic to the congestion level of the network. A super-network approach is adopted in the proposed model. It is assumed that commuters＇ trips are categorized into two types, auto mode only and a combined mode with both auto and transit modes. The former is referred to as the pure mode trip and the latter as the P＆R mode trip. The proposed model simultaneously considers the commuter＇s choice of the pure mode versus the P＆R mode, the choice of parking location for the pure mode, the choice of transfer point for the P＆R mode, as well as the route choice for each mode. The demand elasticity of transport system, the capacity constraints of transport facilities, and the congestion interaction throughout the super-network are also explicitly incorporated into the proposed model. The results of the numerical experiment show the following key findings： （i） traditional parking/P＆R models may overestimate or underestimate travel demand distribution over network; （ii） parking/P＆R, transit scheduling, and carpooling schemes bring significant impacts on commuters＇ travel behavior and network performance; and （iii） different transport policies may be to some extent mutually substituted .     

基于模糊神经网络的信号交叉口交通量预测

预测精度高,实时性强的交叉口交通量预测算法可以极大地提高城市交通控制的效率。文中提出了基于模糊神经网络的信号交叉口交通量预测方法。该方法以模糊神经网络为核心,应用在线滚动学习模型实现交叉口交通量预测,并应用了交通量微观仿真系统对模型进行检验,仿真结果表明该模型比传统方法精度高,收敛速度快。本模型在城市交通控制系统研究中有巨大的应用潜力。     

混合交通体系中弹性需求的网络平衡

讨论的城市交通体系模型由快速道路网和广布的街区道路连续区域组成 .针对这样特征的城市交通体系 ,建立了满足弹性需求及用户平衡条件的数学规划模型 ,并提出了以有限元算法为基础的迭代求解方法 .最后 ,给出了城市交通体系模型的算例 ,证明了模型和算法的有效性     

区域交通枢纽敏感性有限元分析模型

在二维连续空间多类型平衡配流模型的基础上,采用三角形单元有限元离散方法,建立了区域交通枢纽设施敏感性分析的一般模型,并给出了常用指标的敏感性计算公式.利用本模型,对珠江三角洲区域内的各大机场航空客流分布相对于通关费用的敏感性进行了分析.分析结果表明,所提出的方法是区域交通系统敏感性分析的有效方法.     

基于有限元方法的连续型交通分配模型解法

针对一般城市形态模型的弹性需求连续型交通分配模型 ,提出了一种基于有限元方法的牛顿迭代解法 .残余向量Re 和雅克比矩阵Je 是更优解迭代式中的算子 ,可以通过三角形线性插值函数 ,利用单元节点的数值求得 .最后给出的数值算例的结果证明了算法的可行性和有效性 .     

Optimization of Time-Varying Parking Charges and Parking Supply in Networks with Multiple User Classes and Multiple Parking Facilities

The optimization of parking charges and parking supply over the time of a day is an important problem in the design of transportation networks. This paper presents a bilevel model to determine the opti-mal time-varying parking charges and parking supply in road networks with multiple user classes and different types of parking facilities. The upper level of the model aims to maximize the network net benefit in response to the parking charges and parking supply, whereas the lower level is a time-dependent network equilibrium problem with elastic demand. A descent-gradient-based solution algorithm is adapted to solve the model. The numerical results show that the implementation of time-varying parking charges and parking supply is useful to effectively cater to the time-varying demand with different parking needs. The model provides a powerful tool for strategically designing parking locations and evaluating various parking policies.