基于神经网络的道路通行能力与交通需求匹配度判别研究

交通的供需是否匹配关系到城市和枢纽的发展前景。文中在探讨道路通行能力与需求匹配特性的基础上,用BP神经网络理论建立一种交通匹配预测模型。该模型发挥神经网络的优势,对数据并行处理和分布存储,通过训练、学习产生一个非线性映射,自适应地对数据进行预测。通过相关数据实验证明,该神经网络模型有较高的精度,并有较好的适用性。     

基于标度扩展的AHP在飞机空战效能评估中的应用

阐述了标度扩展AHP法的基本原理和步骤,基于该方法对三种典型战斗机的空战效能进行评估,结果表明,采用标度扩展的AHP法进行效能评估,可以减少计算量,并能提高结果的可信度。     

边坡稳定性分析的广义Bishop法

鉴于简化B ishop法作为一种简单实用且精度较高的极限平衡方法却仅限于分析圆弧破坏的缺陷,提出将B ishop法应用于任意滑裂面的广义方法.基于极限平衡理论和简化B ishop法的简化条件,推导其用于一般滑裂面破坏的边坡安全系数计算公式.通过实例分析考证比较该法的精度,并提出取矩中心的确定方法,以保证竖向力简化假设下的精度,为土坡稳定性分析提供了一种简单通用的方法.     

新会基地码头软基加固监测及效果评价分析

以新会基地码头软基处理工程为例,着重介绍软土地基在堆载预压下土体的变形、固结过程。通过对地表沉降、孔隙水压力、水平位移的现场观测及对实测数据的分析,结果表明,堆载预压法能达到预期的加固目的,是经济可靠的软基加固方法。     

影响交叉口控制方式选择的主要因素的筛选与权重分析

城市平面交叉口是城市道路网络的基本节点,对其实施舍理的控制,是解决交叉口问题的关键。影响交叉口控制方式选择的因素很多,因此必须对各种影响因素做出筛选,找到主要的影响因素,才能合理地确定控制方式。相关的研究成果可以应用于交叉口的改造．并为交叉口的综合效益分析奠定基础。     

线路客流预测分析与运营组织设计

从运营需要出发,提出客流预测的年限和内容;通过对客流量级的阐述,分析客流预测三级数据,确定运营的规模;根据OD(起讫点)客流分析来研究行车交路,做出满载率和拥挤度的评价;最终确定车辆编组与行车密度的合理组合,形成系统全面的技术方案,使客流预测更好地为运营组织服务.     

交通运输方式协调发展的状态评价

为促进道路运输、铁路运输、水路运输与航空运输的协调发展,根据各运输方式的系统构成,分别从数量和质量方面提出了反映各运输方式发展水平的指标体系,利用主成分分析方法,对中国1995~2005年各运输方式的综合发展水平进行了计算,并建立了综合发展水平的隶属度模型,对它们之间的协调状态进行了评价。评价结果表明:运输方式之间的平均静态协调度为0.297 8,说明目前中国各运输方式虽然得到快速发展,但彼此之间的发展并不协调。为改变这种不协调发展状态,提出运输方式之间相互促进与相互配合的发展理念,完善运输政策体系,充分开发和利用各种运输方式,建立真正意义上的综合运输枢纽。     

基于Nash平衡的轨道交通列车牵引计算

列车牵引计算是整个城市轨道交通的重要组成部分.就城市轨道交通的牵引计算提出牵引计算的仿真模型,对城市轨道交通的列车运行进行基于Nash平衡的轨道交通研究,着重讨论城市轨道列车在多目标条件下实现多牵引力的列车运行问题,并进行相关的计算研究,可较好地实现在整个列车运行过程中牵引过程的模拟.     

A new schedule-based transit assignment model with travel strategies and supply uncertainties

This paper proposes a new scheduled-based transit assignment model. Unlike other schedule-based models in the literature, we consider supply uncertainties and assume that users adopt strategies to travel from their origins to their destinations. We present an analytical formulation to ensure that on-board passengers continuing to the next stop have priority and waiting passengers are loaded on a first-come-first-serve basis. We propose an analytical model that captures the stochastic nature of the transit schedules and in-vehicle travel times due to road conditions, incidents, or adverse weather. We adopt a mean variance approach that can consider the covariance of travel time between links in a space–time graph but still lead to a robust transit network loading procedure when optimal strategies are adopted. The proposed model is formulated as a user equilibrium problem and solved by an MSA-type algorithm. Numerical results are reported to show the effects of supply uncertainties on the travel strategies and departure times of passengers.     

On the degradation of performance for traffic networks with oblivious users

We consider the problem of characterizing user equilibria and optimal solutions for routing in a given network. We extend the known models by considering users oblivious to congestion in the following sense: While in the typical user equilibrium setting the users follow a strategy that minimizes their individual cost by taking into account the (dynamic) congestion due to the current routing pattern, an oblivious user ignores congestion altogether; instead, he or she decides his routing on the basis of cheapest routes on a network without any flow whatsoever. These cheapest routes can be, for example, the shortest paths in the network without any flow. This model tries to capture the fact that a certain percentage of travelers base their route simply on the distances they observe on a map, without thinking (or knowing, or caring) about the delays experienced on this route due to their fellow travelers. In this work we study the effect of such users using as the measure of network performance its price of anarchy, i.e., the ratio of the total latency experienced by the users (oblivious or not) at equilibrium over the social optimum.