双模式网络停车限制交通需求管理模型与方法研究

在轨道网和公路网并存的双模式交通网络, 合理设计出行终点的停车容量可优化汽车出行需求, 改善路网交通环境。本文通过分析私家车与城市轨道两种交通模式的出行需求, 并考虑私家车模式的终点停车收费服务, 建立了一种带路段环境容量和终点停车需求容量共同约束的交通需求管理模型。模型中路网使用者的出行模式采用二元Logit模型来计算, 而私家车的路线选择行为服从Logit随机用户均衡, 因此该模型是一个带不动点约束的数学规划问题。针对模型求解困难, 文中采用灵敏度分析来获取各路段流量和需求量关于终点容量波动的梯度信息, 进而设计了一种新的灵敏度分析求解算法.最后通过数值仿真实验, 验证了算法的有效性, 同时分析了不同停车收费参数对模型各指标变化趋势的影响。     

行车时间估计与路径寻优问题

通过公路上安装的传感器采集数据,从而估算出车辆的行驶时间并求取最优路径,可以方便人们的出行.根据某段公路上传感器提供的数据分析了该段公路的交通状况,建立微分方程模型和关联度分析模型分析交通状况特征及相互影响,并利用ARIMA模型对速度进行了预测.通过对交通干线图进行分析,在假定各路段上的运行时间为独立的随机变量、考虑路段间的相互影响和根据给定的条件这三种情况下,分别建立模型用于估计跟路段通过时间和寻找最优路径,求解得到理想的结果.所建立模型有较强的实用性,有一定的参考作用.     

路段容量约束弹性需求交通均衡分配近似算法

本文研究了带路段容量约束弹性需求用户均衡交通分配问题及其近似解法.采用超需求模型将弹性需求转化为固定需求,提出了一种带路段容量约束弹性需求用户均衡交通分配近似算法.该算法在迭代过程中,通过不断自适应调节排队延误因子、误差因子来近似真实路段行驶时间,使路段流量逐步满足约束条件,最终达到广义用户均衡.这种方法克服了容量约束弹性需求用户均衡分配计算量大及随机分配法要求枚举所有路径的困难.随后证明了算法的收敛性,并对一个小型路网进行了数值试验.     

基于Stackelberg博弈的时变双层交通分配模型

提出一个时变双层交通分配模型,其中上层网络管理者设立了一个路段的最大排队长度,其目标是使由网络流和排队长度定义的总出行时间最小.目标函数在离散时段内以路段流量和排队长度作为决策变量,同时考虑不同类型的信号交叉口延误的影响.下层网络用户的反应依赖于上层管理者的决策,其选择是使自身感知阻抗最小的路径,服从一个基于成对组合Logit的路径选择模型,构成一个成对组合Logit的均衡分配问题.结合了交通分配和流传播方法,将其表示为一个均衡约束下的双层数学规划问题,形成了一个Stackelberg非合作博弈.使用遗传算法求解该双层规划问题,并采用实证分析来表现模型的特征和算法的计算表现.结果表明路径重叠、路段流量、路段排队长度等因素对网络均衡流分布均有显著影响.     

考虑道路修复的应急资源配送可靠路径选择问题研究

灾害发生后第一时间选择可靠路径完成应急资源的配送分发是应急救援快速展开的必要保障。本文考虑道路修复下的应急资源配送可靠路径规划问题,引入了道路中断和通行可靠性降低来描述灾难对应急资源配送交通路网的影响,以最大化配送效率为目标,构建了道路修复与应急资源配送可靠路径选择集成优化模型,给出了道路修复与可靠路径选择的全局优化方案;设计了多吸引子的粒子群优化模型算法,并结合仿真与分析,验证了模型和算法的有效性。模型与算法的研究对于突发事件下不确定交通路网应急资源配送决策具有很好的指导意义。     

交通灯数学模型

主要讨论在假定车流均匀的前提下如何安排路口的交通灯时间才能使路口的交通达到最大限度的畅通.这里交通最大限度通畅的定义是一个交通周期内积存车辆的最大可能长度达到最小.文章首先以最大限度通畅为目标,道路条件、行人通过马路等条件为约束,建立优化模型解决孤立丁字路口的交通灯安排问题,这个模型也适用于孤立十字路口的分析.随后文章建立了多个路口相连时路口交通灯的安排模型.最后,文章讨论了上述几个模型的稳定性以及改进方向.     

多品种生鲜农产品的车辆路径优化

针对多品种生鲜农产品建立了带软时间窗约束的车辆路径优化模型,模型以配送总成本最少为目标,以生鲜农产品新鲜度阈、时间窗等为约束条件.然后,通过引入Dijkstra算法,改进交叉算子,提出了针对上述模型的改进遗传算法.最后,以上海市交通道路生鲜农产品配送作为案例,对算法进行测试.     

基于改进遗传算法的城市道路级配模型

为缓解交通拥堵的问题,构建满足供需平衡的城市道路等级配置模型.从出行链的特征出发,对道路等级进行分层,结合交通功能进行分类,将城市道路等级划分为三层四类道路.在交通供需平衡、道路总里程、道路用地面积的约束下,以出行总时耗最小为优化目标构建模型,并通过改进的遗传算法求解得各等级道路的级配比.以南京市的城市道路为例进行应用,得到快速路、干路、支路、巷道四类道路的理想级配比为1:4.8:6:7.2.结果表明,该方法对我国城市道路的等级配置有较好的理论借鉴意义.     

货运列车编组调度问题的模型与算法研究

从双向编组站运输生产实际情况出发,以最大化车站发出车数和最小化车辆在站平均停留时间(中时)为目标,综合考虑解体、编组调机能力限制、到发列车车流接续、车流在站停留时间约束的影响,建立了车站货运列车编组调度问题的多目标非线性混合整数规划模型,结合该优化模型难以求解的特点,将编组调度问题分解为配流、待解车列解体和待编车列编组三个子问题,进而设计了求解该问题的分层启发式算法,对正常和特殊运输组织条件下的列车编组调度问题进行了求解.     

高速公路行车时间估计和最优路径

行车时间估计和最优路径选择是智能交通系统中的研究热点,特别是对于车辆导航系统更具有深远的意义.首先以传统的交通流理论为基础,采用间接模型和动力学模型进行行车时间估计,通过仿真实验比较了两模型的优劣,并使用实测数据分析得到的车流量信息对动力学模型进行改进.然后使用Dijkstra算法寻找出静态状态下的最优路径,再结合前面建立的时间估计模型,给出了适用于动态随机状态下的路径寻优算法,用于解决路段行车时间期望随出发时刻动态变化的问题.最后指出了交通实时信息对解决动态随机最优路线问题的重要性,并结合卡尔曼滤波算法对路段相关的情况作了进一步讨论.     

带时空相关性分析的行车时间估计模型

基于流体动力学方程的行车时间估计模型不能很好地反映真实的行车时间,需要对其进行一定的改进.在对交通流进行流体动力学建模的基础之上,引入对高速公路路网中不同路段之间的行车时间相关性和同一路段不同季节、不同时段的行车时间相关性分析,建立了带时空相关性分析的时间估计模型,使用统计学的方法消除动力学模型的误差.     

主路多车道无信号交叉口混合交通流的通行能力

Highway capacity is defined as maximum volume of traffic flow through the particular highway section under given traffic conditions,road conditions and so on.Highway construction and management is judged by capacity standard.The reasonable scale and time of highway construction,rational network structure and optimal management mode of highway network can be determined by analyzing the fitness between capacity and traffic volume.All over the world,highway capacity is studied to different extent in different country. Based on the gap acceptance theory,the mixed traffic flow composed of two representative vehicle types heavy and light vehicles is analyzed with probability theory.Capacity model of the minor mixed traffic flows crossing m major lanes,on which the traffic flows fix in with M3 distributed headway,on the unsignalized intersection is set up,and it is an extension of minor lane capacity theory for one vehicle-type and one major-lane traffic flow.     

简单闭环路网交通流定常解

基于在分岔路口满足用户均衡原理的假定,研究了由三条路段和两个交叉路口组成的简单闭环路网的交通流定常解问题,发现定常解参数及其性态依赖于路网上的车流总数:当车流总数不大于第一个临界值,或不小于第二个临界值时,定常解在每一条路段上均为密度取常数的平凡解;否则,在瓶颈路口（上游最大流量大于下游最大流量的路口）的上游路段将产生激波间断,呈排队等候现象.对分岔路口和交汇路口为瓶颈的情况,分别给出了完整的解析结果     

Optimal Control for Traffic Flow Networks

We consider traffic flow models for road networks where the flow is controlled at the nodes of the network. For the analytical and numerical optimization of the control, the knowledge of the gradient of the objective functional is useful. The adjoint calculus introduced below determines the gradient in two ways. We derive the adjoint equations for the continuous traffic flow network model and derive also the adjoint equations for a discretized model. Numerical examples for the solution of problems of optimal control for traffic flow networks are presented.This author was supported by Deutsche Forschungsgemeinschaft (DFG), Grant KL 1105/5.     

Instantaneous control for traffic flow

The solution methods for optimal control problems with coupled partial differential equations as constraints are computationally costly and memory intensive; in particular for problems stated on networks, this prevents the methods from being relevant. We present instantaneous control problems for the optimization of traffic flow problems on road networks. We derive the optimality conditions, investigate the relation to the full optimal control problem and prove that certain properties of the optimal control problem carry over to the instantaneous one. We propose a solution algorithm and compare quality of the computed controls and run‐times. Copyright © 2006 John Wiley & Sons, Ltd.     

An N-path user equilibrium for transportation networks

The traditional trip-based approach to transportation modeling has been employed for the past decade. The last step of the trip-based modeling approach is traffic assignment, which has been typically formulated as a user equilibrium (UE) problem. In the conventional perspective, the definition of UE traffic assignment is the condition that no road user can unilaterally change routes to reduce their travel time. An equivalent definition is that the travel times of all the used paths between any given origin–destination pair are equal and less than those of the unused paths. The underlying assumption of the UE definition is that road users have full information on the available transportation paths and can potentially use any path if the currently used path is overly congested. However, a more practical scenario is that each road user has a limited path set within which she/he can choose routes from. In this new scenario, we call the resulting user equilibrium an N-path user equilibrium (NPUE), in which each road user has only N paths to select from when making route choices in the network. We introduce a new formulation of the NPUE and derive optimality conditions based on this formulation. Different from traditional modeling framework, the constraints of the proposed model are of linear form, which makes it possible to solve the problem with conventional convex programming techniques. We also show that the traditional UE is a special case of an NPUE and prove the uniqueness of the resulting flow pattern of the NPUE. To efficiently solve this problem, we devise path-based and link-based solution algorithms. The proposed solution algorithms are empirically applied to networks of various sizes to examine the impact of constrained user path sets. Numerical results demonstrate that NPUE results can differ significantly from UE results depending on the number of paths available to road users. In addition, we observed an interesting phenomenon, where increasing the number of paths available to road users can sometimes decrease the overall system performance due to their selfish routing behaviors. This paradox demonstrates that network information should be provided with caution, as such information can do more harm than good in certain transportation systems.     

道路修复条件下灾后应急资源配送LRP研究

灾后道路中断、道路通行可靠性减弱从根本上影响着救援工作的效率,文章通过在应急资源配送定位路径问题的基础上考虑对障碍道路进行修复。通过构建应急设施定位、障碍道路修复以及配送路径选择的综合优化模型,以应急救援的时间总成本最小为目标。集中考虑应急设施定位选址、修复障碍道路和选择配送路径的基础上,以时间总成本最小为目标函数,通过结合相关案例仿真与数据分析的基础上运用多吸引粒子群优化算法对模型进行求解,以期为灾后道路选择、提升道路通行可靠性和应急物资配送效率提供借鉴于理论指导。     

A hybrid optimization algorithm for area traffic control problem

For an area traffic control road network subject to equilibrium flows, the maximum possible increase in travel demands is considered while total delays for travellers are minimized with respect to the common cycle time, the starts and durations of green times and the offsets. Using the concept of reserve capacity of signal-controlled junctions, the problem of finding the maximum increase in traffic demands can be formulated as a mathematical program with equilibrium constraints. In this paper, we present a hybrid optimization algorithm to simultaneously solve the maximum increase in travel demands and minimizing total delays of travellers. Numerical computations are made for the values of performance index and the reserve capacity achieved at various sets of initial signal settings on a variety of signal-controlled networks. Encouraging results are obtained when compared with other alternatives.     

基于新老司机道路选择行为的交通流均衡研究

针对新上路司机数量的爆发式增长带来的交通流均衡变化问题,本文在对司机进行分类和道路选择行为分析的基础上,应用决策树方法构建了基于新老司机道路选择行为的交通流均衡模型,并用实际案例研究了主要参数的敏感性。研究发现:路况通过联合系统车流量的分配情况、车速预期和司机学习过程等因素共同对司机比例产生影响;当某一条道路达到均衡时,车流量对司机比例的敏感程度受到路况差异的影响;司机在驾驶经验、对道路的熟悉程度以及学习能力等方面存在差异,但这种差异仅存在于对交通信息的感知方面。该研究有助于加深对城市交通流变化规律的认识和理解,对于发展出有效的交通管制措施有积极的理论价值和现实意义。     

Joint optimization traffic signal control for an urban arterial road

This paper considers the optimal traffic signal setting for an urban arterial road. By introducing the concepts of synchronization rate and non-synchronization degree, a mathematical model is constructed and an optimization problem is posed. Then, a new iterative algorithm is developed to solve this optimal traffic control signal setting problem. Convergence properties for this iterative algorithm are established. Finally, a numerical example is solved to illustrate the effectiveness of the method.