Development potential of the Northeast Passage based on a multinomial-logit-based stochastic user equilibrium model

We developed a multinomial-logit-based stochastic user equilibrium(MNL SUE)model incorporating time value of cargo to investigate future proportions of cargo flow through the Northeast Passage(NEP)and the Suez Canal Route between representative ports.We studied navigation during the ice-free and ice-covered seasons using sea ice projections for 2070 based on 1991–2021 NEP ice data.Sailing distance and time between selected ports are lower via the NEP than the Suez Canal Route.Under the scenario of year-round operation of the NEP,the proportion of cargo flow through the NEP is estimated to be 68.5%,which represents considerable commercial potential.Proportions are higher for the ice-free season and for ports at high latitudes.We also assessed flow under different scenarios.Under the scenario of fuel price increase,proportion of flow through the NEP in the ice-covered season is expected to increase.If time value is ignored,flow through the NEP is expected to increase all year round.If shippers become more cost-conscious,flow through the NEP is also expected to increase.

Robust user equilibrium model based on cumulative prospect theory under distribution-free travel time

The assumption widely used in the user equilibrium model for stochastic network was that the probability distributions of the travel time were known explicitly by travelers. However, this distribution may be unavailable in reality. By relaxing the restrictive assumption, a robust user equilibrium model based on cumulative prospect theory under distribution-free travel time was presented. In the absence of the cumulative distribution function of the travel time, the exact cumulative prospect value(CPV) for each route cannot be obtained. However, the upper and lower bounds on the CPV can be calculated by probability inequalities.Travelers were assumed to choose the routes with the best worst-case CPVs. The proposed model was formulated as a variational inequality problem and solved via a heuristic solution algorithm. A numerical example was also provided to illustrate the application of the proposed model and the efficiency of the solution algorithm.

Cumulative prospect theory-based user equilibrium model with stochastic perception errors

The cumulative prospect theory(CPT) is applied to study travelers' route choice behavior in a degradable transport network. A cumulative prospect theory-based user equilibrium(CPT-UE) model considering stochastic perception error(SPE) within travelers' route choice decision process is developed. The SPE is conditionally dependent on the actual travel time distribution, which is different from the deterministic perception error used in the traditional logit-based stochastic user equilibrium. The CPT-UE model is formulated as a variational inequality problem and solved by a heuristic solution algorithm. Numerical examples are provided to illustrate the application of the proposed model and efficiency of the solution algorithm. The effects of SPE on the reference point determination, cumulative prospect value estimation, route choice decision and network performance evaluation are investigated.

Modified stochastic user-equilibrium assignment algorithm for urban rail transit under network operation

Based on the framework of method of successive averages(MSA), a modified stochastic user-equilibrium assignment algorithm was proposed, which can be used to calculate the passenger flow distribution of urban rail transit(URT) under network operation. In order to describe the congestion's impact to passengers' route choices, a generalized cost function with in-vehicle congestion was set up. Building on the k-th shortest path algorithm, a method for generating choice set with time constraint was embedded, considering the characteristics of network operation. A simple but efficient route choice model, which was derived from travel surveys for URT passengers in China, was introduced to perform the stochastic network loading at each iteration in the algorithm. Initial tests on the URT network in Shanghai City show that the methodology, with rational calculation time, promises to compute more precisely the passenger flow distribution of URT under network operation, compared with those practical algorithms used in today's China.

Integrating Origin-Destination Survey and Stochastic User Equilibrium: A Case Study for Route Relocation

The paper analyses integrating origin-destination (O-D) survey results with stochastic user equilibrium (SUE) in traffic assignment. The two methods are widely used in transportation planning but their applications have not yet fully integrated. While O-D gives a generalized trip patterns, purpose and characteristics, SUE provides optimal trip distributions using the characteristics found in O-D survey. The paper utilized O-D and SUE in route relocation study for the town of Coamo in Puerto Rico. The O-D survey was used initially in studying possible trip distribution and assignment for the new route. Initial distribution and assignment of traffic to the existing roadway networks and the proposed route were allocated utilizing the O-D survey findings. The SUE was then used to optimize the assignments considering roadway characteristics such as number of lanes, capacity limits, free flow speed, signal spacing density, travel time and gasoline cost. The travel time was optimized through the Bureau of Public Roads (BPR) equation found in 2000 HCM. The optimal trips found from the SUE were then used to propose the final alignment of the new route. Traffic assignment from the SUE was slightly different from those initially assigned using O-D, indicating there was optimization. The assignment on new route was increased by 13.8% from the one assigned using O-D while assignment on the existing link was reduced by 22%.

Combinatorial Model Involving Mixed Deterministic Freight Volume Distribution and User's Equilibrium Assignment

Considering characteristics of Chinese urban mixed traffic,the author develops a combinatorial model involving the mixed deterministic traffic volume distribution and user's equilibrium (UE) assignment on the basis of symmetrical link travel time function (or deterrence).Its uniqueness and equivalance to the Wardropian principle of UE are also proved.Finally,we give the algorithm of model.

ATIS与收费策略下多用户随机均衡的效率损失

考虑ATIS作用的交通网络,用户具有交通信息接受程度的异质性;进一步,考虑实施道路收费策略情形下,用户具有时间价值的异质性;基于这两类异质性,研究了ATIS下异质性交通网络的效率损失问题。用户对ATIS系统的响应程度,亦即ATIS信息遵从率,是影响ATIS系统运行效率的关键因素。因此,通过ATIS信息遵从率参数的引入,将用户分为不同类型。假设用户均按照随机方式进行择路,建立了基于时间准则与基于费用准则的多用户Logit-随机均衡变分不等式。当系统总出行成本包含收费时,建立了多用户双准则系统最优模型,界定了多用户Logit-随机均衡相对于多用户系统最优的效率损失,推导出效率损失上界;进一步分析了当路段阻抗函数为多项式情形时,引入了自由流出行时间参数,给出了双准则下效率损失上界的解析式,分析了效率损失上界与各参数之间的关系。研究结论表明,双准则下效率损失上界为ATIS信息遵从率的减函数;此外,效率损失上界与路段阻抗函数、用户时间价值及其对路网的熟悉程度、路网本身复杂程度等因素有关。最后,通过算例验证了结论的有效性。

基于双重限制的公交网络SUE配流模型及算法

考虑站点泊车容量和运送能力双重限制条件下的公交网络系统随机平衡分配问题,建立了与其相等价的数学规划模型,并提出有效的迭代算法.由于线路容量的限制,会导致乘客的过载延迟,车辆排队会使过载延迟进一步增加.在该模型中,乘客的过载延迟时间可由相应容量约束的拉格朗日乘子计算得到,车辆排队延误时间由排队论的理论求得.最后,实例表明该模型和算法是合理和有效的.

交通信息条件下道路和停车选择SUE模型及算法

考虑交通信息系统(advanced traveler information system,ATIS)对出行者道路和停车选择行为的影响,并将出行者分成两类:一类出行者使用ATIS,另一类不使用ATIS.在此基础上,构造了一个基于概率的随机用户均衡模型来描述ATIS条件下的道路和停车选择问题,并给出了相应的求解算法.最后,通过一个算例分析了模型及算法的使用效果.

快慢车模式下早高峰时空乘车路径选择研究

研究早高峰通勤乘客的时空出行规律有助于更好地组织快慢车运营模式。本文从一种常见的快慢车运营模式出发,首先,根据乘客的起点车次和直达/换乘方案联合选择构建乘车路径;其次,以出行时间、早到/迟到延误和车内拥挤度作为早高峰通勤乘客出行选择的影响因素,对不同乘车路径下的出行成本进行构建;再次,以用户均衡理论建立乘车路径分配模型,并证明了该模型用户均衡路段解的存在性及唯一性;最后通过案例,对均衡模型进行验证。研究结果发现:短途乘客更愿意接受高拥挤但终点到达时刻接近工作开始时刻的车次,而长途乘客的车次选择分布较为均匀;除出行时间因素以外,延误惩罚和乘车拥挤同样影响早高峰通勤乘客的换乘行为,虽然换乘快车有可能降低出行时间,但高延误惩罚和拥挤成本会导致部分站点的乘客不选择换乘路径。

考虑随机用户均衡的区县级电动汽车快充站规划

电动汽车渗透率的提高和城市化进程的发展使得区县级充电设施的建设具有重要意义。综合考虑用户充电需求时空分布和用户充电决策中的有限理性,提出一种面向区县的电动汽车快充站优化规划模型。首先,针对区县用户的出行特征,构建包含外部连接的交通网络拓扑扩展形式,采用出行链仿真捕捉用户快充需求;其次,结合影响用户充电选择的多种因素,建立用户充电决策模型并给出随机用户均衡条件;然后,建立以投资运行成本、用户绕行距离最小为目标的多场景快充站选址定容优化模型,通过多种线性化手段处理指数等式均衡约束,将优化问题转换为混合整数线性规划以高效求解;最后,以33节点交通系统为例对快充站规划结果进行分析,验证所提模型和线性近似方法的合理性。

基于出行时间预算的SUE交通分配

基于均匀分布的路段容量,分析了降级路网中路段和路径出行时间的随机变动,假定出行者根据以往的出行经验获取路径出行时间的可变性,并以出行时间预算的形式将这种可变性纳入到其路径选择过程中,进而定义路径出行时间预算为路径出行时间均值与出行时间安全边际之和.在此基础上,采用变分不等式技术构建了基于出行时间预算的多用户类型弹性需求随机用户均衡交通分配模型,并证明了模型解的等价性.

Equilibrium Arrivals to Preemptive Queueing System with Fixed and Random Population Size

A single-server queueing system with preemptive access is considered.Each customer has one attempt to enter the system at its working interval[0,T].As soon as the customer request enters the system,the server immediately starts the service.But when the next request arrives in the system,the previous one leaves the system even he has not finished his service yet.We study a non-cooperative game in which the customers wish to maximize their probability of obtaining service within a certain period of time.We characterize the Nash equilibrium and the price of anarchy,which is defined as the ratio between the optimal and equilibrium social utility.Two models are considered.In the first model the number of players is fixed,while in the second it is random and obeys the Poisson distribution.We demonstrate that there exists a unique symmetric equilibrium for both models.Finally,we calculate the price of anarchy for both models and show that the price of anarchy is not monotone with respect to the number of customers.

基于Python 的等离子体平衡重建程序设计及实现

基于Python环境,设计和编写了等离子体平衡重建算法(Py-EFIT)。利用NumPy和SciPy库求解平衡重建算法中矩阵的运算问题,运用Matplotlib库实现重建算法计算结果的可视化,基于交互式可视化设计包QT Designer,使用PyQt库设计并实现该程序的用户界面。Py-EFIT的测试结果显示等离子体平衡重建过程操作更加简单、直观,为托卡马克实验数据分析提供了一种有效的工具。

随机用户均衡准动态交通分配模型

动态交通分配问题是交通科学研究的热点和难点,将动态交通分配方法应用于大规模网络往往产生过高的计算成本。通过研究准动态交通分配问题,降低动态交通分配中时间的连续性和动态交通分配模型的复杂性。采用路段行程时间计算公式定义一种新的剩余交通需求计算方法;然后考虑剩余交通需求在时段之间的传播过程和出行者对路网的熟悉程度差异,建立基于Logit的随机用户均衡准动态交通分配模型,基于逐次平均法设计模型的求解算法。最后通过Braess网络和九节点网络说明模型的应用情况,并分析模型参数的敏感度,验证模型的合理性与算法的有效性。本研究丰富了交通科学基础理论,为交通政策的制定提供参考依据。

考虑用户出行成本预算的电力-交通耦合网络充电站定价策略

随着电动汽车的规模化发展,研究如何有效考虑用户的出行行为机理并制定合理的充电站充电价格,对电力-交通网络的协同优化调度具有重大意义。针对此问题,提出了考虑用户出行成本预算的电力-交通耦合网络充电站定价策略。首先,建立考虑出行成本预算的交通用户均衡模型,将均衡状态通过变分不等式进行等效描述,从而对电动汽车出行需求和充电行为进行刻画。其次,构建考虑功率削减的配电网二阶锥优化模型,将充电站定价问题转化为含有变分不等式约束的优化问题,并根据问题设计交替迭代算法和外梯度算法进行求解。最后,通过算例对所提模型和方法的有效性进行验证,结果表明了考虑出行成本预算对耦合网络充电定价的必要性。

电-路耦合网络下电动汽车充电站选址定容低碳规划

针对现有电动汽车充电站规划研究鲜有考虑碳排放的问题,提出了一种电-路耦合网络下电动汽车充电站选址定容低碳规划的方法。首先,建立电-路耦合网络,考虑不同车辆的相互影响并计及电动汽车用户里程焦虑,利用蒙特卡洛法模拟车流;其次,对耦合网络碳排放进行溯源和追踪;然后,考虑经济成本和碳排放量,建立多目标充电站规划模型,并利用帕累托前沿求取最优解;最后,以IEEE 33节点配电网和12节点交通网组成的耦合网络作为算例,验证所提方法的有效性。

UE交通分配求解的C语言实现

在交通分配过程中 ,模型的直接求解往往比较困难。文章主要针对UE交通分配问题 ,介绍了连续平均法 (methodofsuccessiveaverages,MSA) ,并利用图论方法和规划方法给出了利用连续平均法求解的C语言程序实现过程。文章最后通过一个算例证明该算法是切实可行的。

基于SUE客流分配的城市轨道交通可达性研究

多数学者在研究城市轨道交通可达性以分析网络的静态拓扑属性为主,部分学者通过站点间的时间最短路或距离最短路分析城市轨道交通的可达性。本文在研究城市轨道交通可达性时,以乘客为城市轨道交通主体,在考虑客流分布的情况下建立一套系统的可达性指标。从可动性和易达性两个方面分析城市轨道交通车站、线路及路网的可达性。并以《黔江区现代有轨电车线网规划》中规划线路为例,采用规划文件中数据,对黔江区有轨电车网络的早高峰站间OD进行随机用户均衡客流分配,得出可达性指标。对比分析未考虑客流分配时的可达性指标,发现该方法和指标能更好地反应城市居民的出行特征和城市轨道交通网络的实际特征。该方法和指标对城市轨道交通线网规划、线路调整及城市轨道交通运营管理具有一定参考意义。

MSA算法求解轨道交通SUE模型问题研究

建立了拥挤条件下的出行阻抗函数,通过引入随机均衡配流条件,构建Logit形式的Fisk轨道交通随机均衡配流(SUE)模型。以随机网络加载算法作为相继平均法(MSA)的基础,给出了轨道交通SUE模型的求解算法。