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.

Sensitivity analysis for stochastic user equilibrium with elastic demand assignment model

This paper puts forward a rigorous approach for a sensitivity analysis of stochastic user equilibrium with the elastic demand （SUEED） model. First, proof is given for the existence of derivatives of output variables with respect to the perturbation parameters for the SUEED model. Then by taking advantage of the gradient-based method for sensitivity analysis of a general nonlinear program, detailed formulae are developed for calculating the derivatives of designed variables with respect to perturbation parameters at the equilibrium state of the SUEED model. This method is not only applicable for a sensitivity analysis of the logit-type SUEED problem, but also for the probit-type SUEED problem. The application of the proposed method in a numerical example shows that the proposed method can be used to approximate the equilibrium link flow solutions for both logit-type SUEED and probit-type SUEED problems when small perturbations are introduced in the input parameters.

A mixed stochastic user equilibrium model considering influence of advanced traveller information systems in degradable transport network

Advanced traveler information systems （ATIS） can not only improve drivers＇ accessibility to the more accurate route travel time information, but also can improve drivers＇ adaptability to the stochastic network capacity degradations. In this paper, a mixed stochastic user equilibrium model was proposed to describe the interactive route choice behaviors between ATIS equipped and unequipped drivers on a degradable transport network. In the proposed model the information accessibility of equipped drivers was reflected by lower degree of uncertainty in their stochastic equilibrium flow distributions, and their behavioral adaptability was captured by multiple equilibrium behaviors over the stochastic network state set. The mixed equilibrium model was formulated as a fixed point problem defined in the mixed route flows, and its solution was achieved by executing an iterative algorithm. Numerical experiments were provided to verify the properties of the mixed network equilibrium model and the efficiency of the iterative algorithm.

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.

A self-regulating pairwise swapping algorithm to search reliability-based user equilibrium

The violation of monotonicity on reliability measures(RMs)usually makes the mathematical programming algorithms less efficient in solving the reliability-based user equilibrium(RUE)problem.The swapping algorithms provide a simple and convenient alternative to search traffic equilibrium since they are derivative-free and require weaker monotonicity.However,the existing swapping algorithms are usually based on linear swapping processes which cannot naturally avoid overswapping,and the step-size parameter update methods do not take the swapping feature into account.In this paper,we suggest a self-regulating pairwise swapping algorithm(SRPSA)to search RUE.SRPSA comprises an RM-based pairwise swapping process(RMPSP),a parameter self-diminishing operator and a termination criterion.SRPSA does not need to check the feasibility of either solutions or step-size parameter.It is suggested from the numerical analyses that SRPSA is effective and can swap to the quasi-RUE very fast.Therefore,SRPSA offers a good approach to generate initial points for those superior local search algorithms.

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.

A stochastic user equilibrium model solving overlapping path and perfectly rational issues

Traffic assignment has been recognized as one of the key technologies in supporting transportation planning and operations.To better address the perfectly rational issue of the expected utility theory(EUT)and the overlapping path issue of the multinomial logit(MNL)model that are involved in the traffic assignment process,this paper proposes a cumulative prospect value(CPV)-based generalized nested logit(GNL)stochastic user equilibrium(SUE)model.The proposed model uses CPV to replace the utility value as the path performance within the GNL model framework.An equivalent mathematical model is provided for the proposed CPV-based GNL SUE model,which is solved by the method of successive averages(MSA).The existence and equivalence of the solution are also proved for the equivalent model.To demonstrate the performance of the proposed CPV-based GNL SUE model,three road networks are selected in the empirical test.The results show that the proposed model can jointly deal with the perfectly rational issue and the overlapping path issue,and additionally,the proposed model is shown to be applicable for large road networks.

Generalized nested logit-based stochasticuser equilibrium model with distance constraint of electric vehicles

Considering the range anxiety issue caused by the limited driving range and the scarcity of battery charging stations,the conventional multinomial logit(MNL)model with the overlapping path issue was used in route choice modeling to describe the route choice behavior of travelers effectively.Furthermore,the generalized nested logit-based stochastic user equilibrium(GNL-SUE)model with the constraints of multiple user classes and distance limits was proposed.A mathematical model was developed and solved by the method of successive averages.The mathematical model was proven to be analytically equivalent to the modified GNL-SUE model,and the uniqueness of the solution was also confirmed.The proposed mathematical model was tested and compared with the GNL-SUE model without a distance limit and the MNL-SUE model with a distance limit.Results show that the proposed mathematical model can effectively handle the range anxiety and overlapping path challenges.

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%.

Bounding the Inefficiency of the C-Logit Stochastic User Equilibrium Assignment

Compared with standard logit-based stochastic user equilibrium assignment model,the C-logit model describes route choice behavior in a more realistic way by considering the overlapping effect between routes.This paper investigates the inefficiency upper bounds of this model against the deterministic system optimum and the C-logit stochastic system optimum in terms of the total network travel time.It is found that the commonality factor of overlapping routes significantly affects the inefficiency bound,besides link congestion degree,total demand and the number of feasible routes.If the commonality factor is not considered,the efficiency loss resulting from selfishly stochastic travel behavior will be to large extent underestimated.

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.

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。

Research on passenger flow control at metro transfer stations based on real-time flow calculation of streamlines

Purpose – The volume of passenger traffic at metro transfer stations serves as a pivotal metric for theorchestration of crowd flow management. Given the intricacies of crowd dynamics within these stations andthe recurrent instances of substantial passenger influxes, a methodology predicated on stochastic processesand the principle of user equilibrium is introduced to facilitate real-time traffic flow estimation within transferstation streamlines.Design/methodology/approach – The synthesis of stochastic process theory with streamline analysisengenders a probabilistic model of intra-station pedestrian traffic dynamics. Leveraging real-time passengerflow data procured from monitoring systems within the transfer station, a gradient descent optimizationtechnique is employed to minimize the cost function, thereby deducing the dynamic distribution of categorizedpassenger flows. Subsequently, adhering to the tenets of user equilibrium, the Frank–Wolfe algorithm isimplemented to allocate the intra-station categorized passenger flows across various streamlines, ascertainingthe traffic volume for each.Findings – Utilizing the Xiaozhai Station of the Xi’an Metro as a case study, the Anylogic simulation softwareis engaged to emulate the intra-station crowd dynamics, thereby substantiating the efficacy of the proposedpassenger flow estimation model. The derived solutions are instrumental in formulating a crowd controlstrategy for Xiaozhai Station during the peak interval from 17:30 to 18:00 on a designated day, yielding crowdmanagement interventions that offer insights for the orchestration of passenger flow and operationalgovernance within metro stations.Originality/value – The construction of an estimation methodology for the real-time streamline traffic flowaugments the model’s dataset, supplanting estimated values derived from surveys or historical datasets withreal-time computed traffic data, thereby enhancing the precision and immediacy of crowd flow managementwithin metro stations.

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。

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。

公交-合乘车道优化设计的多目标双层规划模型

为提高公交专用道利用率,构建了公交-合乘车道(bus-HOV lanes)优化设计的多目标双层规划模型。该模型上层最小化交通总阻抗、公交运营成本和车辆排放;下层考虑非合乘车、合乘车和公交车实现多方式交通网络用户均衡;由快速非支配排序遗传算法求解,其下层由相继平均法和连续权重平均法求解;并使用Nguyen-Dupuis网络验证模型及其求解算法。结果表明:所给算法能有效获得公交-合乘车道设置方案的Pareto最优解集;合理的公交-合乘车道设置方案能有效促进合乘出行;相比不设置公交-合乘车道,全部和部分合乘车进入公交-合乘车道分别使交通总阻抗降低-0.007%~1.088%和0.038%~4.493%,使公交运营成本上升1.057%~3.864%和4.011%~5.611%,使车辆排放减少-7.598%~-1.111%和-0.677%~3.526%;当起讫点(OD)对客流量不低于其临界值,设置公交-合乘车道有利于增加公交车客流量。

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。

Alpha-reliable combined mean traffic equilibrium model with stochastic travel times

Based on the reliability budget and percentile travel time(PTT) concept, a new travel time index named combined mean travel time(CMTT) under stochastic traffic network was proposed. CMTT here was defined as the convex combination of the conditional expectations of PTT-below and PTT-excess travel times. The former was designed as a risk-optimistic travel time index, and the latter was a risk-pessimistic one. Hence, CMTT was able to describe various routing risk-attitudes. The central idea of CMTT was comprehensively illustrated and the difference among the existing travel time indices was analyzed. The Wardropian combined mean traffic equilibrium(CMTE) model was formulated as a variational inequality and solved via an alternating direction algorithm nesting extra-gradient projection process. Some mathematical properties of CMTT and CMTE model were rigorously proved. Finally, a numerical example was performed to characterize the CMTE network. It is founded that that risk-pessimism is of more benefit to a modest(or low) congestion and risk network, however, it changes to be risk-optimism for a high congestion and risk network.

考虑可再生能源协调出力的电动汽车充电定价方法

在一个配电网和城市交通网耦合框架中,提出一种电动汽车充电定价方法。建立以社会总成本最小为目标的电动汽车充电服务费的双层优化模型,模型上层为在含风电的配电网中求解充电服务费(Charging Service Fees, CSF)的二阶锥问题;下层为一个遵循用户均衡(User Equilibrium, UE)原则的交通分配问题。该模型考虑了风电输出和OD交通流的不确定性,建立基于深度强化学习的求解框架,对随机双层问题进行解耦和近似求解。以5节点系统和某城市交通-电力耦合网为例,验证了该模型的有效性。