scholarly journals Stochastic User Equilibrium Assignment in Schedule-Based Transit Networks with Capacity Constraints

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Wangtu Xu ◽  
Lixin Miao ◽  
Wei-Hua Lin
Keyword(s):  
Waiting Times ◽  
User Equilibrium ◽  
Capacity Constraint ◽  
Mathematical Programming Problem ◽  
Stochastic User Equilibrium ◽  
Transit Network ◽  
Travel Costs ◽  
Assignment Model ◽  
Proposed Model ◽  
Full Knowledge

This paper proposes a stochastic user equilibrium (SUE) assignment model for a schedule-based transit network with capacity constraint. We consider a situation in which passengers do not have the full knowledge about the condition of the network and select paths that minimize a generalized cost function encompassing five components: (1) ride time, which is composed of in-vehicle and waiting times, (2) overload delay, (3) fare, (4) transfer constraints, and (5) departure time difference. We split passenger demands among connections which are the space-time paths between OD pairs of the network. All transit vehicles have a fixed capacity and operate according to some preset timetables. When the capacity constraint of the transit line segment is reached, we show that the Lagrange multipliers of the mathematical programming problem are equivalent to the equilibrium passenger overload delay in the congested transit network. The proposed model can simultaneously predict how passengers choose their transit vehicles to minimize their travel costs and estimate the associated costs in a schedule-based congested transit network. A numerical example is used to illustrate the performance of the proposed model.

scholarly journals Dynamic Schedule-Based Assignment Model for Urban Rail Transit Network with Capacity Constraints

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Baoming Han ◽  
Weiteng Zhou ◽  
Dewei Li ◽  
Haodong Yin
Keyword(s):  
User Equilibrium ◽  
Capacity Constraints ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Stochastic User Equilibrium ◽  
Temporal And Spatial Distribution ◽  
Transit Network ◽  
Passenger Flow ◽  
Assignment Model ◽  
Urban Rail

There is a great need for estimation of passenger flow temporal and spatial distribution in urban rail transit network. The literature review indicates that passenger flow assignment models considering capacity constraints with overload delay factor for in-vehicle crowding are limited in schedule-based network. This paper proposes a stochastic user equilibrium model for solving the assignment problem in a schedule-based rail transit network with considering capacity constraint. As splitting the origin-destination demands into the developed schedule expanded network with time-space paths, the model transformed into a dynamic schedule-based assignment model. The stochastic user equilibrium conditions can be equivalent to the equilibrium passenger overload delay with crowding penalty in the transit network. The proposal model can estimate the path choice probability according to the equilibrium condition when passengers minimize their perceptive cost in a schedule-based network. Numerical example in Beijing urban rail transit (BURT) network is used to demonstrate the performance of the model and estimate the passenger flow temporal and spatial distribution more reasonably and dynamically with train capacity constraints.

Probit-Based Time-Dependent Stochastic User Equilibrium Traffic Assignment Model

2008 ◽  
Vol 2085 (1) ◽  
pp. 86-94 ◽  
Author(s):  
Kuilin Zhang ◽  
Hani S. Mahmassani ◽  
Chung-Cheng Lu
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Spatial Correlation ◽  
Traffic Assignment ◽  
User Equilibrium ◽  
The Other ◽  
Time Dependent ◽  
Stochastic User Equilibrium ◽  
Assignment Model ◽  
Temporal And Spatial

This study presents a time-dependent stochastic user equilibrium (TDSUE) traffic assignment model within a probit-based path choice decision framework that explicitly takes into account temporal and spatial correlation (traveler interactions) in travel disutilities across a set of paths. The TDSUE problem, which aims to find time-dependent SUE path flows, is formulated as a fixed-point problem and solved by a simulation-based method of successive averages algorithm. A mesoscopic traffic simulator is employed to determine (experienced) time-dependent travel disutilities. A time-dependent shortest-path algorithm is applied to generate new paths and augment a grand path set. Two vehicle-based implementation techniques are proposed and compared in order to show their impact on solution quality and computational efficiency. One uses the classical Monte Carlo simulation approach to explicitly compute path choice probabilities, and the other determines probabilities by sampling vehicles’ path travel costs from an assumed perception error distribution (also using a Monte Carlo simulation process). Moreover, two types of variance-covariance error structures are discussed: one considers temporal and spatial path choice correlation (due to path overlapping) in terms of aggregated path travel times, and the other uses experienced (or empirical) path travel times from a sample of individual vehicle trajectories. A set of numerical experiments are conducted to investigate the convergence pattern of the solution algorithms and to examine the impact of temporal and spatial correlation on path choice behavior.

scholarly journals Stochastic Electric Vehicle Network with Elastic Demand and Environmental Costs

2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
Jie Ma ◽  
Hua Wang ◽  
Tianpei Tang
Keyword(s):  
Large Scale ◽  
Transportation Network ◽  
Urban Transportation ◽  
User Equilibrium ◽  
Environmental Costs ◽  
Elastic Demand ◽  
Stochastic User Equilibrium ◽  
Travel Costs ◽  
Large Scale Network ◽  
Scale Network

Along with the increasing number of the electric vehicles (EVs), an urban transportation network with a large number of EVs will come true in the near future. Since many countries encourage EVs due to their environmental-friendly benefits, the environmental costs of vehicles have attracted much attention in recent years. In this paper, besides the environmental costs, we take into account the issues of the stochastic user equilibrium (SUE), the elastic demand (ED), and the driving range of EVs in the network. We propose an SUE with ED (SUEED) problem to consider these issues in the urban transportation network with EVs. An SUEED model is developed. We also propose a method of successive average (MSA) to solve the SUEED problem. The computational feasibility of the algorithm is tested in a large-scale network. Through a comparison analysis, we show the benefits of introducing EVs into the urban transportation network in the SUEED circumstance. Moreover, a sensitivity analysis is conducted to reveal the potential values of EVs against the development of EVs. The results suggest that EVs may help to reduce both the travelers’ travel costs and the environmental costs of the entire network.

scholarly journals A Stochastic User Equilibrium Model Under Traffic Rationing Based on Mode Shifting Rate

2020 ◽  
Vol 12 (13) ◽  
pp. 5433
Author(s):  
Xueyan Wei ◽  
Wei Wang ◽  
Weijie Yu ◽  
Xuedong Hua ◽  
Yun Xiang
Keyword(s):  
Equilibrium Model ◽  
Traffic Congestion ◽  
Travel Demand ◽  
User Equilibrium ◽  
License Plate ◽  
Stochastic User Equilibrium ◽  
Long Distance ◽  
Traffic Demand ◽  
Proposed Model ◽  
Reasonable Approach

As a countermeasure to urban exhaust pollution and traffic congestion, traffic restriction based on the last digit of license plate numbers has been widely introduced throughout the world. However, the effect of traffic restriction is weakened as it causes the long-distance detour of restricted travel modes and induces travel demand to shift to unrestricted travel modes. To consider detour and shift of traffic demand caused by traffic restriction, we propose a stochastic user equilibrium model under traffic rationing based on mode shifting rate and the corresponding solution algorithm. A case study is conducted to verify the effectiveness of proposed model and algorithm. Main findings of numerical experiments include: (1) Compared with traditional stochastic user equilibrium model, the temporary traffic demand shift caused by long-distance detour are well considered in proposed model. (2) Sensitivity analysis of the consumption parameters used in the proposed model shows that, the involved cost parameters have different effectiveness on the mode shifting rate. This study provides a reasonable relaxation of the intensively used assumption, that all restricted vehicles outside the restricted district will detour in traffic rationing research, and provides a reasonable approach to evaluate the change of link flow and the beneficial effectiveness on the sustainability of traffic environment after implementation of traffic restriction policy.

Study on Optimal Frequency Design Problem for Multimodal Network Using Probit-Based User Equilibrium Assignment

2005 ◽  
Vol 1923 (1) ◽  
pp. 236-245 ◽  
Author(s):  
Kenetsu Uchida ◽  
Agachai Sumalee ◽  
David Watling ◽  
Richard Connors
Keyword(s):  
Design Problem ◽  
Waiting Times ◽  
User Equilibrium ◽  
Stochastic User Equilibrium ◽  
Transit Systems ◽  
Factors Affecting ◽  
Bus Stop ◽  
Equilibrium Assignment ◽  
Multimodal Network ◽  
Transport Modes

In this paper, a probit-based multimodal transport assignment model is developed. Three transport modes (railway system, bus system, and automobiles) and their interactions are considered. The walking time to a bus stop or a station also plays an important role in multimodal networks. Thus, walking to a bus stop or to a railway station is included in the model. The factors affecting travelers’ route choices considered in this model include actual travel times, discomfort effects on transit systems, expected waiting times, fares, and constants specific to transport modes. A route in the model may be composed of different modes. The paper also deals with the optimal transit frequency design problem. The frequency design problem is formulated as an implicit program in which the objective function of total disutility in the multimodal network is minimized with respect to frequencies of transit lines. The flows on a multimodal network follow a probit-based stochastic user equilibrium assignment. A numerical example is presented.

scholarly journals ROAD NETWORK RESERVE CAPACITY WITH STOCHASTIC USER EQUILIBRIUM

Transport ◽  
2015 ◽  
Vol 30 (1) ◽  
pp. 103-116 ◽  
Author(s):  
Jian Wang ◽  
Wei Deng ◽  
Jinbao Zhao
Keyword(s):  
Road Network ◽  
User Equilibrium ◽  
Reserve Capacity ◽  
Stochastic User Equilibrium ◽  
Strong Assumption ◽  
Solution Algorithms ◽  
Proposed Model ◽  
Network Investment ◽  
The Difference

To relax the strong assumption associated with User Equilibrium (UE) in the previous research of network reserve capacity conducted by Gao and Song (2002), this paper assumes that the drivers all make route choices based on Stochastic User Equilibrium (SUE) principle. Similarly, two bi-level programs are formulated to study the network reserve capacity with SUE problem. The first bi-level program is developed to maximize the network reserve capacity by optimizing signal settings while the traffic demands are reassigned by SUE model. The second program extends the research with Continuous Network Design (CND) problem to find the maximum possible increase in reserve capacity through optimizing allocation of network investment. Two methods, i.e. the sensitivity analysis-based method and Genetic Algorithm (GA), are detailed formulated to solve the bi-level reserve capacity problem. Application of the proposed model and its solution algorithms on two numerical examples find that the network reserve capacity does not always increase with improved quality of drivers’ information. Besides, CND can not only help to increase network reserve capacity, but also can help to make more use of physical capacity of road network at Deterministic User Equilibrium (DUE) condition, thus reduces the difference of reserve capacity between the assumptions of SUE and DUE.

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