scholarly journals Supernetwork Representation Formulation of a Multiclass Simultaneous Transportation Equilibrium Model as a Fixed Demand User Equilibrium Problem

2021 ◽  
Vol 12 (3) ◽  
pp. 18-33
Author(s):  
Mohamad K. Hasan ◽  
Mohammad Saoud ◽  
Raed Al-Husain
Keyword(s):  
Equilibrium Model ◽  
Supply And Demand ◽  
User Equilibrium ◽  
Trip Purpose ◽  
Forecasting Models ◽  
Travel Forecasting ◽  
Transportation Modes ◽  
Departure Time ◽  
Flexible Framework ◽  
Multimodal Network

A multiclass simultaneous transportation equilibrium model (MSTEM) explicitly distinguishes between different user classes in terms of socioeconomic attributes, trip purpose, pure and combined transportation modes, as well as departure time, all interacting over a physically unique multimodal network. It enhances the prediction process behaviorally by combining the trip generation and departure time choices to trip distribution, modal split, and trip assignment choices in a unified and flexible framework that has many advantages from both supply and demand sides. However, the development of this concept of multiple classes increases the mathematical complexity of travel forecasting models. In this research, the authors reduce this mathematical complexity by using the supernetwork representation formulation of the diagonalized MSTEM as a fixed demand user equilibrium (FDUE) problem.

A cell-based multiple vehicle type dynamic user equilibrium model with physical queues

2016 ◽  
Vol 43 (1) ◽  
pp. 1-12 ◽  
Author(s):  
ShuGuang Li
Keyword(s):  
Equilibrium Model ◽  
User Equilibrium ◽  
Transmission Model ◽  
Single Type ◽  
Cell Transmission Model ◽  
Dynamic User Equilibrium ◽  
Vehicle Type ◽  
Time Space ◽  
Departure Time ◽  
A Cell

This paper proposes a cell-based multiple vehicle type dynamic user equilibrium model with physical queues. A single-type traffic flow model is extended to a general case with multiple vehicle types that can be partly solved by the time-space discretization method. Then, a network version of the multiple vehicle type cell transmission model is given. An integrated variational inequality (VI) formulation is presented to capture the complex traveler choice behaviors such as route and departure time choices. Furthermore, a genetic algorithm with a flow-swapping method is adopted to solve the VI problem. Two examples are used to evaluate the properties of this formulation. The results show that the model can reflect dynamic phenomena, such as multiple vehicle type speed consistent under congested conditions, queue formation and dissipation and so on. Moreover, the solutions can approximately follow the multiple vehicle type dynamic route and departure time user equilibrium conditions.

Exploratory Modeling and Analysis for Transportation: An Approach and Support Tool - TMIP-EMAT

2019 ◽  
Vol 2673 (9) ◽  
pp. 407-418 ◽  
Author(s):  
Martin Milkovits ◽  
Rachel Copperman ◽  
Jeffrey Newman ◽  
Jason Lemp ◽  
Thomas Rossi ◽  
...  
Keyword(s):  
Travel Demand ◽  
Supply And Demand ◽  
Single Point ◽  
Transportation Systems ◽  
Analysis Tool ◽  
Demand Model ◽  
Improvement Program ◽  
Modeling And Analysis ◽  
Forecasting Models ◽  
Travel Forecasting

Traditionally, travel forecasting models have been used to provide single point predictions. That is, a single future scenario is developed and the model is applied to that scenario. This approach, however, ignores the deep uncertainty that exists in future land use, demographic, and transportation systems inputs, not to mention the uncertainty that exists in the model itself. More importantly, transportation policy decisions made on the basis of such model outputs may be misguided and ineffective. This paper demonstrates and motivates the use of travel forecasting models in an exploratory manner that accounts for the inherent uncertainties of the future. Specifically, this paper describes the user workflow for a new planning and modeling tool: the Travel Model Improvement Program Exploratory Modeling and Analysis Tool (TMIP-EMAT) that has been developed to facilitate the use of exploratory techniques with travel forecasting models. Examples from the proof of concept deployment using the Greater Buffalo-Niagara Regional Transportation Council regional travel demand model are included. The goal of the longer term study is to provide TMIP-EMAT for state and regional transportation planning agencies to assess how technological innovations will affect traffic and transit demand on major corridors 20 to 30 years down the road. The tool will illuminate interactions between transportation supply and demand on urban surface transportation systems (especially at the corridor level) through exploratory modeling and simulation, and facilitate insights into potential, possible, plausible, probable or preferred futures.

scholarly journals A regret-based route choice model with asymmetric preference in a stochastic network

2018 ◽  
Vol 10 (8) ◽  
pp. 168781401879323
Author(s):  
Lei Zhao ◽  
Hongzhi Guan ◽  
Xinjie Zhang ◽  
Xiongbin Wu
Keyword(s):  
Loss Aversion ◽  
Equilibrium Model ◽  
Choice Model ◽  
User Equilibrium ◽  
Stochastic User Equilibrium ◽  
Regret Minimization ◽  
Route Network ◽  
Travel Decision ◽  
Gains And Losses ◽  
Random Regret Minimization

In this study, a stochastic user equilibrium model on the modified random regret minimization is proposed by incorporating the asymmetric preference for gains and losses to describe its effects on the regret degree of travelers. Travelers are considered to be capable of perceiving the gains and losses of attributes separately when comparing between the alternatives. Compared to the stochastic user equilibrium model on the random regret minimization model, the potential difference of emotion experienced induced by the loss and gain in the equal size is jointly caused by the taste parameter and loss aversion of travelers in the proposed model. And travelers always tend to use the routes with the minimum perceived regret in the travel decision processes. In addition, the variational inequality problem of the stochastic user equilibrium model on the modified random regret minimization model is given, and the characteristics of its solution are discussed. A route-based solution algorithm is used to resolve the problem. Numerical results given by a three-route network show that the loss aversion produces a great impact on travelers’ choice decisions and the model can more flexibly capture the choice behavior than the existing models.

A THEORY OF MULTIPLE VEHICLE TYPE DYNAMIC MARGINAL COST CONSIDERING DEPARTURE TIME CHOICES

Transport ◽  
2010 ◽  
Vol 25 (3) ◽  
pp. 307-313
Author(s):  
Shu-Guang Li ◽  
Qing-Hua Zhou
Keyword(s):  
Marginal Cost ◽  
User Equilibrium ◽  
System Optimum ◽  
Equilibrium Conditions ◽  
Traffic Demand ◽  
Vehicle Type ◽  
Departure Time ◽  
Single Vehicle ◽  
Link Model ◽  
Analytic Expression

The analysis of single vehicle type dynamic marginal cost is extended to multiple vehicle type dynamic one based on time‐dependent multiple vehicle type queue analysis at a bottleneck. First, a dynamic link model to rep‐ resent the interactions between cars and trucks is provided. Then, the analytic expression of a multiple vehicle type dynamic marginal cost function considering departure time choices is deduced under congested and un‐congested conditions and consequently, a dynamic toll function is given. A heuristic algorithm is introduced to solve multiple vehicle type dynamic queues and toll under system optimum and user equilibrium conditions taking into account traveler's departure time. A numerical example shows that a dynamic congestion toll can diminish queues and improve system conditions when traffic demand is not changed.

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