scholarly journals A Combined Activity Nodes Choice and Trip-chain Based User Equilibrium Traffic Assignment Model

2017 ◽  
Vol 25 ◽  
pp. 2461-2472
Author(s):  
Chung-Yung Wang ◽  
Shou-Ren Hu ◽  
Chih-Peng Chu
Keyword(s):  
Traffic Assignment ◽  
User Equilibrium ◽  
Trip Chain ◽  
Assignment Model

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.

STUDY ON USER EQUILIBRIUM TRAFFIC ASSIGNMENT MODEL CONSIDERING STOCHASTIC ROUTE CHOICE ON EXPRESSWAY NETWORK

2011 ◽  
Vol 67 (5) ◽  
pp. 67_I_779-67_I_786
Author(s):  
Shin-ichi INOUE ◽  
Shuichi YAMAGUCHI ◽  
Yusuke SUZUKI ◽  
Takuya MARUYAMA ◽  
Hirohisa MORITA
Keyword(s):  
Traffic Assignment ◽  
Route Choice ◽  
User Equilibrium ◽  
Assignment Model

scholarly journals An Integrated Pipeline Architecture for Modeling Urban Land Use, Travel Demand, and Traffic Assignment

2018 ◽  
Author(s):  
Paul Waddell ◽  
Geoff Boeing ◽  
Max Gardner ◽  
Emily Porter
Keyword(s):  
Land Use ◽  
Travel Demand ◽  
Traffic Assignment ◽  
Urban Land ◽  
User Equilibrium ◽  
Urban Land Use ◽  
Analysis Tool ◽  
Demand Model ◽  
Pipeline Architecture ◽  
Assignment Model

Integrating land use, travel demand, and traffic models represents a gold standard for regional planning, but is rarely achieved in a meaningful way, especially at the scale of disaggregate data. In this report, we present a new pipeline architecture for integrated modeling of urban land use, travel demand, and traffic assignment. Our land use model, UrbanSim, is an open-source microsimulation platform used by metropolitan planning organizations worldwide for modeling the growth and development of cities over long (~30 year) time horizons. UrbanSim is particularly powerful as a scenario analysis tool, enabling planners to compare and contrast the impacts of different policy decisions on long term land use forecasts in a statistically rigorous way. Our travel demand model, ActivitySim, is an agent-based modeling platform that produces synthetic origin--destination travel demand data. Finally, we use a static user equilibrium traffic assignment model based on the Frank-Wolfe algorithm to assign vehicles to specific network paths to make trips between origins and destinations. This traffic assignment model runs in a high-performance computing environment. The resulting congested travel time data can then be fed back into UrbanSim and ActivitySim for the next model run. This technical report introduces this research area, describes this project's achievements so far in developing this integrated pipeline, and presents an upcoming research agenda.

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