A Review of Dynamic Traffic Assignment Computer Packages

Jeihani, Mansoureh

doi:10.5399/osu/jtrf.46.2.1021

Cited by 14 publications

(12 citation statements)

References 18 publications

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“…Jeihani (2007) reviewed the DTA models used in some well-known computer packages. Jeihani (2007) reviewed the DTA models used in some well-known computer packages.…”

Section: Introductionmentioning

confidence: 99%

“…Regarding the real-world application, there are several computer packages in the literature. Jeihani (2007) reviewed the DTA models used in some well-known computer packages. Indeed, a lot of effort has been paid in providing a new mathematical representation to solve the DTA problem; however, it is also essential to have an idea about the overall efficiency of different computational methods.…”

Section: Introductionmentioning

confidence: 99%

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Cross‐comparison of convergence algorithms to solve trip‐based dynamic traffic assignment problems

Ameli

Lebacque

Leclercq

2020

Computer aided Civil Eng

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Solving a dynamic traffic assignment problem in a transportation network is a computational challenge. This study first reviews the different algorithms in the literature used to numerically calculate the user equilibrium (UE) related to dynamic network loading. Most of them are based on iterative methods to solve a fixed-point problem.Two elements must be computed: the path set and the optimal path flow distribution between all origin-destination pairs. In a generic framework, these two steps are referred to as the outer and the inner loops, respectively. The goal of this study is to assess the computational performance of the inner loop methods that calculate the path flow distribution for different network settings (mainly network size and demand levels). Several improvements are also proposed to speed up convergence: four new swapping algorithms and two new methods for the step size initialization used in each descent iteration. All these extensions significantly reduce the number of iterations to obtain a good convergence rate and drastically speed up the overall simulations. The results show that the performance of different components of the solution algorithm is sensitive to the network size and saturation. Finally, the best algorithms and settings are identified for all network sizes with particular attention being given to the largest scale.

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“…Jeihani (2007) reviewed the DTA models used in some well-known computer packages. Jeihani (2007) reviewed the DTA models used in some well-known computer packages.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Cross‐comparison of convergence algorithms to solve trip‐based dynamic traffic assignment problems

Ameli

Lebacque

Leclercq

2020

Computer aided Civil Eng

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“…These complexities are implemented in some traffic simulation software using microscopic models (Cheng and Wang 2013). Demand estimation, supply presentation, methods for computing dynamic traffic assignment, and convergence among several well-known computer packages were compared by Jeihani (2007).…”

Section: Transims Implementation For a Small Network And Comparison Wmentioning

confidence: 99%

TRANSIMS Implementation for a Small Network and Comparison with Enhanced Four-Step Model

Jeihani¹,

Ardeshiri²

2014

J Transp Res Forum

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Travel demand forecasting is a major tool to assist decision makers in transportation planning. While the conventional four-step trip-based approach is the dominant method to perform travel demand analysis, behavioral advances have been made in the past decade. This paper proposes and applies an enhancemnt to the four-step travel demand analysis model called Sub-TAZ. Furthermore, as an initial step toward activity-based models, a TRANSIMS Track-1 approach is implemented utilizing a detailed network developed in Sub-TAZ approach. The conventional four-step, Sub-TAZ, and TRANSIMS models were estimated in a small case study for Fort Meade, Maryland, with zonal trip tables. The models were calibrated and validated for the base year (2005), and the forecasted results for the year (2010) were compared to actual ground counts of traffic volume and speed. The study evaluated the forecasting ability of TRANSIMS versus the conventional and enhanced four-step models and provided critical observations concerning strategies for the further implementation of TRANSIMS.BACKGROUND Traffic pattern prediction is necessary for infrastructure improvement, and travel demand modeling provides tools to forecast travel patterns under various conditions. This modeling involves a series of mathematical equations that represent how people make travel choices. Traditional travel demand models use the four-step method, which was introduced in the 1950s and has been used widely in transportation planning. Although the four-step method has been practical in producing aggregate forecasts, it has some shortcomings. For example, in short-range planning networks, existing and newly constructed roads become congested much faster than forecasted (TRB 2007) and the performance of current four-step models is not always satisfactory. Additionally, these models are not behavioral in nature and as a result they are unable to represent the time chosen for travel, travelers’ responses to demand policies (e.g., toll roads, road pricing, and transit vouchers), non-motorized

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“…3 Boyce et al [15] addressed analytical DTA formulations, with a focus on the variational inequality approach 4 Szeto and Lo [16] compared the properties of DTA with different forms of traffic flow models, discussed their implications, and suggested future research directions 5 Szeto and Lo [17] addressed the properties of DTA problems with and without considering the effects of spatial queues, and discussed their implications 6 Mun [18] addressed the traffic flow component of DTA 7 Jeihani [19] focused on the DTA models used in some well-known computer packages such as TRANSIMS, PARAMICS, VISSIM, DYNASMART, DynaMIT, and CONTRAM 8 Szeto [20] outlined the latest developments in one type of DTA models, namely cell-based dynamic equilibrium models, of which the first model was proposed in 1999…”

Section: Figure 2 Cumulative Arrivals and Departures On Links 1 Andmentioning

confidence: 99%

Dynamic traffic assignment: model classifications and recent advances in travel choice principles

Szeto

Wong

2011

Open Engineering

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Dynamic Traffic Assignment (DTA) has been studied for more than four decades and numerous reviews of this research area have been conducted. This review focuses on the travel choice principle and the classification of DTA models, and is supplementary to the existing reviews. The implications of the travel choice principle for the existence and uniqueness of DTA solutions are discussed, and the interrelation between the travel choice principle and the traffic flow component is explained using the nonlinear complementarity problem, the variational inequality problem, the mathematical programming problem, and the fixed point problem formulations. This paper also points out that all of the reviewed travel choice principles are extended from those used in static traffic assignment. There are also many classifications of DTA models, in which each classification addresses one aspect of DTA modeling. Finally, some future research directions are identified.

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A Review of Dynamic Traffic Assignment Computer Packages

Cited by 14 publications

References 18 publications

Cross‐comparison of convergence algorithms to solve trip‐based dynamic traffic assignment problems

Cross‐comparison of convergence algorithms to solve trip‐based dynamic traffic assignment problems

TRANSIMS Implementation for a Small Network and Comparison with Enhanced Four-Step Model

Dynamic traffic assignment: model classifications and recent advances in travel choice principles

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