Comparison of Simulation-Based Dynamic Traffic Assignment Tools for Operations Management

Balakrishna, Ramachandran; Morgan, Daniel; Yang, Qifan; Slavin, Howard

doi:10.1061/41167(398)112

Cited by 3 publications

(3 citation statements)

References 4 publications

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“…However, recent improvements in the hardware and software capacities have allowed for the use of microscopic models on a larger scale. Software applications like TransModeler (18,19) and MITSIMLab (20) implemented the DA procedure by using a microscopic DNL. Microsimulation DNL denotes a more realistic representation of individual vehicle movements, travel time, and delay for a given scenario.…”

Section: Introductionmentioning

confidence: 99%

“…As a countermeasure, the model was made to run for many more replications, between 75 and 100, beyond the point at which the relative gap was visibly seen to level off (4). Balakrishna et al reported the results for a single model run at a specified convergence criterion but did not explain how to account for the stochasticity attributable to the microscopic DNL (19). Moreover, the previous two studies used the DA(E[DNL]) modeling approach, which is an incorrect evaluation method.…”

Section: Introductionmentioning

confidence: 99%

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Consistency Between Convergence of Dynamic Assignment and Stochasticity of Microsimulation: Implication for Number of Runs

Saxena

Dixit

Waller

2017

Transportation Research Record: Journal of the Transportation R

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Dynamic transportation models route vehicles by using the principles of dynamic user equilibrium. These models include a dynamic network loading (DNL) module that is used to evaluate link costs. However, an element of stochasticity creeps into the modeling framework when the analytical dynamic assignment (DA) procedure is used along with a stochastic microscopic DNL. A methodologically correct way of approaching this problem is by solving the entire DA with a microscopic DNL (DA-microDNL) model until convergence for a given random seed and then repeating the process with different seed values. This paper proposes an approach to determine the minimum number of replications of the DA-microDNL model to determine a statistically valid estimate of the measure of effectiveness (MOE). The approach was tested on a small and medium-size network having different demand and network characteristics. Results show that running the integrated DA-microDNL framework for a minimum number of replications provides a statistically significant MOE at much lower computation time. The consistent estimates obtained by using this approach would provide robust information to transportation planners and practitioners in evaluating the impacts of several policy decisions on network performance.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Consistency Between Convergence of Dynamic Assignment and Stochasticity of Microsimulation: Implication for Number of Runs

Saxena

Dixit

Waller

2017

Transportation Research Record: Journal of the Transportation R

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show abstract

“…DTA frameworks incorporate drivers’ response to different sources of information, so as to model traffic flows over a planning horizon in a transportation network. Time-dependent travel times provided by DTA models can be utilized in travel choice modeling practices, and as a result, generate proactive strategies for systems based on predicted traffic conditions ( 2 , 3 ). Given that simulation-based DTA tools can be used as effective analysis tools to evaluate a broad range of operational and strategic improvements to transportation networks, having simulation models that are sensitive to the interactions between regular (human-driven vehicles without connectivity), connected (human-driven vehicles with connectivity), and AVs plays a pivotal role in predicting future traffic dynamics under emerging vehicle technologies.…”

mentioning

confidence: 99%

Impacts of Connected and Autonomous Vehicles on Traffic Flow with Heterogeneous Drivers Spatially Distributed over Large-Scale Networks

Fakhrmoosavi

Saedi

Zockaie

et al. 2020

Transportation Research Record: Journal of the Transportation R

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Connected and automated vehicle technologies are expected to significantly contribute in improving mobility and safety. As connected and autonomous vehicles have not been used in practice at large scale, there are still some uncertainties in relation to their applications. Therefore, researchers utilize traffic simulation tools to model the presence of these vehicles. There are several studies on the impacts of vehicle connectivity and automation at the segment level. However, only a few studies have investigated these impacts on traffic flow at the network level. Most of these studies consider a uniform distribution of connected or autonomous vehicles over the network. They also fail to consider the interactions between heterogeneous drivers, with and without connectivity, and autonomous vehicles at the network level. Therefore, this study aims to realistically observe the impacts of these emerging technologies on traffic flow at the network level by incorporating adaptive fundamental diagrams in a mesoscopic simulation tool. The adaptive fundamental diagram concept considers spatially and temporally varying distributions of different vehicle types with heterogeneous drivers. Furthermore, this study considers the intersection capacity variations and fundamental diagram adjustments for arterial links resulting from the presence of different vehicle types and driver classes. The proposed methodology is applied to a large-scale network of Chicago. The results compare network fundamental diagrams and hysteresis loop areas for different proportions of connected and autonomous vehicles. In addition to quantifying impacts of connected and autonomous vehicles, the results demonstrate the impacts of various factors associated with these vehicles on traffic flow at the network level.

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Traffic Modeling for Wildland–Urban Interface Fire Evacuation

Intini

Ronchi

Gwynne

et al. 2019

J. Transp. Eng., Part A: Systems

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Several traffic modelling tools are currently available for evacuation planning and real-time decision support during emergencies. In this article, we review potential traffic modelling approaches in the context of Wildland-Urban-Interface (WUI) fire evacuation applications. An overview of existing modelling approaches and features are evaluated pertaining to: fire-related, spatial and demographic factors, intended application (planning or decision support), and temporal issues. This systematic review shows the importance of the following modelling approaches: dynamic modelling structures, considering behavioural variability and en-route choice; activity-based models for short-notice evacuation planning; macroscopic traffic simulation for real-time evacuation management. Subsequently, the modelling features of twenty-three traffic models and applications currently available in practice and the literature are reviewed and matched with the benchmark features identified for WUI fire applications. Based on this review analysis, recommendations are made for developing traffic models specifically applicable to WUI fire evacuation, including possible integrations with wildfire and pedestrian models.

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Comparison of Simulation-Based Dynamic Traffic Assignment Tools for Operations Management

Cited by 3 publications

References 4 publications

Consistency Between Convergence of Dynamic Assignment and Stochasticity of Microsimulation: Implication for Number of Runs

Consistency Between Convergence of Dynamic Assignment and Stochasticity of Microsimulation: Implication for Number of Runs

Impacts of Connected and Autonomous Vehicles on Traffic Flow with Heterogeneous Drivers Spatially Distributed over Large-Scale Networks

Traffic Modeling for Wildland–Urban Interface Fire Evacuation

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