Gap-based transit assignment algorithm with vehicle capacity constraints: Simulation-based implementation and large-scale application

2016 ◽  
Vol 93 ◽  
pp. 1-16 ◽  
Author(s):  
Ömer Verbas ◽  
Hani S. Mahmassani ◽  
Michael F. Hyland
Keyword(s):  
Large Scale ◽  
Capacity Constraints ◽  
Transit Assignment ◽  
Assignment Algorithm ◽  
Simulation Based ◽  
Vehicle Capacity

Integrated simulation-based dynamic traffic and transit assignment model for large-scale network

2020 ◽  
Vol 47 (8) ◽  
pp. 898-907 ◽  
Author(s):  
Islam Kamel ◽  
Amer Shalaby ◽  
Baher Abdulhai
Keyword(s):  
Large Scale ◽  
Traffic Assignment ◽  
Dynamic Traffic ◽  
Transit Assignment ◽  
Large Scale Network ◽  
Assignment Model ◽  
Morning Peak ◽  
Simulation Based ◽  
Scale Network ◽  
Assignment Models

Although the traffic and transit assignment processes are intertwined, the interactions between them are usually ignored in practice, especially for large-scale networks. In this paper, we build a simulation-based traffic and transit assignment model that preserves the interactions between the two assignment processes for the large-scale network of the Greater Toronto Area during the morning peak. This traffic assignment model is dynamic, user-equilibrium seeking, and includes surface transit routes. It utilizes the congested travel times, determined by the dynamic traffic assignment, rather than using predefined timetables. Unlike the static transit assignment models, the proposed transit model distinguishes between different intervals within the morning peak by using the accurate demand, transit schedule, and time-based road level-of-service. The traffic and transit assignment models are calibrated against actual field observations. The resulting dynamic model is suitable for testing different demand management strategies that impose dynamic changes on multiple modes simultaneously.

scholarly journals PRISMS-Fatigue computational framework for fatigue analysis in polycrystalline metals and alloys

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Mohammadreza Yaghoobi ◽  
Krzysztof S. Stopka ◽  
Aaditya Lakshmanan ◽  
Veera Sundararaghavan ◽  
John E. Allison ◽  
...  
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Large Scale ◽  
Metals And Alloys ◽  
Analysis Tool ◽  
Computational Framework ◽  
Crystal Plasticity Finite Element ◽  
Polycrystalline Metals ◽  
Simulation Based ◽  
Open Source Framework

AbstractThe PRISMS-Fatigue open-source framework for simulation-based analysis of microstructural influences on fatigue resistance for polycrystalline metals and alloys is presented here. The framework uses the crystal plasticity finite element method as its microstructure analysis tool and provides a highly efficient, scalable, flexible, and easy-to-use ICME community platform. The PRISMS-Fatigue framework is linked to different open-source software to instantiate microstructures, compute the material response, and assess fatigue indicator parameters. The performance of PRISMS-Fatigue is benchmarked against a similar framework implemented using ABAQUS. Results indicate that the multilevel parallelism scheme of PRISMS-Fatigue is more efficient and scalable than ABAQUS for large-scale fatigue simulations. The performance and flexibility of this framework is demonstrated with various examples that assess the driving force for fatigue crack formation of microstructures with different crystallographic textures, grain morphologies, and grain numbers, and under different multiaxial strain states, strain magnitudes, and boundary conditions.

scholarly journals Quantifying the effects of passenger-level heterogeneity on transit journey times

2020 ◽  
Vol 1 ◽  
Author(s):  
Ramandeep Singh ◽  
Daniel J. Graham ◽  
Richard J. Anderson
Keyword(s):  
Large Scale ◽  
Semiparametric Regression ◽  
Related Factors ◽  
Network Characteristics ◽  
Journey Time ◽  
Time Variance ◽  
Assignment Algorithm ◽  
Rail Systems ◽  
Urban Rail ◽  
Potential Applications

Abstract In this paper, we apply flexible data-driven analysis methods on large-scale mass transit data to identify areas for improvement in the engineering and operation of urban rail systems. Specifically, we use data from automated fare collection (AFC) and automated vehicle location (AVL) systems to obtain a more precise characterisation of the drivers of journey time variance on the London Underground, and thus an improved understanding of delay. Total journey times are decomposed via a probabilistic assignment algorithm, and semiparametric regression is undertaken to disentangle the effects of passenger-specific travel characteristics from network-related factors. For total journey times, we find that network characteristics, primarily train speeds and headways, represent the majority of journey time variance. However, within the typically twice as onerous access and egress time components, passenger-level heterogeneity is more influential. On average, we find that intra-passenger heterogeneity represents 6% and 19% of variance in access and egress times, respectively, and that inter-passenger effects have a similar or greater degree of influence than static network characteristics. The analysis shows that while network-specific characteristics are the primary drivers of journey time variance in absolute terms, a nontrivial proportion of passenger-perceived variance would be influenced by passenger-specific characteristics. The findings have potential applications related to improving the understanding of passenger movements within stations, for example, the analysis can be used to assess the relative way-finding complexity of stations, which can in turn guide transit operators in the targeting of potential interventions.

Application of smart card data in validating a large-scale multi-modal transit assignment model

2017 ◽  
Vol 10 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Ahmad Tavassoli ◽  
Mahmoud Mesbah ◽  
Mark Hickman
Keyword(s):  
Smart Card ◽  
Large Scale ◽  
Transit Assignment ◽  
Assignment Model ◽  
Smart Card Data

scholarly journals Optimum contributions of hydropower reservoirs to the minimum flow of Vu Gia – Thu Bon river basin

2020 ◽  
Vol 15 (4) ◽  
pp. 1083-1095
Author(s):  
To Viet Thang ◽  
Nguyen T. Thu Nga ◽  
Ngo Le Long
Keyword(s):  
River Basin ◽  
Large Scale ◽  
Search Algorithm ◽  
Scatter Search ◽  
Water Levels ◽  
Electricity Production ◽  
Minimum Flow ◽  
Simulation Based ◽  
Scatter Search Algorithm ◽  
Hydropower Reservoirs

Abstract Upstream hydropower development has a great impact on downstream flows. According to the Regulation of Multi-reservoir Operation in Vu Gia – Thu Bon River Basin (Regulation 15371), four large-scale upstream reservoirs must discharge certain flow during the dry season to increase water levels at downstream hydrological stations named Ai Nghia and Giao Thuy. These stations are used as the control points for the downstream water supply. An optimizing-simulation based model was developed that both maximizes total electricity production and ensures minimum flow downstream as required. A thousand combinations of the reservoir inflows were generated by Monte Carlo simulation, considering the correlation between tributaries. Then, the Scatter search algorithm available in the Optquest module of Crystal Ball was used to find the optimal release from the reservoirs. The results show that the current Regulation 1537 can be improved for more efficient water resources management.

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