Improving the calibration time of traffic simulation models using parallel computing technique

Dadashzadeh, Nima; Ergun, Murat; Kesten, Ali Sercan; Žura, Marijan

doi:10.1109/mtits.2019.8883322

Cited by 9 publications

(10 citation statements)

References 15 publications

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“…Initially, PSO and PSOGA start with the higher MANE values -just above 0.55, whereas GAPSO registers a better value. After around 240 NFEs, good improvement of MANE values proposed calibration methodology shows successful computational performance, one might consider using parallel computing techniques to decrease the calibration time of the proposed calibration procedure [37].…”

Section: Resultsmentioning

confidence: 99%

An Automatic Calibration Procedure of Driving Behaviour Parameters in the Presence of High Bus Volume

Dadashzadeh

Ergun

Kesten

et al. 2019

PROMET

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Most of the microscopic traffic simulation programs used today incorporate car-following and lane-change models to simulate driving behaviour across a given area. The main goal of this study has been to develop an automatic calibration process for the parameters of driving behaviour models using metaheuristic algorithms. Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and a combination of GA and PSO (i.e. hybrid GAPSO and hybrid PSOGA) were used during the optimization stage. In order to verify our proposed methodology, a suitable study area with high bus volume on-ramp from the O-1 Highway in Istanbul has been modelled in VISSIM. Traffic data have been gathered through detectors. The calibration procedure has been coded using MATLAB and implemented via the VISSIM-MATLAB COM interface. Using the proposed methodology, the results of the calibrated model showed that hybrid GAPSO and hybrid PSOGA techniques outperformed the GA-only and PSO-only techniques during the calibration process. Thus, both are recommended for use in the calibration of microsimulation traffic models, rather than GA-only and PSO-only techniques.

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Section: Resultsmentioning

confidence: 99%

An Automatic Calibration Procedure of Driving Behaviour Parameters in the Presence of High Bus Volume

Dadashzadeh

Ergun

Kesten

et al. 2019

PROMET

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“…GAs have three common operators; (1) selection (selects parents randomly from initial population for the reproduction process, based on their fitness value), ( 2) crossover (combines parents to produce new offspring (children), with single, double, or uniform crossover techniques), and (3) mutation (modifies individuals/gens which are selected based on mutation probability). GAs are suitable for discrete and noisy spaces to find the optimal design solution [32]- [34]. Complex circumstances, such as nonlinearity and shifting parameters, impose increased demands on the use of GA in land-use research with infinite issues [35].…”

Section: A Genetic Algorithmmentioning

confidence: 99%

A Novel LUTI Model Calibration Using Differential Evolution Algorithm

2021

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LUTI (Land-Use and Transportation Interaction) models are decision-making aid tools that simulate complex dynamic bilateral feedback between transportation and land-use models within a territory. Although calibration (parameter estimation) is a crucial requirement of LUTI models, fully automated approaches with the usage of multi-objective functions have not been fully addressed. To address this limitation, a generic calibration approach is proposed for the parameters of the land-use model using a differential evolution algorithm. A global sensitivity analysis was performed to identify the most important land-use model parameters. These parameters were then calibrated using the differential evolution algorithm with the Root Mean Square Error (RMSE) and Mean Absolute Normalized Error (MANE) as multi-objective functions. Five key capabilities are provided in the suggested technique for calibration of LUTI models including 1) global estimation rather than local estimation, 2) consideration of multi-objective functions, 3) continuously improving the results, 4) easily adaptability, and 5) involving multi parameters in the calibration process. The TRANUS land-use model was used to test the performance of the suggested calibration technique. The validation and consolidation of the approach were tested based on convergence, minimization of errors, and modeled/observed data ratio by comparing with the genetic algorithm and particle swarm optimization techniques. The suggested approach using a deferential evaluation algorithm outperformed both genetic and particle swarm optimization techniques and provided the most stable and diverse solutions.

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“…Thus, before any analysis can take place, models need to be calibrated to be able to represent real-life conditions. An automatic calibration procedure of driving behavior parameters using a metaheuristic algorithm has been proposed previously by the authors [41,42]. In this research, a calibrated model of the study area, which has been previously calibrated and validated by the authors, was used.…”

Section: Model Calibrationmentioning

confidence: 99%

“…In this research, a calibrated model of the study area, which has been previously calibrated and validated by the authors, was used. A brief summary of objective function and calibration results has been discussed below; however, to get detailed information regarding the calibration procedure, please see the authors' previous work [41,42].…”

Section: Model Calibrationmentioning

confidence: 99%

An Integrated Variable Speed Limit and ALINEA Ramp Metering Model in the Presence of High Bus Volume

Dadashzadeh

Ergun

2019

Sustainability

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Under many circumstances, when providing full bus priority methods, urban transport officials have to operate buses in mixed traffic based on their road network limitations. In the case of Istanbul's Metrobus lane, for instance, when the route comes to the pre-designed Bosphorus Bridge, it has no choice but to merge with highway mixed traffic until it gets to the other side. Much has been written on the relative success of implementing Ramp Metering (RM), for example ALINEA (‘Asservissement line´ aire d’entre´ e autoroutie’) and Variable Speed Limits (VSL), two of the most widely-used “merging congestion” management strategies, in both a separate and combined manner. However, there has been no detailed study regarding the combination of these systems in the face of high bus volume. This being the case, the ultimate goal of this study is to bridge this gap by developing and proposing a combination of VSL and RM strategies in the presence of high bus volume (VSL+ALINEA/B). The proposed model has been coded using microscopic simulation software—VISSIM—and its vehicle actuated programming (VAP) feature; referred to as VisVAP. For current traffic conditions, the proposed model is able to improve total travel time by 9.0%, lower the number of average delays of mixed traffic and buses by 29.1% and 81.5% respectively, increase average speed by 12.7%, boost bottleneck throughout by 2.8%, and lower fuel consumption, Carbon Monoxide (CO), Nitrogen Oxides (NOx), and Volatile Organic Compounds (VOC) emissions by 17.3% compared to the existing “VSL+ALINEA” model. The results of the scenario analysis confirmed that the proposed model is not only able to decrease delay times on the Metrobus system but is also able to improve the adverse effects of high bus volume when subject to adjacent mixed traffic flow along highway sections.

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Improving the calibration time of traffic simulation models using parallel computing technique

Cited by 9 publications

References 15 publications

An Automatic Calibration Procedure of Driving Behaviour Parameters in the Presence of High Bus Volume

An Automatic Calibration Procedure of Driving Behaviour Parameters in the Presence of High Bus Volume

A Novel LUTI Model Calibration Using Differential Evolution Algorithm

An Integrated Variable Speed Limit and ALINEA Ramp Metering Model in the Presence of High Bus Volume

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