A Multi-Objective Approach for the Calibration of Microscopic Traffic Flow Simulation Models

The calibration of traffic-flow simulation models continues to be a significant problem without a generalized, comprehensive, and low-cost solution. Existing calibration approaches either have not explicitly addressed the multi-objective characteristics of the problem or determining their hyperparam...

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Vydáno v:IEEE access Ročník 8; s. 103124 - 103140
Hlavní autoři: Cobos, Carlos, Paz, Alexander, Luna, Julio, Erazo, Cristian, Mendoza, Martha
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Calibration
Computing time
Continuity (mathematics)
Flow simulation
Linear programming
Memetics
Microscopy
MOGBHS
Multi-objective optimization
NSGA-II
Optimization
Parallel processing
Search problems
Simulation
Solid modeling
Traffic flow
traffic flow simulation
Traffic models
ISSN:2169-3536, 2169-3536
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Shrnutí:The calibration of traffic-flow simulation models continues to be a significant problem without a generalized, comprehensive, and low-cost solution. Existing calibration approaches either have not explicitly addressed the multi-objective characteristics of the problem or determining their hyperparameters requires significant effort. In addition, statistical evaluation of alternative solution algorithms is not performed to ensure dominance and stability. This study proposes an adaptation and advanced implementation of the Multi-Objective Global-Best Harmony Search (MOGBHS) algorithm for calibrating microscopic traffic-flow simulation models. The adapted MOGBHS provides five key capabilities for solving the proposed problem including 1) consideration of multiple objectives, 2) easily extendable to memetic versions, 3) simultaneous consideration of continuous and discrete variables, 4) efficient ordering of no dominated solutions, 5) relatively easy tuning of hyperparameters, and 6) easily parallelization to maximize exploration and exploitation without increasing computing time. Three traffic flow models of different dimensionality and complexity were used to test the performance of seventeen metaheuristics for solving the calibration problem. The efficiency and effectiveness of the algorithms were tested based on convergence, minimization of errors, calibration criterion, and two statistical nonparametric tests. The proposed approach dominated all alternative algorithms in all cases and provided the most stable and diverse solutions.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.2999081