TY  - JOUR
TI  - A Multi-Objective Approach for the Calibration of Microscopic Traffic Flow Simulation Models
T2  - IEEE Access
SP  - 103124
EP  - 103140
AU  - C. Cobos
AU  - A. Paz
AU  - J. Luna
AU  - C. Erazo
AU  - M. Mendoza
PY  - 2020
KW  - calibration
KW  - evolutionary computation
KW  - nonparametric statistics
KW  - optimisation
KW  - road traffic
KW  - search problems
KW  - statistical testing
KW  - traffic engineering computing
KW  - generalized cost solution
KW  - low-cost solution
KW  - calibration approaches
KW  - multiobjective characteristics
KW  - microscopic traffic-flow simulation models
KW  - dominated solutions
KW  - traffic flow models
KW  - calibration problem
KW  - calibration criterion
KW  - comprehensive cost solution
KW  - Calibration
KW  - Optimization
KW  - Microscopy
KW  - Memetics
KW  - Linear programming
KW  - Search problems
KW  - Solid modeling
KW  - Multi-objective optimization
KW  - calibration
KW  - traffic flow simulation
KW  - MOGBHS
KW  - NSGA-II
DO  - 10.1109/ACCESS.2020.2999081
JO  - IEEE Access
IS  - 
SN  - 2169-3536
VO  - 8
VL  - 8
JA  - IEEE Access
Y1  - 2020
AB  - 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.
ER  -