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http://dx.doi.org/10.12815/kits.2019.18.2.29

Calibration of Car-Following Models Using a Dual Genetic Algorithm with Central Composite Design  

Bae, Bumjoon (Center for Private Financing Highway, The Korea Transport Insititute)
Lim, Hyeonsup (Center for Transportation Analysis, Oak Ridge National Laboratory)
So, Jaehyun (Jason) (Division for Smart City and Transportept, The Korea Transport Insititute)
Publication Information
The Journal of The Korea Institute of Intelligent Transport Systems / v.18, no.2, 2019 , pp. 29-43 More about this Journal
Abstract
The calibration of microscopic traffic simulation models has received much attention in the simulation field. Although no standard has been established for it, a genetic algorithm (GA) has been widely employed in recent literature because of its high efficiency to find solutions in such optimization problems. However, the performance still falls short in simulation analyses to support fast decision making. This paper proposes a new calibration procedure using a dual GA and central composite design (CCD) in order to improve the efficiency. The calibration exercise goes through three major sequential steps: (1) experimental design using CCD for a quadratic response surface model (RSM) estimation, (2) 1st GA procedure using the RSM with CCD to find a near-optimal initial population for a next step, and (3) 2nd GA procedure to find a final solution. The proposed method was applied in calibrating the Gipps car-following model with respect to maximizing the likelihood of a spacing distribution between a lead and following vehicle. In order to evaluate the performance of the proposed method, a conventional calibration approach using a single GA was compared under both simulated and real vehicle trajectory data. It was found that the proposed approach enhances the optimization speed by starting to search from an initial population that is closer to the optimum than that of the other approach. This result implies the proposed approach has benefits for a large-scale traffic network simulation analysis. This method can be extended to other optimization tasks using GA in transportation studies.
Keywords
Simulation calibration; Optimization; Central composite design; Genetic algorithm; Gipps car-following model;
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