Microscopic simulation model calibration and validation handbook.
Byungkyu Park, Jongsun Won
Abstract
Byungkyu Park, Jongsun Won
Abstract
Microscopic traffic simulation models are widely used in the transportation engineering field. Because of their cost-effectiveness, risk-free nature, and high-speed benefits, areas of use include transportation system design, traffic operations, and management alternatives evaluation. Despite their popularity and value, the credibility of simulation models falls short due to the use of default parameters without careful consideration. Improper model parameters prevent simulation models from accurately mimicking field conditions, limiting their ability to aid decision-making. Therefore, the user needs to pay more attention to fine-tune each model that they are using by calibrating the parameters inside the model. To summarize, we can define calibration as the adjustment of model parameters such that the model’s output more closely represents field conditions. The intention of this handbook is to outline and explain the calibration and validation procedure for the parameters controlling human and vehicle characteristics for CORSIM and VISSIM.
OpenAlex reports 53 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Microscopic traffic simulation models are widely used in the transportation engineering field. Because of their cost-effectiveness, risk-free nature, and high-speed benefits, areas of use include transportation system design, traffic operations, and management alternatives evaluation. Despite their popularity and value, the credibility of simulation models falls short due to the use of default parameters without careful consideration. Improper model parameters prevent simulation models from accurately mimicking field conditions, limiting their ability to aid decision-making. Therefore, the user needs to pay more attention to fine-tune each model that they are using by calibrating the parameters inside the model. To summarize, we can define calibration as the adjustment of model parameters such that the model’s output more closely represents field conditions. The intention of this handbook is to outline and explain the calibration and validation procedure for the parameters controlling human and vehicle characteristics for CORSIM and VISSIM.
Key concepts: VisSim, Calibration, Traffic simulation, Credibility, Limiting, Computer science, Field (mathematics), Simulation modeling