Increase in efficiency of car following parameters by calibration model

Abstract

Previous studies show that parameter value for car following model, such as, maximum and minimum headway, acceleration, and gap are necessary but there is a big error found while comparing between original and simulated data. Therefore, it is not appropriately applicable to determine the real driver behavior for the different traffic systems. In this study, the calibration method has been proposed to estimate the model parameter and to find the best fit to the car following model. Here, Intelligent Driver Model (IDM) has been used for simulating car behavior and data have been collected from NGSIM eastbound I-80 in the San Francisco Bay area in Emeryville, CA, USA. Simultaneous perturbation stochastic approximation algorithm (SPSAA) has been used as the calibration model in the system to calculate parameters. The calculation has been made by using MATLAB software. SPSAA is proven to have a very much lower error between original simulation data and real trajectory observation I-80 data. Furthermore, this paper investigates that such kinds of estimated parameter are more appropriate to be used in different traffic system.