An Efficient Calibration Methodology of Microsimulation Model for Signalized Intersections under Heterogeneous and Indiscipline Traffic Environment

Abstract

A microsimulation software, PTV-VISSIM is gaining popularity to model heterogeneous traffic conditions that exists on Indian roads. However, for such traffic condition, a detailed calibration of VISSIM model in terms identification of model parameters considering different vehicle class is still lacking. The present study proposed an efficient technique to calibrate VISSIM model using data collected from signalized intersections located in Delhi, India. As traffic flow varies in urban networks during different time of day, the calibration of VISSIM model is done for both peak and off-peak hour traffic. Model calibration is done for one site whereas another one is used to check models’ transferability. Initially, an automated sensitivity analysis is carried out for different traffic hour models with respect to each vehicle class by considering saturation flow (SF) as a performance measure. Results shows that all the vehicle classes have a distinct influence on the driving behaviour parameters as well as model’s sensitivity differ with respect to peak and off-peak hour volume. Subsequently, simulated SF and the optimum values of calibrated model parameters are obtained for each vehicle class using an optimization technique, Genetic Algorithm (GA). The error between simulated SFs and field ones are identified in terms of GEH statistics for each case of calibration, validation and model transferability. For all cases, GEH values are found within the recommended value for acceptable fit thus indicating the models are applicable for locations of similar as well as varying intersection width and different traffic volume ranging from 2057 to 4012 veh/hr.