TY - JOUR TI - Calibration of Vehicle and Driver Characteristics in VISSIM and ANN-based Sensitivity Analysis AU - Bandi, Marsh M AU - George, Varghese VL - 13 IS - 2 PY - 2020 DA - 2020/08/31 SP - 79-101 C1 - IJM 2020;13(2):79-101 DO - 10.34196/ijm.00219 UR - https://doi.org/10.34196/ijm.00219 AB - Traffic-flow modeling using microsimulation approaches facilitates the study of bottlenecks and assists in the analysis of traffic-flow characteristics, the movement of individual vehicles, and in the study of vehicle and driver characteristics. The present study focuses on performing investigations on assessing the influence of vehicle and driver characteristics on accurate prediction of traffic volumes in Mangalore city road network. The multi-stage first-level of calibrations were performed starting with default values of vehicle and driver characteristics followed by testing of various combinations. The accuracy of predicting simulated volumes was measured using GEH-statistic. An ANN-based sensitivity analysis was performed to find the relative importance of vehicle and driver characteristics, which revealed that the average standstill distance, minimum look-ahead distance, and the desired speed: lower bounds for speed distributions were highly sensitive. The second-level of calibrations were performed by fine-tuning these three characteristics in three stages and the final VISSIM model was validated. KW - microsimulation KW - VISSIM KW - vehicle characteristics KW - driver characteristics KW - traffic flow modeling KW - sensitivity analysis JF - IJM SN - 1747-5864 PB - International Journal of Microsimulation ER -