Modeling of Effective Parameters for Capacity Prediction at Signalized Intersection Lanes

Current capacity manuals do not allow comprehensively evaluating negative effects on lane caused by undisciplined vehicle movements and utilization, such as failure to obey distance rules, blockage roadside parking effect, formation of an extra using in the emergency lane, etc., which are mostly observed undeveloped developing countries. Irregularities traffic flow utilization result decreased or change urban lanes. To overcome this problem, a lane-based study was carried out determine relation among effective parameters their effect capacity. In order model impact these parameters, comprehensive conducted two cities Turkey. Two different methods (statistical analysis metaheuristic search algorithm) were used for purpose new more reasonable estimation models (ALLCEM-1 ALLCEM-2) developed examining all local conditions. The results proved that both examined modelling signalized intersections. It also found type intersection (either roundabout not), green time, saturation rate, volume, heavy ratio, number actively lanes have major accuracy prediction road