Modeling the Impact of Traffic Density on Critical Gap Distribution at Unsignalized Intersections

Abstract

This study constructs mathematical models to evaluate the connection between critical gap dimensions and traffic flow volumes at traffic intersections without signals. Drivers need critical gap as the briefest gap between vehicles to safely move through the road. Traditional theoretical models maintain fixed traffic density patterns even though actual conditions from urban roads typically exhibit changing densities. Including fluctuating traffic density in this model will improve accuracy when studying how changing traffic conditions influence critical gap measurements. The model applies exponential distribution to compute acceptance probabilities of different gap sizes while traffic density adjusts. In more congested traffic conditions drivers accept shorter gaps because the critical gap becomes smaller. The conclusion matches what existing traffic flow theories have previously demonstrated. This model delivers meaningful information regarding traffic management procedures and road intersection design standards particularly for city areas experiencing shifting traffic congestion throughout the day.