Simulation of Urban Dynamic Traffic Network Based on Greedy Algorithm

Abstract

This study explores the intricate dynamics of urban traffic flow under varying degrees of intersection and road section carrying capacity. We simulate a city-wide traffic network and examine the impact of extreme situations such as a decline in urban road carrying capacity on the entire traffic system. Our experimental procedure involved simulating traffic flow through intersections and road sections, artificially reducing their maximum carrying capacity, and observing the resultant changes in traffic patterns. Our data reveals a robust correlation between the decrease in carrying capacity and the actual flow percentage across intersections and adjacent sections, with a marked decrease in flow observed when the capacity reduction exceeds 40%. The actual flow percentage of nearby intersections increased significantly under the same conditions, suggesting a degree of redistribution of traffic flow. This study contributes to the broader understanding of urban traffic dynamics, offering valuable insights for urban planning and traffic management strategies.