Efrat Blumenfeld Lieberthal

Abstract The complexity of traffic jam is expected to increase significantly as cities expand. While existing studies have examined local bottlenecks and global traffic patterns, the daily evolution of traffic congestion is unclear yet crucial for understanding network-scale jam formation. We analyze the daily patterns of traffic jams in typical urban networks using real-world data based on a recently developed jam tree model.

Abstract In urban environments, attention has traditionally been paid to public open spaces. However, private open spaces constitute a significant percentage of the urban area and can thus play a significant role in enhancing biological diversity and facilitating direct interactions between humans and nature within urban settings.

Abstract Heavy traffic jams are difficult to predict due to the complexity of traffic dynamics. Understanding the network dynamics of traffic bottlenecks can help avoid critical large traffic jams and improve overall traffic conditions. Here, we develop a method to forecast heavy congestions based on their early propagation stage. Our framework follows the network propagation and dissipation of the traffic jams originated from a bottleneck emergence, growth, and its recovery and disappearance.