Congestion, flow and capacity
Guoqing Liu
Abstract
Guoqing Liu
Abstract
A new model reflecting the relationships between congestion, flow and capacity is presented. The two concepts of capacity are dealt with in this model: one is the output capacity of a length-limited link or road in traffic systems, which is the same meaning as the capacity adopted usually in Highway Capacity Manual; another is the carrying capacity of the link. All of the two capacities influence traffic congestion: the finiteness of the output capacity is a critical factor for causing congestion; the carrying capacity affects the time evolution of traffic congestion on such a link. Through analysing the new model, one may find that the time evolution of traffic congestion on a link can exhibit an extraordinarily rich spectrum of dynamic behavior, from stable states, to regular oscillations, to apparently random fluctuations–chaotic behavior. This implies that there can be complicated patterns in traffic flow under congested conditions.
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A new model reflecting the relationships between congestion, flow and capacity is presented. The two concepts of capacity are dealt with in this model: one is the output capacity of a length-limited link or road in traffic systems, which is the same meaning as the capacity adopted usually in Highway Capacity Manual; another is the carrying capacity of the link. All of the two capacities influence traffic congestion: the finiteness of the output capacity is a critical factor for causing congestion; the carrying capacity affects the time evolution of traffic congestion on such a link. Through analysing the new model, one may find that the time evolution of traffic congestion on a link can exhibit an extraordinarily rich spectrum of dynamic behavior, from stable states, to regular oscillations, to apparently random fluctuations–chaotic behavior. This implies that there can be complicated patterns in traffic flow under congested conditions.
Key concepts: Flow (mathematics), Computer science, Mathematics, Geometry