Abstract
In this study, the influence of traveler's departure time choice in day-to-day dynamic evolution of traffic flow in a transportation network is investigated. Combining historical information and real-time information, a dynamic evolution model of traffic flow with a study period divided into two intervals is proposed for a simple two-link network. Then, the evolution of network traffic flow is investigated using numerical experiments. Three types of information are considered: (1) only historical information, (2) only real-time information, and (3) both historical and real-time information. The results show that the dynamic evolution of network traffic flow under the three types of information is similar. However, the possibility of chaos occurrence under both historical and real-time information is smaller than that under two individual types of information. When chaos occurs, the chaotic behavior in traffic-flow evolution under only real-time information is relatively less complex than that under the other two types of information.
Highlights
Both traditional static and dynamic traffic assignments only focus on the equilibrium solution and its solution algorithm
The results show that the dynamic evolution of network traffic flow under the three types of information is similar
Such research does not focus on network flows equilibrium but on the dynamic evolution process of network traffic flow, exploring whether equilibrium exists in network flows and how the equilibrium is reached
Summary
Both traditional static and dynamic traffic assignments only focus on the equilibrium solution and its solution algorithm. The authors presented a discrete dynamic model for the day-to-day adjustment process of route choice and found oscillations and chaos of network traffic flow when travelers were sensitive to travel cost and demand. Ziliaskopoulos and Rao [28] proposed a simulation-based model for equilibrium on dynamic networks when travelers simultaneously optimize their departure times and route choices, but did not consider the instability of traffic-flow evolution. Srinivasan and Guo [29] investigated the dayto-day dynamics in an urban traffic network induced by departure time dynamics in commuter decisions, but did not consider traveler’s route choice behavior. A day-to-day dynamic evolution model considering the departure time and route choice is proposed and the dynamic evolution characteristics of traffic flow under the influence of different travel information are evaluated with a focus on the characteristics of chaos. The presented two-interval formulation lays the foundation for the study of traffic-flow evolution in complex networks with multiple intervals
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