Abstract
To understand the status quo of urban recurrent traffic congestion, the current results of recurrent traffic congestion, and gating control are reviewed from three aspects: traffic congestion identification, evolution trend prediction, and urban road network gating control. Three aspects of current research are highlighted: (a) The majority of current studies are based on statistical analyses of historical data, while congestion identification is performed by acquiring small-scale traffic parameters. Thus, congestion studies on the urban global roadway network are lacking. Situation identification and the failure to effectively warn or even avoid traffic congestion before congestion forms are not addressed; (b) correlation studies on urban roadway network congestion are inadequate, especially regarding deep learning, and considering the space-time correlation for congestion evolution trend prediction; and (c) quantitative research methods, dynamic determination of gating control areas, and effective countermeasures to eliminate traffic congestion are lacking. Regarding the shortcomings of current studies, six research directions that can be further explored in the future are presented.
Highlights
In recent years, with the rapid development of the social economy, the contradiction between the limited carrying capacity of urban roadway networks, and the rapidly growing tra c demand has become increasingly acute
Prediction Control. e goal of gating control is to reduce the tra c congestion degree of a roadway network by actively controlling the tra c demand at the boundary intersection of the road network to e ectively reduce the duration of tra c congestion and decrease the probability of roadway network oversaturation. e speci c content focuses on the gating control domain determination method according to the network tra c congestion evolution state. e mathematical model of the tra c congestion gating control problem can be constructed according to the model predictive control principle and network tra c state constraints, and the implementation strategy of gating control should be investigated
Many scholars have performed numerous studies of this problem, determining the mechanism of congestion evolution is difficult since the urban transportation system is a complex and vast system. erefore, the effect of blocking is not very optimistic. e contradiction between the limited carrying capacity of an urban roadway network and the rapidly growing traffic demand is becoming increasingly acute; traffic congestions o en occur
Summary
With the rapid development of the social economy, the contradiction between the limited carrying capacity of urban roadway networks, and the rapidly growing tra c demand has become increasingly acute. Tra c congestion in urban areas primarily includes two types: occasional and recurrent. The proportion of recurrent congestion is greater but the processes of its formation, propagation, and dissipation have certain rules. E temporal and spatial evolution of recurrent congestion should be continually evaluated, and this rule should be applied to actively control the tra c ow in a congested area. 1: Keyword co-occurrence network of tra c congestion studies. Provides massive order data and travel trajectory data for urban tra c congestion analysis. Provides massive order data and travel trajectory data for urban tra c congestion analysis. ese data can be integrated with traditional tra c ow detection data, and the relevant time and space features can be extracted by data mining technology to perform an in-depth analysis of the tra c ow characteristics. is process can be utilized to e ciently identify congestion and reveal the temporal and spatial correlation and evolution of the congestion state, which has an important role in the formulation of tra c control schemes and the control of tra c congestion
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