Extraction of Catastrophe Boundary and Evolution of Expressway Traffic Flow State

Abstract

As the main road type in an urban traffic system, the increasingly severe congestion of the expressway restricts social and economic development. It is essential to explore the evolution law of congestion and dissipation to ensure the efficient operation of the expressway. In order to accurately grasp the evolution law of the expressway traffic flow state, this paper selects the expressway weaving section, which is a traffic flow frequency-changing area, to study the traffic operation state, change process, and evolution law, and determine the traffic state discrimination standard. The simulation analysis was carried out using the traffic simulation platform, Vissim software. The simulation results showed an apparent catastrophe phenomenon in the mutual transformation between free and congestion flow. The spectral clustering analysis algorithm was used to accurately extract the boundary of traffic state mutation, combined with the cusp catastrophe theory, to study and analyze the traffic flow state at different times and positions, thus completely displaying the evolution characteristics of traffic flow state. The research results provide an essential theoretical basis for formulating control measures of expressway traffic flow and strategies for traffic congestion dissipation.

HetroTraffSim: A Macroscopic Heterogeneous Traffic Flow Simulator for Road Bottlenecks

“…Qu et al [11] explored traffic congestion on freeways using VISSUM. Spectral clustering was used to determine the transition boundary between free flow traffic and congested traffic.…”

Two-Stage Fuzzy Traffic Congestion Detector

“…In [32], the authors used three inputs-the length of the lanes, the number of lanes, and flow data-to obtain the congestion level output. However, the experiment was only based on a one-week period of data; Kalinic and Keler [33] worked on a fuzzy method that compares two input sets: flowdensity and occupancy-mean speed parameters for detecting traffic congestion; Kalinic and Krisp [34] presented a model containing only two inputs (flow and density), as in most classical traffic studies, which relate pairs of fundamental variables, with a few noticeable exceptions, like the application of Catastrophe theory to a 3D traffic state space, introduced in the 1980s [34], and which is still being studied and applied for the identification of traffic congestion [35,36].…”

Mathematical Modelling of Qualitative System Development

“…These indicators generally describe what happens in a system. If the correct number of inputs and outputs is used, then the indicators are able to reveal the positive/negative development of the system as well as major events within the system, including periods of system development to be investigated by the theory of catastrophes (see, [26][27][28] for details). Long periods of time in which the dynamic intensity indicator has a value of zero or a negative value indicates that the system was hit or has experienced problems, including serious catastrophes such as sudden sharp changes in the price of the inputs or outputs, [29], traffic accidents [30], etc.…”