Chaos In Traffic Flow Research Articles

Incorporation of Duffing Oscillator and Wigner-Ville Distribution in Traffic Flow Prediction

The main purpose of this study was to investigate the use of various chaotic pattern recognition methods for traffic flow prediction. Traffic flow is a variable, dynamic and complex system, which is non-linear and unpredictable. The emergence of traffic flow congestion in road traffic is estimated when the traffic load on a specific section of the road in a specific time period is close to exceeding the capacity of the road infrastructure. Under certain conditions, it can be seen in concentrating chaotic traffic flow patterns. The literature review of traffic flow theory and its connection with chaotic features implies that this kind of method has great theoretical and practical value. Researched methods of identifying chaos in traffic flow have shown certain restrictions in their techniques but have suggested guidelines for improving the identification of chaotic parameters in traffic flow. The proposed new method of forecasting congestion in traffic flow uses Wigner-Ville frequency distribution. This method enables the display of a chaotic attractor without the use of reconstruction phase space.

Train flow chaos analysis based on an improved cellular automata model

To control the chaos in the railway traffic flow and offer valuable information for the dispatchers of the railway system, an improved cellular model is presented to detect and analyze the chaos in the traffic flow. We first introduce the working mechanism of moving block system, analyzing the train flow movement characteristics. Then we improve the cellular model on the evolution rules to adjust the train flow movement. We give the train operation steps from three cases: the trains running on a railway section, a train will arrive in a station and a train will departure from a station. We simulate 4 trains to run on a high speed section fixed with moving block system and record the distances between the neighbor trains and draw the Poincare section to analyze the chaos in the train operation. It is concluded that there is not only chaos but order in the train operation system with moving blocking system and they can interconvert to each other. The findings have the potential value in train dispatching system construction and offer supporting information for the daily dispatching work.

Chaos analysis and delayed-feedback control in a discrete dynamic coupled map traffic model

The presence of chaos in traffic flow is studied using a modified discrete dynamic coupled map model which is derived from both the flow–density–speed fundamental diagram and Del Castillo’s speed–density model. The modified model employs occupancy as its new variable and introduces a coupling strength with the consideration of effect of the front adjacent vehicle. And we analyze its stability of the control system and provide a procedure to design the decentralized delayed-feedback controllers for the traffic control system. These theoretical results are illustrated by numerical simulations.

Chaos Characteristics of Expressway Traffic Flow

AbstractAn improved algorithm for largest Lyapunov exponent is put forward for rapid identification of chaos in traffic flow based on Zuo Binwu’s algorithm. The chaos of expressway traffic flow is studied with the improved algorithm and the power spectrum. The power spectrums of the time series of traffic flow are illustrated. Through the analysis of the power spectrum of the headway, it is clear that there are variations of noise and wide apices. The largest Lyapunov exponents of the time series of traffic flow are computed and used to identify the chaos in the expressway traffic flow. The results prove that chaos in the expressway traffic flow exists indeed. The results are analyzed. Finally, useful conclusion of the study and application for traffic flow is presented.