Abstract: The present invention discloses a method for expressing traffic flow characteristics based on a quantum harmonic oscillator model, including: (1) constructing an energy eigenequation of a quantum harmonic oscillator (QHO) for vehicle movement, and converting the energy eigenequation to an Hermite polynomial; (2) solving traffic flow characteristic parameters using K-order Hermite polynomial approximation; and (3) expressing the traffic flow characteristic parameters on a sphere. On the premise of the autonomous decision of a driving strategy by a driver and centering on the objective limitation that the individual accurate state information in the long-distance expressway traffic flow is not observable, the dynamic evolution of the speed and the state of the vehicle is described using a quantum state, the driving state of the vehicle is expressed as the superposition state of three driving states, and the probability of the three states is represented using QHO model parameters.

Abstract: The present invention discloses a method for simulating stochastic oscillation in an individual-granularity long-distance expressway traffic volume using a quantum harmonic oscillator, which includes: firstly, describing the speed and position of a vehicle by a quantum superposition state, and constructing an energy eigenequation of the quantum harmonic oscillator to represent movement of the vehicle; secondly, constructing an n-order Hermite polynomial based on the energy eigenequation, constructing a quantum harmonic oscillator model for simulating the stochastic oscillation in the long-distance traffic flow in a mode featuring aliasing of multiple strategies, and optimizing a solution model; and finally, constructing a mapping mechanism between the probability and the traffic volume to simulate the traffic volume.

Abstract: The present invention discloses a characteristic modes decomposition method for traffic volume based on generation-filtering mechanism, which includes: firstly, the expressway traffic flow is regarded as a closed traffic system. According to the randomness of drivers, each driver is regarded as a separate particle to simulate its trajectory, and then the corresponding traffic modes are obtained according to the probability distribution of the trajectory under different parameters; secondly, taking different parameters of the quantum walk, the time evolution of the probability distribution of the traffic volume caused by different driving patterns at a station is obtained, and then performing the same for other different stations to generate a set of expressway traffic mode set; and finally, according to observed traffic volume data, the generated traffic modes are screened to inverse the mode structures of traffic volume.

Abstract: The present invention discloses a method for fitting modes of a traffic flow based on a quantum walk, including: (1) constructing a mode generator based on the quantum walk; (2) preparing multiple modes; (3) screening the modes; and (4) constructing a mapping mechanism between the modes and the traffic volume. The present invention takes the expressway traffic flow as a complex geographic spatial-temporal process formed by aliasing and coupling of a plurality of traffic modes with different structures, and attempts to realize modeling and simulation of the traffic flow from a multi-scale analysis view. Specifically, under a basic framework of an expressway network topological structure, all possible traffic modes in the expressway traffic flow are generated using quantum walks; and under the constraints of the observed traffic volume time series, the modes are screened based on a specific screening rule.

Abstract: The present invention discloses a quantum computing method for expressway traffic flow distribution simulation considering destination selection. The method comprises the following steps. (1) Construct an expressway exit and entrance network structure. (2) Use a complex number to represent direction-and-flow superposition states of vehicles. (3) Construct a model and setting parameters. (4) Simulate a quantum random walk. (5) Perform model check and time-space matching. and (6) Fit and compare the quantum random walk with real flow data. The present invention can simulate the characteristics of quasi-periodic oscillation and irregularity in expressway traffic flow, closely integrate traffic observation data and reveal the deep characteristics of traffic behavior from a new perspective, thus increasing the accuracy and efficiency of expressway traffic flow simulation.