US 12,314,817 B2
Method for simulating stochastic oscillation in individual-granularity long-distance expressway traffic flow using quantum harmonic oscillator
Zhaoyuan Yu, Jiangsu (CN); Xu Hu, Jiangsu (CN); Zhenjun Yan, Jiangsu (CN); Linwang Yuan, Jiangsu (CN); and Jiyi Zhang, Jiangsu (CN)
Assigned to NANJING NORMAL UNIVERSITY, Jiangsu (CN)
Appl. No. 17/606,050
Filed by NANJING NORMAL UNIVERSITY, Jiangsu (CN)
PCT Filed Nov. 20, 2020, PCT No. PCT/CN2020/130410
§ 371(c)(1), (2) Date Oct. 25, 2021,
PCT Pub. No. WO2022/104693, PCT Pub. Date May 27, 2022.
Claims priority of application No. 202011282775.4 (CN), filed on Nov. 17, 2020.
Prior Publication US 2022/0309377 A1, Sep. 29, 2022
Int. Cl. G06N 10/20 (2022.01); G06F 17/13 (2006.01); G06N 10/60 (2022.01); G06Q 50/40 (2024.01)
CPC G06N 10/60 (2022.01) [G06F 17/13 (2013.01); G06N 10/20 (2022.01); G06Q 50/40 (2024.01)] 3 Claims
OG exemplary drawing
 
1. A method for simulating stochastic oscillation in an individual-granularity long-distance expressway traffic flow using a quantum harmonic oscillator, comprising the following steps: (1) describing 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; (2) constructing an n-order Hermite polynomial based on the energy eigenequation, constructing a quantum harmonic oscillator model for simulating a stochastic oscillation in a long-distance traffic flow with multiple driving strategies, and optimizing a solution model; and (3) constructing a mapping mechanism between a probability and a traffic volume to simulate the traffic volume, wherein each individual vehicle in the long-distance expressway traffic flow is abstracted as a quantized particle, a driving strategy selected by the individual vehicle is regarded as an independent energy state, and the transition of the driving strategy is regarded as approximately the transition of an energy level,
wherein the step (3) is implemented as follows:

OG Complex Work Unit Math
wherein Nt is the traffic volume of vehicles driving off from the expressway, a and Rare normalized coefficients, at ˜ is a number of vehicles in a single time window element determined by traffic volume density in a time window [0, t], and has a strong positive correlation with the number of vehicles driving off from the station, f3t is a number of vehicles driving off from the station in the absence of oscillation, and is the average number of vehicles driving into the expressway in the time window [0, t]; f(x) is obtained by fitting the wave function based on series Nt, and then mapping coefficients a and f3 of the probability density to the total traffic volume are estimated by the least square method.