Hybrid traffic flow collaborative optimization control method based on model predictive control

Abstract

The invention discloses a mixed traffic flow collaborative optimization control method based on model predictive control. According to the method, a double-layer optimization model based on model predictive control is adopted to perform hybrid traffic flow collaborative decision control. The method is suitable for different traffic scenes in hybrid traffic flow under the conditions of two crossed one-way roads and no vehicle driving signal indication in front of the intersection. The model predictive control means that real-time closed-loop control is realized by establishing a system architecture so as to solve the randomness problem in the actual situation. The double-layer optimization model comprises an upper-layer model and a lower-layer model, the upper-layer model is a vehicle sorting problem solved by applying dynamic programming recursion, the lower-layer model is a trajectory optimization problem solved by applying a dynamic matrix prediction algorithm for each single vehicle, and the trajectory optimization result of each single vehicle in the lower-layer model is one input in the dynamic programming recursion solving process of the upper-layer model. Optimal operation of a system vehicle is guaranteed through the model predictive control and the double-layer optimization model.

Description

technical field [0001] The invention relates to a model predictive control-based collaborative optimization control method for mixed traffic flow, which belongs to the field of traffic engineering. Background technique [0002] Since the concept of autonomous driving was proposed in the 1940s, intelligent networked vehicles have experienced nearly 80 years of development. In recent years, with the extensive application of navigation, electronic map, sensor detection, wireless communication, automatic control and mobile Internet technologies in the transportation and automotive industries, the development of intelligent networked vehicles has entered a new stage. Autonomous vehicles (intelligent connected vehicles) are defined as vehicles that are able to sense and communicate with the driving environment, and the operation of the vehicle can be carried out (partially or fully) without the driver's operation. Compared with traditional human-driven vehicles (traditional drivi...

AI Technical Summary

Problems solved by technology

For various micro-traffic scenarios, such as crossroads, T-junctions, and expressway ramp merges, there is basically no research on collaborative decision-making control in a mixed traffic flow environment to eliminate traffic conflicts to the greatest extent and ensure traffic operation efficiency and capacity.

Images