Expressway mixed traffic flow confluence collaborative optimization underlying control method

Abstract

The invention relates to an expressway mixed traffic flow confluence collaborative optimization underlying control method, and belongs to the field of traffic engineering. The method comprises the following steps: determining a microcosmic car-following model; predicting an initial trajectory of the vehicle; establishing a confluence model; drawing up a cooperative control strategy set; judging whether the vehicle can smoothly finish confluence or not; if the judgment result is that the vehicle can smoothly complete confluence, the vehicle continuing to run according to the speed of the microscopic car-following model; if the judgment result is that the vehicle cannot smoothly finish confluence, further judging the specific situation of the vehicle in the confluence process, and making a corresponding cooperative control strategy according to the specific situation; and optimizing the driving track of the target vehicle according to the made cooperative control strategy to obtain a cooperative optimization control strategy about the target vehicle, and acting the cooperative optimization control strategy on the target vehicle to control the operation of the target vehicle. By meansof the method, the vehicles can stably run at a high speed, and then the vehicle traffic capacity of the highway ramp in the confluence area is improved.

Description

technical field [0001] The invention relates to a low-level control method for synergistic optimization of mixed traffic flows on expressways, belonging to the field of traffic engineering. Background technique [0002] As a traffic demand input link of the entire expressway system, the on-ramp of the expressway is also a link that is prone to congestion, and is of great significance to the smooth and stable operation of the entire expressway system. With the emergence and development of intelligent networked vehicles, future highways will face traffic conditions where intelligent networked vehicles and traditional human-driven vehicles are mixed. Decision-making control in the mixed traffic flow environment of intelligent networked vehicles and traditional human-driven vehicles is a long-term realistic problem in future traffic travel. Therefore, it is of great significance to study the optimization control of freeway ramp merge under the environment of mixed traffic flow....

AI Technical Summary

Problems solved by technology

[0003] For the optimization control problem of expressway ramp cooperative merging, some model methods have been proposed, but the decision-making control methods studied at this stage are mostly decision-making methods for traffic environment design assuming that the penetration rate of autonomous vehicles is 100%, and only Discussed in a specific scenario, it fails to fully describe the combination and sorting scenarios of autonomous vehicles and human-driven vehicles and give the corresponding trajectory optimization scheme

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