Control method of high-speed ramp entrance merging

Abstract

The invention discloses a control method for merging at the entrance of a high-speed ramp, relates to the technical field of motion control of intelligent transportation vehicles, and solves the technical problems of low merging efficiency and low safety at the entrance of a high-speed ramp. The vehicle motion control equation is established in the control area and the confluence area of ​​the scene, a multi-agent Markov decision is constructed based on the vehicle motion control equation, a multi-agent Q-learning algorithm is constructed based on the multi-agent Markov decision, and according to the The multi-agent Q-learning algorithm is described to solve the optimal trajectory of vehicle merging and realize vehicle merging. The multi-agent Q-learning algorithm is used to solve the optimal trajectory of vehicle traffic, and the reward function including energy consumption, delay and safety is innovatively constructed, so that the vehicle can achieve optimal energy consumption and optimal traffic when driving ,Safe Driving.

Description

technical field [0001] The present disclosure relates to the technical field of motion control of intelligent traffic vehicles, and in particular, to a control method of high-speed ramp entrance merging. Background technique [0002] With the increasing population and car ownership in our country, the phenomenon of traffic congestion is also becoming more and more serious. The high-speed ramp entrance scene is a common traffic environment in urban traffic. At present, the low driving safety of on-ramp vehicles and excessive energy consumption are mostly caused by the serious vehicle queuing phenomenon; the on-ramp vehicles stop and wait to find a suitable gap to merge into the main road , resulting in low traffic efficiency. Therefore, effective merging control at the entrance of the high-speed ramp will greatly improve the efficiency and safety of vehicle traffic and reduce energy consumption. [0003] In the prior art, the confluence control method based on the minimum v...

AI Technical Summary

Problems solved by technology

[0003] In the prior art, the confluence control method based on the minimum value principle cannot achieve real-time performance, which is not conducive to driving safety; the optimal control method represented by the dynamic programming control algorithm is mainly numerical solution, and the computational complexity is high; in addition, Few existing studies consider the three optimization objectives of driving safety, energy saving, and high efficiency at the same time, and only solve a single problem

Images