Intelligent targeted dredging method for expressway confluence area

Abstract

The invention relates to an intelligent targeted dredging method for an expressway confluence area, and the method comprises the steps: step 100, taking an automatic unmanned vehicle (CAV) on an expressway as a detector to carry out the sampling of a state space, and carrying out the distributed sampling through a plurality of independent detectors; step 200, judging the capacity condition of the highway confluence area, if the capacity is reduced, performing a ramp control method, and the ramp control method controlling the traffic flow of an entrance ramp by calculating the occupancy rate of the confluence area at the current moment and the flow rate of the entrance ramp at the last moment; step 300, comparing the traffic density of the upstream of the expressway with the critical density, and if the traffic density of the upstream is greater than the critical density, using a D4PG algorithm as a differential variable speed limit strategy to output speed limit strategies of different lanes; and step 400, through coordinated optimization control of a ramp control method and differential variable speed limit, issuing an intelligent targeted dredging strategy to the highway traffic flow.

Description

technical field [0001] The invention belongs to the technical field of intelligent traffic control, and in particular relates to an intelligent targeted congestion removal method for expressway merge areas. Background technique [0002] With the rise of traffic big data and artificial intelligence technology, intelligent vehicles are developing rapidly. In the case of excessive traffic demand, traffic congestion is very easy to occur in the merge area, which is the main factor restricting the development of expressway traffic. In recent years, traffic control methods to alleviate expressway congestion have achieved remarkable results, but current research mainly focuses on expressway main road sections and on-ramps, and lacks effective coordination on the overall road conditions of expressways. Especially in the merging area, the capacity may drop, that is, the traffic capacity of the bottleneck drops below the normal traffic capacity. Using the existing control method, sett...

AI Technical Summary

Problems solved by technology

In recent years, traffic control methods to alleviate expressway congestion have achieved remarkable results, but current research mainly focuses on expressway main road sections and on-ramps, lacking effective coordination on the overall road conditions of expressways

Especially in the merging area, the capacity may drop, that is, the traffic capacity of the bottleneck drops below the normal traffic capacity. Using the existing control method, setting a unified speed control strategy on the main road section will not be able to accurately eliminate the interference caused by the merging of vehicles

Not only that, but with the intensification of CAV (Connected and Autonomous Vehicle), that is, the mixing of autonomous unmanned vehicles and human vehicles, traditional traffic control strategies are invalidated.

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