Collaborative control method of freeway traffic capacity based on dynamic lane allocation of cavs mixed traffic flow

Abstract

The invention discloses a collaborative control method for expressway traffic capacity based on the dynamic allocation of lanes of CAVs mixed traffic flow. When the CAVs of Internet-connected automatic driving vehicles have a certain market penetration rate, a dedicated network-connected automatic driving vehicle is set on the expressway. Lane, through multi-factor constraints, establishes an integer nonlinear lane dynamic allocation model; dynamically adjusts the allocation of lane rights and vehicle driving data, outputs the change curve of expressway traffic capacity, selects the optimal solution, and feeds back to the traffic control platform , timely and dynamically adjust the expressway lane allocation scheme and vehicle driving data management and control, and realize the coordinated regulation of expressway traffic capacity. The invention separates the mixed traffic flow by rationally arranging special lanes for CAVs, and at the same time considers the road service level and the impact of the merging area on the road, so that the designed traffic capacity of the basic section of the expressway meets the actual traffic demand, and achieves the purpose of improving traffic efficiency and traffic safety.

Description

technical field [0001] The invention belongs to the technical field of intelligent transportation, and relates to a method for collaborative regulation and control of expressway traffic capacity based on the dynamic allocation of lanes of CAVs mixed traffic flows. Background technique [0002] In recent years, Connected and Automated vehicles (CAVs) have gradually entered the actual road from the test site. It has become a consensus that a single CAVs traffic flow can improve the efficiency, safety, and fuel utilization of expressways. Popularization does not happen overnight, and it takes a long period of time to go through the mixed traffic flow (HMVs and CAVs) stage where CAVs and HMVs are mixed. [0003] The characteristics of mixed traffic flow and its safety are still unclear. At present, most studies on the characteristics of mixed traffic flow are based on simulation experiments or numerical models. The disadvantage is that it is not easy to characterize the randomne...

AI Technical Summary

Problems solved by technology

In the prior art, there is no expressway traffic capacity for the dynamic allocation of lanes of CAVs mixed traffic flow established by combining complex conditions such as the penetration rate of CAVs (MPRs), CAVs lane management (road network and lanes), and the randomness of traffic conditions. collaborative regulation method

[0008] Therefore, in order to expand the mixed traffic flow lane management strategy and make up for the overly optimistic results of the analytical model, it is necessary to propose a collaborative control method for expressway capacity based on the dynamic allocation of lanes for CAVs mixed traffic flow. Traffic flow, while considering the road service level and the impact of the merge area on the road, so that the design capacity of the basic section of the expressway can meet the actual traffic demand, achieve the purpose of improving traffic efficiency and traffic safety, and provide important information for the future mixed traffic flow management of the expressway. It can also provide a theoretical basis for the calculation of the theoretical capacity of expressways

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