Signal control intersection traffic capacity determination method considering man-machine mixed driving traffic flow

Abstract

The invention relates to a signal control intersection traffic capacity determination method considering man-machine mixed driving traffic flow. The method comprises the following steps: S1, setting that a traffic flow in an intersection comprises two types of motor vehicles including human-driven vehicles and intelligent network connection automatic driving vehicles; S2, obtaining the occupancy rates of HDV and CAV; S3, obtaining operation indexes such as saturation flow rates, green light loss time and the like of the HDV and the CAV through actual measurement; S4, obtaining running indexes such as the saturation flow rate and the like in a lane through actual measurement; S5, obtaining the saturation flow rate and the green light loss time of the man-machine mixed driving traffic flow at the signal control intersection; S6, obtaining a probability distribution function of the traffic capacity of the signal control intersection considering the man-machine mixed driving traffic flow; and S7, adopting deterministic expression and probabilistic expression as an expression mode of the traffic capacity. According to the invention, the heterogeneous traffic flow of man-machine mixed driving is considered, the essence of the traffic capacity of the intersection can be reflected, and the probabilistic expression of the traffic capacity is innovatively given.

Description

technical field [0001] The invention relates to the technical field of traffic system analysis of road vehicles, in particular to a method for determining traffic capacity of a signal-controlled intersection considering human-machine mixed driving traffic flow. Background technique [0002] Capacity is one of the core concepts of traffic engineering, and it is also the theoretical cornerstone of traffic planning, traffic design, traffic management and control. As the motor vehicle traffic flow changes from a homogeneous traffic flow that only includes human driving vehicles (Human Driving Vehicle, HDV) to a heterogeneous traffic flow that includes both HDV and connected autonomous vehicles (Connected Autonomous Vehicle, CAV), the existing The capacity algorithm has shown its inadaptability. [0003] In the existing technology, the traffic capacity of the lane is based on the "homogeneous traffic flow" as the research object. The "Road Capacity Manual (2016 Edition)" defines...

AI Technical Summary

Problems solved by technology

As the motor vehicle traffic flow changes from a homogeneous traffic flow that only includes human driving vehicles (Human Driving Vehicle, HDV) to a heterogeneous traffic flow that includes both HDV and connected autonomous vehicles (Connected Autonomous Vehicle, CAV), the existing The capacity algorithm has shown its inadaptability

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