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A Cooperative Optimal Control Method for Mixed Traffic Flow Based on Bi-Level Programming

A technology of mixed traffic and collaborative optimization, applied in the field of traffic engineering

Active Publication Date: 2020-08-28
SOUTHWEST JIAOTONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For various micro-traffic scenarios, such as crossroads, T-junctions, and expressway ramp merges, there is basically no research on collaborative decision-making control in a mixed traffic flow environment to eliminate traffic conflicts to the greatest extent and ensure traffic operation efficiency and capacity.

Method used

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  • A Cooperative Optimal Control Method for Mixed Traffic Flow Based on Bi-Level Programming
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  • A Cooperative Optimal Control Method for Mixed Traffic Flow Based on Bi-Level Programming

Examples

Experimental program
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Effect test

Embodiment 1

[0098] In this embodiment, the method of the invention is described by taking the merging of vehicles on a freeway ramp as an example.

[0099] Such as figure 2 As shown, it is a schematic diagram of vehicle convergence on a highway ramp in a mixed traffic flow scenario, in which the main road (that is, the Y road) and the ramp (that is, the X road) are both one-way and one-way roads, and there are several autonomous vehicles A on the main road ( Vehicles that can be optimally controlled) and human-driven vehicles H (that is, vehicles that cannot be optimally controlled) are irregularly arranged traffic flows, and there are several autonomous vehicles A and human-driven vehicles H that are irregularly arranged on the ramp. between traffic on the main road. It is assumed that the autonomous driving vehicle A and the human driving vehicle H on the main road and ramp follow the microscopic car-following model.

[0100] Upper-level model description: The merging of vehicles on ...

Embodiment 2

[0197] In this embodiment, the method of the invention is described by taking vehicles merging at an intersection as an example.

[0198] Vehicle merging at an intersection: Road X and Road Y are two one-way one-way roads with intersections, and there are several autonomous vehicles (that is, vehicles that can be optimally controlled) and human-driven vehicles (that is, vehicles that cannot be optimally controlled) on the Y road. Irregularly arranged traffic flow, there are several self-driving vehicles and human-driven vehicles on the X road to form an irregularly arranged traffic flow, which needs to turn at the intersection and merge into the interval between the traffic flows on the Y road. Assume that both autonomous vehicles and human-driven vehicles on road X and road Y follow a microscopic car-following model.

[0199] Upper-level model description: The merging of vehicles at an intersection is the process of vehicles waiting to merge turn and merge into the through tr...

Embodiment 3

[0252] In this embodiment, the method of the invention is described by taking a vehicle passing through an intersection as an example.

[0253] Vehicles passing through the intersection: Road X and Road Y are two one-way one-way roads with intersections, and there are several autonomous vehicles (that is, vehicles that can be optimally controlled) and human-driven vehicles (that is, vehicles that cannot be optimally controlled) on the Y road. In the irregularly arranged traffic flow, there are several self-driving vehicles and human-driven vehicles on the X road to form an irregularly arranged traffic flow that needs to pass through the intersection and pass through the interval between the traffic flows on the Y road in turn. Assume that both autonomous vehicles and human-driven vehicles on road X and road Y follow a microscopic car-following model.

[0254] Upper-level model description: Vehicles pass through the intersection, that is, the process of vehicles waiting to pass...

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Abstract

The invention provides a hybrid traffic flow collaborative optimization control method based on double-layer planning, which belongs to the field of traffic engineering. The hybrid traffic flow collaborative optimization control method adopts a double-layer optimization model based on dynamic planning recursion to carry out hybrid traffic flow collaborative decision-making control, and is suitablefor different traffic scenes in a hybrid traffic flow, including highway ramp vehicle confluence, intersection vehicle confluence and intersection vehicle passing; the double-layer optimization modelcomprises an upper-layer model and a lower-layer model, the upper-layer model is a vehicle sorting problem solved by dynamic planning recursion, and the lower-layer model is a single vehicle trajectory optimization problem in different traffic scenes solved by dynamic planning recursion; and the upper-layer model and the lower-layer model are established, and the models are solved. According to the hybrid traffic flow collaborative optimization control method, the optimal vehicle operation of the system is guaranteed by means of the upper-layer model and the lower-layer model, so that the vehicle conflict of the vehicles in the process of convergence, confluence or intersection passing in the hybrid traffic flow environment, and effectively improves the traffic efficiency and comfort of the vehicles.

Description

technical field [0001] The invention relates to a collaborative optimization control method for mixed traffic flows based on bi-level programming, which belongs to the field of traffic engineering. Background technique [0002] New technologies such as Global Positioning System (GPS), wireless communication, advanced sensing, and automatic control have led to the rapid development of autonomous vehicles (i.e. intelligent connected vehicles, optimally controlled vehicles, CAVs). An autonomous vehicle is defined as a vehicle that is able to sense and communicate with the driving environment, and the operation of the vehicle can be carried out (partially or fully) without the driver's operation. Compared with the difficult coordination of traditional human-driven vehicles (vehicles that cannot be optimally controlled), autonomous vehicles have better controllability and coordination. Therefore, this may lead to benefits such as improved fuel / energy efficiency, traffic safety, ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G08G1/01G08G1/07
CPCG08G1/0145G08G1/07G08G1/075Y02T10/40
Inventor 孙湛博
Owner SOUTHWEST JIAOTONG UNIV
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