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相关概念视频

Open and closed-loop control systems01:17

Open and closed-loop control systems

732
Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal...
732
Feedback control systems01:26

Feedback control systems

307
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
307
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

106
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
106
Root-Locus Method01:19

Root-Locus Method

148
A cruise control system in a car is designed to maintain a specified speed automatically by adjusting the gas pedal. The system continuously measures the vehicle's speed and makes fine adjustments to the pedal to achieve this goal. The root locus method is particularly useful for understanding how the cruise control system's behavior changes under varying conditions, such as when the car goes uphill, downhill, or faces strong wind resistance.
This system can be represented by a block...
148
Controller Configurations01:22

Controller Configurations

95
Controller configurations are crucial in a car's cruise control system because they manage speed over time to maintain a consistent pace regardless of road conditions, thereby meeting design goals. In traditional control systems, fixed-configuration design involves predetermined controller placement. System performance modifications are known as compensation.
Control-system compensation involves various configurations, most commonly series or cascade compensation, in which the controller...
95
PD Controller: Design01:26

PD Controller: Design

223
In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
223

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基于基于模型的强化学习框架的高速公路道的变速限制控制方法与安全感知.

Jieling Jin1, Ye Li1, Helai Huang1

  • 1School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China.

Accident; analysis and prevention
|April 13, 2024
PubMed
概括

本研究引入了一种新的变速限制 (VSL) 策略,使用基于模型的强化学习 (MBRL) 与安全感知来提高高速公路道交通安全和效率. 与传统方法相比,MBRL方法显著提高了安全性和效率.

关键词:
崩风险预测和预测自由道路道的道.基于模型的强化学习学习.多层电池传输模型多层电池传输模型可变速度限制 变速限制

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科学领域:

  • 交通工程是交通工程.
  • 人工智能的人工智能
  • 控制系统 控制系统

背景情况:

  • 高速公路道在保持交通安全和效率方面面临着挑战.
  • 传统的变速限制 (VSL) 策略在适应实时条件方面存在局限性.

研究的目的:

  • 为高速公路道提出一种新的VSL控制策略,使用基于模型的强化学习 (MBRL) 与安全感知.
  • 通过先进的VSL方法提高高速公路道的交通安全和效率.

主要方法:

  • 开发了一种用于高速公路道的多车道细胞传输模型,作为MBRL的环境模型.
  • 集成实时撞车风险预测模型与随机深度和交叉网络进行安全感知.
  • 使用深度dyna-Q方法与安全触发机制训练VSL控制剂.

主要成果:

  • 与固定速度限制相比,拟议的VSL策略将交通安全提高16.00% - 20.00%,效率提高3.00% - 6.50%.
  • 优于基于流量预测和无模型强化学习的传统VSL策略.
  • 有安全触发器的VSL策略与没有安全触发器的VSL策略相比,显示出更高的安全性.

结论:

  • 基于MBRL的VSL战略与安全感知为高速公路道交通安全和效率提供了显著的改善.
  • 开发的战略是有效的,并且可以适应当前的道应用条件.
  • 这种方法显示出在智能运输系统中实现现实世界的巨大潜力.