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A platform for research: civil engineering, architecture and urbanism
Gravity center adjustable intelligent traffic cone based on deep reinforcement learning
According to the gravity center adjustable intelligent traffic cone based on deep reinforcement learning provided by the invention, a deep reinforcement learning algorithm is adopted, so that the gravity center position of the traffic cone can be automatically adjusted according to the magnitude of wind power and the change of external impact force, and thus the stability is kept. The intelligent traffic cone can resist the influence of high-speed airflow in an expressway construction area through self-learning and adaptation, keeps stable in an area with large wind power, and meanwhile achieves rapid deployment and environment adaptation in urban road construction. In addition, the intelligent traffic cone has the advantages of reducing manual intervention, reducing maintenance cost, improving construction efficiency and the like.
本发明提出了一种基于深度强化学习的重心可调式智慧交通锥，采用了深度强化学习算法，使得交通锥能够根据风力大小和外部撞击力的变化，自动调整其重心位置，从而保持稳定性。本发明的智慧交通锥通过自我学习和适应能够在高速公路施工区域抵御高速气流的影响，在风力较大的地区保持稳定，同时在城市道路施工中实现快速部署和环境适应。此外，本发明的智慧交通锥具备减少人工干预、降低维护成本和提高施工效率等优点。
Gravity center adjustable intelligent traffic cone based on deep reinforcement learning
According to the gravity center adjustable intelligent traffic cone based on deep reinforcement learning provided by the invention, a deep reinforcement learning algorithm is adopted, so that the gravity center position of the traffic cone can be automatically adjusted according to the magnitude of wind power and the change of external impact force, and thus the stability is kept. The intelligent traffic cone can resist the influence of high-speed airflow in an expressway construction area through self-learning and adaptation, keeps stable in an area with large wind power, and meanwhile achieves rapid deployment and environment adaptation in urban road construction. In addition, the intelligent traffic cone has the advantages of reducing manual intervention, reducing maintenance cost, improving construction efficiency and the like.
本发明提出了一种基于深度强化学习的重心可调式智慧交通锥，采用了深度强化学习算法，使得交通锥能够根据风力大小和外部撞击力的变化，自动调整其重心位置，从而保持稳定性。本发明的智慧交通锥通过自我学习和适应能够在高速公路施工区域抵御高速气流的影响，在风力较大的地区保持稳定，同时在城市道路施工中实现快速部署和环境适应。此外，本发明的智慧交通锥具备减少人工干预、降低维护成本和提高施工效率等优点。
Gravity center adjustable intelligent traffic cone based on deep reinforcement learning
一种基于深度强化学习的重心可调式智慧交通锥
ZHAO XIAORONG (author) / SHEN ZHI (author) / LIU JUNPING (author) / LIU HAIFENG (author) / WEI SEN (author) / ZHAO YOUZHANG (author) / LIU HUAYI (author) / DONG RUIJIE (author)
2024-12-27
Patent
Electronic Resource
Chinese
IPC:
E01F
ADDITIONAL WORK, SUCH AS EQUIPPING ROADS OR THE CONSTRUCTION OF PLATFORMS, HELICOPTER LANDING STAGES, SIGNS, SNOW FENCES, OR THE LIKE
,
Zusätzliche Baumaßnahmen, wie die Ausstattung von Straßen oder die bauliche Ausbildung von Bahnsteigen, Landeplätzen für Hubschrauber, Wegweisern, Schneezäunen oder dgl.
/
G06N
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
,
Rechnersysteme, basierend auf spezifischen Rechenmodellen
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