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Author:

张利国 (张利国.) (Scholars:张利国) | 景艳枰 (景艳枰.) | 崔铜巢 (崔铜巢.)

Indexed by:

incoPat zhihuiya

Abstract:

本发明公开了一种基于深度强化学习的自主驾驶规则学习方法,在车联网环境下,路网中存在两种类型车辆,自主驾驶车和网联车。自主驾驶车通过车载控制系统与车联网的车车(Vehicle‑to‑Vehicle,V2V)通信技术实时获取路网中网联车的行驶状态,通过深度强化学习的方式,在保证交通安全的情况下,学习自主驾驶规则,调节车辆队列驾驶间距,以最大化路网的平均速度和提高路网的通行效率。为以后利用深度强化学习进一步提高车辆的自主决策能力奠定了基础。

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Patent Info :

Type: 发明授权

Patent No.: CN202010050338.3

Filing Date: 2020-01-17

Publication Date: 2023-07-25

Pub. No.: CN111222630B

Applicants: 北京工业大学

Legal Status: 授权

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 8

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