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随着轨道交通网络规模的扩大和列车运营间隔的缩短，列车牵引能耗在快速增加。因此，通过优化列车的驾驶策略降低牵引能耗，对于轨道交通系统的节能减排具有重大意义。针对列车的驾驶策略优化问题，提出一种基于深度 Q 网络（DQN）的列车节能驾驶控制方法。首先介绍了传统的列车节能驾驶问题并构造其反问题，即通过分配最少的能耗达到规定运行时分。进一步将该问题转化为有限马尔可夫决策过程（MDP），通过设计状态动作值函数、定义动作策略选取方法等，构建基于 DQN 方法的列车节能驾驶控制方法。通过实际驾驶数据对DQN 进行训练，得到最优的状态动作值函数，并通过该值函数确定最优的能耗分配方案，从而得到最优驾驶策略。最后，以北京地铁亦庄线的实际运营数据设计了仿真算例，对方法的有效性进行验证，并对方法参数进行了敏感度分析。提出的方法可充分利用列车的驾驶数据提升驾驶策略，降低列车牵引能耗，对未来我国智慧城轨的发展具有一定的借鉴意义。

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Copyright of Engineering Mechanics / Gongcheng Lixue is the property of Engineering Mechanics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Engineering Mechanics / Gongcheng Lixue is the property of Engineering Mechanics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)