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高速列车辅助驾驶系统研究与开发

Research and development of driving assistance system for high-speed train

  • 摘要: 在高速铁路现有列车运行控制系统设备配置条件下,司机驾驶列车存在工作强度高、控车决策难度大、受操作经验不足导致列车运行能耗高等问题,人工驾驶难以满足高速铁路更高运营品质的需求。文章基于列车控制与管理系统(TCMS,Train Control and Management System)技术平台,研究开发了高速列车辅助驾驶系统,可自动采集与列车运行控制相关的信息,以安全、准点、节能为目标,建立列车运行控制与能耗优化模型,能够动态生成适合不同运行场景的最优目标速度规划曲线,可为司机提供最优驾驶指导,降低司机控车难度,有利于提升驾驶安全性和节能性;基于TCMS恒速控制功能,还实现了区间巡航功能,丰富了高速列车运行控制自动化模式,可极大地减轻司机工作负担,并保证列车启动、停止的精准度。该系统接受TCMS 的管理和控制,可实现故障导向安全,保障其安全性和可维护性。通过实车试验,初步验证该系统生成的列车最优驾驶指导的有效性和较好的节能效果。

     

    Abstract: Under the current equipment configuration condition of train control system for Chinese high-speed railways, there are problems such as high work intensity, difficulty in making control decisions, and low energy consumption due to drivers' insufficient train operation experience. Manual driving cannot meet the higher operational quality requirements of high-speed railways. Based on the technology platform of Train Control and Management System (TCMS), the driving assistent system for high-speed train is developed. This system can automatically collect information related to train operation control. With the goals of safety, punctuality, and energy conservation, a train operation control and energy consumption optimization model is established, which can dynamically generate the planned optimal target speed curve suitable for different train operation scenarios, provide optimal driving guidance for drivers, reduce the difficulty of driver's decision making on train operations, and improve driving safety and energy efficiency; Based on the TCMS's constant speed control function, section cruise control function has also been implemented, enriching the automation mode of high-speed train operation, greatly reducing the workload of drivers, and ensuring the accuracy of train start and stop. The system is managed and controlled by TCMS, which can enable it fail to safe, ensuring its safety and maintainability. Through real train test, the effectiveness and good energy-saving effects of the optimal driving guidance generated by the system have been preliminarily verified.

     

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