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基于人機協同的車道保持輔助系統研究進展

Overview of lane-keeping assist system based on human–machine cooperative control

  • 摘要: 基于人機動態協同控制的車道保持輔助系統有助于兼顧汽車的安全性與駕駛員的舒適性,分析了該系統在車道偏離決策模型、駕駛權動態分配及性能評估等方面的研究現狀和發展趨勢。在車道偏離決策模型方面,應根據駕駛員的狀態制定不同的決策模型,既可以建立自適應調節的決策模型,又應允許駕駛員根據自己的喜好和外部駕駛環境手動調整決策模型中預設的參數;在駕駛權分配方面,應探索更加合理的駕駛權動態分配方式,設計智能的優化算法或控制模型;在性能評估指標方面,應加入與降低人機沖突及減少駕駛員控制量相關的評估指標,制定科學完善的主觀評估體系。未來研究應該深度融合駕駛員因素,實時發出警報與主動干預,并能夠對系統進行完善的測試與評估。

     

    Abstract: As the final stage of intelligent vehicle, traffic accidents can be effectively reduced by automatic driving. However, neither the technology nor the regulations are mature for autonomous driving. The lane-keeping assist system is one of the important components of the advanced driver-assistance system. When driver fatigue or inattention is detected, the system can effectively prevent the vehicle departure from the lane. Information such as vehicle status, driver status, and external environment can be used by the lane-keeping assist system based on human–machine dynamic cooperative control, thereby smoothly changing the driving rights between the driver and the automatic controller. The system can keep the vehicle in the lane while complying with the driver's intention, thereby ensuring vehicle safety and driver comfort. The research status and future development suggestions on lane-departure decision models, dynamic allocation of driving rights, and performance evaluation were analyzed in this paper. Regarding lane-departure decision models, different decision models considering the driver's state should be developed. The decision model can be established as an adaptive adjustment model and also should allow the manual adjustment of the preset parameters according to the driver’s preferences and the external driving environment. Concerning the allocation of driving rights, a more reasonable dynamic allocation of driving rights should be explored, and intelligent optimization algorithms or control models should be designed. Regarding performance evaluation indicators, evaluation indicators related to the reduction of human–machine conflict and the amount of control effort should be added. A scientific and complete subjective evaluation system should be developed. Future studies on lane-keeping assist system based on human–machine cooperative control should deeply integrate driver factors, issue real-time warnings and active intervention, and perform complete testing and evaluation of the system.

     

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