Active Deceleration Support in Car Following
Active Deceleration Support in Car Following
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跟车中的主动减速支持
DOI：
10.1109/tsmca.2010.2044998
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发表时间：
2010
期刊：
影响因子：
--
通讯作者：
D. Abbink
中科院分区：
文献类型：
--
作者：
M. Mulder;J. Pauwelussen;R. V. Paassen;M. Mulder;D. Abbink
开发了一种触觉油门踏板反馈系统，该系统通过来自油门踏板的触觉提示提供车辆跟随信息。在正常的汽车跟随情况下，触觉反馈（HF）线索足以减少控制活动，提高汽车跟随性能。然而，在更关键的情况下，驾驶员使用制动踏板来保持与前车的分离。减速控制（DC）算法被设计为除了HF之外，在车辆跟随情况期间在释放油门踏板时提供增加的减速，所述车辆跟随情况需要比单独释放油门踏板更快的减速。在设计中，根据驾驶模拟器数据估计了在不同情况下车辆跟随的驾驶员模型。对驾驶员模型的蒙特卡罗分析得出了主观决策点，即驾驶员松开油门踏板开始踩刹车。这使得能够定义反应场，从而确定DC算法所需的减速输入。在固定基座驾驶模拟器实验中测试了调谐DC算法。结果表明，主动减速支持改善了车辆跟随性能，同时减少了驾驶员制动踏板输入幅度的条件下测试。
A haptic gas pedal feedback system is developed that provides car-following information via haptic cues from the gas pedal. During normal car-following situations, the haptic feedback (HF) cues were sufficient to reduce control activity and improve car-following performance. However, in more critical following situations, drivers use the brake pedal to maintain separation with the lead vehicle. A deceleration control (DC) algorithm is designed that, in addition to the HF, provided increased deceleration upon release of the gas pedal during car-following situations that required faster deceleration than releasing the gas pedal alone would do. For the design, a driver model for car following in different situations was estimated from driving simulator data. A Monte Carlo analysis with the driver model yielded subjective decision points, where drivers released the gas pedal to start pressing the brakes. This enabled the definition of a reaction field, which determined the needed deceleration input for the DC algorithm. The tuned DC algorithm was tested in a fixed-base driving simulator experiment. It was shown that the active deceleration support improved the car-following performance while reducing the driver brake pedal input magnitude in the conditions tested.