基于句法模式的连续驾驶意图识别

Mohd Nizam Husen, Sukhan Lee
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引用次数: 3

摘要

随着道路交通事故伤亡人数的增加,智能驾驶辅助系统正在成为每辆未来汽车的必需品。在汽车上安装各种各样的传感器可以用来检测驾驶员的意图,以提高安全性。本文采用上下文无关语法的句法识别方法,对汽车驾驶员变道和转弯行为的行为模式识别进行了分析。驾驶数据,包括驾驶员的眼神注视;汽车的速度、方向盘角度、信号指示;以符号形式表示,从而形成代表特定行为的句子。语法是基于从训练数据中训练出来的句子来制定的。然后通过解析测试数据来评估语法。结果表明,在驾驶机动行为开始后不到0.5秒的时间内,驾驶行为就被正确检测出来,识别率达到90%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Continuous Car Driving intention recognition with syntactic pattern approach
Intelligent driver assistance systems are becoming a necessity in every future cars with the increased of injuries and fatalities from road accidents. The implementation of a wide array of sensors in a car could be utilised to detect driver's intention to improve safety. This paper present an analysis of car driver's behaviour pattern recognition in lane changes and turns behaviour using context-free grammar in syntactic recognition approach. The driving data which consists of the driver's eye gaze; the car's speed, steering wheel angle, and signal indication; are represented in symbolic form thus forming sentences which represent a specific behaviour. Grammars are formulated based on the sentences trained from training data. The grammars are then evaluated by parsing the testing data. The results shows that driving behaviours are correctly detected at 90% recognition rate from less than 0.5 seconds after a driving maneuver behaviour commenced.
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