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引用次数: 0

摘要

本文提出了一种新的智能交通系统设计方法,该方法利用现有的交通系统智能技术和人类行为检测来对抗独狼威胁和驾驶员违规行为。该设计可以作为智能嵌入式系统附着在车辆上。在本设计中,使用脑电图分析技术来检测驾驶员行为的不规则性,将其分为威胁行为和侵犯行为。在发生故意碾压事故等威胁行为时,系统会尽快停车并通知安全机构以确保快速响应。在司机犯困等违规行为中,系统会根据危险程度提醒司机或通知相关部门并停车。为了最大限度地减少车辆快速停车的后果,建议将下一个交通灯标志变为绿色。通过将该系统应用于车辆,可以避免很多事故,特别是那些由孤狼造成的事故,如故意的车辆逃逸事故或车辆被盗。
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Novel design based Internet of Things to counter lone wolf, part-B: Berlin attack
This paper proposes a new design approach for intelligent transportation systems, which uses existing smart techniques in transportation systems and human behavior detections to counter lone wolf threats and driver violations. The design can be attached to vehicles as an intelligent embedded system. In this design, the electroencephalogram analyses techniques are used to detect the irregularity in driver behavior which can be categorized into threatened or violated behavior. In threaten behavior like deliberate run-over accidents, the system will stop the vehicle as soon as possible and inform the security agency to ensure a speed response. In violated behavior like driver drowsiness, the system will alert the driver or inform the responding authorities and stop the vehicle, depending on the level of danger. To minimize the consequences of the vehicle fast stopping, it is proposed to green the next traffic light signs. By applying this system in vehicles a lot of accidents can be avoided, in particular those caused by lonely wolves like deliberate runover accidents or stealing of vehicles.
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