机器人司机应该比人类更安全。我们期望从配备传感器的机器中获益,这些传感器能够对周围环境提供广阔的,敏锐的,毫不动摇的感知,对前方可能路径进行认真分析的处理器以及能够快速准确地执行计划机动的执行器。当然,机器人有时可能会崩溃:例如,在传感器被雪弄糊涂而处理器被车辆,骑自行车者和行人组成的混合物征税时,突然有一只狗突然溜到湿滑的街道上,就像一个陌生的,难以识别的物体落到了人行道上,最终压倒了机器人的能力。但是,我们希望这种无可避免的崩溃几乎不会发生。自行驾驶的测试车辆在3月18日晚上发生的致命事故并不符合该描述。亚利桑那州坦佩市的天空很清晰,路面宽阔,没有交通,路灯照亮了路面;但不知怎的,机器人司机并没有设法避开一名女子在米尔大道穿越她的自行车。据警方透露,这辆来自Uber公司的试车队没有试图制动。人的后备“安全驾驶员”未能纠正车辆的轨迹;它以38英里/小时的速度击中了Elaine Herzberg。她后来在医院因伤死亡。在向旧金山纪事报发表讲话时,Tempe警察总监Sylvia Moir强调了Herzberg女士“如何从阴影中走出来进入公路”。这个故事在事故发生后三天得到了支持,当时警方发布了一个低质量的摄像机视频,给人一种令人产生误导的压迫黑暗条件的印象。但即使在完全黑暗中,道路被遮挡了,车辆配备了可在“黑暗中看到”的激光雷达 – 传感器发出自己的红外光。尽管如此,可以肯定的是,国家运输安全委员会仍在调查中 – 如果自动驾驶车辆仅仅是一名合格的驾驶员,Herzberg女士今天依然活着。那么,优步的崩溃是技术的一个可悲的失败。但是矛盾的是,它也可以提醒人们,安全机器人驾驶员比他们看起来更近距离 – 只要技术的开发者选择安全作为首要优先事项。无可否认,技术进步可能是漫长的道路,机器人具有惊人的驾驶技术,但这不是通向安全机器人驾驶员的唯一途径。还有另一条路线;也许不那么壮观,但更直接。

加拿大渥太华大学Assignment代写:驾驶方式

Robot drivers are supposed to be safer than humans. We would expect no less from machines equipped with sensors that afford expansive, acute, and unwavering perception of their surroundings, processors that meticulously analyze the possible paths ahead, and actuators that quickly and precisely execute the planned maneuvers. Sure, a robot might crash on occasion: say in a situation where the sensors are confused by snow and the processors are taxed by a mix of vehicles, cyclists, and pedestrians moving unpredictably, when suddenly a dog darts out onto the slippery street just as an unfamiliar, hard-to-identify object falls onto the pavement, finally overwhelming the robot’s capabilities. But we would hope that such all-but-unavoidable crashes would be few and far between. The fatal crash of a self-driving test vehicle on the night of March 18 did not fit that description. The sky in Tempe, Arizona was clear, the road was wide and free of traffic, streetlights illuminated the road; yet somehow, the robot driver did not manage to avoid a woman walking with her bicycle across Mill Avenue. The vehicle, from the test fleet of ride-hailing company Uber, made no attempt to brake, according to police. The human backup “safety driver” failed to correct the vehicle’s trajectory; it struck Elaine Herzberg at a speed of 38 mph. She died of her injuries later in hospital. Speaking to the San Francisco Chronicle, Tempe Chief of Police Sylvia Moir emphasized how Ms. Herzberg “came from the shadows right into the roadway”; this narrative was bolstered three days after the crash when the police released a low-quality dashcam video that gave a misleading impression of oppressively dark conditions. But even had the road been obscured in total darkness, the vehicle was outfitted with lidar, which can “see in the dark” — the sensor emits its own infrared light. By all appearances — though, to be sure, the National Transportation Safety Board is still investigating — Ms. Herzberg would still be alive today if the automated vehicle had been a merely competent driver. The Uber crash, then, was a miserable failure of technology. But paradoxically, it can also serve as a reminder that safe robot drivers are within closer reach than they may appear — as long as developers of the technology choose safety as the overriding priority. Admittedly, it may be a long road of technological advancements to a point where robots have prodigious driving skills, but that isn’t the only path to safe robot drivers. There is another route; perhaps less spectacular, but more direct.

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