交通安全|【中英文】IIHS对自动驾驶的灵魂拷问,比人更安全吗?( 二 )
IIHS研究专家 , 同时也是该项研究的主要作者Alexandra Mueller说:“ 自动驾驶想达到人类驾驶水平本身就是巨大的挑战 。 ”“实际上需要超越人类 , 才能达到减少事故的目标 。 ”
To estimate how many crashes might continue to occur if self-driving cars are designed to make the same decisions about risk that humans do, IIHS researchers examined more than 5,000 police-reported crashes from the National Motor Vehicle Crash Causation Survey. Collected by the National Highway Traffic Safety Administration, this sample is representative of crashes across the U.S. in which at least one vehicle was towed away, and emergency medical services were called to the scene.
如果自动驾驶汽车能像人类一样对风险做出预判 , 还会发生多少起事故呢?为了估算这一数值 , IIHS的研究人员对全国机动车事故原因调查中5000多起警方报告的事故进行了调查 。 该样本由NHTSA(美国公路交通安全管理局)收集 , 针对的是美国各地发生的至少一辆车被拖走 , 并且紧急医疗服务人员被派往现场的车祸事故 。
The IIHS team reviewed the case files and separated the driver-related factors that contributed to the crashes into five categories:
IIHS小组审查了案件档案 , 并将导致车祸的驾驶员相关因素分为五类:【交通安全|【中英文】IIHS对自动驾驶的灵魂拷问,比人更安全吗?】
- “Sensing and perceiving” errors included things like driver distraction, impeded visibility and failing to recognize hazards before it was too late.
- “Predicting” errors occurred when drivers misjudged a gap in traffic, incorrectly estimated how fast another vehicle was going or made an incorrect assumption about what another road user was going to do.
- “Planning and deciding” errors included driving too fast or too slow for the road conditions, driving aggressively or leaving too little following distance from the vehicle ahead.
- “Execution and performance” errors included inadequate or incorrect evasive maneuvers, overcompensation and other mistakes in controlling the vehicle.
- “Incapacitation” involved impairment due to alcohol or drug use, medical problems or falling asleep at the wheel.
- “感知”错误: 驾驶员分心、视线受阻和未及时发现危险等 。
- “判断”错误: 错估另外一辆车的速度、方向变化和行车间隙 。
- “决策”错误: 车速太快或太慢、驾驶情绪过激或与前方车辆跟车距离太小 。
- “执行”错误: 规避不充分或不正确、过度补偿和其他驾驶操作层面的错误 。
- “丧失驾驶能力”: 因酒精、毒品、药物等导致驾驶员能力受损的情况 。
研究人员还表明 , 有些事故是不可避免的 , 比如那些由于车辆故障造成的(如爆胎或车轴断裂) 。
For the study, the researchers imagined a future in which all the vehicles on the road are self-driving. They assumed these future vehicles would prevent those crashes that were caused exclusively by perception errors or involved an incapacitated driver. That’s because cameras and sensors of fully autonomous vehicles could be expected to monitor the roadway and identify potential hazards better than a human driver and be incapable of distraction or incapacitation.
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