Question

【题目】 Self-driving cars have been backed by the hope that they will save lives by getting involved in fewer crashes with fewer injuries and deaths than human-driven cars. But so far， most comparisons between human drivers and automated vehicles have been unfair.

Crash statistics for human-driven cars are gathered from all sorts of driving situations， and on all types of roads. However， most of the data on self-driving cars' safety have been recorded often in good weather and on highways， where the most important tasks are staying in the car's own lane and not getting too close to the vehicle ahead. Automated cars are good at those tasks， but so are humans.

It is true that self-driving cars don't get tired， angry， frustrated or drunk. But neither can they yet react to uncertain situations with the same skill or anticipation of an attentive human driver. Nor do they possess the foresight to avoid potential perils. They largely drive from moment to moment，rather than think ahead to possible events literally down the road.

To a self-driving car， a bus full of people might appear quite similar to an uninhabited corn field. Indeed， deciding what action to take in an emergency is difficult for humans， but drivers have sacrificed themselves for the greater good of others. An automated system’s limited understanding of the world means it will almost never evaluate(评估) a situation the same way a human would. And machines can't be programmed in advance to handle every imaginable set of events.

Some people may argue that the promise of simply reducing the number of injuries and deaths is enough to support driverless cars. But experience from aviation(航空) shows that as new automated systems are introduced， there is often an increase in the rate of disasters.

Therefore comparisons between humans and automated vehicles have to be performed carefully. To fairly evaluate driverless cars on how well they fulfill their promise of improved safety， it's important to ensure the data being presented actually provide a true comparison. After all，choosing to replace humans with automation has more effects than simply a one-for-one exchange.

【1】What makes the comparison between self-driving cars and human-driven cars unfair?

A.Self-driving cars never get tired.B.Statistics are collected differently.

C.Machines can make decisions faster.D.Self-driving cars know the world better.

【2】What does the underlined word “perils” in Paragraph 3 most probably mean?

A.Dangers.B.Self-driving cars.

C.Pedestrians.D.Human-driven cars.

【3】In which aspect can self-driving cars beat human-driven cars?

A.Driving steadily.B.Climbing steep slopes.

C.Evaluating the cost of loss.D.Making complex decisions.

【4】Why does the author write this text?

A.To support human-driven cars.

B.To show his doubt about self-driving cars.

C.To call for exact evaluation of self-driving cars.

D.To stress the importance of reducing car accidents.

Answer 1

【答案】

【1】B

【2】A

【3】A

【4】C

【解析】

这是一篇说明文。不同的数据记录方式使得人为驾驶和自动驾驶的比较是不公平的，人类和自动化车辆之间的比较必须谨慎进行。

【1】细节理解题。根据第二段中Crash statistics for human-driven cars are gathered from all sorts of driving situations， and on all types of roads. However， most of the data on self-driving cars' safety have been recorded often in good weather and on highways.可知，人为驾驶的车祸统计数据来自于各种驾驶情况和在各种类型的道路上。然而，大多数关于自动驾驶汽车安全性的数据经常是在好天气和在高速公路上行驶的情况下记录的，因此统计数据的收集方式不同。故选B项。

【2】词义猜测题。根据后文They largely drive from moment to moment，rather than think ahead to possible events literally down the road.可知，自动驾驶车辆不会提前考虑可能发生的事件。这说明所以它们不会避免潜在的危险（danger），故选A项。

【3】推理判断题。根据第三段第一句It is true that self-driving cars don't get tired， angry， frustrated or drunk.可知，自动驾驶汽车不会感到疲倦、愤怒、沮丧或喝醉，所以会比人类平稳。故选A项。

【4】推理判断题。根据最后一段Therefore comparisons between humans and automated vehicles have to be performed carefully. To fairly evaluate driverless cars on how well they fulfill their promise of improved safety， it's important to ensure the data being presented actually provide a true comparison.可知，作者认为人类和自动化车辆之间的比较必须谨慎进行。要评估无人驾驶汽车在履行承诺改进安全方面表现的如何，确保提供的数据可以提供一个真正的比较是很重要的。所以作者写这篇文章是为了呼吁对自动驾驶汽车进行准确的评估。故选C项。