The message couldn’t be clearer: don’t drive under the influence of alcohol or drugs. Yet people still put themselves and others in danger by getting behind the wheel while intoxicated. Despite decades of education programmes and law enforcement, road collisions attributable to intoxicated driving remain unacceptably high. We need a better approach and we are in the middle of a technological boom that may just deliver one.

    “切勿在飲酒或服藥后駕車”，這道理再淺顯不過，但總有些人罔顧自身與他人安危，以身試法。數(shù)十年來，交通安全方面的教育與執(zhí)法并舉，但因酒駕造成的交通事故率仍居高不下，令人不滿。道路交通亟待更有效的安全措施，科學(xué)技術(shù)的蓬勃發(fā)展或許能獻(xiàn)上一計。

Seat belts and airbags have dramatically reduced the number of lives lost on roads. However, they do little to prevent the cause of crashes. Someone dies every 25 seconds globally due to road traffic injuries, and one in five of the drivers involved will test positive for alcohol following the collision.

     安全帶和安全氣囊極大地減少了道路交通事故中的死亡人數(shù)，但就預(yù)防車禍而言，它們能起到的作用微乎其微。全球每25秒就有一人死于道路交通傷害，其中五分之一的肇事司機(jī)在隨后的酒精檢測中呈陽性。

Some cars already have intelligent driver monitoring systems that help to reduce deaths by human error, such as inattention. These use cameras to monitor drivers’ alertness. When there is a deviation from the behaviour it has been trained to recognize, such a system can either warn the driver or take complete control of the vehicle to stop a collision from occurring. These systems may reduce collisions by up to 20 per cent.

     目前，一些車輛已配備駕駛員智能監(jiān)控系統(tǒng)，可減少因注意力不集中等人為過失造成的事故死亡。這些汽車內(nèi)設(shè)攝像頭，可監(jiān)控駕駛員是否保持行車警覺性。若監(jiān)控識別到系統(tǒng)外的駕駛行為，可向駕駛員發(fā)出警報，或完全控制駕駛以避免碰撞發(fā)生。裝有該系統(tǒng)的車輛能將碰撞率減少20%。

Now, a second wave of intelligent driver monitoring technology is on its way. Internal cameras can be combined with other biometric sensors, such as heart rate monitoring or skin conductibility, to determine a driver’s internal state in real time. In other words, a car could determine when its driver is impaired by drugs or alcohol.

    現(xiàn)在，新一代駕駛員智能監(jiān)控技術(shù)正在研發(fā)之中。車內(nèi)攝像頭將與其他生物傳感設(shè)備結(jié)合，如心率檢測、皮膚傳感器等，以便實(shí)時確認(rèn)駕駛員的身體情況。換句話說，車輛本身就可以判斷駕駛員是否受到藥物或酒精的影響。

These technologies can already spot certain behaviours that are hallmark features of intoxication. For example, alcohol significantly impairs alertness and attentiveness, which such systems can detect, and the more someone drinks, the more pronounced these effects are.

    這類技術(shù)現(xiàn)已能識別出酒駕的部分典型表現(xiàn)。比如，飲酒后人的警覺性和注意力大幅下降，飲酒量越大，受影響越顯著，這些都能被系統(tǒng)識別到。

Therefore, it might be possible to retrain such systems to identify and monitor the individual “impairment signature” for a range of other substances that are known to negatively affect driving. Creating individual profiles will help to differentiate between a driver who has taken legal prescription drugs needed to treat a medical condition and someone who has consumed illegal drugs. Ideally, this information would be used to automatically block the person from driving.

    因此，未來很可能對系統(tǒng)進(jìn)行更新訓(xùn)練，就已知對行車有負(fù)面影響的物質(zhì)進(jìn)行識別和監(jiān)控，形成駕駛員個人化的特征檔案。個人檔案的創(chuàng)建將有助于區(qū)分藥物影響，有的駕駛員服用的是治療疾病的合法處方藥，而有的則使用了違禁藥品。理想情況下，這些數(shù)據(jù)會被用來自動阻止某些駕駛員行車。

選編自New Scientist International Edition, September 5th 2020