《2026年水木金卷高考模拟试卷精编英语》

C
"More and more data are made available to drivers through in-vehicle systems. However, it's not safe or practical to inform drivers of the information unless you know the state of the driver," said Dr Bashar Ahmad from Cambridge's Department of Engineering.
Ahmad, together with other researchers, developed an algorithm(算法) to address this problem. The algorithm analyzes factors like the driver's behaviour and road conditions to measure the driver's workload so that the driver and the in-vehicle systems such as navigation system and advanced driver assistance system (ADAS) can interact at the right time. "Driving in an unfamiliar area may mean a high workload, so we should avoid flustering the driver then, while driving in our neighborhood may involve a lower workload, making it the right time for a message to appear on a screen," said Ahmad.
To measure drivers' workload, the researchers first collected, in an automated way, drivers' subjective workload information during driving. For the experiment, a phone showing a route on a navigation app was fixed to the car, next to a small LED ring light that would flash at regular periods. Participants all followed the same route through a mix of rural, urban and main roads. They were asked to push a finger-worn button whenever the LED light turned red and they perceived they were in a low-workload situation.
Video analysis of the experiment, paired with the data from the buttons, allowed the researchers to identify high-workload situations. The researchers used the on-road data to develop a machine learning framework to assess drivers based on their average workload, and a Bayesian filtering approach(贝叶斯滤波法) to estimate the drivers' real-time workload.
"Most machine learning applications like this are trained on data from a particular driver, but this application enables us to adjust the models accordingly using a simple Bayesian filtering technique," said Ahmad. "It can easily adjust to different road types and conditions, or different drivers using the same car."
"This research is vital for understanding the impact of our design from a user's perspective, so that we can continually improve safety and driving experiences," said Senior Technical Specialist Dr Lee Skrypchuk.
46. What is the main function of Ahmad's algorithm?
A. Assessing people's driving skills.
B. Stimulating drivers' best driving state.
C. Collecting traffic information from surrounding areas.
D. Finding the appropriate time for driver-vehicle interactions.
47. What does the underlined word "flustering" in Paragraph 2 mean?
A. Blaming.
B. Monitoring.
C. Disturbing.
D. Restricting.
48. What did pressing a finger-worn button indicate in the experiment?
A. The driver requested a speed increase.
B. The driver was in a relaxed driving state.
C. The driver had switched on the headlights.
D. The driver encountered complex road conditions.
49. What distinguishes this machine learning application from many others?
A. It is highly adaptable.
B. It is of amazing accuracy.
C. It needs simple data processing.
D. It is limited to specific drivers.
50. Which can be the best title for the passage?
A. Machine Learning for Improving Road Safety
B. ADAS: A Model for Future Autonomous Driving
C. The Wide Application of New In-Vehicle Systems
D. Autonomous Vehicles: Redefining the Driving Experience

答案： 46.D细节理解题。题干意为：Ahmad的算法的主要功能是什么？根据第二段中“Thealgorithmanalyzes...tomeasurethedriver’sworkloadsothatthedriverandthein-vehiclesystems...caninteractattherighttime.”可知，Ahmad的算法的主要功能是找到驾驶员与车辆进行交互的合适时间。故选D。
47.C词义猜测题。题干意为：第二段中的画线单词“flustering”是什么意思？根据画线单词所在句中“while”和“drivinginourneighborhoodmayinvolvelowerworkload,makingittherighttimeforamessagetoappearonascreen”可知，上下文之间为转折关系，下文提到在附近驾驶意味着工作负荷较低，是屏幕上出现信息的合适时机，由此可推知，上文应是指在不熟悉的地区驾驶可能意味着工作负荷很大，所以要避免打扰驾驶员。所以，flustering意为“打扰”，与“disturbing”意义相近。故选C。
48.B细节理解题。题干意为：在实验中，按下手指佩戴的按钮表明什么？根据第三段中“Theywereaskedtopushafinger-wornbuttonwhenever...theyperceivedtheywereinalow-workloadsituation.”可知，在实验中，按下手指佩戴的按钮表明驾驶员处于低工作负荷状态，即放松的驾驶状态。故选B。
49.A细节理解题。题干意为：这个机器学习程序与许多其他程序的不同之处是什么？根据倒数第二段中“thisapplicationenablesustoadjustthemodelsaccordinglyusingasimpleBayesianfilteringtechnique”和“Itcaneasilyadjusttodifferentroadtypesandconditions,ordifferentdriversusingthesamecar.”可知，与其他程序相比，这一程序可以使用简单的贝叶斯滤波技术调节模型，而且它可以很容易地适应不同的道路类型和路况，或是不同的驾驶员。由此可知，该程序与许多其他程序的不同之处在于它具有很高的适应性。故选A。
50.A标题归纳题。题干意为：哪一项可以是这篇文章的最佳标题？通读全文，并根据第二段中“Ahmad,togetherwithotherresearchers,developedanalgorithm(算法)toaddressthisproblem.”可知，文章主要介绍了Ahmad等研究人员开发了一种机器学习程序来确定驾驶员与车载系统交互的最佳时间，以提高驾驶安全性和体验。所以，A项“用于提高道路安全的机器学习”是本文的最佳标题。故选A。