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Artificial Intelligence (AI) and Autonomous Vehicles

2022-10-12
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Artificial Intelligence and Autonomous Vehicles
Illustration: © IoT For All

Artificial Intelligence (AI) is the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. It involves the development of systems endowed with human intellectual characteristics, such as the ability to reason. In our 21st-century world, digital technologies such as Artificial Intelligence (AI) and Machine Learning (ML) have taken center stage and are blazing the trail by changing the traditional way of doing business. Today with the aid of neural networks and intelligent algorithms, AI technology is replacing human thinking ability with machine control and is doing so with greater accuracy and precision, a development that was thought impossible a few years back. Let’s take a look at the role of AI and autonomous vehicles and how this technology will shape the future.

'It is expected that the combination of blockchain technology and self-driving cars will create a far better autonomous system.' -Jude ChukwudozieClick To Tweet

Autonomous Vehicle Benefits

The American computer scientist Eliezer Yudkowsky argues that by far the greatest danger about artificial intelligence is that people conclude too early that they understand it. In truth, most people don’t. For the record, AI and cars have a mutual history, and it was the dream of scientists to create intelligent machines that could think and act for themselves which gave birth to autonomous vehicles, or self-driving cars, which have turned out to become one of the best innovations of AI technology. Let’s dive into some of the benefits of these vehicles.

#1: Detection Algorithms

Autonomous vehicles have neural networks and specific algorithms. These are Artificial Intelligence (AI) and Machine Language (ML) based object detection algorithms. These serve to collect data, analyze objects, and make accurate decisions while on the road. These features also enable these intelligent machines to provide solutions to problems occurring in advance of real time by predicting events through the swift processing of data.

For example, autonomous vehicles can predict a potential threat like a car collision ahead or behind and take a decision in real time to avert it. With good data collection sensors, these pieces of information are processed and results are obtained as actions. In addition to the neural network and specific algorithms, self-driving cars have five core components that help them optimize operation in real time, namely: computer vision, sensor fusion, localization, path planning, and control. They also have an enhanced degree of AI perception technology for detecting pedestrians, vehicles, cyclists, and work and obstacles that are 300 yards away. These embedded algorithms help these automobiles to determine and suggest alternative routes based on real-time traffic conditions. Indeed, an amazing technology.

#2: Autopilots

Quite recently, Tesla manufactured electric cars that are self-driving and equipped with autopilots to enable automatic steering, accelerating braking, lane changing, and parking actions. Added to these features is the fact that these cars have the potential to reduce emissions globally, a milestone achievement from fuel-driven vehicles. Today, autonomous vehicles can be found in some of the biggest cities of the world. Even heavy-duty trucks without drivers that can deliver goods over long distances have been manufactured. This has not only reduced transportation costs significantly but also reduced the loss of human lives through accidents, much of which arise from human errors.

#3: AI-enhanced Features

In recent times, some automotive companies have manufactured autonomous vehicles with enhanced AI features like personal AI assistants, radar detectors, and cameras, all of which serve to prioritize security among other functions. These self-driving cars have implemented AI-enhanced features which are a huge advancement over their predecessors. Self-driving can learn about traits exhibited by the driver like driving speed, preferred car temperature, driving mood, observance of traffic signs, regular songs, or favorite radio stations. By rating driving skills, these autonomous vehicles have helped to change bad driving behaviors and habits.

Autonomous Vehicle Drawbacks

Though one of the most anticipated technologies in this century, AI and autonomous vehicles have been associated with a number of problems:

  • Autonomous vehicles are limited to more narrow situations and clearer weather. Just like the human eyes, sensors do not do well in fog, rain, or snow.
  • Autonomous vehicles rely on maps and sensors to function effectively. Unfortunately, these maps have limited test areas at the moment. Creating and maintaining maps for self-driving cars is a difficult and time-intensive process and one that is yet to happen. Its test areas will also need to be increased. In the U.S. for instance, detailed maps would have to be built and maintained across the 4 million miles of public road and this is no small task.
  • Tesla’s self-driving cars have raised certain safety concerns. In a certain L.A. Times editorial, they are said to be, “crossing double yellow lines and heading toward oncoming traffic, failing to stop for cars crossing the street and steering toward metal posts and roadside boulders.”
  • Autonomous vehicles controlled by AI robots cannot engage in complex social interactions with other drivers, cyclists, and pedestrians. These situations require generalized intelligence and common sense to navigate, qualities that robots do not possess at the moment.
  • Tesla’s autopilot has a problem detecting flashing lights, road cones put in place for temporary road and traffic maintenance, and most emergency vehicles traveling in the opposite direction. Again, most of the crashes happen in the dark which points to an apparent flaw in the autopilot technology.
  • The working mechanism of smarter and more connected autonomous vehicles can suffer from cyber attacks which would disrupt their systems and operational processes. When this happens, commuter stress, delayed traffic flow, collisions, accidents, and even loss of human lives become inevitable.
  • Tesla’s advanced driver assistance system (ADAS), otherwise known as autopilot, accounts for a number of crashes and fatalities in the U.S. In most cases, it has been found to shut off around one second before the crash.

Path to the Future

In the crypto world, blockchain technology makes use of mathematical logic and algorithm to create an autonomous system that is both transparent and immutable. Here in the automotive world, it is expected that the combination of blockchain technology and self-driving cars will create a far better autonomous system that would increase the transparency and accuracy of decisions made by these cars.

Car tech giants are working hard to implement natural conversational AI within vehicles, which will utilize speech recognition, natural language understanding, speech synthesis, and smart avatars to boost comprehension of context, emotion, complex sentences, and user preferences. In the future, AI will be engaged in improving vehicle safety, performance, and efficiency, addressing health hazards and environmental issues. It could also be used to create cars that can communicate with each other and with other road users.

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  • Artificial Intelligence
  • Autonomous Vehicles
  • Blockchain
  • Machine Learning
  • Sensors

  • Artificial Intelligence
  • Autonomous Vehicles
  • Blockchain
  • Machine Learning
  • Sensors

参考译文
人工智能(AI)和自动驾驶汽车
人工智能(AI)是指数字计算机或计算机控制的机器人执行通常与智能生物相关的任务的能力。它涉及到具有人类智力特征的系统的发展,例如推理能力。在21世纪的世界中,人工智能(AI)和机器学习(ML)等数字技术已经占据了舞台中央,并正在通过改变传统的经营方式开辟道路。今天,在神经网络和智能算法的帮助下,人工智能技术正在用机器控制取代人类的思维能力,而且准确率和精确度更高,这在几年前被认为是不可能的。让我们来看看人工智能和自动驾驶汽车的作用,以及这项技术将如何塑造未来。美国计算机科学家埃利泽·尤德科夫斯基(Eliezer Yudkowsky)认为,迄今为止,人工智能最大的危险是人们过早地得出结论,认为自己了解它。事实上,大多数人都不知道。郑重声明,人工智能和汽车有一段共同的历史,科学家的梦想是创造能够自己思考和行动的智能机器,这催生了自动驾驶汽车,这已经成为人工智能技术的最佳创新之一。让我们来探讨一下这些交通工具的一些好处。自动驾驶汽车有神经网络和特定的算法。它们是基于人工智能(AI)和机器语言(ML)的对象检测算法。这些功能用于收集数据,分析对象,并在路上做出准确的决定。这些功能还使这些智能机器能够通过快速处理数据预测事件,为实时发生的问题提前提供解决方案。例如,自动驾驶汽车可以预测前方或后方的潜在威胁,如汽车碰撞,并实时作出决定以避免它。有了良好的数据收集传感器,这些信息片段将被处理并作为动作获得结果。除了神经网络和特定算法,自动驾驶汽车还有五个核心组件,帮助它们实时优化操作,即:计算机视觉、传感器融合、定位、路径规划和控制。它们还拥有更高程度的人工智能感知技术,可以探测300码外的行人、车辆、骑自行车的人、工作和障碍。这些嵌入式算法帮助这些汽车根据实时交通状况确定和建议替代路线。的确,这是一项惊人的技术。最近,特斯拉生产了自动驾驶的电动汽车,并配备了自动驾驶仪,以实现自动转向、加速制动、变道和停车操作。除了这些特点之外,这些汽车还有减少全球排放的潜力,这是燃料驱动汽车的一个里程碑成就。今天,自动驾驶汽车可以在世界上的一些大城市找到。甚至无人驾驶的重型卡车也被制造出来,可以远距离运送货物。这不仅大大降低了运输成本,而且还减少了事故造成的人员伤亡,其中许多事故是由人为错误造成的。最近,一些汽车公司生产的自动驾驶汽车具有增强的人工智能功能,如个人人工智能助手、雷达探测器和摄像头,所有这些功能都优先考虑安全。这些自动驾驶汽车采用了人工智能增强的功能,这比之前的汽车有了巨大的进步。自动驾驶可以了解司机表现出的特征,如驾驶速度、喜欢的汽车温度、驾驶情绪、遵守交通标志、定期播放的歌曲或最喜欢的广播电台。通过对驾驶技能进行评级,这些自动驾驶汽车帮助人们改变了不良的驾驶行为和习惯。 虽然人工智能和自动驾驶汽车是本世纪最受期待的技术之一,但它与许多问题有关:在加密世界中,区块链技术利用数学逻辑和算法创建了一个透明且不可变的自动系统。在汽车领域,区块链技术和自动驾驶汽车的结合有望创造出一个更好的自动驾驶系统,提高这些汽车所做决定的透明度和准确性。汽车科技巨头正在努力在车内实现自然对话AI,它将利用语音识别、自然语言理解、语音合成和智能化身来提高对上下文、情感、复杂句子和用户偏好的理解。未来,人工智能将致力于提高车辆的安全性、性能和效率,解决健康危害和环境问题。它还可以用来制造可以相互沟通的汽车,以及与其他道路使用者沟通的汽车。
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