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AI Use Cases

A collection of over 250 uses for artificial intelligence

A continually updated list exploring how different types of AI are used across various industries and AI disciplines,including generative AI use cases, banking AI use cases, AI use cases in healthcare, AI use cases in government, AI use cases in insurance, and more

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Autonomous vehicles

Introduction

AI, ML, and Robotics have become the most promising technologies of the third millennium. There is no other sector which has been affected by these technologies as much as the transportation sector and especially the development of autonomous vehicles. This type of vehicle also known as the autonomous vehicle or self-driving car integrates AI and ML algorithms along with the robotics to perform its task. These are vehicles which have the ability to perceive their environment and move on their own. Such revolution in the transport industry has not happened overnight, it has taken years of development, numerous tests and the global efforts to make transport more effective and safe.

Challenges

There are however several hurdles that have to be addressed before AVs can be fully integrated into our society. First, the technology that is used in the process is very sophisticated and as such, it needs a lot of data to learn and predict. Second, there are fundamental safety issues. The autonomous vehicles have to be able to handle the conditions that are not planned for them as well or even better than the conditions that are expected of them by a human driver. Third, legal and regulatory structures are yet to catch up with the technology thus creating a condition of ambiguity regarding ownership and insurance. Fourth, the costs of developing and integrating such a system are also prohibitive. Last but not the least, there is a split opinion from the public regarding the use of AVs, including the issue of unemployment and trust in technology.

AI Solutions

There are solutions to these challenges that are provided by AI, ML, and Robotics. The state of the art AI and ML algorithms are capable of analyzing huge amount of data gathered from numerous sensors and cameras and thus enable the vehicle to develop a proper understanding of its surroundings and make decisions in real time. Some of the companies such as Waymo and Tesla has adopted the use of Deep Learning and Neural Networks to enhance the accuracy of these algorithms. Robotics is very vital in translating such decisions and actually maneuver the vehicle. This paper also shows how AI is also being applied to drive millions of virtual miles to improve the safety of the system. Also, AI could also help in cutting down on costs that are usually incurred in the development stage by enhancing efficiency and decreasing the need for physical testing.

Benefits

The advantages of using self-driving cars powered by Artificial Intelligence and Robotics are revolutionary. They have the potential of cutting down on the number of accidents that are caused by human mistakes thus making the roads safer. They can also help in the fight against traffic congestion and emissions by changing the driving behavior, which is positive for the environment. For the elderly and people with disabilities, it would be a way of getting around. In economic terms, they may cut the costs of transportation to the bare minimum, which in turn will result in the lowering of prices for various goods and services. Finally, it could take away the time that is usually used in driving to do something more useful or something that one may like to do.

Return on Investment

There are many reasons to invest in the autonomous vehicle technology and the return on investment (ROI) can be quite impressive. McKinsey & Company has predicted that by 2030, between 9% to 15% of new cars sold globally will be fully autonomous and this presents a massive market opportunity. This is especially true for companies such as Uber and Lyft who have identified self-driving cars as a way of becoming profitable in the future since they will not have to spend on drivers. Others such as GM and Ford have adopted AVs as strategic elements in their future strategies for the automotive industry. In the United States for instance, the National Highway Traffic Safety Administration has pointed out that the economic cost of car crashes in the country is $242 billion on an annual basis. In this way, autonomous vehicles have the potential of saving society a significant part of this cost through reducing accidents.

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