Autonomous Vehicles: Skill Gaps in the U.S.A

Global Employability

If you haven’t been living on Mars for a while, you might have heard of Tesla’s self-driving electric vehicles. They are one of the most popular topics of discussion across the automotive industry and have been considered to be one of the foremost players when we speak about autonomous vehicles. With over 10 million people working in the autonomous vehicle industry across the U.S alone, it is quickly growing to be one of the largest sectors encompassing multiple technologies and expertises.

What are CAVs?

Connected and autonomous vehicles (CAV) is the term given to autonomous vehicles that are designed to be uber intelligent compared to the vehicles of today. These vehicles can automatically diagnose issues with the vehicles, provide state-of-the art assistance to drivers (including traffic monitoring, emergency alerts, drive assists and more), stay connected to a large network of connected vehicles to share information, can be controlled remotely by the owner (including and may even be capable of autonomous driving, that is, there needn’t be a driver! Of course, driverless cars aren’t all that advanced today – we still don’t have completely autonomous vehicles on our streets. However, it is estimated that by 2030, around 30% of all car sales will be autonomous vehicles.

In order to be a part of this rapidly burgeoning industry, one must pick up skills that are must-haves! The rapidly changing ecosystem of CAVs has made constant upskilling the need of the hour. Some of the top skills that most employees lack are discussed below.

  • Cybersecurity
  • CAVs require workers to design vehicles that communicate with each other efficiently and in a secure manner. This means that cybersecurity experts are required to come up with robust protocols that control how data is transmitted from one vehicle to another and to road side units. Those who have the relevant set of skills in cloud security, ethical hacking, network security, and have knowledge about security laws and regulations are the need of the hour.

  • Design, development, and testing
  • By now, it must be clear that CAVs require a lot of technical modules to help it run without hiccups. Various software needs to be designed and developed for deployment in CAVs including vehicle diagnostics, GPS, vehicle information display etc. These also have to be tested to make them foolproof since CAVs are being designed to work without the need for human interference. Learning programming languages like Java, Python and C, understanding how testing works, and learning to use testing tools like Selenium, TestingWhiz and HPE are some of the ways in which one could get into design and testing.

  • Manufacturing at assembly lines and manual operations
  • Skilled workers are required for the manufacturing processes of CAVs. As the demand increases, the number of vehicles that need to be manufactured increases as well, which will require a lot of workers along the assembly lines. Assembly line workers are required to know how the various machinery works, understand logistics, have good communication skills, ability to interpret documentation, and possess physical fitness.

  • Artificial Intelligence and Machine Learning
  • Artificial intelligence and machine learning are employed in CAVs to improve the overall experience of the users. AI is employed for optimized route selection and traffic management functions, imaging, data processing, connectivity, and data management.

    Computer vision is a part of artificial intelligence that helps computers to “see” images just like humans. Computer vision processes digital images, videos and other media to derive information based on which actions can be performed. Computer vision experts are in huge demand across the CAV industry currently.

  • Network design
  • Network protocols and devices enable seamless communication in CAVs, which depend on wireless communication technologies to exchange traffic information, vehicle information, and to exchange safety services. Network design of the most overlooked skills in CAVs is the ability to design network protocols, and to design and develop the necessary infrastructure that enables good communication. One must be familiar with network design, networking hardware, protocol design, and simulation of networks using digital tools (because simulation helps to understand how a network may behave in the real world).

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Global Employability


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