A Small Business Owner’s Guide to Autonomous Vehicles

Autonomous vehicles are all set to change the way we view cars, driving, and business, but we are not 100% there yet. Fully automatic, self-driving vehicles are still not ready to take on the roads, but the technology in its early stages is already being implemented to some degree in modern vehicles. To know what the future holds for the transportation industry and also what options a small business owner has in 2020 for utilizing the available self-driving tech, read on.

Understanding the 6 Different Levels of Automation in Self-Driving Vehicles

To provide a simple idea of what’s going on and what is to be expected, let’s first clarify the concept of self-driven vehicles as they stand now. There are six different levels assigned to AI-powered vehicles, that range from AI-assisted driving to full-on automated AI-powered driving.

• Level 0: Similar to what it suggests, there are no qualifying levels of automation here, except perhaps emergency brakes
• Level 1: Also defined as driver assistance or assisted driving level 1, it features any ONE self-driving feature (adaptive cruise control)
• Level 2: Advanced Driver Assistance Systems (ADAS) can control the steering, as well as the brakes and gears, but only in the active presence of a human driver
• Level 3: Known asConditional Driving Automation. This is when the car is able to do everything mentioned in Level 3, alongside taking minor driving decisions on its own, such as changing lanes
• Level 4: Defined as High Driving Automation, Level 4 AI-driven cars offer almost full automation, but with severe limits on their maximum speed capacity and human overriding features
• Level 5: A concept of the future where even the presence of a human driver is not required and the car can take every necessary decision in any possible on-road scenario, all on its own

The Car and the Software Won’t Always Come in as a Bundle

As technology in the field begins to develop even further, a number of changes are expected down the line. For example, self-driving cars (hardware) and the self-driving algorithm (software) will initially be released as uniquely compatible bundles only, but propriety software-vehicle combos may not remain the only option. Similar to how smartphones and computers can be loaded and reloaded with separate Operating Systems, a smart car should be able to offer the same advantage eventually. This will, of course, add an element of choice in the autonomous vehicle segment for both private and commercial users.

SMEs and large enterprises alike will want the ability to switch software if they need to, without having to pay for the hardware again. This is of immense importance to any company within the transportation industry, which stands to benefit the most from adopting autonomous vehicles. If something goes wrong, or in case the company is not satisfied by the AI-driving application, they should not have to pay for a whole new fleet and equipment altogether, whether they can actually afford to do so or not.

For example, a company that owns fifty autonomous delivery trucks cannot be expected to buy fifty new trucks just for a change of software. That would not make any business sense, which is why flexibility and universal compatibility aspects will come into play soon afterward, if not immediately in the commercial self-driving vehicles industry.

The difference in Driving AI: Commercial Vs. Private Vehicles

There are certain, very clear distinctions between how automated driving tech is applied in commercial vehicles and private vehicles. The difference exists because the parameters are significantly or even completely different between the two. A program that has developed itself through machine learning to self-drive heavy factory equipment cannot be used to self-drive SUVs on real roads with real traffic conditions. No vehicle can properly self-drive in real road conditions without human assistance yet, but even when they begin to, the autonomous software will be different for each different drive-case scenario.

Similar to how someone who is used to driving a sedan cannot be licensed to operate an 18-wheeler without due training and practice, AI programs will not be able to take on driving tasks beyond their current specializations either. Therefore, from the perspective of a company looking to make use of software-driven vehicles, their choice of the software and the vehicles must be immaculate.

Specialization and Division of AI-Drivers within Commercial Sectors

A business looking to upgrade its fleet of taxis with self-driving models will not be able to utilize a software that is used to driving heavy mining equipment on an isolated country road. The AI-drivers will differ in their software versions, variants and developers within the commercial sector as well, depending on the particular sector of the transportation industry which it will be used in.

In due time, it is expected that singular, AI-driven software solutions will be able to handle multiple separate types of autonomous driving. That is also an inevitability, considering how industrial software solutions slowly begin to incorporate more and more features within themselves to become comprehensive in their services. That is still a hypothetical situation though, and it will take a long time to happen, since even a single mistake made by self-driving cars will endanger lives, unlike a buggy software that can be patched with proper updates later on.

Current State of Progress within the Self-Driving Vehicles Industry

Almost all major automobile manufacturers have a stake in the game now, with big names in tech and automotive, such as General Motors (GM), Waymo (Alphabet/Google) and Tesla, constantly competing with each other to get ahead in this race for capitalizing on the elusive first mover’s advantage.

There was a post on the Kettering University Online website recently, which elaborated more on this very subject. Given that Mary Barra, the CEO of GM herself was a student at the Kettering University, it doesn’t come as a surprise that the post hints at some amazing developments within the industry soon. It further stresses on the subject of how important application developers, software engineers and automotive engineers educated with AI-mobility are right now. In the absence of necessary talent at this present time, a future for the autonomous automotive industry cannot be built.

To try and explain everything that is going on in the commercial sector of the autonomous, automotive business would be akin to oversimplification. There are also micro improvements that are being made in the AI-driven vehicles segment continuously as well. Nevertheless, this should provide a decent background for any small fleet owner to get started with understanding autonomous vehicles.

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