As the AI is developing, why not have it used in automobile sector to our benefits. The concept of autonomous driving is emerging more as a safer and convenient solution to the past mode of transport, especially for public utilities. Although this concept of autonomous driving is not very new but now it is aiming to ease travel. As far as the benefit of people concerned with its development, it will benefit in multiple ways like reducing traffic congestion, lowering travel costs, and will help for no more circling for parking spaces and hopefully make our daily commutes quicker, less stressful, and affordable. It is also expected to reduce the harmful emission of CO2 hence improving the quality of air we breathe. As we see, Automated driving is not a very new concept and it has been into existence since 1950s, with the Automated guided transport (AGT) systems and Automated guided vehicles (AGVs) .
Transport is always a part of any accomplishment and it has no value of its own.
For this reason, applications where transport could take place without a driver were developed for in-house logistics as early as in the 1950s. The driving robots were primarily developed for taking over special missions in areas of difficult situations. Automated, driverless and partially autonomous vehicles have thus been in operation for transporting goods in production and logistics systems since a while. However, although fully-automated vehicles are yet not the norm, but the reality isn’t as far away as we could imagine. Let us check the basic levels for automated driving by the reference of the SAE International (Society of Automotive Engineers) in 2014 and is often used as a reference point in discussions surrounding vehicle automation as follows.
- First one is when the vehicle is assisted with a driver. In this the driver is responsible for the functioning of the vehicle but with the help of automation and AI. For example, a level one vehicle might provide you with a brake boost if you edge too close to another vehicle, or it might have an adaptive cruise control function to control your distance and speed.
- Like it might have a park assist function, where a beeping sound alerts the driver to an approaching obstacle. Level 1 autonomy is common in most vehicles today, and a typical example would be the 2018 Nissan Sentra, with its Intelligent Cruise Control feature.
- The next one is partial automation in which vehicles are able to assist with functions like steering, acceleration, braking, and maintaining speed, although drivers still need to have both hands on the wheel and be ready to take control if necessary. An example of a vehicle with Level 2 autonomy is the 2019 Volvo S60, with its auto-braking feature and Pilot Assist capabilities.
- Third is Conditional Automation. This allows drivers to sit back and let the vehicle do all the driving. Many Level 3 vehicles don’t require any human intervention at all when driven at a speed of less than 60 km/h. At this level, vehicles can be considered truly autonomous, but only under ideal road conditions. Hondais reportedly set to introduce a level three vehicle on public freeways
- In the fourth level vehicles are capable of steering, accelerating, and braking on their own. They’re also able to monitor road conditions and respond to obstacles, determining when to turn and when to change lanes. Level 4 autonomous driving can only be activated when road conditions are ideal. With this level, vehicles can’t negotiate more dynamic conditions like traffic jams or other major obstacles. The example of a Level 4 autonomous vehicle is Google’s Waymo project in the U.S.
- The last one is about full automation where driving requires no human interaction. Vehicles are able to steer, accelerate, brake and monitor road conditions like traffic jams. This enables the driver to sit back and relax without having to pay any attention to the vehicle’s functions whatsoever. Vehicles will be driven using Artificial Intelligence (AI) and will respond to real-world data points, generated from sensors. In a previous article about AI and mobility, we highlighted that a huge amount of data is produced in autonomous vehicles, as much as 4TB per hour. Only a powerful computing system like Artificial Intelligence can process such large volumes of data quick enough to achieve real-time responses.