Artificial intelligence has been a distant dream for decades, but recent advances in Artificial Intelligence have shown that we can soon use it to solve some of society’s biggest problems.
Almost two years ago, in January 2016, AI beat the world’s best game, which is more complex and has more powerful motions than the atoms we have in the universe.
It shows that computers can now exceed human capabilities in some complex tasks, even if that task is a game. AI is better in voice and face recognition, and error rates are getting smaller and lower, which is a sign of the onset of widespread AI use.
While playing games and tagging Facebook photos is interesting and promising for AI tools, more practical applications of AI are on the horizon. Those applications help the transportation industry address our biggest challenges in moving from place to place.
Also Read: Artificial Intelligence in the Transportation Industry
Here are 4 important ways that AI can help improve our transportation system.
1. Urban Design
Urbanization has been on the rise over the past few decades and has increased house prices, pollution, and congestion on the roads. 50% of the world’s population already lives in cities, and that percentage is expected to grow to 70% in the next 40 years.
Public transport is a mandatory service in urban areas, as pollution and traffic from increasingly personal vehicles are becoming an even bigger problem. AI can help offset these realities of urbanization by optimizing essential urban design.
Reducing congestion in cities involves massive amounts of data collected through sensors and cameras. AI helps urban design and traffic control in many ways, including adjusting variable speed zones based on traffic, traffic light timing, and smart pricing for vehicle tolls.
2. Car Communication
Car communication is the key to the future of autonomous vehicles. Avoiding collisions is a top priority for self-driving car developers, and these efforts have been largely successful.
However, mini-communications between drivers, cyclists and pedestrians occur all the time road We don’t often record how often we make eye contact with others on the road. So how does an automated vehicle safely navigate the many dangers of the road? AI advances are possible.
Drive. I am the most prominent company that uses deep learning to address these communication barriers facing self-driving cars, and see these vehicles as “social robots.” This AI breakthrough and the ability to pick up the nuances of human instruction are essential in the inevitable transition period: some cars on the road have autonomy and some do not.
AI is not just about navigating the instructions on the road, but also providing drivers, ensuring safety for everyone.
3. Manufacturing
Since the first industrial revolution, we have been rapidly improving manufacturing methods and technologies, and AI has been crucial in the subsequent evolution of manufacturing.
3D printing and AI means creating better forms of transportation that are more efficient and more dynamic. Automation and real-time feedback from vehicles on the road help manufacturers optimize their products quickly.
Without waiting for vehicles (personal and commercial) to be shipped overseas, they will be able to make them locally, reduce wait times and lead to better manufacturing without human intervention.
4. Optimization Through Machine Learning
In a nutshell, machine learning describes the machine’s ability to learn without being instructed by programming.
Machine learning is essential for future transportation systems, as self-driving cars must adapt to their environment, and there is no programming to deal with every situation the vehicle encounters on the road.
As more and more autonomous vehicles get on the road, they use the information they get through everyday driving conditions to optimize themselves. AI is smart thanks to innovative programmers — but it also improves our transportation system by building the building blocks provided by these programmers.
