Artificial intelligence (AI) systems have been used in the transportation industry for some time. They’ve helped to reduce accidents, lessen road congestion, and increase safety.
The software to accomplish these benefits has been in development for quite some time, and although there are still kinks to work out, the future looks promising.
For example, in addition to the standard features, there is now a tool known as Empathy AI, which is designed to keep human drivers safe and comfortable. According to fleet software experts at Cetaris, Empathy AI might be useful in the future to monitor a driver’s heart rate, identify signs of possible intoxication, and alert fatigued drivers.
AI has the potential to improve the transportation industry, which in turn will help it grow. In fact, AI has already been helping the industry grow for a while. Below are some examples of what’s happening in this sector right now.
Self-driving vehicles
The notion of self-driving vehicles has been around since 1939, when General Motors introduced a radio-controlled car at the World’s Fair. That model required wires in the road to operate.
Today’s autonomous vehicles are programmed to operate via software that manipulates the car’s controls. The average person isn’t going to benefit from this technology right away, but taxicab and ride sharing companies have been experimenting with autonomous vehicles to reduce their expenses and make passengers more secure.
Several accidents involving self-driving cars have been reported, so the technology probably isn’t ready for general use yet. But many companies have achieved limited success because their vehicles are able to navigate through even the densest of traffic conditions safely.
Another possible application for autonomous vehicles is in the commercial trucking industry. Several companies are currently testing autonomous 18-wheeler semi-trucks.
If these can be made effective, that will change long-haul driving–although it may never be truly human-free. Due to the size of the trucks, it’s possible that regulations may require a human to be present at all times to take over in case of an emergency.
However, autonomous heavy trucks have the potential to reduce the number of collisions attributable to fatigued and distracted drivers.
Computer vision for airport navigation
The struggle to find a parking spot is something most of us have experienced, especially at an airport. Computer vision is an emerging AI technology that uses sensors and cameras to help people find empty parking spots in a visual format.
Airports are starting to use this technology for the convenience of visitors. An airport must install the infrastructure first, but once it’s in place, people can download an app and navigate their way through the parking lot(s) straight to an empty space with the help of a graphic map generated by the app.
This technology goes a step further by estimating wait times for lines at check-in stations, immigration, and security. It will even tell people when the next restroom cleaning will occur and directs them to alternate check-in locations if one is at full capacity.
Any city could use this technology to manage its parking. Residents of especially large and congested cities would likely appreciate this feature if, say, Seattle, San Francisco, and even New York City were to adopt it.
Road condition monitoring
Vehicles that can identify people in the middle of the road have the potential to reduce fatalities in situations where the driver didn’t perceive the pedestrian. It’s also an essential feature in driverless car models.
Currently, this software recognizes human beings only by distinguishing them from other objects, but it’s good enough to work. The technology uses motion, shape, and gradients to identify individuals in the right of way.
Some software developers have been able to predict automatically with 94.45 accuracy whether a person was going to cross the road just by analyzing the individual’s skeletal positioning.
Driver monitoring
This is one of the more controversial applications for AI, but there is undeniable merit in being able to monitor a driver for signs of fatigue, distraction, and intoxication. Each year, fatigue causes around 56,000 accidents, and about 1,500 of them are fatal.
In a perfect world, people wouldn’t drive when they’re tired, but that’s not reality. A technology currently exists that is programmed to detect signs of fatigue by a person’s facial expressions and head pose, including when their eyes close for longer than usual.
If the system detects fatigue, it will alert the driver and suggest he or she would be wise to pull over and rest a bit. This technology would make the roads much safer for everyone.
AI is the future of transportation
Current AI certainly isn’t perfect, but the transportation industry is already seeing improvements in safety and efficiency from it. One day, self-driving vehicles and automation may be the norm. Until then, we can watch this technology evolve.
A 3D model collection with name Artificial Intelligence by Engineer AI on sketchfab.
Industry InsightThe take of global artificial intelligence (AI) in the manufacturing market growth 2020 recorded by Market Research Future reveals that the market can hit 47.09% to the net worth with USD 14.77 billion by 2024 amid the long-term impact of COVID-19.
The years of growth is calculated to be from 2019-2024.Get a Free Sample @ https://www.marketresearchfuture.com/sample_request/7745Top Grossing FactorsThe global artificial intelligence in the manufacturing market has gathered pace in its growth amid COVID-19 breakthrough with rapidly evolving industrial automation and IoT, at present.
Artificial intelligence is allied with human intelligence with similar characteristics such as understanding, problem-solving, reasoning, language, and learning.
An amalgamation of AI in the manufacturing industry offers a safer operational environment, which further assists in enhancing the quality and quantity of production.One of the main factors, such as the exponential growth in digital data, is motivating the growth of artificial intelligence (AI) in the manufacturing market.
All these factors are cheering the adoption of artificial intelligence solutions among the manufacturers to process the data and extract actionable insights.Furthermore, the factor of enhancement in automation in the manufacturing industry and the rise in demand for big data integration boost the escalation of artificial intelligence in the manufacturing market.
With this, prevalent usage of machine vision cameras in manufacturing applications, such as material movement, machinery inspection, quality control, and field service, is also to drive the growth of artificial intelligence in the manufacturing market for the forecast period.Segmentation of Market: Artificial Intelligence in ManufacturingThe study by MRFR also digs some segmentation of the global artificial intelligence in the manufacturing market, which has been done through the component, technology, application, and vertical.In terms of component segment, the market has included software, hardware, and services.
