With the incredible amount of new automotive technologies released by car manufacturers this past year, Artificial Intelligence was at the forefront. Safer driving, full automation, and less traffic congestion are just a few noteworthy possibilities AI brings. With these changes, the future of transportation will be transformed. What does AI stand for in transportation?
Invented in 1955, it has been used in various industries like home appliances, Google, chatbots, and building robots. It has brought more innovative insights to the transportation industry.
AI uses neural networks that recognize specific patterns based on data for automation in vehicles. According to an industry report, AI will grow at an annual rate of 18%.
AI-The Brain Behind Intelligent Transportation
Artificial Intelligence has transcended to become omnipresent in our day-to-day lives. In a simple explanation, AI can be defined as a technology that powers machines with human intelligence, being able to carry out critical thinking jobs and make decisions by themselves.
Businesses, realizing the sheer potential, have made significant investments in the transportation sector to improve revenue generation and stay ahead of competition. AI in transportation is predicted to reach 3.5 billion dollars by 2023, growing year over year.
Some of the applications of Artificial Intelligence in transportation include self-driving vehicles, traffic management, delay predictions, and pilotless helicopters. Autonomous vehicles have already begun operating in Tokyo and come into play in some of the commercialized vehicles we see today, a concept that once was merely sci-fi fantasy.
Advancements in logistics
US logistics are embracing autonomous trucks for many benefits like decreasing maintenance and administration expenses. Most companies are still running their pilot projects to make self-driving vehicles flawless and safe, as of now.
Another transportation advancement that artificial intelligence is responsible for is traffic management. Through a collection of data, AI can analyze traffic pattern revelation and can communicate to commuters important details like road blockages or accidents. Along with this, AI can predict delays in transportation like flights for customers.
One of the most innovative and exciting AI applications in transportation is the drone taxi. Pilotless helicopters develop a unique solution to eliminate traffic congestion and decrease the need for expensive infrastructure plans.
What is the methodology and logistics behind AI in transportation?
From scanning traffic patterns to reducing road accidents and optimizing routes, AI is creating opportunities to make transport cleaner, more reliable, more efficient and safer. AI is not just one type of machine, but a series of methods, approaches, and different technologies that display intelligent behavior by analyzing and taking action to achieve targets that can improve modes of transportation.
What are the advantages of AI in transportation?
There are many advantages to AI in transportation. AI can be used in creating an optimal transit network for any given community, developing an optimal timing plan for a group of traffic signals or maintaining a pavement network. It can even be used in law enforcement capacities.
AI’s opportunities and potential are endless. It can help support greener and cleaner vehicles, supporting sustainability initiatives with eco-friendly technologies by reducing carbon emissions, fuel utilization, and vehicle expenses.
Artificial intelligence also works to improve common issues that emerge mostly due to human failure leading to mistakes, accidents, and mishaps. All in all, artificial intelligence has the potential to increase traffic efficiency, free driver’s time, ease traffic congestion, make parking easier, and encourage ridesharing.
The main disadvantages
While there is an incredible amount of advantages to artificial intelligence, like with any new technology, there are disadvantages. First, traditional ways can’t be replaced overnight.
Adapting to new technologies takes time and new, acquired skills. AI is also not totally independent from human assistance and control and it can be difficult to detect an error. Additionally, many companies use artificial intelligence to manage large amounts of data that contain sensitive information.
This poses a major security risk for organizations that don’t invest in high-quality security systems. Lastly, implementation of artificial intelligence can be a big undertaking, especially for countries who do not support autonomous driving vehicles.
Can AI in transport have the capacity to predict?
Artificial intelligence is fully capable of predicting. Predicting capabilities can be used in traffic, supply chains and logistics.
As an example of how AI can predict, let’s look at traffic. Traffic can cause delays and accidents but with AI, traffic condition forecasting is done with monitoring data, information about events or construction around the area and calculate alternative routes automatically.
Data plays a large role in predicting, using data analytics in logistics.
Is AI in transport a trend or a necessary need?
Artificial Intelligence is here to stay and if transportation companies don’t adapt, they will fall behind. Many companies have already begun to incorporate AI in every aspect of the supply chain and logistics routine. It is predicted to be one of the biggest trends in transportation in the upcoming years with incorporation into all business processes.
Companies like Tesla, Uber, and Ford have made artificial intelligence common practice in their new automotives and companies like Exploride and Amlotive have made great strides in technology. Artificial Intelligence is not limited to just processing big data or atomizing simple tasks. It can boost performance and open new possibilities. AI will also gradually improve manual processing. For example – AI will analyze all data using the embedded analytics to measure all factors influencing the rates of LTL freight and shipping. This could help with preventing potential delays, therefore help business owners choose the right carrier.
How will AI in transport help companies grow?
“Only 12% of transportation companies have adopted AI, compared to 35% in other sectors, says Gartner study.” As companies are recognizing artificial intelligence as game-changing tech, there can be many barriers to entry.
Developing successful AI applications requires both IT expertise and business process owners. Companies that are serious about growing their business with AI need to embrace it as a company-wide priority.
Artificial intelligence can dramatically accelerate business processes and optimization by learning patterns and applying them to real situations. It can take company logistics and planning to great heights by tracking and collecting information to better create a long-term analysis and can assist businesses in growing their infrastructure.
Will the system management be more advanced and how?
Artificial Intelligence is a fairly new technology and developing it as a common business practice is a lot of work. Complex systems call for intelligent control strategies so the system management with artificial intelligence will be more advanced.
It will take a lot more trial and error and caution to manage systems with artificial intelligence because there aren’t many guidelines or walk-throughs and every business is different.
The main component of AI is the study and analysis of data to create more efficient solutions, so examining these solutions to ensure it is optimal for your business will be necessary throughout the process.
We have only scratched the surface of AI and can expect a lot more to come from it in the near future and expected that 33% of assembling supply chains will contain cognitive abilities to create data analytics. By 2050, there could be millions of self-driving vehicles operating in our society.
The applications of AI in transportation showcase only a sliver of the opportunities this technology can offer as it has been one of the most astounding technological innovations ever created before.