Artificial intelligence in the transportation sector is booming right now, and it’s only getting bigger. AI has already been implemented in many industries, including finance, healthcare, and manufacturing. Now, it’s making its way into the world of transportation.
AI can solve many problems that humans cannot, like traffic congestion, parking shortages, long commutes to work, and more. It is also expected to play a crucial role in improving future transportation systems’ quality, safety, efficiency, and sustainability.
According to a report, global AI in the transportation market is projected to reach $3.5 billion by 2023, enabling an impressive growth rate of 16.5%.
In this article, we’ll talk about what AI in transportation really entails and some key challenges that organizations face when implementing AI into their systems. Plus, we will discuss how AI is being used in different parts of the transport industry and what we can expect from AI going forward.
How Is AI Transforming the Transportation Industry?
Self-driving cars are now the norm in many parts of the world. AI systems are used to provide safety warnings, monitor surrounding traffic conditions, and even help identify imminent collisions. AI-driven vehicles are also programmed to brake more quickly than driver-controlled models in emergencies. The systems communicate with one another wirelessly, allowing them to avoid traveling on the same paths or taking up too much space on roads. It can also predict bottlenecks and adjust routes accordingly.
AI may also receive better information about accidents, weather events, and other disruptions than human drivers do. Moreover, it may also take control in dangerous situations. AI-controlled vehicles are also programmed to drive more efficiently than human drivers, which can help reduce traffic congestion.
Traffic management is one of the AI applications in transportation. AI can help with traffic management by suggesting to drivers alternate routes. It could also suggest times when the traffic is expected to be light so drivers can plan and leave earlier than usual. AI would be able to do this by tracking the AI in transportation data of other drivers. It also has the potential to control traffic lights and even parking lots. Moreover, AI can also be used to monitor traffic around construction sites or accidents so that drivers are aware of what is happening and avoid possible delays.
Consumers are becoming more aware of transportation’s impacts on our environment and pollution, so many people want sustainable means to get from point A to B. For example, you can look at electric or solar-powered vehicles. While these technologies are possible without AI, they work more efficiently when recharging, and energy expenditure is controlled with the help of an artificial intelligence system that can predict traffic patterns on public roads to offer better solutions for driverless cars.
If you own a fleet of vehicles, it’s essential to have an AI system that can help manage the company. Firms that operate large fleets face many challenges, including monitoring drivers’ locations through GPS tracking systems for each car in use.
So, it can help businesses streamline their operations by offering real-time updates for fleet managers. Notifications are sent out when a vehicle needs maintenance or has been involved in an accident, among other things that could affect the operations of your company’s vehicles.
Crewless Cargo Ships
The shipping industry is worth hundreds of billions, and it should be no surprise that some innovators are looking for ways to improve their efficiency. Rolls-Royce has partnered with Google to integrate AI into ships scheduled this year. Thus, AI is being implemented in the shipping industry to make it more efficient and cost-effective.
The application of AI in vehicle-related industries has been a topic of frequent speculation and imagination. A new development in this field is drone taxis. Drone taxis are a concept that several companies have explored. In 2016, Uber released a white paper describing the implementation of aerial taxi services as part of the company’s long-term vision and strategy.
Airbus presented at the World Economic Forum in Davos, and Volocopter presented their drone taxi concepts. With all these developments, we see that the drone taxi idea has moved from the conceptual stage to the implementation stage.
So, what exactly is a drone taxi? Drone taxis are autonomous aerial vehicles that aim to transport people from one place to another. There are two main types of drone taxis: low altitude and high altitude. Low-altitude taxi services would be capable of flying close to the ground during short-distance transportation. The second type of service, called high altitude taxis, would fly at heights of over 20,000 feet.
AI Offers Safety
AI can make driving and other forms of AI in transportation safer, which is a top priority for many organizations. AI can help improve safety by monitoring car sensors and detecting cars that are close together or about to crash into one another.
AI can also help improve safety by alerting drivers to dangerous weather conditions, such as heavy rain or snow. AI would be able to do this by tracking the AI in transportation data of other cars and comparing it with the current state of the car’s sensors.
Challenges of AI in Transportation
Cost of Adoption
AI is not cheap, but integrating it into your business can have a significant payoff. Sensors and transmitters are affordable for many companies now, with prices dropping significantly over time as production increases.
What does it mean? Well, this means you’ll be able to leverage these technologies more efficiently to make informed decisions about how they fit within an organization. Moreover, you can also hire AI developers to provide solutions for your business while integrating AI technologies.
The public is still not comfortable with the idea of autonomous vehicles, and many companies are hesitant to invest in them due to their history. The main reason for this? Autonomy systems have been involved in multiple accidents. Inevitably, there will always remain some uncertainty until these issues get resolved.
Cloud Security Challenges
The transportation data is susceptible and may expose private information or enable attackers to access systems with disastrous consequences. Why is it so? Because many AI initiatives rely on cloud technology for their infrastructure and thus it is much easier to compromise the data.
It’s essential to take cloud security seriously when you are integrating AI initiatives. You must ensure that the resources and datasets are appropriately configured to be monitored comprehensively for any leaks or other vulnerabilities in the system.
Availability of Manpower
Availability of workforce is one of the significant challenges that AI in transportation faces. The industry has not met the need for specialists and experts who can work in this field. Plus, there is also a shortage of skilled labor in this sector.
AI is spreading its tentacles into the transportation industry and revolutionizing it even after some challenges. Moreover, the challenges that integrate AI are worth looking into, and they may provide some insight for your own business.
For instance, if you can’t find qualified staff to invest in this technology, you can resolve the issues by hiring an AI developer instead. Keep in mind that working on AI initiatives can be difficult, but the effort put into it will result in a more efficient company.
So, don’t delay anymore and get in touch with the best AI development company to leverage the benefits of this scintillating technology to your transportation business.
About the author: Devesh Chauhan is a technical consultant working with PixelCrayons, an IT outsourcing company for AI developers.