
How Applications of AI is Ensuring in Transport
Artificial intelligence is a broad field of computer science that aims to make machines function similarly to the human brain. It is applied to problems that are difficult to resolve using traditional computational techniques. This technology
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CIO Applications Europe | Thursday, December 02, 2021

AI is creating opportunities to make transportation safer, more reliable, efficient, and cleaner, from scanning traffic patterns to reduce road accidents to optimizing sailing routes to reduce emissions.
Fremont, CA: Artificial intelligence is a broad field of computer science that aims to make machines function similarly to the human brain. It is applied to problems that are difficult to resolve using traditional computational techniques. This technology is already having a significant impact on how we interact with our surroundings. AI has important applications in a variety of fields. One such field is transportation, where AI applications are already reshaping how we transport people and goods. AI is creating opportunities to make transportation safer, more reliable, efficient, and cleaner, from scanning traffic patterns to reduce road accidents to optimizing sailing routes to reduce emissions. There are numerous applications of AI in both advanced and emerging economies that demonstrate the contributions these evolving technologies can make to economies.
Road Safety
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Road safety is a major public health concern for both drivers and pedestrians. In 2016, 1.35 million people were killed in traffic accidents, up from 1.25 million in 2013. 7 The majority of those fatalities occurred in low-income countries. While poor infrastructure, particularly poor roads and vehicles lacking modern safety equipment, contribute to the high death toll, human error is also a factor. Human error, such as speeding, distraction, and drunk driving, contributes to more than 90% of road accidents. When self-driving technologies were activated in Tesla's first attempt at an AV, accident rates were reduced by 40 percent. While AVs may not be ready for mass deployment in emerging markets in the near future, some optimistic estimates predict that by 2020, there will be 10 million AVs on the road, with one out of every four cars being driverless by 2030.
Accidents Detection Made Faster
Many times, it is difficult to fully comprehend the relationships between the characteristics of the transportation system; thus, AI methods can be presented as a smart solution for such complex sustainability. Many researchers have demonstrated the benefits of artificial intelligence in transportation. One example is transforming traffic sensors on the road into a smart agent that detects accidents and predicts future traffic conditions. In addition, many AI methods, such as ANNs, are used in transportation. ANNs can be used for road planning, public transportation, traffic incident detection, and traffic forecasting. It is divided into two types: supervised and unsupervised learning methods. Support Vector Machine (SVM), Probabilistic Neural Network (PNN), K-Nearest Neighbors, Radial Basis Network (RBN), and Decision Tree are examples of supervised methods, whereas unsupervised NNs include greedy layer-wise and cluster analysis.
Though autonomous vehicles (AVs) receive a lot of attention in the media, AI applications in transportation go far beyond driverless vehicles and are already having an impact. On a much larger scale, AI can aid in the resolution of a wide range of transportation issues, including safety, reliability, and predictability, as well as efficiency and sustainability.
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