• AI and transportation

AI and transportation

The use of Artificial Intelligence (AI) has become increasingly prevalent in transportation, especially in the optimization of transport systems. A key application of AI in transport is the use of sensors located on roads to reduce fuel consumption and minimize delivery times. AI can also predict weather conditions and congestion, which helps airlines avoid cancellations. Other benefits of AI in transport include the reduction of traffic congestion, the optimization of public transport scheduling, and the safety of riders using self-driving vehicles.

The adoption of self-driving vehicles is expected to grow rapidly in the future, leading to a significant increase in the value of deep learning. Researchers estimate that if 30% of vehicles in Australia are autonomous by 2030, it could reduce congestion costs from $38 billion to around $26 billion. AI has also been identified as a promising tool for predicting long-term traffic state and enhancing predictive operations.

AI is used across various industries, with the travel sector and transportation seeing an increase in value from 62% to 128% due to the integration of AI techniques. Other industries using AI include retail, automotive and assembly, high tech, oil and gas, chemicals, media, entertainment, basic materials, consumer packaged goods, agriculture, banking, healthcare systems and services, public and social sector, telecommunications, medical products, insurance, and aerospace and defense.

Neural networks have been identified as a robust model for AI tasks due to their ability to cover multiple tasks without requiring a deep understanding of the process. Their advantages include the ability to relate inputs to outputs using pattern recognition, their ability to handle large amounts of data, adjust well to noise, and their fast computation speed. However, research on neural networks for long-term traffic prediction is limited.

AI has the potential to revolutionize the transportation industry, increasing efficiency while reducing costs. The use of AI can minimize fuel consumption and optimize transport systems, reducing travel times and improving safety. The growth of autonomous vehicles is expected to increase the adoption of AI, which will lead to an increase in its value.

In conclusion, the integration of AI in transportation has the potential to revolutionize the industry. It is already being used to optimize transport systems, predict weather conditions and congestion, and reduce fuel consumption. The growth of autonomous vehicles is expected to increase the adoption of AI, leading to an increase in its value. The adoption of AI in various industries is also expected to continue to grow, with neural networks being identified as a robust model for AI tasks. However, further research is needed to enhance predictive operations and improve long-term traffic state prediction.

Full article on ResearchGate

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