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The IUP Journal of Telecommunications

AI in Transportation: Current and Promising Applications

Article Details

Pub. Date	: Nov' 2022
Product Name	: The IUP Journal of Telecommunications
Product Type	: Article
Product Code	: IJTC031122
Author Name	: T Aditya Sai Srinivas, G Mahalaxmi, R Varaprasad, A David Donald and G Thippanna
Availability	: YES
Subject/Domain	: Arts & Humanities
Download Format	: PDF Format
No. of Pages	: 21

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Abstract

Artificial Intelligence (AI) is advancing rapidly, and this has improved the efficiency of many businesses and industries, including the transportation industry. AI in transportation might minimize travel, lower emissions and make roadways safer. Some examples of AI technologies used in the transportation sector include: Artificial Neural Networks (ANN), Genetic Algorithms (GA), Simulated Annealing (SA), Artificial Immune System (AIS), Ant Colony Optimizer (ACO) and Bee Colony Optimizer (BCO). The paper explores how AI is being used to address some of the most pressing issues in transportation today, including traffic control and safety. The limitations of AI transport are also discussed.

Introduction

Artificial Intelligence (AI) allows machines to mimic the performance of human brain. It is used to shed light on the mysteries that cannot be solved by conventional computing techniques. The AI field, which John McCarthy pioneered in 1956, was initially unable to achieve its goals (Abduljabbar et al., 2019) and produce any significant technological advances. Between 1960 and 1970, scientists dug deep into the synergistic use of Knowledge-Based Systems (KBS) and Artificial Neural Networks (ANNs) for AI (Srinivas et al., 2022a). The KBS systems offer guidance based on established criteria. ANNs are multilayered systems of neuron connections inspired by the structure of the human brain. A lack of data and ways to use ANN kept people from getting excited about AI until the 1980s (Minsky and Papert, 1988).