Artificial Intelligence for Smart Transportation

Michael Wilbur, Amutheezan Sivagnanam, Afiya Ayman, Samitha Samaranayeke, Abhishek Dubey +1 more
8/14/2023
cs.AI

No official code found. Best implementation: duanra17/ai_smart_transportation (0 stars, last commit 2026-02-05).

Abstract

There are more than 7,000 public transit agencies in the U.S. (and many more private agencies), and together, they are responsible for serving 60 billion passenger miles each year. A well-functioning transit system fosters the growth and expansion of businesses, distributes social and economic benefits, and links the capabilities of community members, thereby enhancing what they can accomplish as a society. Since affordable public transit services are the backbones of many communities, this work investigates ways in which Artificial Intelligence (AI) can improve efficiency and increase utilization from the perspective of transit agencies. This book chapter discusses the primary requirements, objectives, and challenges related to the design of AI-driven smart transportation systems. We focus on three major topics. First, we discuss data sources and data. Second, we provide an overview of how AI can aid decision-making with a focus on transportation. Lastly, we discuss computational problems in the transportation domain and AI approaches to these problems.

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Code Implementations(1)

duanra17/ai_smart_transportationCommunity65%

Machine learning project for our Artificial Intelligence for Smart Transportation course.

00HTML, PythonDec 8, 20258 months ago

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Cite this paper

@article{wilbur2023artificial,
  title  = {Artificial Intelligence for Smart Transportation},
  author = {Michael Wilbur and Amutheezan Sivagnanam and Afiya Ayman and Samitha Samaranayeke and Abhishek Dubey and Aron Laszka},
  year   = {2023},
  eprint = {2308.07457},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2308.07457v1}
}

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