TxDOT Research Library - Publication Details

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Title:

A White Paper on Artificial Intelligence & Big Data in Transportation

Report No.:

FHWA/TX-18/0-6806-CTR-4

Authors:

Amy Fong [and five others]

Published:

2018

Austin, Texas

University of Texas at Austin. Center for Transportation Research

Type:

Online document

1 PDF (58 pages)

Online Access:

https://www.txinnovationalliance.org/learning-hub-...

Access Note:

6.5 MB

Summary

Advances in computing techniques and processing capacity as well as increased data collection are beginning to enable artificial intelligence applications in a myriad real-world setting. Artificial intelligence (AI) algorithms at their most advanced can provide decision support, ease labor-intensive operations, perform predictive analysis, and inform targeted outreach. In the transportation sector such applications could reduce the administrative burden at public agencies such as TxDOT and the DMV, and collect higher resolution traffic data with less infrastructure, thus enabling detailed transportation planning models and predicting and identifying traffic incidents. Artificial intelligence is also being applied to traffic control devices, and preliminary deployments have been promising. However, with the advent of advanced models and the significantly higher quantity of data they typically consume and produce, key challenges will include managing complex data sources, ensuring their ethical application in decision-making, protecting the privacy of the public, and reducing cybersecurity risks. This white paper provides an overview of key technologies that are enabling AI, a menu of AI applications across five transportation application areas, and case-studies from deep-dive interviews with technology companies.

Publ. Place

Austin, Texas

Contents

Executive Summary --
Motivation --
Process --
Technical Primer --
Menu of Applications --
Case Studies --
Conclusion: Technology Horizon --
Recommendations

Notes

"Report Date: August 2018"

Study Number

TxDOT Research Project 0-6806-CTR

Study Title

TxDOT Administration Research

Study Sponsor

Lead University

CTR