Government Action in AI and Transportation

By Michael Taylor

Artificial intelligence (AI) is transforming fleet management in many ways, from optimizing fleet operations to speeding up repairs. According to the 2024 Market.us AI in Transportation Market report, AI in transportation is expected to reach around $21.4 billion globally by 2033, growing annually at a rate of 19.5 percent. Alongside this investment growth, we see more government activity focused on AI and transportation as well.

Executive Actions

Almost a year ago, President Biden issued his Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence (E.O. 14110). This issuance ushered in more efforts in AI policy work, coordination, and research throughout the federal government.

In January of this year the Transforming Transportation Advisory Committee (TTAC) of the U.S. Department of Transportation (USDOT) held its first meeting. The participants discussed key topics such as autonomous driving, safety, and the application of emerging technologies like AI. During the meeting, discussion ensued around possible AI applications for battery management in HEV/EV and advanced driver-assistance systems (ADAS). Additionally, TTAC has extensively discussed AI safety and the impact of AI on the U.S. transportation system.

On May 3rd the Advanced Research Projects Agency — Infrastructure (ARPA–I) issued a request for information seeking input from interested parties on the potential applications of AI in transportation, as well as emerging challenges and opportunities in creating and deploying AI technologies in applications across all modes of transportation.

On August 13th, USDOT announced that it intended to award a total of $2.4 million in contracts to 12 American small businesses across the country to leverage advancements in AI to improve transportation. This Complete Streets AI Initiative began as a multi-phase endeavor to develop robust new decision support tools for state, local, and Tribal transportation agencies that assist in the siting, design, and deployment of Complete Streets, streets, and networks that prioritize destination-focused safety, comfort, and connectivity for all people.

Congressional Actions

On April 16th the House Transportation and Infrastructure Committee held a Full Committee Roundtable on AI in Transportation. On May 15th, the Senate AI Working Group — Senate Majority Leader Chuck Schumer (D-NY) and Senators Mike Rounds (R-SD), Todd Young (R-IN), and Martin Heinrich (D-NM) — issued their long-anticipated Roadmap for AI Policy in the United States with their recommendations to the Senate.

The current session of Congress has seen an unprecedented amount of attention on AI. Committees in the House and Senate have held more than 50 hearings this year to examine AI’s impact on a broad range of issues. Despite all this attention, none of the over 80 individual pieces of legislation related to AI have passed.

State Actions

States have stood out more than the federal government when it comes to taking action around AI and transportation. Considered a leading state in using AI in the transportation industry, the California Department of Transportation (Caltrans) is developing AI-powered traffic management systems to analyze real-time traffic data and optimize traffic flow on major roads.

During the inaugural meeting of Texas House Committee on Artificial Intelligence, the Texas Department of Transportation briefed members on an AI pilot program that monitors traffic cameras and automatically dispatches emergency crews upon detecting accidents.

The North Carolina Department of Transportation is working on a series of pilot and modernization initiatives to integrate tools to help advance transportation equity across the state’s diverse communities. The most sophisticated pilot project so far is one NCDOT is doing in cooperation with UNC Charlotte. It is focused on testing shuttle vehicles that interact with traffic signals and operate in a particularly intense mixed traffic environment that includes other vehicles and shared stops with the existing campus bus fleet.

The Maryland Department of Transportation is implementing AI-controlled traffic lights that dynamically adjust timing based on road conditions to alleviate congestion, and Vermont’s DOT is using AI-powered modeling to predict bridge deterioration and understand road treatment longevity.

The speed with which more applications for AI in transportation will be explored and implemented at federal and state levels will greatly accelerate, and so too will their impacts on fleet operators.

MICHAEL TAYLOR is senior advisor for HillStaffer, NAFA’s advocacy team.