COVER PAGE

Transportation in the Age 

of Artificial Intelligence and

Predictive Analytics

A U.S. DOT Volpe Center 

Thought Leadership Series

Final Report

January 2019

DOT-VNTSC-19-01
NOTICE 

This document is disseminated under the sponsorship of the 

United States Department of Transportation in the interest of 

information exchange. 

The United States Government assumes no liability for the 

contents or use thereof. The United States Government does 

not endorse products or manufacturers.Trade or manufacturers’ 

names appear herein solely because they are considered essential 

to the objective of this report. 

WHAT’S INSIDE 

SERIES INTRODUCTION:TRANSPORTATION IN 

THE AGE OF ARTIFICIAL INTELLIGENCE AND 

PREDICTIVE ANALYTICS 

ANALYTICS AND ARTIFICIAL INTELLIGENCE IN 

A FEDERAL FRAMEWORK THAT ENCOURAGES 

TRANSPORTATION INNOVATION 

FORECASTING FREIGHT 

TRANSPORTATION RATES 

THE FOUR ROLES OF GOVERNMENT IN A 

NEW MOBILITY OPERATION SYSTEM 

ARTIFICIAL INTELLIGENCE IN 

TRANSPORTATION: A CONVERSATION 

TRANSFORMATIONAL TECHNOLOGIES: 

A STATE GOVERNMENT PERSPECTIVE 

DELIVERING THE BENEFITS OF SELF-DRIVING 

TECHNOLOGY SAFELY, QUICKLY,

AND BROADLY 

STAKEHOLDER 

ENGAGEMENT DATA 

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SERIES INTRODUCTION:TRANSPORTATION IN THE AGE OF 

U.S. DOT VOLPE CENTER DIRECTOR ANNE AYLWARD 

ARTIFICIAL INTELLIGENCE AND PREDICITIVE ANALYTICS 

E very year, the U.S. Department of Transportation’s Volpe 

National Transportation Systems Center convenes 

government officials, academics, and private sector leaders to 

discuss fresh approaches to future and emerging transportation 

challenges, and to facilitate knowledge-sharing and inform 

decision making across modes. 

Transportation in the Age of Artificial Intelligence and Predictive 

Analytics, held from June to October 2018, convened distinguished 

experts in government innovation, vehicle automation, and 

logistics to consider the promise and potential of recent 

breakthroughs in machine learning and data analysis. 

These experts shared their bold visions for how new technologies 

can be applied throughout the transportation enterprise—such 

as troves of data from mapping applications that can improve 

traffic modeling and save lives on U.S. roads.

They challenged government professionals at the state and 

local levels to think critically about how to keep transportation 

systems safe and moving, recognizing that the time horizon for 

widespread adoption of innovative technologies can be decades. 

They discussed how data is helping freight professionals better 

understand complex shipping markets. And, they shared how the 

federal government can encourage transportation innovation 

without being overly prescriptive. 

Read on for more insights on the technologies that are 

transforming transportation, shaping how we move, and 

advancing the U.S. DOT’s strategic goals of safety, innovation, 

infrastructure, and accountability. Plus, watch video highlights 

from each speaker. 

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U.S. DOT UNDER SECRETARY OF TRANSPORTATION FOR POLICY DEREK KAN 

ANALYTICS AND ARTIFICIAL INTELLIGENCE 

IN A FEDERAL FRAMEWORK THAT ENCOURAGES TRANSPORTATION INNOVATION 

Watch the video highlights June 4, 2018 

A “growing torrent” of technology advances are poised to 

fundamentally change transportation, according to U.S. 

DOT Under Secretary of Transportation for Policy Derek Kan, 

who kicked off Transportation in the Age of Artificial Intelligence 

and Predictive Analytics. 

“Three technology areas are garnering significant investment,

testing, and deployment,” Kan said. “They are data integration 

and analytics, automated vehicles, and unmanned aerial systems.” 

Safety is propelling U.S. DOT programs, and the safety impetus is 

real. In 2017, 37,133 people died in motor vehicle crashes, down 

following two consecutive years of large increases. More than 

3 million people were injured in motor vehicle crashes in 2016. 

Drawing on New Data Analytics to 

Prevent Road Fatalities 

The department has access to a vast amount of data. Looking 

at that data in new ways may help turn the fatal crash trend 

south, Kan said. One way is to rethink how U.S. DOT modal 

administrations collect and organize road data. 

“The department’s data is often siloed and it comes at different 

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cadences,” Kan said. “Data sources are analyzed separately, 

housed in different modes, and many are only made available 

on an annual basis. Much of this data has been collected and 

organized in the same way for years, and maybe even decades. 

Recent innovations in data science provide the opportunity to 

do so much more.” 

Automated vehicles use artificial intelligence,and big-data sources 

provide previously unseen amounts of information on roadway 

and operating conditions. This data can help transportation 

professionals assess fatal crash risk at increasingly granular levels. 

“This is one of the big pushes Secretary [Elaine L.] Chao has 

given us: use the latest technology to prevent traffic fatalities,” 

Kan said. 

U.S.DOT established its Safety Data Initiative to do that. Because 

speed is a contributing factor in many traffic fatalities, one pilot 

project will integrate established data on crashes and highway 

design with anonymous data from GPS devices. 

For the first time, U.S. DOT will be able to directly analyze how 

speed—and speed differentials—and roadway characteristics 

interact to affect the likelihood of crashes. 

Another pilot project will integrate crash data with data 

on hazards and conditions from the crowd-sourced Waze 

application. This effort will determine if it is possible to use a 

crowd-sourced application as a reliable,timely indicator of traffic 

crashes, and to estimate crash risk. 

“The vision has always been, ‘Let’s use new countermeasures— 

let’s deploy capital to install countermeasures, broader roads, 

traffic circles,’” Kan said.“But there’s a whole other way to bring 

down traffic fatalities, and that’s using 0s and 1s—bits and bytes.”

Frameworks—Not Prescriptions—for Deploying 

Automated Vehicles 

Volpe Center analysts were closely involved in developing 

Preparing for the Future of Transportation: Automated Vehicles 3.0, 

released October 2018, which offered a holistic, multimodal 

framework to accelerate the safe testing and integration of 

surface automated driving systems. 

AV 3.0 builds on Automated Driving Systems 2.0: A Vision for Safety, 

which encourages best practices and prioritizes safety for 

automakers deploying advanced driver assistance technologies. 

As U.S. DOT continues to refine its approach to automated 

vehicle deployment, it will only pursue regulations that focus on 

the capabilities those vehicles should have, without prescribing 

the technologies to achieve those capabilities, Kan said. 

“We hope to prepare for the future and encourage innovation 

without compromising safety,” Kan said. “Under this approach, we 

will not pick winners and losers among technology innovations. 

We will remain tech-neutral and let the quality of safety 

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performance and market interest drive the evolution of

innovative technologies.” 

Integrating Drones into the National Airspace 

Similar to U.S.DOT’s approach to automated vehicles,regulations 

related to unmanned aerial systems (UAS) need to strike a 

careful balance between ensuring safety and allowing the public 

and private sectors to boldly experiment with UAS technologies 

and operations, Kan said. 

“The small UAS rule—Part 107—is the first comprehensive set 

of performance-based rules for routine small UAS operations 

in the United States,” Kan said. “Today, we have 50,000 new 

commercial drone pilots.” 

Drone technology and public acceptance are still developing, but 

U.S.DOT already has several efforts that are striking that balance 

between public safety and UAS integration. 

The UAS Integration Pilot Program is bringing together state, 

local, and tribal governments with private industry to understand 

public response to expanded UAS operations. FAA’s B4UFLY 

app is helping UAS operators understand restrictions or 

requirements in areas where they want to fly.And U.S. DOT is 

coordinating UAS cybersecurity challenges with partners at the 

Departments of Defense, Homeland Security, and Justice. 

“It’s exciting to me to be here,” Kan said.“It’s an exciting time 

to be at Volpe because all of you will be playing a critical role in 

helping form these regulations and usher in new technologies.” 

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CHRIS CAPLICE, PHD, EXECUTIVE DIRECTOR, MIT CENTER FOR TRANSPORTATION AND LOGISTICS 

FORECASTING FREIGHT TRANSPORTATION RATES 

August 13, 2018 Watch the video highlights 

A car driving on an interstate passes a freight truck.The 

truck is hauling refrigerators at a rate of $2.93 per mile. 

Down the highway, the car passes another freight truck, hauling 

televisions at a rate of $2.88 per mile.That other truck further 

along on the horizon? It’s empty, on its way to pick up its next 

load, and isn’t making a cent right now. 

The market for buying freight transportation services, in

particular trucking services, can be challenging to forecast. There 

are traditional statistical forecasting models, and models that use 

artificial intelligence and can incorporate large amounts of data.

How Freight Transportation Markets Work 

Before examining different ways to forecast freight transportation 

rates, it helps to know how freight transportation markets work, 

according to Massachusetts Institute of Technology Center for 

Transportation Logistics Executive Director Chris Caplice, PhD. 

“Truckload operations are like a taxi cab, not a bus,” Caplice said. 

“You might pick up a load at Reno, take it to Rapid City, drive 

empty to Denver, pick up another load.” 

Shippers purchase truck transportation based on two kinds 

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of rates. Contract rates are rates that are set by contract and 

are fixed over a period of time. They cover 80 to 95 percent 

of freight trucking volume. Spot rates come from a secondary 

market, where shippers bid for one-off deals, typically at higher 

rates than by contract. The spot market covers 5 to 20 percent 

of volume. 

“Contract rates are very different from spot rates, and that is 

what causes the problem in trying to forecast,” Caplice said. 

Spot rates are binding. The carrier accepts the load and goes right 

away. Contract rates, however, are non-binding. Carriers refuse 

between 5 and 10 percent of loads under contract, Caplice said. 

“So what am I going to predict?” Caplice said. “Do I predict the 

average rate? Do I predict the median? Do I predict the range? 

This is the challenge. There is more going on than just a single 

market rate, and this is why there is variability in contract rates.” 

Using Artificial Intelligence to Develop 

Market Predictions 

Time series prediction is the most popular technique to estimate 

product demand, Caplice said. With the time series method, the 

average of the last eight weeks is taken to forecast the next week. 

Exponential smoothing is another method that uses past data 

to predict demand, and also incorporates patterns to identify 

trends. Another slightly more sophisticated method takes into 

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account that an event from two weeks ago may have a different 

effect on a prediction than an event from a month ago. 

“The problem is that these are good for an individual lane,” 

Caplice said. “A shipper can have thousands of lanes. So running 

a time series for each lane is time consuming, and I don’t know 

anyone who does it.” 

Regression analysis, which correlates a host of factors to shipping 

costs, is useful for long-term prediction, he said. Artificial neural 

networks, loosely based on the brain’s neural network structure, 

may be useful for predicting short-term rates. 

“I had a student, she went and looked at this, trying to predict 

the next seven days on a lane and do a rolling forecast,” Caplice 

said.“And we’re trying to figure out,should I do one big forecast 

for the previous year and then predict seven days? Should I have 

a rolling, where it takes the last seven to predict the next seven? 

Do I do the last three weeks to predict the next seven?” 

Those questions are still open, but initial findings showed 

that neural networks had comparable predictive power to 

sophisticated time series analysis, Caplice said. 

Data Mining and Other New Directions 

The Center for Transportation Logistics is exploring several 

other areas related to how freight transportation markets are 

structured, Caplice said. 

One is the possibility of index-based rates, where rates adjust 

based on market trend benchmarks. Another is guaranteed 

contracts, where the carrier provides a lower rate but gets paid 

whether or not they deliver a particular load. 

Electronic logging devices with real-time location data on drivers 

and loads have downsides but also strong upsides, Caplice said, 

and shippers are interested in how they can mine that data. 

There is also the potential to bring ridesharing concepts to 

freight movement, with more loads sold on the spot than the 

contract market. 

“It’s interesting to see what’s going to happen,” Caplice said. 

“Will a larger percentage of truckloads move to spot instead of 

contract if you can ride that market and make it more reliable?” 

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STEPHEN GOLDSMITH, DIRECTOR, INNOVATIONS IN AMERICAN GOVERNMENT PROGRAM, HARVARD UNIVERSITY 

THE FOUR ROLES OF GOVERNMENT 

IN A NEW MOBILITY OPERATING SYSTEM 

September 25, 2018 Watch the video highlights 

A new mobility operating system requires government, 

especially at the city-level, to design transportation 

around the user—not the mode—according to Stephen 

Goldsmith, Director of the Innovations in American Government 

Program at Harvard University’s Kennedy School of Government. 

Governments pursuing new mobility operating systems will have 

data-driven protocols, not strict regulations.They will seek rules 

that make markets work for citizens. And they will give regional 

planners real authority. 

Transportation Meets User Experience 

In Indianapolis, where Goldsmith was mayor from 1992 to 2000, 

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the number of taxi medallions was limited by law. But people who 

needed taxi services most were not getting them, and those who 

wanted medallions lived in those neighborhoods—but couldn’t 

get them, Goldsmith said. 

The issue, in addition to medallion caps, was a transportation 

system designed around a mode—taxis—instead of a system 

that promoted cross-modal mobility. 

“If we think about the user experience of mobility, if we design a 

system around the user, that’s different than designing a system 

around the user of a bus, or a taxi, or a transportation network 

company, or a bike,” Goldsmith said. “If we’re thinking about a 

system designed around the omni-channel experience of the 

user, and if we could come up with that orientation, it would 

dramatically change things.” 

Coding the Curb 

Curb space used to be a maintenance liability for governments. 

Today, the curb is valuable, Goldsmith said. But most cities don’t 

know where their signage is,and the curb is not coded to evaluate 

the cost of using it to drop off from a transportation network 

company vehicle, or perhaps an automated vehicle. 

Los Angeles is one city innovating with curb space through its 

Code the Curb program. Code the Curb identifies where curb 

assets are and seeks to use dynamic pricing related to curb use. 

“As we think about managing mobility, we also need to think 

inherently about managing the curb,” Goldsmith said. “Not 

managing parking, but managing the curb.” 

Making Transportation Markets Work for Residents 

The government role over the past 25 years has been to provide 

transportation, like bus transit, or to regulate transportation, as 

with taxis. In a new mobility operating system, the government’s 

core responsibility would be equity, to ensure communities are 

served broadly, fairly, and openly, Goldsmith said. 

Data that is real-time, accurate, and comes from multiple sources 

can help encourage transportation equity. Government can 

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act as a data aggregator that can inform pricing and consumer 

decisions, Goldsmith said. 

“One of the things we need to consider in this new government 

role is, what information should government require from a 

commercial operator in its jurisdiction as a condition to use its 

easements and streets?” Goldsmith said. “What’s in real-time? 

What’s not in real-time? What formats? How is privacy handled? 

How is anonymity handled? And we need to get there.Sometimes 

it will be relatively easy to negotiate data-sharing agreements, 

and other situations are more complex.” 

Regional Planning—With Authority 

With enormous amounts of information and the ability to code 

the curb, government can take a more enlightened approach 

to managing mobility, Goldsmith said. Government structures, 

however, may not be up to the challenge. In most places, transit 

organizations like metropolitan planning organizations (MPOs) 

are the only regional transportation government bodies, but 

MPOs may not have the authority to innovate at the city level. 

“I would suggest we need to think about new governance 

structures,” Goldsmith said. “We need to think about regional 

governance and more authority for the MPOs, we need to think 

about what the platform looks like.Volpe is a terrific place to 

suggest what the protocols and analytics should look like in 

those platforms.” 
 

 

 

 

KYLE VOGT, FOUNDER AND CEO, CRUISE AUTOMATION 

U.S. DOT UNDER SECRETARY OF TRANSPORTATION FOR POLICY DEREK KAN 

ARTIFICIAL INTELLIGENCE IN TRANSPORTATION: 

A CONVERSATION 

October 4, 2018 Watch the video highlights 

K yle Vogt, founder and CEO of Cruise Automation, and 

Derek Kan, U.S. DOT Under Secretary of Transportation 

for Policy, discussed how automated vehicles fit into current 

transportation systems, and how vehicle automation is a lot like 

NASA’s Apollo program. The following conversation has been 

edited for clarity and length. 

Under Secretary Kan: Kyle started his career just down the 

street at MIT (Massachusetts Institute of Technology). MIT does 

a lot of brilliant things, probably most notably tech development. 

Given all the things you’ve done in your career, walk us through 

some of the big challenges in autonomous vehicle (AV) technology 

development. 

Kyle Vogt:I’ll be the first to say this is a really,really hard problem.

This is one of the first really great applied artificial 

intelligence problems. It’s become clear that building a prototype 

autonomous vehicle is something that 5 or 10 talented engineers 

can do in a few months. 

What is becoming apparent now is that the difference between 

a prototype that can drive around the block once and not hit 

something, and a commercial product that people can entrust 

their safety to, is enormous. It’s several orders of magnitude 

more complex, it takes more time to design, develop, to validate 

and to collect data on, and so there are immense challenges. 

Under Secretary Kan: As everybody here knows, 

transportation is one of the keys to a vibrant economy. The 

sector itself is incredible. So how do AVs fit into the broader 

transportation system? 

Vogt: First off, transportation is huge: 3.2 trillion miles traveled 

in a year. If you look at what AVs could do to that, we can look 

at the rideshare industry as a proxy for what it might become. 

Rideshare companies today drive less than 1 percent of those 3.2 

trillion miles traveled, so everything you think about rideshare, 

that’s just the tip of the iceberg in terms of having an impact on 

transportation. 

AVs have the potential to lower the cost of transportation like 

in rideshare, to the point where a lot of people are going to flip 

from owning a car and all the burden that comes with that to 

using a shared autonomous vehicle on a rideshare network. It’s 

going to make sense economically, it’s going to be safer, more 

convenient, it’s going to give you that time back that you spend 

on your commute. 

Under Secretary Kan: What areas of research and development 

should be done either in the application, development, or testing 

and deployment of AV technology? 

Vogt: The things that are underexploited today are the things 

that come a little further into the future. There’s a lot of focus 

right now on sensor processing and the first versions of selfdriving car systems. What there isn’t as much of is thinking about 

vehicles at a fleet scale. Not just building the first self-driving 

car, but what happens when you have hundreds or thousands 

of these in a city and they’re all sharing information? Can they 

look around corners? How can they coordinate to do things like 

reducing congestion, or even acting as infrastructure for one 

another? 

Under Secretary Kan: You mentioned that AVs are perhaps 

the best application of AI. Help us unpack that a little bit. You 

talked about sensing, but why is today unique and what is the arc 

of AI today that makes this time special? 

Vogt: Engineers love to work on AI problems because there 

are some promising results and there is a lot of innovation in 

the field right now.What’s happening with AVs now is because 

there is a huge market opportunity and because there is a huge 

social impact on improving safety. In our case we’re using electric 

vehicles so it’s a cleaner form of transportation. All of those 

things are motivating more people to enter the space and work 

on these problems. What I meant was this is one of the most 

impactful applied AI problems you can do today. 

People coming out of graduate programs and getting degrees now 

have a place to go where they can take that academic curiosity and 

fascination and apply it to a problem that has perhaps one of the 

largest impacts of any engineering work being done today. That’s 

a powerful combination. This only happens maybe once every 

ten years or several decades where you have this convergence of 

high social impact, deeply challenging technology problems, and 

big market opportunity. When those three things come together 

it creates something really special. I see self-driving cars today as 

the Apollo program of this generation. 

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KIRK STEUDLE, FORMER DIRECTOR, MICHIGAN DEPARTMENT OF TRANSPORTATION 

TRANSFORMATIONAL TECHNOLOGIES: 

A STATE GOVERNMENT PERSPECTIVE 

October 22, 2018 Watch the video highlights 

B efore the traffic signal, a busy intersection could 

easily become a tangle of pedestrians, bicyclists, and 

other vehicles vying for rights of way. The electric traffic 

signal, introduced in the early 20th century, was the first step 

in automating traffic flow, and is one of the first examples of 

automation in transportation. 

“Automation has been continuing since that time, and it’s going 

to continue,” said Kirk T. Steudle, director of the Michigan 

Department of Transportation. 

Vehicle Automation: Safety First 

The primary reason for the explosion of vehicle automation

technology over the past few years is not convenience, or

efficiency, or novelty.

From a road operations perspective, the reason for vehicle 

automation is safety, Steudle said. In 2017, 37,133 people died 

in motor vehicle crashes, and more than 3 million people were 

injured in motor vehicle crashes in 2016. 

“If we know that the technology can save lives, why are we 

waiting to deploy it?” Steudle said. “We can choose to wait to 

deploy when we don’t have a family member in those numbers. 

When we have a family member in those numbers, waiting until 

next year is too long.” 

Many highly automated functions are available on current 

vehicles.With adaptive cruise control, for example, radar keeps 

the vehicle a safe distance from a vehicle that slows down. 

But full automation, where a human is not needed to operate 

or monitor vehicle movement, is many years away, Steudle said. 

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Balancing the Ideal and the Possible 

“It’s easy for us in the technology transportation space to think 

forward,” Steudle said. “In my job, and my counterparts across 

the country, we have to balance what’s possible—what’s utopia 

50 years from now—versus what’s possible next year.And how 

do you manage for the maybe 50 years in the middle?” 

More than half of states allow autonomous vehicles on public 

roads, either by executive order or statute. Michigan is among 

those trying to limit regulatory hurdles to automated vehicle 

deployment. 

“Michigan law allows for complete operations,” Steudle said. “If 

you can buy a vehicle and get FMVSS [Federal Motor Vehicle 

Safety Standards] approval, you can take it to the Secretary of 

State with your insurance certificate, you get a metal plate with 

white and blue letters, and off you go.” 

The future of vehicle transportation may be fully 

automated—but that future isn’t happening tomorrow 

By 2040, 30 percent of vehicles produced will be automated, 

Steudle said. That means 70 percent of vehicles produced will 

likely have highly automated functions, but will also still have a 

brake pedal and steering wheel. 

“We have to understand there is a transition—that as a public 

agency, we’ve got to provide infrastructure for both,” Steudle 

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said. “This is going to be a difficult time. In the near-term, we still 

have a transportation network that has to serve those legacy 

vehicles.” 
 

 

CHRIS URMSON, CO-FOUNDER AND CEO,AURORA 

DELIVERING THE BENEFITS OF SELF-DRIVING TECHNOLOGY

 SAFELY, QUICKLY,AND BROADLY 

October 25, 2018 Watch the video highlights 

T hree things that drivers do: accelerate, brake, and steer. 

Three things drivers don’t do: take naps, write novels, 

catch up on work, or anything that takes time and doesn’t involve 

driving. 

But self-driving cars could free up two weeks every year for the 

average driver, according to Chris Urmson, co-founder and CEO 

of Aurora, who delivered the final talk in the U.S. DOT Volpe 

Center’s Transportation in the Age of Artificial Intelligence and 

Predictive Analytics speaker series. 

If cars drove themselves, they wouldn’t just give commuters back 

time. They could vastly improve mobility options for people with 

disabilities, and they could save thousands of lives. 

“We think about the opportunity to save 140 lives a day,” Urmson 

said. “We think about the fact that 6 million people don’t have 

access to transportation that they should, and by bringing this 

technology to market we can enable them to have the mobility 

that we all take for granted.” 

The Driver and the Rider:Two Directions for 

Self-Driving Vehicles 

Current levels of vehicle automation require that people be alert 

and in charge of driving. The future of self-driving vehicles may 

continue to follow this path, with drivers ultimately responsible 

for safe vehicle operation. 

Or, the future may be one of widespread, high-level vehicle 

automation, where the driver becomes a rider, Urmson said. 

“There’s profound opportunities for change by getting the

technology to the point where you can sit back and it’s really 

the technology getting you where you want to go on your day,” 

Urmson said.“We think about that as riding in the vehicles.” 

Automation Could Bring Big Cost Savings 

According to Urmson’s “cocktail napkin math,” a ride with a 

transportation network company costs about $1.60 per mile. 

That’s 60 cents for the vehicle and a dollar for the driver. A 

vehicle operating at a high level of automation would bring 

today’s dollar cost for the driver down to 10 cents per mile— 

and with three trillion miles of road in the United States, that 

could mean big aggregate cost savings. 

“That’s a $300 billion economic opportunity,” Urmson said. 

“This is really the direction this technology is going to push.” 

Success for Self-Driving Cars Comes Down To 

Improving Mobility and Safety 

The brother of the best man at Urmson’s wedding was in his 

early 20s when he was paralyzed. He was driving in northern 

Canada and hit a moose. If vehicle automation had existed, that 

accident might never have happened, Urmson said. 

“He’s had an incredible career,” Urmson said.“He’s been in 

politics, he was a cabinet minister in Canada, but throughout that 

time he has had to rely on others to get around. He never had 

privacy in transportation. It’s never been on-demand the way you 

or I would take it for granted. So, giving someone like him the 

mobility and access that we have is just incredible.” 

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