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(gentle music)

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- [Narrator] Texas has emerged

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as a center for automated
trucking operations,

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with daily routes managed
by various companies.

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That in turn means the
state's infrastructure

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is crucial for ensuring the
safety of current drivers,

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while preparing for future
connected and automated vehicles.

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Researchers investigated ways

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to access real-time data
on pavement, signage,

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and other road conditions

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to modernize maintenance operations

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that will benefit the driving public.

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- TxDOT will spend a lot of money and time

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planning for and carrying
out roadway maintenance.

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- Currently, TxDOT relies
on quarterly inspections

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for its staff members

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to manually detect
roadway maintenance issues

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such as potholes, guard
rail damage or fallen signs.

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- [Jianming] But it's autonomous trucks,

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they're currently
operating across the state.

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There's an opportunity
to use data these trucks

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are already collecting
about roadway conditions.

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- [Kristie] Each of these trucks

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is actually equipped with a number

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of sophisticated cameras and sensors

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that are able to detect several

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of these roadway maintenance issues.

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So CTR and TxDOT partner

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with two autonomous trucking companies,

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Kodiak Robotics and Aurora, to share data

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related to six different
routine maintenance issues.

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- Basically, we got data
from Kodiak and Aurora

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on five TxDOT roadways
across 13 districts.

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We developed a prototype and
we tested it out in Odessa

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and the Dallas districts.

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- We leveraged TxDOT's
Nighttime Inspection Suite,

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which is an ESRI app built

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in partnership with TxDOT's ITD division.

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So we worked with them to
upload the AB trucking data

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and create a feature layer

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in the nighttime inspection
app alongside the portal

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that TxDOT maintenance
teams traditionally use.

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The second piece, we worked
with the Odessa district,

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the Houston district,

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and the Dallas district
to access the data,

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test it out, and provide
input on how they used it

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and in which cases it was helpful

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to their maintenance operations.

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And then the last piece
of location and process

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was a Tableau dashboard.

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So we developed a
dashboard for maintenance,

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personnel, and leadership
to visualize the data,

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look at trends in maintenance events,

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locations, roadways, different indicators,

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and help prioritize and allocate resources

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through that Tableau dashboard.

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- So overall, the project was
able to demonstrate the value

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of using autonomous trucking data

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to address these routine
maintenance issues

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in a more timely manner.

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There's interest from TxDOT

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to advance an implementation project

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that would automate
several different steps.

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So in particular, the
autonomous trucking companies

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are interested in automating
the data collection process

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and then uploading information directly

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to TxDOT's nighttime inspection app.

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And this process could be expanded

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to include additional TxDOT districts

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beyond the ones that were
involved in this project,

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really to grow as the
autonomous trucking space

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expands across Texas.

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- [Narrator] For more information

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and to find the publication
for this project,

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please visit the TxDOT research library

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at the link shown below.