(gentle music)
- [Narrator] Texas has emerged
as a center for automated trucking operations,
with daily routes managed by various companies.
That in turn means the state's infrastructure
is crucial for ensuring the safety of current drivers,
while preparing for future connected and automated vehicles.
Researchers investigated ways
to access real-time data on pavement, signage,
and other road conditions
to modernize maintenance operations
that will benefit the driving public.
- TxDOT will spend a lot of money and time
planning for and carrying out roadway maintenance.
- Currently, TxDOT relies on quarterly inspections
for its staff members
to manually detect roadway maintenance issues
such as potholes, guard rail damage or fallen signs.
- [Jianming] But it's autonomous trucks,
they're currently operating across the state.
There's an opportunity to use data these trucks
are already collecting about roadway conditions.
- [Kristie] Each of these trucks
is actually equipped with a number
of sophisticated cameras and sensors
that are able to detect several
of these roadway maintenance issues.
So CTR and TxDOT partner
with two autonomous trucking companies,
Kodiak Robotics and Aurora, to share data
related to six different routine maintenance issues.
- Basically, we got data from Kodiak and Aurora
on five TxDOT roadways across 13 districts.
We developed a prototype and we tested it out in Odessa
and the Dallas districts.
- We leveraged TxDOT's Nighttime Inspection Suite,
which is an ESRI app built
in partnership with TxDOT's ITD division.
So we worked with them to upload the AB trucking data
and create a feature layer
in the nighttime inspection app alongside the portal
that TxDOT maintenance teams traditionally use.
The second piece, we worked with the Odessa district,
the Houston district,
and the Dallas district to access the data,
test it out, and provide input on how they used it
and in which cases it was helpful
to their maintenance operations.
And then the last piece of location and process
was a Tableau dashboard.
So we developed a dashboard for maintenance,
personnel, and leadership to visualize the data,
look at trends in maintenance events,
locations, roadways, different indicators,
and help prioritize and allocate resources
through that Tableau dashboard.
- So overall, the project was able to demonstrate the value
of using autonomous trucking data
to address these routine maintenance issues
in a more timely manner.
There's interest from TxDOT
to advance an implementation project
that would automate several different steps.
So in particular, the autonomous trucking companies
are interested in automating the data collection process
and then uploading information directly
to TxDOT's nighttime inspection app.
And this process could be expanded
to include additional TxDOT districts
beyond the ones that were involved in this project,
really to grow as the autonomous trucking space
expands across Texas.
- [Narrator] For more information
and to find the publication for this project,
please visit the TxDOT research library
at the link shown below.