(graphic whooshing)
- [Narrator] Although completely
autonomous self-driving cars are still years away,
semi-autonomous vehicles already travel our roadways.
To prepare for fully-autonomous vehicles,
digitizing the locations of traffic control infrastructure,
like traffic signals, signs, and intersections,
is essential to safely ushering in that future reality.
The Texas Department of Transportation funded research
led by the Texas A&M Transportation Institute
to study the use of emerging data sources
in mapping TCI locations
with the ultimate goal of improving the safe interaction
of automated vehicles with the driving environment.
- Autonomous vehicles heavily rely on the sensing devices
to operate safely on our roads.
However, when the sensors fail,
having access to digitized data about roads
or traffic signs becomes critical
for the vehicle's continued operation.
The main goal of this project was to develop a framework
for digitizing and providing TCI data
to autonomous vehicles.
- Basically, the research team focused
on enhancing the traffic control infrastructure
to provide a digital access to automating codes
and adding some redundancy
to their perception system for improved safety.
- The most important thing we have accomplished
in this project is that we have built up
additional map layer with up-to-date TCI information,
so the AV sensors can be augmented
by this digital TCI map layer,
and also this map layer can also provide redundancy
for AV perception and safety.
- The research also explored the various, you know,
traffic control infrastructure digitization approaches,
including like data collection,
the artificial intelligence solutions,
and dashcam image processing.
The research team also acquired
some sample traffic control infrastructure datasets
from some of the commercial companies.
- We evaluate and collect this kind of TCI dataset.
Then we do the quality check and the data fusion.
We get the final, more complete,
more accurate TCI layer.
Then we pass this layer to our UT data team.
They can use this layer to do the simulation
on their AV simulation platform called the MATISSE.
- The simulations clearly demonstrated the positive impact
of TCI-digitized data on AV operations.
However, the simulations also unveiled
that in certain scenarios,
AVs cannot solely rely on digitized data
to ensure safety operations.
- This team also addressed the potential legal issues
and that created a data management plan for the agency.
This project offers the department a streamlined framework
for textiles, traffic control,
infrastructure digitization and sharing.
And I think this traffic control infrastructure layer
enhances automated vehicle perception and safety,
and it presents a robust solution
for improved AV integration into Texas roadway system.
- [Narrator] For more information
and to find the publications for this project,
please visit the text at research library
at the link shown below.