Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
CTR Introduction
1. Center for Transportation Research
UT Austin
1616 Guadalupe, Suite 4.202
Austin, Texas 78701
http://ctr.utexas.edu/
2. Vision
• Serve the public through transportation research,
linking research with practice, and promoting a
safer, happier, & healthier society.
• Contribute to development of transportation
workforce through research-based & experiential
learning.
3. CTR Library
• TxDOT Research
Library
• One of the 1st and
largest resources
affiliated with a
university or DOT
• Over 24,000 catalog
items
4. ITS Initiatives in the State of Texas
Projects from the Center for Transportation Research
at The University of Texas at Austin
(Thanks to Alice Chu and Kristie Chin)
5. Areas of Research
Connected &
Autonomous
Vehicles
Emerging
Technologies
Policy Impact
Analysis
Pavements &
Infrastructure
6. Areas of Research
Connected &
Autonomous
Vehicles
Emerging
Technologies
Policy Impact
Analysis
Pavements &
Infrastructure
7. Connected & Autonomous Vehicles
Objective
– Develop a framework to harness
and mature wireless technology to
improve transportation safety
– Cyber-security considerations in
V2X communications
Outcomes
– Research and technology transfer
– Improved roadway safety
– Effective and customized safety
systems
– Improved privacy & security
Communications and Radar-Supported Transportation Operations
and Planning / Related Research Projects
8. Connected & Autonomous Vehicles
Consumer Preferences and
Willingness to Pay for Advanced
Vehicle Technology Options and Fuel
Types
Objective
– Analyze consumer preferences for
advanced vehicular technologies
Outcomes
– Heterogeneity in preferences for
wireless internet, vehicle
connectivity, voice command
features
– Less heterogeneity in preferences
for real-time traveler information
Data-Supported Transportation Operations & Planning
Other Projects
Transit Demand and Routing after
Autonomous Vehicle Availability
Semi-Autonomous Parking for
Enhanced Safety and Efficiency
Learning Approach to Beam
Alignment for mmWave Vehicular
Communications