ANN ARBOR, Mich., Aug. 2, 2017 /PRNewswire/ -- Toyota's
Collaborative Safety Research Center (CSRC) today announced a
sweeping set of new research programs studying the opportunities
and addressing the challenges of emerging vehicle technologies. The
eleven projects, launched in partnership with eight leading
research institutions in North
America, mark the first projects launched under CSRC Next,
the Center's new five-year program that continues to support a
safer transition to the future of mobility.
The research projects will focus on the impact of advanced
technology on broader road safety trends and the interaction
between humans and machines. Specific research challenges include
the integration of advanced active safety systems, like automatic
emergency braking, and passive systems, human experience design for
advanced technology vehicles, driver state detection, and using
analytics to help improve the study of naturalistic driving
data.
"Autonomous and connected vehicle technologies are only just
beginning to transform the transportation landscape," said
Chuck Gulash, Director of CSRC. "By
working together with world-renowned institutions and making our
results public, we are proud to help realize the promise of
advanced mobility solutions and a safe, convenient transportation
future."
Since its launch in 2011, CSRC has launched and completed 44
research projects with 23 partner universities, publishing more
than 200 papers and presenting at multiple industry conferences.
CSRC projects have made meaningful contributions to auto safety
industrywide, including research into human factors on vehicle
safety and the efficacy of active and passive safety systems, as
well as the collection of driving data and development of new tools
to analyze that data.
Launched in January 2017, CSRC
Next builds upon the insights gained from the CSRC's first five
years and will direct $35 million
towards safety research into advanced vehicle technologies,
including both autonomous and connected systems. CSRC Next will
continue to support ongoing research programs at the Toyota
Research Institute (TRI) and Toyota Connected (TC) to help
accelerate the development of autonomous and connected driving
technologies and services.
CSRC projects will follow four research tracks:
- The potential integration of advanced active safety systems and
passive safety systems, using advanced pre-crash sensors to improve
and personalize crash protection;
- Building research models to help understand and strengthen the
driver-vehicle relationship, and to support the social acceptance
of advanced vehicle technologies;
- Studying driver state detection, working to improve mobility
using metrics for physiology and health;
- Applying big data and safety analytics techniques to develop
algorithms and tools to study naturalistic driving data.
The full list of new CSRC Next research projects and partners
includes:
Project
Title
|
Description
|
Partner
|
Motion and Muscle
Activation of Young Volunteers in Evasive Vehicle
Maneuvers
|
Quantify key occupant
responses (kinematics and muscle activity) to evasive swerving and
emergency braking using both adult and child subjects on a test
track.
|
Children's Hospital
of Philadelphia
|
Integrated Benefit
Estimation for Comprehensive Active / Passive Systems
|
Estimate the Residual
Safety Problem after Integrated Safety Systems (ISS) is deployed in
the future. ISS consists of all active (auto braking for vehicle,
pedestrian, bicyclist, lane keeping, etc.) and passive safety
systems (advanced airbag, curtain shield airbag, roof strength,
pedestrian protection active hood, etc.).
|
Virginia
Tech
|
Vehicle Occupant
Dynamics During Crash Avoidance Maneuvers
|
Investigate
kinematics of minimally aware adult occupants exposed to Automatic
Emergency Braking (AEB) and evasive maneuvers on a test
track.
|
University of
Michigan Transportation Research Institute
|
Study for Developing
an In-Vehicle Emergency Medical Condition Detection
System
|
Develop a
computational technique for noise tolerant robust detection and
prediction of Myocardial Infarction and Myocardial Ischemia (MI)
inside a vehicle. Machine learning models will be trained with ECG
data collected from in-hospital and in-vehicle subjects to help
detect and predict the in-vehicle occurrence of MI as well as other
related severe cardiac arrests.
|
University of
Michigan Center for Integrative Research in Critical Care
(MCIRCC)
|
Adaptive Headlamp
System Benefit Estimation
|
Measure the response
characteristics and estimated benefit with respect to reduction in
injury/fatalities of adaptive headlamp system that highlights
detected pedestrians and bicyclists using both driver and
pedestrian/bicycle simulator study.
|
University of Iowa –
National Advanced Driving Simulator
|
Naturalistic and
Controlled Driving Studies – Transitions in Automated
Driving
|
Provide a meaningful
and useful dataset of driver behaviors when encountering situations
where transfer of control between automation and the human is
required.
|
University of Iowa –
National Advanced Driving Simulator
|
Road Departure Test
Method Development
|
Develop test
scenarios and methods for the evaluation of vehicle road departure
warning, assist and control systems on a test track.
|
Indiana
University-Purdue University Indianapolis, Transportation Active
Safety Institute (TASI)
|
Analysis of
Communication Between Drivers – The Language of Driving
|
Identify what kind of
communication we have with other road users (e.g., pedestrians,
other vehicles) with cutting-edge technology of computer
vision.
|
Massachusetts
Institute of Technology Age Lab
|
Surrounding
Environment Recognition Technology and Evaluation
Metrics
|
Develop a deep
learning based full-scene recognition of vehicle environment from a
vision sensor. Examples are vehicles, pedestrians, bicyclists,
traffic signs, buildings, curbs, etc.
|
Massachusetts
Institute of Technology Age Lab
|
Theory of
Communication Between Drivers – Enhancing Social
Interaction
|
Provide theoretical
and mathematical framework of how drivers communicate at an
intersection.
|
University of
Wisconsin
|
Human Centered
Automated Driving in the Real World: Holistic Perception and
Performance Metrics
|
Provide a
computational prediction model for a transfer of control between
the automation and the human driver. The model has factors
originated from human motor and perceptual behaviors as well as
from scenarios and environments.
|
University of
California, San Diego
|
Media Contacts:
TMNA Corporate Communications
Brian Lyons
469-292-3573
brian.lyons@toyota.com
Ming-Jou Chen
469-292-3799
ming-jou.chen@toyota.com
About Toyota
Toyota (NYSE:TM) has been a part of the cultural fabric in the U.S.
and North America for 60 years,
and is committed to advancing sustainable, next-generation mobility
through our Toyota and Lexus brands. During that time, Toyota has
created a tremendous value chain as our teams have contributed to
world-class design, engineering, and assembly of more than 33
million cars and trucks in North
America, where we operate 14 manufacturing plants (10 in the
U.S.) and directly employ more than 46,000 people (more than 36,000
in the U.S.). Our 1,800 North American dealerships (nearly
1,500 in the U.S.) sold almost 2.7 million cars and trucks (2.45
million in the U.S.) in 2016 – and about 85 percent of all Toyota
vehicles sold over the past 15 years are still on the road
today.
Toyota partners with community, civic, academic, and
governmental organizations to address our society's most pressing
mobility challenges. We share company resources and extensive
know-how to support non-profits to help expand their ability to
assist more people move more places. For more information about
Toyota, visit www.toyotanewsroom.com.
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