Presentation describes how automobile companies developing self-driving cars and NASA face similar challenges which can be solved using similar technologies. To provide context, the presentation also describes how NASA Ames is working with automobile companies, such as Nissan, to research and development relevant technologies

Fong, Terrence W.

Worden, Simon Peter

NASA Technical Reports Server

https://ntrs.nasa.gov/search.jsp?R=20150021270 2019-08-31T05:53:54+00:00Z
2 
NACA Laboratories 
NACA 
Langley 
Joseph S. Ames 
Ames 
Lewis 
Dryden 
NASA 
1958 1946 1940 1939 1915 
3 
Aerial View of NASA Ames Research Center 
4 
1940 
Conical  
Camber 
Lifting Body 
Swept- 
Back/Wing 
Transonic  
Flow 
Flight 
Simulator 
Apollo  
Re-Entry Shape 
Hypervelocity Free 
Flight 
Apollo  
Guidance  
System 
Apollo Heat  
Shield Tests 
Arcjet Research 
1960 
Life Sciences  
Research 
Viking 
80x120 Wind Tunnel 
1970 
1980 
1990 2000 
2014 
CFD 
ER-2 
Astrobiology 
Institute 
NASA Research 
Park 
Pleiades 
SOFIA 
Kepler 
LCROSS 
1950 
Flight  
Research 
Blunt Body  
Concept  Pioneer 10/11 
Pioneer 
Venus 
Tiltrotor 
Kuiper Observatory 
X-36 
Galileo 
Tektites 
Nanotechnology 
LADEE 
O/OREOS 
IRIS 
Aero 
Institute 
Air 
 Transportation 
   System 
Mars Science 
Lab 
SSERVI 
Space 
Biology 
Sustainability 
Base 
Human 
Centered 
Computing 
Lunar 
Prospector 
Quantum 
Computing 
5 
Ames Technology Areas 
Aerospace and 
Aeronautics Integrated Systems 
Health 
Management (ISHM) 
Small Satellite Systems 
Robotics and Artificial Intelligence 
Systems Engineering 
Materials Science and  
Entry Systems 
High-end Computing & Quantum 
Computing 
BioTech / Biomedical 
Astrobiology 
Institute 
SSERVI 
6 
International Partnerships 
 1. Australia 
 2. Brazil 
 3. Denmark 
 4. France 
 5. Japan 
 6. India 
 7. Ireland 
 8. Israel 
 9. Italy 
10. Mexico 
11. Norway 
12. Poland 
13. Spain 
14. S. Korea 
15. UAE 
16. UK 
 1. Canada 
 2. Chile 
 3. France 
 4. Germany 
 5. Italy 
 6. Japan 
 7. Lithuania 
 8. Mexico 
 9. Netherlands 
10. Norway 
11. Saudi Arabia 
12. Sweden 
13. Spain 
14. Trinidad & 
Tobago 
15. UK 
Interns & 
Researchers 
Technical 
Collaboration 
7 
•  Managing fleets of autonomous 
and semi-autonomous vehicles in 
space, extra-planetary surfaces, 
and in the National Air Space  
•  Networked vehicles monitored and 
operated from a control center  
•  Semi-autonomous control 
•  Human-autonomy teaming 
•  Deep-space human missions 
•  Requires increasingly autonomous 
crew operations 
•  Requires autonomy that is reliable, 
resiliant, and robust 
•  Requires effective human-autonomy 
coordination and collaboration 
NASA Challenges 
8 
NASA  
Missions"
Planned human- 
machine interaction  
in natural and time  
delayed environment"
Space & planetary nav"
Spacecraft autonomy"
Cyber-security for  
“one-off” systems"
Space environment"
Limited ability to 
address/recover faults "
Etc."
Self-Driving 
Cars"
Diverse human- 
machine interaction 
in a structured   
environment "
GPS & map-based  
navigation "
Distributed and 
cloud-based  
autonomy"
Cyber-security for  
consumer product"
Etc."
Autonomy"
Advanced Planning & "
Scheduling Algorithms, etc."
Human-Autonomy Teaming"
Robotic Supervision including "
Human/Robotic Interactions, etc. "
Networked Operations"
Remote Vehicle Management, etc."
Prognostics and Diagnostics"
Including State Management, etc."
Sensor Technologies"
Data Processing / Fusion"
Methodologies, etc. "
Verification & Validation"
Methodologies &"
Application Experiences, etc."
Common  
Technologies "
9 
•  Self-driving cars require planning, 
navigation and coordination 
•  On-board autonomy: automated 
hazard mapping, obstacle avoidance, 
local path planning; non-GPS matching 
terrain to 3D and image data. 
•  Off-board autonomy: telemetry 
monitoring, data archiving, mapping, 
etc. for remote support  
•  New autonomy approaches can  
be applied to NASA missions 
•  Manned and robotic deep space 
exploration  
•  Unmanned Aerial System Traffic 
Management (UTM)  
•  Safe Autonomous Systems Operations 
Autonomy 
10 
•  Self-driving cars provide testbeds 
of cyber-physical systems  
•  Increasingly autonomous agents 
communicating with each other to plan 
and execute coordinated activities  
•  Minimal / intermittent human support 
•  Field testing of managing set or swarm 
of autonomous and semi-autonomous 
systems in real-time 
•  Complex multi-vehicle operations  
•  Changing/uncertain environments  
•  Information is passed directly from one 
vehicle to another.  
•  Wireless cloud-based architecture 
continuously tracking constraints 
and dynamically adjusting routing 
Networked Operations 
11 
•  Self-driving cars are an ideal test-
bed for maturing advanced vehicle 
prognostics/diagnostics 
•  Complex interaction with a dynamic 
environment and situations 
•  Large amount of test time. 
•  NASA can use these test-beds to 
develop real-time prognostic and 
diagnostic methods 
•  Application to a wide range of crewed 
space vehicles (including but not 
limited to surface vehicles) 
•  Application to unmanned aerial 
systems, single pilot operations and air 
traffic management. 
Prognostics and Diagnostics  
12 
•  Self-driving car companies are 
developing new, rugged, low-cost, 
high-performance sensors 
•  Lidar: flash and scanning 
•  Radar: high-res narrow angle 
•  Real-time stereo vision 
•  These sensors are needed for: 
•  Detecting static/dynamic hazards 
•  Mapping and positioning (localization) 
•  Sensors (and algorithms) can be 
applied to NASA missions 
•  Robots (Space Station Free-Flyers, 
planetary rovers, etc.)  
•  Unmanned Aerial Systems in  
the National Air Space 
Sensor Technologies 
13 
•  Self-driving cars represent one of 
the most challenging applications 
for V&V due to the unpredictability 
of the operational environment: 
•  variable lighting / shadows 
•  weather 
•  human/automation interaction  
(driver, bystander, cyclist, etc.) 
•  dynamic road environment 
•  mixed-initiative decision making 
•  New V&V methods can be applied 
to future exploration mission 
systems, particularly those that 
involve high reliance on autonomy 
(e.g., evolvable Mars) 
Verification and Validation 
14 
•  Variety of approaches 
•  Google and Nissan are developing 
fully self-driving vehicles  
•  BMW, Mercedes Benz, etc are 
pursuing targeted autonomy (e.g.,  
self-parking, lane changing, etc.) 
•  Manned deep space missions will 
require better human-autonomy 
teaming than we have today 
•  Increased aviation autonomy 
•  Depends on many factors 
•  Control center to help resolve off-
nominal situations 
•  Requires public trust in autonomous 
vehicles 
Human-Autonomy Teaming 
15 
Applicability to NASA Goals 
Autonomy" Networked Operations"
Prognostics 
and 
Diagostics"
Sensor 
Technology"
Verification 
and"
Validation"
Human-
Autonomy 
Teaming"
Manned Deep 
Space Missions" +++" +" +++" ++" +++" +++"
Robotic Deep 
Space Missions" +++" ++" +++" +++" ++" +++"
Single-Pilot 
Operations" ++" ++" ++" ++" +++" +++"
Tele-Robotic 
Operations" +" ++" ++" +++" ++" ++"
Unmanned 
Aerial Systems" +++" +++" ++" +++" ++" +++"
Air Traffic 
Management" +++" +++" +++" ++" ++" ++"
Self-Driving Car Technology Challenges"
NA
SA
 C
ha
lle
ng
es
"
+++  Strong Alignment 
++    Moderate Alignment 
+      Partial Alignment 
16 
•  Aligned with NASA autonomy 
development priorities 
•  Enables NASA to gain valuable 
knowledge and lessons learned 
from extensive real-world testing 
•  Enables joint development and 
demonstration of high-impact 
vehicle applications  
•  Mobility, transport, remote ops, and 
cyber-physical systems 
•  Facilitates spin-off of NASA 
technologies to the private sector 
•  Robot navigation, perception, user 
interface, etc. 
•  Dual-use in energy, environment, 
security, and other terrestrial domains. 
Self-Driving Cars at NASA Ames 
17 
•  R&D agreement (5 year term) 
•  Autonomous vehicle systems 
•  Human-machine interface 
•  Network-enabled applications 
•  Software analysis and verification 
•  Vehicle testing at NASA Ames 
•  Initial focus: Tele-robotics technologies 
•  Application of NASA algorithms and concepts 
•  Joint development, testing, and assessment 
•  Demonstration: fleet management of multiple autonomous vehicles 
Nissan-NASA Partnership 
1 of 13                       SAA2-402911 
REIMBURSABLE UMBRELLA SPACE ACT AGREEMENT  
BETWEEN  
THE NATIONAL AERONAUTICS AND SPACE ADMINISTRATION, 
AMES RESEARCH CENTER 
AND  
NISSAN NORTH AMERICA, INC.  
FOR  
RESEARCH AND DEVELOPMENT 
  
 
ARTICLE 1. AUTHORITY AND PARTIES  
  
In accordance with the National Aeronautics and Space Act (51 U.S.C. § 20113), this 
Agreement is entered into by the National Aeronautics and Space Administration Ames 
Research Center, located at Moffett Field, CA 94035 (hereinafter referred to as "NASA" 
or "NASA ARC") and Nissan North America, Inc., Nissan Research Center Silicon 
Valley, located at 1215 Bordeaux Drive, Sunnyvale, CA 94089 (hereinafter referred to as 
"Partner" or "Nissan").  NASA and Partner may be individually referred to as a "Party" 
and collectively referred to as the "Parties." 
  
ARTICLE 2. PURPOSE AND IMPLEMENTATION  
  
This Umbrella Agreement (hereinafter referred to as the "Agreement" or "Umbrella 
Agreement") shall be for the purpose of research and development. Potential areas of 
partnership include autonomous vehicle systems, robotics, human-machine interface, 
software analysis/verification, and network-enabled applications. These areas represent 
crosscutting topics with applications spanning mobility, transport, remote operations, and 
next-generation cyber-physical systems. In addition, technology developed in each area 
has significant potential for dual-use in energy, environment, security, and other 
terrestrial domains. 
 
The Parties shall execute one (1) Annex Agreement (hereinafter referred to as the 
"Annex") concurrently with this Umbrella Agreement.  The Parties may execute 
subsequent Annexes under this Umbrella Agreement consistent with the purpose and 
terms of this Umbrella Agreement. This Umbrella Agreement shall govern all Annexes 
executed hereunder; no Annex shall amend this Umbrella Agreement.  Each Annex will 
detail the specific purpose of the proposed activity, responsibilities, schedule and 
milestones, and any personnel, property or facilities to be utilized under the task. This 
Umbrella Agreement takes precedence over any Annexes. In the event of a conflict 
between the Umbrella Agreement and any Annex concerning the meaning of its 
provisions, and the rights, obligations and remedies of the Parties, the Umbrella 
Agreement is controlling. 
  
ARTICLE 3. RESPONSIBILITIES 
 
A. NASA ARC will use reasonable efforts to: 
18 
Candidate Test Routes at NASA Ames 
•  urban zones 
•  rural zones 
•  up to 40 km/hr 
19 
•  Develop Fleet Management 
•  Focus on remote monitoring for 
transport (taxi service, goods delivery) 
•  Adapt and enhance NASA robot 
operator interfaces to Nissan vehicles 
•  Demonstrate proof-of-concept using 
NRC-SV simulator 
•  Key 2015 activities 
•  March  Digital street map of NASA 
 Ames for NRC-SV simulator 
•  April  Integrate 3D model of Nissan 
 Leaf in NASA user interface 
•  Sept.  Dynamic map updates to 
 from simulator to interface 
•  Dec  Demo remote monitoring of 
 single vehicle in NRC-SV 
 simulator from NASA Ames 
Nissan-Ames 2015 
20 
•  Test Fleet Management Concept 
•  Extend monitoring from single vehicle 
to multiple vehicles 
•  Add technology for remote intervention 
(diagnose and handle contingency 
situations) 
•  Test with NRC-SV simulator and 
Nissan vehicle at NASA Ames 
•  Key 2016 activities 
•  March  Fleet management test with  
 NRC-SV simulator 
•  June  Complete implementation of  
 multi-vehicle monitoring 
•  Sept.  Demo #1 of Nissan Leaf at 
 NASA Ames 
•  Dec  Demo #2 of Nissan Leaf at 
 NASA Ames 
Nissan-Ames 2016 


How NASA's Technology Can Help the Automotive Industry

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