National Academy of Sciences Building
Washington D.C.
Informal report
Peter Sweatman (Chair)
Maxime Flament (Co-Chair)
Bob Denaro
Outline
• Symposium concept
• Event April 14-15 2015
– NAS Washington DC
• Beyond the technology
– Economic, environmental and societal implications
• Identifying opportunities for research
collaboration
Symposium Concept
Planning Committee
US
• Peter Sweatman, University
of Michigan Transportation
Research Institute, Chair
• David Agnew, Continental
Automotive
• Robert Denaro, ITS
Consulting
• Ginger Goodin, Texas A&M
Transportation Institute
EU
• Maxime Flament, ERTICO–ITS
Europe, Vice Chair
• Roberto Arditi, SINA Group
• Aria Etemad, Volkswagen AG,
Germany
• Natasha Merat, University of
Leeds
4
Towards Road Transport Automation:
Opportunities in Public-Private Collaboration
5
Mission
What are the complementary roles and
responsibilities of the actors in a Public-Private
ecosystem needed to drive the evolution of the
automated vehicles towards a 21th century
mobility system (integrating and optimising
vehicle, user, and infrastructure)?
6
Expected Outcome
• Foster Transatlantic Partnerships and future
collaboration on research areas of mutual
interest
• Draw out research challenges worthy of
international collaboration
7
Key Elements
White papers, Constituencies, Key
Topics, Use Cases
White Paper #1
Road Transport Automation as a Public–Private Enterprise, Steven
Shladover and Richard Bishop
• Diversity of automation concepts
• Diversity of operational environments
• Different deployment approaches:
everything somewhere vs something
everywhere
• Need for support from infrastructure
• New business models emerging
• How safe is safe enough?
White Paper #2
Road Transport Automation as a Societal Change Agent,
Risto Kulmala and Oliver Carsten
• Significant potential benefits both in short and
long term but disadvantages exist as well
• High uncertainties on best deployment models
• Major challenges related to mixed traffic and
other vulnerable road users
• Potentially higher costs of operation allocated to
all road transport actors e.g.training,
maintenance, periodic inspections, signage, road
markings, digital infrastructure, accurate, traffic
information
Constituencies
Automotive (8)
Authorities (5)
Infra/Road
Operators (6)
Public Transport
(3)
Goods Transport
(3)
Users/Drivers/
VRU (2)
Shared
Vehicles/Fleet
(1)
Insurers (2)
Service Providers
(4)
Research (12)
Legal/Lawyers
(2)
11
Key Topics
Legal
Business
Models
Security
Policy
Making
Technology
Human
Factors
Testing
Acceptance
12
Use Case Scenarios
Use Case 2
Use Case 1
Moderately Automated
Highway Operation
(Platooning)
Highly Automated
Urban Operation
Use Case 3
Fully Automated
Tailored Mobility
Service (Urban
Chauffeur)
Automated Driving Use Cases
USE CASE
Level of
Autom.
(SAE)
1 Freeway
platooning
2-3
2 Automated
city centre
3-4
3 Urban
Chauffeur
4
Speed
High
(> 70
mph)
Low
(10-40
mph)
Low
(< 25
mph)
Dedicat Private Example
ed
or
s
space public (project
needed
s)
Possibly BOTH Sartre,
both
Peloton
No
PRIVAT Adaptive
E
Both
PUBLIC Google,
Citymob
il2
Preliminary Observations
a personal sampling
Use Case #1: Freeway platooning
Moderately automated highway operation
• May be a good business case for fleets but it addresses only
highways and limited transport issues
– What is the benefit across fleets? Who should be first in line? How
does it affect non-users?
– Early benefits modest due to wider gaps and slower speeds for
vehicles
• Challenges related to functional safety, dumb trailers,
acceleration and braking capacity, cooling vents, lead driver
responsibilities, planning of platoons, fleet relations,
acceptance
• Liability, driver training and licensing issues may be overcome
Large-scale platoon pilots and field tests are needed for further learnings
Use Case #2: Automated City Center
Highly automated urban operation, low-speed, no dedicated space
• Focus on improving safety and efficiency where it is
most needed i.e. in urban environment
• Opens for sharing economy solutions
• May not answer some of the current trends in urban
development policies
• Challenges in human factors in mixed urban traffic,
urban traffic management, needs for investment in
facilities, certification of roads and vehicles, liability
of L3, quantification of impacts and costs, business
models, role of collected data, need for AI &
machine learning.
Most urgent research needs:
Human Factors, Legal and liability framework and evaluation of impacts
Use Case #3: Urban Chauffeur
Highly automated urban mobility service, low-speed, dedicated or shared space
•
•
•
•
•
•
•
Offers large savings for first- last- mile of public mass transit, transport accessibility and
urban goods deliveries
Opens to new urban center design in-line with “liveable cities” concept
Reduces the need and usage of private cars
Requires political courage and careful community consultations: regulatory barriers
Not clear public acceptance for trading off status quo
Cybersecurity and data privacy concerns
High safety paramount, certification issue
– How safe is safe enough?
– Interactions with vulnerable road users
Most urgent research needs: Large scale trials, interaction with VRU, minimum standards
and performance requirements, impact, acceptance, cybersecurity, certification models
Other takeaways
• Never underestimate the power of status quo
• Importance of data collection, sharing and analysis is
underestimated
• Level 3 may not be viable from a liability stand point
• Levels of automation are helping the expert communities
but are not designed for the wide public: functionalities
will be the end-products
• Keep the end-users in mind, solving problems that people
have in getting around
• It is not enough to be as safe as today: What is safe
enough?
FOTs, deployments, use cases
• No common understanding of the terminology!
• FOTs
– Data on technology + user behavior
• Deployments
– Model deployments
• Platform validation
– Initial deployments
• User benefits
• Use cases
– Embedded operation of technological platforms and business
models
– Specific, advantageous locations with known policy
environments
The clarity challenge
Three levels of definition
Differing philosophies
• Goals of the system (e.g.
enhancing driving comfort,
reducing travel time,
improving user safety or
broader traffic safety)
• Roles of the driver and the
vehicle (SAE levels 0-5 deal
with this aspect)
• Complexity of the operating
environment
• Everything somewhere
• Something everywhere
• How safe is safe enough?
• Incrementalism
• Responsible capitalism
• Certification and regulation
Role(s) of research community
• Research support in key topic areas
–
–
–
–
–
–
–
–
Technology readiness
Human factors
“Data to understand the impacts of automated cars”
Cybersecurity
Legal and liability
Insurance
Public/private business models
User acceptance
• Purveyors of clarity
– Understanding the levels of automation
– Scrutiny of L3
• Conveners and deployers
–
–
–
–
Operating FOTs, deployments and use cases
Ecosystem cooperation
Public-private investment
Reducing uncertainty
Concluding remarks
• The collaboration is only beginning
–
–
–
–
Public-private
Academic role, cooperation between research groups
New constituencies (the full ecosystem)
EU-US
• 21st century mobility is voting with its feet
–
–
–
–
Private sector innovation
Consumer excitement
“Sooner rather than later”
New roles and opportunities for research community
Thank you!