Nagoya University Center of Innovation (COI)-Empowering an aging society through advanced mobility-

August 22, 2017

Vice Research Leader, Nagoya University COI

Professor Hirofumi Aoki, Ph.D.

The 18th International Conference on Industrial Technology Innovation (ICITI, 2017)

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What is “Center of Innovation”?

Research funding by the Ministry of Education (MEXT) through Japan Science and Technology Agency (JST),(from Nov., 2013 to Mar. 2022)

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What is “Center of Innovation”?

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Nagoya（名古屋）

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-Empowering an aging society through advanced mobility-

The Objective of Nagoya COI activities

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TOYOTA MOTOR CORPORATIONDENSO CORPORATIONTOYOTA CENTRAL R&D LABS., INC.Aichi PrefectureNational Institute of Advanced Industrial Science and Technology Tokyo University of Agriculture and TechnologyAichi Prefectural University

MobilityResearch

FUJITSU LIMITEDInformationInfrastructure

Research

AGC ASAHI GLASSDaily

HealthcareInfrastructure

Research

Panasonic CorporationSustainableInfrastructure

Research

CooperativeResearch

The University of TokyoToyota CityNagoya City

Participating Organizations in Nagoya COI

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Driving Assistance System and Autonomous Cars for safe and reliable mobility

Physical Conditions and Mental Inspiration to stimulate going outside

Participatory Society to foster mutual aid and self-respect

Vitalizing the aging society by mobility advances

Three Pillars to Realize the Objective

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1 【Driving Assistance System and Autonomous Cars for safe and reliable mobility】Provide an enjoyable mobility experience even for those who cannot or do not like to drive

Proactive driving assistance, Slocal (slow and local) autonomous driving®, Driver agent, Dynamic map, Stress-free traffic management

Activity recommendation, Walking assistance robot, Casual sensing device

Use the personal information gathered through casual sensingto maintain physical and mental health

2 【Physical Conditions and Mental Inspiration to stimulategoing outside】

Model community building, Social science assessments

Create a social system that inspires self-efficacy among seniors through social participation

3 【Participatory Society to foster mutual aid and self-respect】

Three Pillars and R&D Items

Vitalizing the aging society by mobility advances

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1 【Driving Assistance System and Autonomous Cars for safe and reliable mobility】Provide an enjoyable mobility experience even for those who cannot or do not like to drive

Proactive driving assistance, Slocal (slow and local) autonomous driving®, Driver agent, Dynamic map, Stress-free traffic management

Activity recommendation, Walking assistance robot, Casual sensing device

Use the personal information gathered through casual sensingto maintain physical and mental health

2 【Physical Conditions and Mental Inspiration to stimulategoing outside】

Model community building, Social science assessments

Create a social system that inspires self-efficacy among seniors through social participation

3 【Participatory Society to foster mutual aid and self-respect】

Three Pillars and R&D Items

Vitalizing the aging society by mobility advances

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Recognition Judgement

Operation

Mobility Research

Path planning based on a driving AI

Assistance with proactive driving

Senior drivers’ database

Environment recognitionSituation assessment

- System works like a driving instructor offering safety tips to senior drivers -

Driver Agent support system

Cooperative assistance

Advanced Driving Assistance System

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High performance environment recognition

Pedestrian Detection

Recognition rate(Caltech Benchmark)(1/10 frames error rate)

Conventional(HOG+SVM) 32%Past(Dn’MI) 63%Cutting-edge(Checkerboard, 2015： speed×) 82%

Proposed(EIN Dn’MI) 73%

World top level performance in pedestrian detection using Deep Learning

90% pedestrian detection rate with faster algorithm

Hig

h p

erf

orm

ance

Traffic accident risk prediction: High accuracy detection Target attribute recognition

Pedestrian detection and target attribute recognition（orientation, adult/child, walking while looking at the smart phone)

Environment Recognition

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Achieve the planned path performance

in various traffic environments.

Planned path

Driving data

Artificial Intelligence (AI) learns from good driving data and generates a path according to the environment.

Supervisory Driver Assistance System

Path Planning Based on a Driver Model

Position Error: 14cm Velocity error: 3.7km/h

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The effectiveness of the system was tested with 80 senior drivers, comparing their driving behaviors before and after they experience the driver assistance system.

Driving skills are improved after the experience of the driver assistance system.

Supervisory Driver Assistance System Education effect of the system

Cooperative Assistance

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Post- Post-

Steering wheel with LED↓

Gas pedal vibration↓

Steering control intervention

Risk factor;Hazard without direct view (e.g., cross traffic)

Risk factor;Hazard with direct view (e.g., walking pedestrian)

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Research on Features of Senior Drivers

Database Institution cognitive visual physical driving

behaviorfollow-

upsample & notes

TC/DS DR

Data repository for human life-driving anatomy (Dahlia)

Nagoya COI ○ ○ ○ ○ ○ ○ ○50-95 years,300 drivers

Research on elderly drivers (III)

JSDC (Japan) × ○ × ○ × × ○68-90 years, 191 drivers(report in March 2014)

Driving behaviordatabase

HQL (Japan) × × × ○ × ○ ○20-71 years, 97 driversNEDO project （2001-2003）

The salisbury eye evaluation and driving

studyNHTSA (US) ○ ○ × △ × ○ ×

67-87 years, 1155 drivers,5days Driver Monitoring System (Round2)

Maryland pilot older drivers study

NHTSA (US) ○ ○ × ○ × × ×55-96 years, 2508 drivers(1996-2003)

Factors associatedwith driving

performance of older drivers

University of Nebraska

○ ○ × ○ × ○ × 65-88 years，105 drivers

Candrive IICandrive II Research

Team (Canada)○ ○ ○ ○ × × ×

70-94 years, 928 drivers（577 males and 351 females)from 2009

Driving of cognitivelyimpaired elderly

peopleNCGG (Japan) ○ ○

65 years and more,10,000 drivers,Cognitive function test of questions, 2011-2013

Database for the assistance of senior drivers

On-road experiment

Driving aptitude test

Driving simulator experiment

Building an effective basis

to develop assistance systems

for senior drivers.

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Driving Assistance with the Dynamic Map for Senior Drivers

POV

PredictedPositions

Traffic Simulator

Lane-change request to the driver

Senior’s own vehicle

Drive in DS connected with traffic simulator

Simulation-based Evaluation EnvironmentDynamic Map (DM) shares vehicles’ (the senior’s own vehicle and principal other vehicle (POV’s)) information (i.e., position, direction, velocity) on a virtual map via network

Use Case

The POV that receives the lane-change request moves to the next lane for smooth merging.

Traffic safety, driver’s stress mitigation

Effectiveness of DM can be evaluated with the simulation

system in virtual environments.

Driving Simulator (DS)

Static Info.

Dynamic Info.

Predicted Info.

Map Info.

Dynamic Map(Our prototype system)

Dynamic Map View

CollisionDetection

Lane-based Navigation

QueryQueryQuery

Dynamic Map (DM)

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1 【Driving Assistance System and Autonomous Cars for safe and reliable mobility】Provide an enjoyable mobility experience even for those who cannot or do not like to drive

Proactive driving assistance, Slocal (slow and local) autonomous driving®, Driver agent, Dynamic map, Stress-free Traffic management

Activity recommendation, Walking assistance robot, Casual sensing device

Use the personal information gathered through casual sensingto maintain physical and mental health

2 【Physical Conditions and Mental Inspiration to stimulategoing outside】

Model community building, Social science assessments

Create a social system that inspires self-efficacy among seniors through social participation

3 【Participatory Society to foster mutual aid and self-respect】

Three Pillars and R&D Items

Vitalizing the aging society by mobility advances

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Watch over everyday life

Collecting continuous daily activity database

Information Platform Research

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Inspires seniors to go outside using real-time activity recognition.

Signals from multiple sensors embedded in the smartphone(e.g., acceleration and sound)

-> 91% recognition accuracy for nine kinds of daily activities.

Twitter Bot can encourage seniors based on the recognized daily activities

Information Platform Research

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“Casual sensing” of health condition in living spaceGrasp our own physical and mental conditions from ordinary living

environments to support daily life according to the conditions.Casual sensing

Noncontact brain waves measurement

Noncontact pulse wave measurement

Pulse wave measurement with miniaturized all-crystal load sensor

Field demonstration has started by prototype of biosignal sensing system with non-contact sensors.

Smart chair

Sustainable Platform Research

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Casual Health Sensing in Daily Life

Intellectual Glass

Bioaerosol measurement

Outside

Home

Car

Microfiltration glass

10 μm separation structure

Single-cell Isolation!

Bioaerosol

・10,000 particles in a cough・0.01～100 μm in size・Biological components・Bacteria and viruses・Fatigue and stress markers

Daily Healthcare Platform Research

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1 【Driving Assistance System and Autonomous Cars for safe and reliable mobility】Provide an enjoyable mobility experience even for those who cannot or do not like to drive

Proactive driving assistance, Slocal (slow and local) autonomous driving®, Driver agent, Dynamic map, Stress-free Traffic management

Activity recommendation, Walking assistance robot, Casual sensing device

Use the personal information gathered through casual sensingto maintain physical and mental health

2 【Physical Conditions and Mental Inspiration to stimulategoing outside】

Model community building, Social science assessments

Create a social system that inspires self-efficacy among seniors through social participation

3 【Participatory Society to foster mutual aid and self-respect】

Three Pillars and R&D Items

Vitalizing the aging society by mobility advances

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Through Mobility Enhancement, Outing Promotion, andHealth Maintenance, we are to upgrade the well-being in aging communities.

Pleasant Outing

Unconstrained Mobility

Healthy Daily Life

“Mobility Blend” Micro EV usageSlocal (slow and local) autonomous driving®

Outing promotion Activity monitoring

Community point

Commitment of local residentsBuilding a Role-Model of

Exploiting Mobility

for Semi-Mountainous

CommunitiesAsuke Mobility Project is supported by TOYOTA Mobility Foundation .(2016～)

Started a pilot projectin Asuke Region of Toyota City

Pilot Project: Model Community Building

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Community Support System (CSS)

CSS works as a bonding agent and fillers to the existing community system.

Community Support

System (CSS)

Mobility Blend

Existing community bus

Proposed ride-share

Proposed micro EV

Outing Promotion

Health Maintenance

Existing activities

Existing health care

Proposed motion

monitoring

Mutual Aid Promotion Point

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Proposed taxi-share

Proposed activities

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Mobility Blend

Ride-share

モビリティスポット

•Promote outings•Facilitate transfers among various transport

modes including inter-district one

•Enhance mobility utilizing various transport modes

Mobility Center

•Monitor health conditions•Provide tablets for CSS

DR Bus

Taxi-share

Micro EV

Mobility Spot

DR Bus

Slocal Autonomous Cars

Slow PM

Trunk Route Bus

Home

Home

Home

Mobility Spot

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Toward an Open Innovation Platform using COI Program

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NU MIRAI2020Nagoya University Matsuo Initiatives for Reform, Autonomy and Innovation 2020

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Academic Research & Industry-Academia-Government Collaboration Division

(Est. 2013)

Institutes of Innovation for Future Society (Est. 2014)

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Nagoya COI is one of the projects of the Institutes

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Collaborative and educational activities in Nagoya ＣＯＩ

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R&D testbeds

Establish R&D testbeds for Industry/Academia collaborations

Industry/academia collaborations

Young researchers’ appointment

Challenging exploratory/collaborative reseaech by young researchers

Outreach activities(Tactics committee by young researchers and university research administrators)

Human resources development/education

Bus stop

Senior’s house

“Last mile” autonomous vehicle