Update of ITS Research and Development

in Japan

Shinji ITSUBO Senior researcher, ITS Division, Road Traffic Department

National Institute for Land and Infrastructure Management (NILIM),

Ministry of Land, Infrastructure, Transport and Tourism (MLIT),

JAPAN

29th October-2nd November, 2017

ITS Wold Congress 2017

Montreal

1

Outline

1.ETC2.0 system

2.“Next-generation C-ITS”

3.Low Speed Automated Driving (LSAD)

Services in Rural and Mountainous Areas

1. ETC2.0 SYSTEM

2

3

1.1. ITS Development in Japan

VICS： Vehicle Information and Communication System

1996 2000 2011 1990’ 2015

Upgrade of

existing

services

New services

・ Smart investment

based on big data

・Smart tolls that

reduce congestion

and accidents

・ Smart toll gate

with ETC basically

・Smart logistics that

improve

productivity

ITS Spot

Various

applications

by a single

onboard

unit (OBU)

•Dynamic route

guidance

•Safety driving

support

•ETC

etc.

Evolved

Car navigation

70 million units shipped

(March 2016)

VICS

50 million units shipped

(March 2016)

ETC

53 million units shipped (March 2016)

4

ETC 2.0 on-board unit

ETC 2.0 compatible car

navigation system

Basic Information Provision

Warning of accident-prone locations, Warning of

dangerous situations (e.g. congestion around blind curves)

Road

この先渋滞、追突注意

この先、渋滞しています。

注意して走行して下さい。

外苑出口先(約1km先)

Vehicle

V2I Communication

Roadside units (RSU)

Expressways: 1,700 +

National Highways directly administered :

1,900 +

On-board units (OBU)

2+ million

Roadside unit

Beware of rear-end

collisions.

Congestion ahead.

Congestion ahead. Beware

of rear-end collisions.

東京方面 御殿場付近

Time-shortest

Distance-shortest

Minimum fuel consumption

Wide-area traffic information

○km先の現在の路面状

況です。雪のため注意して走行して下さい。

Snow on the road,

ahead.

東京方面 御殿場付近 Tokyo-bound lanes near Gotemba

Safe Driving Support

1.2. Overview of ETC2.0 system

Congestion Avoidance

At end of Gaien Exit

(approximately 1 km ahead)

5

Data collected

• Travel Record: Time, Positional data, Speed, etc.

Recorded at every 200 m of driving distance or when the direction of travel

has changed 45°.

• Behavior Record: Time, Acceleration, etc.

Recorded when acceleration is 0.25 G or more.

Intranet

ETC2.0

On-board unit

Probe data server Data integration /

aggregation

• Probe data is accumulated in on-board units and collected when

vehicles pass under roadside units.

1.3. Probe data collection

5

Probe data

Roadside unit

Road administrators

6

1.4. Various Applications

(1) Smart investment based on “big data” (community roads)

(2) Smart Tolls (Phased Revision of Toll System in Tokyo Metropolitan Area)

(4) Highly productive “smart” logistics

(5) Map of passable routes after disasters

(6) V2I communications to support

automated driving

Hazardous short cut View is obstructed

by plant

Sudden braking locations

Changes depending on congestion status

EXIT (Interchange)

(3) Service improvement using ETC 2.0

To use nearby facilities without additional toll.

17:30 18:40

ETC 2.0 probe data helps to improve the productivity of logistics operations.

2. “NEXT-GENERATION C-ITS”

7

(cooperative)

8

2.1. Concept of next-generation C-ITS

• enable vehicles and road administrators to share

data and fill in the gaps with their information.

next-generation

C-ITS

probe data, road work schedule, traffic

regulations, etc.

More various

Information

Safer and more

convenient automated

driving

Braking

data

Speed

data

Camera detection

data

Steering data

Windshield wiper data

Location data

Radar detection

data ABS activation

data

-More efficient road

management

-Reduction of costs

Information for road management

(abnormal weather conditions, obstacles,

pavement damage etc.)

Look ahead information (congestion, accidents, obstacles,

etc.)

9

2.2.1. Public-Private Joint Research Project (1)

Phase1: to create a common understanding on overview of C-ITS

Phase2: to narrow down the scope for realizing automated driving

• Period: September 2012 - December 2013

• Investigated architecture and systems used in C-ITS

• Investigated C-ITS concepts using the architecture – Selected 196 C-ITS services

– Selected 35 services prioritized for more detailed examination

• Period: April 2015 - March 2017

• Investigated the practical use of C-ITS based on the results of Phase1 – The four services are examined (requirements and definitions) by focusing

on automated driving on expressways:

1. “Look ahead information provision service"

2. “Merging support service”

3. “Diversing support service”

4. “Wrong-way prevention service”

10

2.2.2. Participants in joint research

• 17 participants in Phase2

Automobile

manufacturers (3)

Electronic

equipment

manufacturers (6)

Map companies (2)

Road administrators

(3)

Other (3)

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- Merging support

- Look ahead information provision

- Advanced road management using

vehicles’ data

Information about

mainline traffic

conditions

Autonomous car

Difficult situation for autonomous cars

Merging locations

• Traffic status on the main road is unknown,

so unable to merge safely and smoothly.

Obstacles on road

• Unable to detect obstacles until just before

reaching them, so there is no time to change

lanes safely

Speed adjustment

Autonomous cars cannot go independently through merging sections or when

there are obstacles ahead.

V2I communication will improve automated driving to higher stage for safe and

comfortable driving.

Roadside unit

Merging support

started in Dec 2017.

2.3. Public-Private Joint Research Project Phase 3

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2.4.1. Merging Support Service

Traffic flow data

Providing traffic conditions on mainline helps drivers and AD vehicles

merge smoothly.

CCTV camera

DSRC

RSU

C-ITS Platform

Information

provision

Information

collection

13

2.4.2. Look Ahead Information(LAI) Provision Service

Change

routes

⇒Improve

comfort

Change

lanes

⇒Improve

comfort

Slow down

⇒Enhance

safety

C-ITS Platform

Look Ahead

Information

information

Falling object!

Broken-down vehicle!

Icy road surface!

Telematics

CCTV camera

DSRC

RSU DSRC

RSU

DSRC

RSU

Telematics

LAI* helps drivers or AD vehicles take safer maneuver. *LAI(Look Ahead Information): information of anticipated events which can’t be detected by on-board-sensors

14

2.4.3. Advanced road management using vehicles data

Vehicle data, such as brake and turn signal operation, can enhance road

management.

Ex. Early detection and quick response

Data collected by vehicle (CAN, camera, sensor, etc.)

Camera data

Turn signal operation data

Radar detection

data

Road Administrators

Traffic Events

Objects

on Roads

Congestion

Traffic

Accidents

Patrol Car

Quick Response

Speed

Turn Signal

Probe data

3. LOW SPEED AUTOMATED DRIVING (LSAD) SERVICES IN RURAL MOUNTAINOUS AREAS

15

16

3.1. Issues in rural mountainous areas

• It gets difficult to maintain daily-life services.

Rapidly aging population

Ratio of the population over 65 years old to the total

population (2010)

Japan

rural mountainou

s areas

About 40% of

truck drivers

are over 50

years old.

Rapid increase of elderly people who cannot drive

Abolishment of public transport to go shopping

and/or to clinics

Shortage of truck drivers who deliver goods

1,832 1,911 1,8561,720

842 902

1,143

1,590

1,312

0

500

1,000

1,500

2,000

2,500

H19 H20 H21 H22 H23 H24 H25 H26 H27

路線バスの廃止路線延長の推移

Total 13,108km

(2009)

Length of bus routes abolished

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

H19 H20 H21 H22 H23 H24 H25 H26 H27 H28

運転免許の自主返納件数（ 65歳以上） の推移

Approx.

20,000

Approx.

330,000

Number of returned driving licenses from people over 65 years old

over 50

37%

below 30 9%

30-39 22%

40-49 22%

Age group of truck drivers

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3.2.Automated driving services in rural area

• expected for ensuring both people’s daily transport and maintain

the flow of goods, and further local revitalization.

• A series of pilot project with autonomous cars was started in 2017.

Clinic

Market City hall

branch office

Library

Community center (Michi-no-Eki)

Bus stop

Bus

Highway

City

Hall

Station

Autonomous car

Meeting

places

Farm

Nursing

homes

Mobility in everyday life

Door-to-door delivery service

Collection of local products

V2I Cooperation will be

considered as well

(e.g. guide cables)

Hamlet

18

3.3. Test sites

Community centers (“Michi-no-Eki”s)

designated by MLIT for technical verification

designated by public offer for business model

designated by public offer for business model

FOTs

Feasibility Study

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Bus type Passenger-car type

1) DeNA Co., Ltd. 3) Yamaha Motor Co., Ltd.

2) Advanced Smart Mobility Co., Ltd. 4) Aisan Technology Co., Ltd.

3.4. Test-vehicles

Autonomous technology • Identify own position by GPS

and IMU.

• Drive according to a

predetermined route.

• Acquire point-group data.

GPS: Global Positioning System

IMU: Inertial Measurement Unit

LIDAR: Light/Laser Imaging Detection and Ranging

Note: Vehicle speed responds to the posted speed

limit of each road.

Capacity: 6 people (seated)

(Total 10 people

seated and standing)

Speed: Approx. 10km/h

(Max: 40km/h)

V2I technology • Drive a predetermined route by

following embedded magnetic-

induction lines.

Capacity: Approx. 4–6 people

Speed: Automated: Approx.

12km/h

Manual: <20km/h

V2I technology • Identify own position and

drive a predetermined route

using GPS, magnetic markers

and gyro sensors.

Capacity: 20 people

Speed: Approx. 35km/h

Max. 40km/h

Autonomous technology • Drive a predetermined route

using a high-precision 3D map.

• Detect surrounding conditions by

LIDAR.

Capacity: 4 people

Speed: Approx. 40km/h

Max. 50km/h

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3.5. V2I cooperation technologies for rural areas

Magnetic markers (Advanced Smart Mobility Co., Ltd) Magnetic-induction lines (Yamaha Motor Co., Ltd. )

Environmental condition is severe in rural area. e.g. AD vehicle cannot catch GPS signal due to forest.

Performance of Lidar sensors decrease in snowy condition.

Some of the AD vehicle providers use low-tech but robust technology against severe weather,

so that vehicles can identify their own location accurately.

sensor

line

Magnetic marker Magnetic Marker

Sensor

You can see this technology

in Japan booth!!

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3.6. Evaluation viewpoint

1) Roads and traffic 2) Environmental conditions

3) Costs 4) Public acceptance 5) Beneficial effects on

regions

1) Road structure (Straightness, grade,

etc.) 2) Road management (demarcation lines,

planted trees, etc.) 3) Support for mixed

traffic 4) Space required

1) Weather conditions

(rain, snow, etc.) 2) Communication

conditions (GPS reception)

1) Costs for vehicles 2) Costs for others

1) Comfort(speed, psychological

impact, etc.)

2) Convenience (routes, frequency

of service, etc.)

e.g., Typical road

in rural area e.g., Snowy roads

（電磁誘導線の敷設イメージ）

e.g.. Combined transport of passengers and cargo

1) Opportunity for elderly to go out

2) Collection and shipping of

agricultural produce, etc.

e.g., Installation magnetic

induction lines

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3.7. Prompt report of the FOT

On-board-camera view of an AD On-board-camera view of an AD

Some of the issues to be solved

Speed difference btw. AD vehicles and

normal vehicles Poor maintenance of rural road

Following vehicle overtook AD vehicle in

“No overtaking” section.

Appropriate passing place should be

provided.

Roadside bushes are detected as obstacles

on the route.

Appropriate mainteinance level should be

considered.

bushes

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Summary and Future Works

1. ETC2.0 system

• Enrich its services with an increase of data

2. “Next-generation C-ITS”

• Discussion about more concrete data requirements

and methodologies for Look Ahead Information

Provision Service and Merging Support Service

3. Low Speed Automated Driving (LSAD) Services

in Rural and Mountainous Areas

• FOTs and its evaluation from technical viewpoints

for installing LSAD services in rural areas

Thank you for your attention!