Vehicular Networks - csie.ntu.edu.twhsinmu/courses/_media/wn_16spring/... · Mobile and Vehicular Network Lab Vehicle Talks. • Safety related – Warn you about an accident ahead

Mobile and Vehicular Network Lab

Vehicular Networks車輛網路

Prof. Michael Tsai 蔡欣穆2016/5/27


Future cars

• GM EN-V video

2


Vehicle Talks.

• Safety related– Warn you about an accident

ahead (emergency brake)– Tell you a component in your car is

about to fail

• Energy related– Provide routing to avoid a traffic

jam– Smart traffic light

(or, “no traffic light”)

• Information and entertainment (“Infotainment”)– Advertisement– Electronic toll collection– Social networking for passengers– Internet connection

3


How do they talk?

• “Blackbox” (On-Board Unit, OBU) with wireless radios

• Direct Vehicle-to-Vehicle (V2V) Communications– IEEE 802.11p: designed for wireless access in

vehicular environments (WAVE)

– IEEE 1609: Higher layer protocols and operations

– Dedicated Short Range Communications (DSRC): U.S. standard for vehicular communications

• Via Pre-deployed Infrastructure (V2I)– Cellular Networks, e.g.,

Long Term Evolution (LTE)

– Road-side Unit (RSU) with V2V radio

4


Vehicular Networks

5


DSRC/WAVE/802.11p

• PHY layer almost identical to IEEE 802.11a • OFDM using BPSK/QPSK/16 QAM/64 QAM • Reduced inter symbol interference (multipath effects and

Doppler shift)– Doubled timing parameters (double the time durations)– Channel bandwidth (10 MHz instead of 20 MHz)

• Reduced throughput (3 ... 27 Mbit/s instead of 6 ... 54 Mbit/s) • Communication range of up to 1000 m • Vehicles’ velocity up to 200 km/h

– MAC layer with extensions to IEEE 802.11a – Randomized MAC address – QoS (Priorities, see IEEE 802.11e, ...)

• Support for multi-channel and multi-radio • New ad hoc mode

6


DSRC/WAVE/802.11p

7

(a) WAVE protocol stack

(b) DSRC channel allocation


Change the world (on the road)

• What we will talk about today:

0. Google driver-less car (autonomous vehicle)

1. Increase highway capacity (efficient)

2. Avoid scooter accidents (safe)

3. Business perspective (whether it will happen)

8


Blinds can drive

• Google car video

9


What is in Google Car

Cost: • Estimated total:

NT$ 9 M• 3D LIDAR (laser

scanner): over NT$2 M

• Video cameras: a few hundred NT$

• Radar sensors: a few thousands NT$

• Processor & others

10


Some Statistics

• As of 2015:

– 1,000,000 autonomous-driving miles (1,600,000 km) accident-free.

– 75 years of typical U.S. adult driving

– 14 minor collisions for 23 cars as of

• February 14, 2016, a Google car struck a bus.

• 4 U.S. States, Nevada, Florida, Michigan and California, plus Washington D.C., have passed laws that permit driverless cars on the road.

• Available to the public in 2020.

11


But Google Driverless Cars do not talk (to other cars).

12








13


http://virginiaits.blogspot.com/

http://2howto.com/how-to-cope-with-ever-rising-traffic-congestion-in-india/

http://www.csee.umbc.edu/courses/undergraduate/FYS102D/streetsmart.pdf

Preventing Congestion

14


http://www.permatopia.com/wetlands/traffic.html

http://semesterinthesouth.blogspot.com/2008_04_01_archive.html

http://english.peopledaily.com.cn/200701/05/eng20070105_338437.html

Preventing Congestion

15


雪隧挑戰賽

• The Hsuehshan Tunnel is the main artery between Taipei & Yilan, but it can be severely clogged. Build new apps to help drivers avoid congestion and improve traffic flow in the tunnel.

• http://hsuehshantunnel.devpost.com

• Winner: E-Pass 宜pass

• Video: https://youtu.be/mukfjyyim3U

16


Building Roads: No Moore’s Law Here

Wugu-Yangmei Overpass (completed in 2013)

(for Freeway No. 1 in Taiwan)

– Cost: 3B USD for 40 km of elevated road

- The most expensive (per unit length) in the history

– Divert approximately 25% of traffic from the original

highway

– Improve rush hour average speed:

- 40-50 kmph 80-90 kmph

http://twimg.edgesuite.net//images/twapple/640pix/20121217/LN06/LN06_004.jpg

17Hsin-Mu Tsai (c) 2010-2015 All rights reserved.


Increase Road Efficiency

• Maximum highway capacity per lane = 2,200 vehicle/hr

• At 100 kmph, the road surface utilization = 5%

• Automatic steering reduce lane width

• Longitudinal control (adaptive cruise control) reduce the gap

• Drivers’ response delays cause stop and go disturbances

• Only possible through cooperation with communications

45.5 m

5 m

3.5

m

1.8

m


Reduce Energy Consumption

• At highway speeds, HALF of energy is used to overcome aerodynamic drag– Close-formation automated platoons can save 10% to

20% of total energy use

• Acceleration/deceleration cycles waste energy (and produce excess emissions)– Automation can eliminate stop-and-go disturbances

• Again, only possible through cooperation

http://www.autoguide.com/auto-news/wp-content/uploads/2012/05/43905_1_5-31.jpg

http://www.autoguide.com/auto-news/wp-content/uploads/2012/05/43905_1_5-31.jpg

http://www.google.com.tw/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&docid=qHMD1j6Y_CJoHM&tbnid=sqO7l566AdyXUM:&ved=0CAUQjRw&url=http://www.path.berkeley.edu/PATH/Research/Demos/&ei=K7jSUo7GHISEkgWQ6oHAAw&psig=AFQjCNHPIB2WyzN1vaV3DuKZUjezMbVupQ&ust=1389627812234830





Platooning

• Small gap between cars in a platoon

– Gentle impacts between vehicles in faulty cases

• Large gap between platoons

– Prevent severe impacts in faulty cases

• Platoons enable lane capacity to be doubled or tripled, while maintaining safety

– 6000 – 8000 cars/hour in 10-car platoons

– 1500 heavy trucks/hour in 3-truck platoons

20


Platooning

21

Volvo SARTRE project demonstration


D[ !

; (=%$)X ' 0' !PGG0&$1<!Green Light Optimal Speed Advisory

GLOSA

http://www.sigmobile.org/mobisys/2011/slides/signalguru.pdf

Real-time optimal speed advisoryon smartphone screen

15km


Traffic Light Talks to Your Car / Phone

“To Pass or Not to Pass”東元Green Tech 2015競賽佳作

沈雯萱, 傅蕎, 鄭嘉文, 王維楨, 陳艾苓, 蔡欣穆


Back to “what’s wrong with Google Car”

• Cooperation Can Augment Sensing– Autonomous vehicles are “deaf-mute”

– Cooperative vehicles can “talk” and “listen” as well as “seeing”

• Communicate performance and condition data directly rather than sensing it indirectly– Reduce uncertainties

– Reduce filtering lags

– More sources of information available, including beyond line of sight

• Expand performance envelope – capacity and ride quality

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25


What is available in today’s car?

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1. Crash – post crash2. Crash is unavoidable3. Crash may occur4. Risk has appeared

5. Risk has not yet appeared

Risk

12

34

5

Larger

Shield is

SAFER!

For :• Blind Spot Information System

(BLIS)• Adaptive Cruise Control (ACC)• Forward collision warning• Pedestrian detection• Lane departure warning

We are here.

What can we do here?

The “Safety Shield”

5

4

3

2

1

4

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Overcome Visual Obstacles

Conventional Approach:Video camera and/or radar only

Cooperative approach:Sensors + Communications

Scooter A

12

3

4

1

24

3

Detects only risks with a LOS path Detects also risks via comm. / nLOS path

3

4

Line-Of-Sight blocked by a bus

Line-Of-Sight blocked by the road corner

2

1

I’m merging into the middle lane!

I’m turning right!

Be careful to the car on my left!

28


Reduce Uncertainty

• Measurements of location/velocity always have a level of uncertainty

• Self-information is the most accurate.

• Observation from nearby vehicles is more accurate than that from distant vehicles.

13

2

1

2

3

Location Uncertainty:Possible Location

(e.g., vision-based localization)29


Reduce Uncertainty: How?

30

Localization Using Images Taken from Multiple Cameras


Bring Down the Cost

Individual vehicle does not need to have total sensor coverage.

EXPENSIVE

Do we need every sensor in every car?

Cost down. Energy saving. CHEAP

31


1. Crash – post crash2. Crash is unavoidable3. Crash may occur4. Risk has appeared

5. Risk has not yet appeared

Risk

12

34

5

• Blind Spot Information System (BLIS)

• Adaptive Cruise Control (ACC)• Forward collision warning• Pedestrian detection• Lane departure warning

Next-generation Vehicle Safety

Vehicle-to-Vehicle technologies eliminate the “gap”, and make these solutions applicable to as well!5

4

3

2

1

532


Scooters in Taiwan

33*http://www.epochtw.com http://upload.wikimedia.org

• In Taiwan, 68.35% of registered vehicles are scooters or motorcycles.

• Every 1.56 persons own a scooter.


Scooters Around the World

34

CountryNumber of Motorcycle/Scooter Number of Population per Scooter

Taiwan 14,844,932 1.56

Malaysia 9,443,922 2.95

Vietnam 25,414,689 3.38

Thailand 17,229,814 3.88

Indonesia 52,433,132 4.47

Italy 9,425,098 6.39

Spain 4,958,879 9.26

Switzerland 806,577 9.60

Japan 12,477,417 10.22

Czech 903,346 11.61

Austria 712,092 11.75

China 100,004,714 13.35

Netherlands 1,228,058 13.46

Brazil 13,088,074 14.63

USA 7,929,724 38.72 United Kingdom 1,433,124 43.13


Scooter Accidents in Taiwan

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• Scooter passengers account for most deaths/injuries

• The percentages and the actual numbers are both rising!

Hsin-Mu Tsai (c) 2010-2015 All rights reserved.


Safety Features inOff-the-Shelf Vehicle Product

Car Scooter

Active Safety Feature 1. Anti-lock Breaking System(ABS)

2. Electronic Brake-Force Distribution (EBD)

3. Electronic Stability Control (ESC) / Traction Control System (TCS)

1. Anti-lock Breaking System (ABS)

2. Traction Control System (TCS)

3. Power mode map

Passive Safety Feature 1. Seat belts2. Body frame3. Head restraints4. Front air bags (driver

passenger)5. Side curtain air bags

1. Full-face helmet2. Leather suit (jacket,

gloves, pants)3. Boots

Not common!

Open-face helmet only

Not much development! 36


Advantages of Using a Smartphone

Useful Components

Multi-touch Screen

Powerful CPU

Useful Sensors:

GPS

Accelerometer

High initial market penetration rate

Gyro

• Lower effect cost for users

• 2012 smartphone market share:

• Existing Supporting Infrastructure

42% 44%

Good user experience

• Know about the user behaviors in other context as well

• Already familiar with the smartphone’s HCI

37

CameraWiFi Cellular

and DSRC (Qualcomm)


Classification of Causes of Fatal Accidents

• Of the 3,209 deaths in accidents in 2010, top 4 causes of accidents are:

• Drive Under Influence (drunk driver) – 17.82% (572)

• Did not yield to others – 16.45% (528)

• Lost of attention to the road – 15.39% (494)

• Violation of traffic signals – 7.35% (236)

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What can be done to avoid these accidents? (and save over 1,000 lives per year!)

Submission

doc.: IEEE 802.11-13/0541r1

Safety Applications – V2V

Forward Collision Avoidance FCA

Emergency Electronic Brake Lights EEBL

Blind Spot Warning BSW

Lane Change Assist LCA

Do Not Pass Warning DNPW

Intersection Collision Warning ICA

Wrong Way Driver Warning WWDW

Cooperative Adaptive Cruise Control CACC

Examples Follow:

Slide 39 John Kenney, Toyota Info Technology Center

May 2013

Submission

doc.: IEEE 802.11-13/0541r1

V2V Safety Use Case

If driver of approaching car does not stop, or slow

appropriately, warning issued within car.


May 2013

DSRC communication

Stopped

CarApproaching

Car

Forward Collision Warning (FCW)

Submission

doc.: IEEE 802.11-13/0541r1

V2V Safety Use Case

High deceleration by car approaching jam. Trailing

car Informed via DSRC within 100 msec.


May 2013

Emergency Electronic Brake Lights (EEBL)

Traffic

Jam

Submission

doc.: IEEE 802.11-13/0541r1

V2V Safety Use Case


May 2013

Normal driving –

advisory indicator

of car in blind spot

Driver receives warning

when showing intent

to change lanes

Blind Spot Warning (BSW)

Note: Specific timing, format, or decision logic for advisories

and warnings will likely vary for each car manufacturer

Submission

doc.: IEEE 802.11-13/0541r1

V2V Safety Use Case

When showing intent to move to oncoming lane,

driver receives warning if not safe to pass.


May 2013

Do Not Pass Warning (DNPW)

Oncoming

traffic

Submission

doc.: IEEE 802.11-13/0541r1

V2V Safety Use Case

If intersecting trajectories are indicated,

driver is warned.


May 2013

Building: Leads to

Non-Line Of

Sight (NLOS)

communication

Intersection Collision Warning (ICA)

Submission

doc.: IEEE 802.11-13/0541r1

Safety Applications – V2I Applications enabled by SPaT:

Red Light Running RLR

Left Turn Assist LTA

Right Turn Assist RTA

Pedestrian Signal Assist PED-SIG

Applications enabled by Signal Request Message

(bi-directional communication):

Emergency Vehicle Preempt PREEMPT

Transit Signal Priority TSP

Freight Signal Priority FSP

Rail Crossing RCA

Examples follow:


May 2013

Submission

doc.: IEEE 802.11-13/0541r1

Safety Use Case: Work Zone Warning

Slide 47

Grass Divider

up to 1100 ft range

Work Zone Warning Com. Zone

Work Zone

Traffic Cones

RSU

In-Vehicle Display

and AnnunciationZONE

AHEAD

WORK

May 2013

John Kenney, Toyota Info Technology Center

Submission

doc.: IEEE 802.11-13/0541r1

V2I Safety Use Case: Road Hazard Warning


May 2013

Median

Dynamic Message Sign

and Multi-App RSU

Road Condition Warning Com. Zone

Road Sensor Station

Bridge

ICE

Up to 650 ft

forward of the

Hazard

90 m (300 ft)

range

Variations include:

Road Condition (ice), Curve Speed

Low Bridge Roll-over

Roadway Weather (RWIS) In Vehicle Signage

Accident Ahead Rock slide, etc.

Submission

doc.: IEEE 802.11-13/0541r1

V2I Safety Use Case: (PREEMPT)(also used for Transit/Freight Priority)

Slide 49

Emergency

Vehicle

RSE

up to 1000 m

(3281 ft)

Preempt Transaction1. DSRC OBE-to-RSE: Vehicle Host Preemption Request

2. DSRC RSE-to-OBE: ACK

3. Emergency Vehicle Host Displays Preempt-ACK within vehicle

DSRC Transaction occurs on Ch. 184 at high power.

OBE

May 2013


Submission

doc.: IEEE 802.11-13/0541r1

V2I Safety Use Case: Standardized Tolls

Slide 50

Open Road Example

Capture Zone

RSE-Equipped

Gantry

30 m

(98 ft)

May 2013


Submission

doc.: IEEE 802.11-13/0541r1

V2I Safety Use Case: RR Grade Crossing

May 2013

John Kenney, Toyota Info Technology Center Slide 51

Train 20-40 sec.

distant

Conventional

RR Grade Crossing

Equipped with RSE

RSE warning range

increased compared to

conventional equipment

Can also be used at non-

signalized crossingsRange up

to 1100 ft

RR Warning Sign

Train 20-40 sec.

distant


Red-light Running:Infrastructure-based Solution

52

A LIDAR or a camera to detectRed-Light Runners

Broadcast to warn near-by vehicles


Red-light Running:Smartphone-based Solution

53

Rider’s smartphone detects possible red-light running

Broadcast to warn near-by vehicles


RedEye: System Design

54

Data collection for D-SVM model training

WiFi range extender


RedEye: Prediction Results

55

Prediction at 25 m from the intersection

Percentage of avoided accidents


Challenge 1: Density and Speed

• Range reaction time

• 200 km/h relative speed

100 m = 1.8 s @ 200 km/h

• A 100-m road segment

can have:

– More than 600 scooters

– More than 120 cars

• Heavy interference

• The need for

reliable communications59Hsin-Mu Tsai (c) 2010-2015 All rights reserved.



Unreliable transmission in high-density traffic!


D. Jiang, V. Taliwal, A. Meier, W. Holfelder, and R. Herrtwich, “Design of 5.9 GHz DSRC-based vehicular safety communication,” IEEE Wireless Communications, vol. 13, no. 5, pp. 36–43, October 2006.



Very unstable wireless channel!

Large possible range ofreceived power


D. Jiang, V. Taliwal, A. Meier, W. Holfelder, and R. Herrtwich, “Design of 5.9 GHz DSRC-based vehicular safety communication,” IEEE Wireless Communications, vol. 13, no. 5, pp. 36–43, October 2006.


Challenge 2:

My location is (X3, Y3) and my speed is 98 mph, and I am braking.

My location is (X2, Y2) and my speed is 101 mph.

My location is (X1, Y1) and my speed is 106 mph.

GPS Uncertainty = 5 -10 m

Who is Speaking?

Is the car in front

of me braking?

Hsin-Mu Tsai (c) 2010-2015 All rights reserved. 62


Challenge 3: Cost and Benefit

• DSRC (IEEE 802.11p) – the current dominant

standard for vehicular communications

• NOT in vehicle products today

• Low adoption incentive:

where is the (day 1) benefit?

– Minimum market penetration rate: 10%

(All new cars have it have to wait for 2 years)

• Low adoption incentive: high initial cost

– Complexity similar to a WiFi radio

– But with much lower quantity,

when bootstrapping the market 63Hsin-Mu Tsai (c) 2010-2015 All rights reserved.








64


Why do we need a business model?

• You have this cool V2V radio that talks to other vehicle in your car

• But you are ALONE.

• What would happen?

• Nothing…

65


Why do we need a business model?

• 300K-500K new cars annually in Taiwan

• 6M car population

• 10% minimum market penetration rate is required for most V2V applications

• Even if all new cars start to equip V2V, it takes 2 years to reach 10%.

66

No customer wants to buy something that has to wait for another 2 years to function normally.

No real products.


Potential Issues: Cooperative Systems

1. Bootstrapping: what is the required initial market penetration?

– If no one is using it, then it is useless

No incentive for the user to purchase the new system

– Possible solution:

• The system is bundled as a "side-feature". You get the main feature you want (e.g., DriverCam), but also get this "nice-to-have" feature additionally.

67


2. Control point:

– How to make sure only paid users can use thesystem/service?

V2V: no obvious methods (need close systems)

V2I: the gateway (base stations & RSUs) can control who can go through

3. Security: will you trust your neighboring vehicles?

68

Potential Issues: Cooperative Systems


Possible Business Model

How to obtain the profit?

1. Bundled as part of the vehicle

– New feature, thus higher price

– Does the user want to pay for the additional cost?

2. Smartphone: deployed as a paid app.

– Obtain profit when the user purchases the app

3. Monthly subscription for the user:

– the user is buying a service

4. Subsidized by the government to mandate a new vehicular system (usually combined with 1.)

69


Case Study 1: Car Following


Case Study 1: Car Following

• Car Following (The SARTRE Project )– Leader (human) drives for revenue.– Followers (auto-driving) pay for enjoy the trip without human driving.

71

Leader | Dest.: TainanFollower | Dest.: Taichung

Leader | Dest.: Tainan

TaichungEXIT Leave Group & Pay to Leader

Follower | Dest.: Tainan

TaichungEXIT


Post-Accident• Insurance claim

– Investigation at the scene (agents and polices

• road-side surveillances

• costly and time consuming

– Lawsuit

– Bogus insurance claim

• £410m of motor insurance fraud detected in UK, 2009

Case Study 2: Networked DriverCam


How about an networking solution?• V2V + V2I

– CSI in vehicular networks

• Business model

– Incentive for insurance company

• A total package for customers

• Annual renewal of insurance policy (steady cash flow?)

Case Study 2: Networked DriverCam


• GM OnStar

– V2I: CDMA cellular network– Stolen Vehicle Assistance, Roadside Assistance, Remote Door

Unlock, Remote Horn and Light Flashing, Red Button Emergency Services and OnStar Remote Vehicle Diagnostics

– Subscribe Service: • Safe & Sound: $18.95/mth ($24.95 in Canada)

74

Case Study 3: GM OnStar

[1] OnStar, https://www.onstar.com/web/portal/landing[2] OnStar, http://en.wikipedia.org/wiki/OnStar, Wiki

https://www.onstar.com/web/portal/landing

http://en.wikipedia.org/wiki/OnStar


• GM OnStar

– Car Rental Service

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Case Study 3: GM OnStar

[1] Telematies News, http://telematicsnews.info/2011/10/06/us-gm-onstar-and-relayrides-launch-car-sharing-program/[2] automotive.com, http://blogs.automotive.com/gm-to-begin-onstar-carsharing-anyone-have-an-available-corvette-59543.html

http://telematicsnews.info/2011/10/06/us-gm-onstar-and-relayrides-launch-car-sharing-program/

http://blogs.automotive.com/gm-to-begin-onstar-carsharing-anyone-have-an-available-corvette-59543.html


Conclusion

• New technology: vehicular networks New opportunity: cooperative systems.

• Change our world on the road - higher performance

– More Efficient: Greener, faster, more capacity

– Safer: zero injuries & fatalities

– Affordable: each vehicle only needs to know a few things

– New applications: remain to be unleashed

• Good research & business opportunities!

• Shameless Plug: MVNL welcomes you.

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Thank you!

Please feel free to contact me for questions:

Prof. Michael Tsai (蔡欣穆)


[email protected]

Dept. of Computer Science and Information Engineering

National Taiwan University

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Documents

Vehicular Networks - csie.ntu.edu.twhsinmu/courses/_media/wn_16spring/... · Mobile and Vehicular Network Lab Vehicle Talks. • Safety related – Warn you about an accident ahead