Vehicular Networks

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Mobile and Vehicular Network Lab

Vehicular Networks –

What can communications do for vehicles?

Prof. Michael Tsai

2015/6/5

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Future cars

•  GM EN-‐V video

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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

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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

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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

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DSRC/WAVE/802.11p

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(a) WAVE protocol stack

(b) DSRC channel allocation

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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)

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Blinds can drive

•  Google car video

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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

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Some Statistics

•  In April 2014, the team announced that they have completed over 300,000 autonomous-‐driving miles (500,000 km) accident-‐free.

•  4 U.S. States, Nevada, Florida, Michigan and

California, have passed laws that permit driverless cars on the road as of December 2013.

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

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Change the world (on the road)

0. Google driver-‐less car (autonomous vehicle) 1.  Increase highway capacity (eﬃcient)

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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

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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

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Increase Road Efficiency

•  Wugu-Yangmei Overpass (just completed in 2013)

(for National Freeway No. 1)

–  Cost: 88.2B TWD (3B USD) for 40 km of elevated road

- The most expensive road per km in Taiwan history –  Divert approximately 25% of traffic from the original

highway

–  Improve rush hour average speed:

- 40-50 kmph à 80-90 kmph

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Increase Road Efficiency

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

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

•  Automatic steering à reduce lane width

•  Longitudinal control (adaptive cruise control)

à 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

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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

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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

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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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Change the world (on the road)

0. Google driver-‐less car (autonomous vehicle) 1.  Increase highway capacity (eﬃcient)

2.  Avoid scooter accidents (safe)

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What is available in today’s car?

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1.  Crash – post crash 2.  Crash is unavoidable 3.  Crash may occur

4.  Risk has appeared

5.  Risk has not yet appeared

Risk

2 1 4 3

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

1 2

3

4

1

2 4

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!

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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.

3 1

2

1

2

3

Location Uncertainty:

Possible Location

(e.g., vision-‐based localization)

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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

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1.  Crash – post crash 2.  Crash is unavoidable 3.  Crash may occur

4.  Risk has appeared

5.  Risk has not yet appeared

Risk

2 1 4 3

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

5 ₂₇

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Scooters in Taiwan

*http://www.epochtw.com http://upload.wikimedia.org 28

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

•  Every 1.56 persons own a scooter.

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Scooters Around the World

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Country Number 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

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Scooter Accidents in Taiwan

•  Scooter passengers account for most deaths/injuries

•  The percentages and the actual numbers are both rising!

2003 2004 2005 2006 2007 2008 2009 2010 60

70 80 90 100

Year Percentage of Scooter Passenger Contribution (%)

1359 1361

1515

1793 1487 1310 1228 2089 2270 2548 1267

2708 2325 2152 2038 2110 119577 138720 157128 166389 174298 184616 201444 243089

Deaths occur within 24 hrs Deaths occur within 30 days Injuries

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Safety Features in

Off-‐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 belts 2.  Body frame 3.  Head restraints

4.  Front air bags (driver passenger)

5.  Side curtain air bags

1.  Full-‐face helmet 2.  Leather suit (jacket,

gloves, pants) 3.  Boots

Not common^!

Open-‐face helmet only Not much development!31

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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

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Camera

WiFi Cellular and DSRC (Qualcomm)

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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!)

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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 34 John Kenney, Toyota Info Technology Center

May 2013

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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

Car Approaching

Car

Forward Collision Warning (FCW)

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Submission

doc.: IEEE 802.11-13/0541r1

High deceleration by car approaching jam. Trailing car Informed via DSRC within 100 msec.

May 2013

Emergency Electronic Brake Lights (EEBL)

Traffic Jam

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Submission

doc.: IEEE 802.11-13/0541r1

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

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Submission

doc.: IEEE 802.11-13/0541r1

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

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Submission

doc.: IEEE 802.11-13/0541r1

If intersecting trajectories are indicated, driver is warned.

May 2013

Building: Leads to Non-Line Of Sight (NLOS) communication

Intersection Collision Warning (ICA)

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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

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Submission

doc.: IEEE 802.11-13/0541r1

Safety Use Cases: SPaT and MAP

May 2013

Messages sent from RSE:

•  Signal Phase and Timing (SPaT) - dynamic

•  MAP (intersection geometric description) - static RSE may also send GPS Correction Data

Application Types:

RLR LTA RTA TSP FSP

PED-SIG

SPaT can also enable non -safety applications like “Green Wave”

Freight Yard Vehicle Without DSRC

Transit Vehicle

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Submission

doc.: IEEE 802.11-13/0541r1

Safety Use Case: Work Zone Warning

Slide 42

Grass Divider

up to 1100 ft range

Work Zone Warning Com. Zone

Work Zone

Traffic Cones

RSU

In-Vehicle Display and Annunciation

ZONE AHEAD WORK

May 2013

John Kenney, Toyota Info Technology Center

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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.

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Submission

doc.: IEEE 802.11-13/0541r1

V2I Safety Use Case: (PREEMPT)

(also used for Transit/Freight Priority)

Slide 44

Emergency Vehicle

~ ~

RSE

up to 1000 m (3281 ft)

~ ~

Preempt Transaction

1. 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

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Submission

doc.: IEEE 802.11-13/0541r1

V2I Safety Use Case: Standardized Tolls

Slide 45

Open Road Example

Capture Zone

RSE-Equipped Gantry

30 m (98 ft) May 2013

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Submission

doc.: IEEE 802.11-13/0541r1

V2I Safety Use Case: RR Grade Crossing

May 2013

John Kenney, Toyota Info Technology Center Slide 46

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 crossings Range up

to 1100 ft

RR Warning Sign

Train 20-40 sec.

distant

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Red-‐light Running:

Infrastructure-‐based Solution

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A LIDAR or a camera to detect Red-‐Light Runners

Broadcast to warn near-‐by vehicles

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Red-‐light Running:

Smartphone-‐based Solution

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Rider’s smartphone

detects possible red-‐light running

Broadcast to warn near-‐by vehicles

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MD-‐SVM Results

0 10 20 30 40 50 49

50 55 60 65 70 75 80 85 90 95 100

False positive rate (%)

True positive rate (%)

MD-SVM: 15-45m

va vaG vaGt vaGtr

LADAR-vatr

0 10 20 30 40 50

50 55 60 65 70 75 80 85 90 95 100

False positive rate (%)

True positive rate (%)

MD-SVM: 20-45m

va vaG vaGt vaGtr

LADAR-vatr

90%,90% for 15-‐45m

85%,80% for 20-‐45m

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NLOS BSM: Motivation

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Implement V2V communications in the scenario

How can we do?

People usually honk the horn, but some problems could occur.

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Environments

Location1 Location2 Location3

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Minimum Beacon Rate to reach a 99% Successful Rate

V=45km/hr

Beacon size = 64 bytes

V=60km/hr

•  nLoS links through the corner buildings often neglected

•  Fairly usable! At (30m,30m), path loss ~ 85 dB!

•  At 45 km/hr, 5 beacons/s can save 99% of collisions!

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Challenge 1: Scalability

•  A 100-m road segment can have:

–  More than 600 scooters –  More than 120 cars

•  Up to 240 km/h relative speed

•  Different routes for different vehicle

•  Communication requirements:

–  Very reliable link –  Decent end-to-end

throughput

–  Application-dependent delay

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“Pairwise Point-‐to-‐Point Links”

for Vehicle-‐to-‐Vehicle and Vehicle-‐to-‐

Infrastructure

EE Times: Top 10 Automotive Agendas for 2014 & Beyond 7. Time to act on V2V,V2I

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Scalability: Interference

Your Car

RF Communication Coverage

VLC Coverage

Utilizing visible light’s property to do

“Automatic neighbor ﬁltering”:

•  Zero communication overhead

•  Zero delay

àAlways Scalable!

Line-‐of-‐Sight only propagation channel

long range + lower interference

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Challenge 2: who is speaking?

My loca(on is (X3, Y3) and my

speed is 98 mph, and I am braking.

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

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

GPS Uncertainty = 5 -‐10 m

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Change the world (on the road)

0. Google driver-‐less car (autonomous vehicle) 1.  Increase highway capacity (eﬃcient)

3.  Business perspective (whether it will happen)

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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…

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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%.

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

à No real products.

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Potential Issues: Cooperative Systems

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

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

Ø  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 (ex. DriverCam), but also get this "nice-‐to-‐have" feature additionally.

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2.  Control point:

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

Ø  V2V: no obvious methods (need close systems)

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

3.  Security:

will you trust your neighboring vehicles?

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Potential Issues: Cooperative Systems

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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.)

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Case Study 1: Car Following

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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.

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Leader | Dest.: Tainan

Follower | Dest.: Taichung

Leader | Dest.: Tainan

Taichung

EXIT Leave Group & Pay to Leader

Follower | Dest.: Tainan

Taichung EXIT

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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

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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

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•  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)

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Case Study 3: GM OnStar

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

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•  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

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Conclusion

•  New technology: vehicular networks à

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)

Mobile and Vehicular Network Lab hsinmu@csie.ntu.edu.tw

Dept. of Computer Science and Information Engineering National Taiwan University

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Vehicular Networks – What can communications do for vehicles?