extend the safety shield – early warning system for...

EXTEND THE SAFETY SHIELD – AN EARLY WARNING SYSTEM FOR VEHICLES

Prof. Michael Tsai Department of Computer Science and Information Engineering and

Intel-NTU Connected Context Computing Center

National Taiwan University

Introduction to M2M course

November 9, 2011


1. Crash – post crash

2. Crash is unavoidable

3. Crash may occur

4. Risk has appeared

5. Risk has not yet appeared

2

Risk

1 2

3 4

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”


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Communication-Assisted Approach

Conventional Approach: Video camera and/or radar only

Communication-assisted approach: Sensors + Communications

Scooter A

1 2

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4

1

2 4

3

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

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4

Line-Of-Sight blocked by a bus

Line-Of-Sight blocked by the road corner

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1

3

I’m merging into the middle lane!

I’m turning right!

Be careful to the car on my left!


Vehicle Behavior Prediction

Intel-NTU Connected Context Computing Center 4

Merging right

OBD II CAN Bus Hey scooter #1! Based on my experience with

my driver and the current sensor readings, he is merging right and I don’t think that he is aware of

you. I will warn him, but you be careful too!

I am here! Here are my location and

speed (50 km/h) .

Thanks! By the way, you should know that scooter #2 is merging from the alley. Judging from the

speed information I received from you and her, she has a high probability to collide with you!

Turning right 1

2

3

Smartphone

GPS

Direction

RPM

Speed

1. Crash – post crash

2. Crash is unavoidable

3. Crash may occur

4. Risk has appeared

5. Risk has not yet appeared

5

Risk

1 2

3 4

5

• Blind Spot Information System (BLIS)

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

Next-generation Vehicle Safety

M2M (V2V) technologies eliminate the “gap”, and make these solutions applicable to as well!


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2

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An Early Warning System for Vehicles Concept:

A new “magic mirror” for you to check for potential risks.

The rider’s smartphone is mounted on a holder.

Connection to the scooter for additional sensor information + V2V communications

V2V Throttle & Brake Accelerometer GPS


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Vehicle coming from the left at the next intersection!

Countdown to show the estimated time to a potential collision.

Additional visual + audio warning when the collision is imminent.

An Early Warning System for Vehicles


Scooter Safety

• 68.34% of registered vehicles are scooters

• Accidents involving scooters/motorcycle account for most of fatalities/injuries (and rising!)

8 Intel-NTU Connected Context Computing Center

2003 2004 2005 2006 2007 2008 200960

65

70

75

80

85

90

95

Year

Ra

te (

%)

Death Rate (24 hrs)

Death Rate (30 days)

Injury Rate (24 hrs)

Injury Rate (30 days)

Off-the-Shelf Product Features

Cars Scooters

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

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Not much development!


A Common Platform: Smartphone


Useful Components

Multi-touch Screen

Powerful CPU

Useful Sensors:

GPS

Accelerometer

High initial market penetration rate

Gyro

• Lower effect cost for users

• 2010 smartphone market share:

• Existing Supporting Infrastructure

27% 31%

Good user experience

CAN V2V

• Know about the user behaviors in other context as well

• Already familiar with the smartphone’s HCI

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Next-Generation Vehicle Safety: An Early-Warning System

Vehicle Behavior Model Reliable V2V Communications

Scooter Smartphone


Research Challenge 1

• Can the system work in this condition? • Urban area, high density scenario

• Delivery Ratio

• Delay

• Bandwidth

all limited by the number of vehicles in the range.

• Density == Performance

Reliability



“Safety Shield”: contains vehicles which could be risks

A Mismatch between the “Safety Shield” & Communication Coverage

Car A

RF Communication Range

Even worse, the “shield” changes with time!!

How do we control the coverage (scale)?

• Conventional Approach: Adaptive Transmission Power

It takes time/bandwidth to estimate the number of neighbors. Not scalable for vehicle safety!

Applies to both omni-directional and direction RF Communications


• Some slides regarding the solution for this problem is removed as the research is still in early stage and highly confidential.



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The behavior of nLoS wireless channel/link in vehicular settings is

1. Very hard to be theoretically modeled (realistically). 2. Highly dependent on “scenarios”.

“Scenarios” mean: 1. The surrounding static objects (buildings, parked vehicles) 2. The surrounding moving objects (human body, other moving vehicles) 3. The speed, location, orientation of the transmitting and receiving vehicles

How do we know whether the nLoS communication is reliable or not?


Corner Building as Obstacles

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Radio: Chipcon CC2420 IEEE 802.15.4, 2.4 GHz TX pwr: 0 dBm

8 dBi peak gain omni-directional antenna


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-100

-90

-80

-70

-60

-50

Distance to intersection (m)Distance to intersection (m)

Pa

th L

oss (

dB

)

Corner Building as Obstacles


1015

2025

3035

4045

1015

2025

3035

4045

-95

-90

-85

-80

-75

-70

-65

-60

Distance to intersection (m)

Pa

th L

oss (

dB

)

• nLoS links through the corner buildings often neglected

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

• Path loss exponent ~ 4.2-4.5

• At 50 km/s, 30m = 2.16 seconds Sufficient for some reactions!

Human Body as Obstacles

• Human Body creates an additional 14-20 dB of attenuation in a 2.4 GHz Scooter-to-Scooter channel


95 cm

10 m

0.8 1 1.2 1.4 1.6 1.8 2

-90

-85

-80

-75

-70

-65

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Distance (Log)

RS

SI

(dB

m)

No Rider

No Rider

W/ Rider

W/ Rider

Path Loss Exponent = 1.821

Path Loss Exponent = 1.993

Required Communication Paradigms

Line-Of-Sight Communications

None-Line-Of-Sight Communications

Communication to vehicles blocked by objects, other vehicles, or buildings.

Communication to immediate neighbor vehicles.

Total Awareness of the Neighborhood


RF Communications VLC Communications

V2V Communications for Vehicle Safety


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The goal of the model: To predict the vehicle behavior (from the sensor data), not just observe.

Communications

Deadline for Reactions Observation Prediction

Communications

The catch: Observation: 100% accuracy (The event already happens) Prediction: ??? accuracy (The event hasn’t happen)

Communications take time. Can we react in time?


Example – Red-Light Runner

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Distance to the intersection (mm)

Speed(km/hr) Speed(km/hr)

Non Red-light runner Red-light runner

Distance to the intersection (mm)


How much time can we buy for communications + the reaction?

Closer to the intersection Closer to the intersection

Time to perform the prediction

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Vehicle Behavior Model

• A vehicle mobility model (cellular automata)

• Estimate vehicle future locations

(In the Demo session)

• Prediction model for certain vehicle events

• Red-light runner, • Lane switching, and • More…

Reliable V2V Communications

NLoS V2V Links: • Extensive RF link

measurements enable the protocol to: • Estimate the link quality • Adjust the parameter

based on the sensor information

LoS V2V Links: • VLC Communications is

naturally scalable for vehicle safety


Recap: Next-Generation Vehicle Safety An Early Warning System

Scooter Smartphone

Both help each other to improve their accuracy!

Vehicle Behavior Model System Prototyping

Vehicle Mobility Model


Prof. 逄愛君 Prof. 蔡欣穆 Dr. 郭新鋼

PI Co-PI Champion

Ph.D. 林浩民

Senior 石浩安

Senior 許永健

Master 黃光世

Master 邱柏睿

Master 游舜翔

Postdoc Dr. 張世豪

Visible Light Communications

Senior 李蕙宇

System/Protocol Design

RF Link Measurement

Master 龍晶

Senior 歐志先

Visiting Scholar Dr. Nawaporn Wisitpongphan

Our Team

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