Leonard Evans President, Science Serving Society President-Emeritus, International Traffic Medicine Association Bloomfield Hills, Michigan USA Devoted

Leonard EvansPresident, Science Serving Society

President-Emeritus, International Traffic Medicine AssociationBloomfield Hills, Michigan

USA

Devoted to adding reason and knowledge to public policy

ScienceServingSociety.com

School of Transportation Science and EngineeringInternational Res. Inst. for Multidisciplinary Science

Beihang University, Beijing1 September 2015

Traffic safety: Key vehicle and driver behavior factors

1.2 million people killed each year on the world’s roads

Harm from traffic - almost incomprehensible magnitude

Injures vastly outnumber fatalities

Victims mainly healthy young people

Key is knowledge gained from science

What can be done to reduce this enormous harm?

A solid edifice of knowledge exists

Scientific literature since 1930s has papers on traffic safety

Is too often ignored – with tragic results

Bow of Titanic – 3.8 km under Atlantic Ocean. Photographed 2 Sept. 2000 by Leonard Evans

Scene from 2000 Chinese movie

The Road Home, (director Zhang Yimou)

Summarizes what science has taught about traffic safety

www.ScienceServingSociety.com

Captain Edward J. Smith27JAN1850–15APR1912

Safety lessons from sinking of the Titanic

Age when Titanic sailed

62 years 2.6 months Titanic leaving Belfast

2 April 1912

Titanic illustrates central distinction between:-

1. Crash Protection

Given crash occurs, to reduce consequent harm

2. Crash Avoidance

To prevent crash occurring

Did Titanic’s superior crash protection save 705 lives, or cause over 1500 deaths?

Did Titanic’s superior crash protection save 705 lives, or cause over 1500 deaths?

Early recognition of distinction between

1. Technology

2. How it is used – driver behavior

Now look at peer-reviewed technical literature

All previous anecdotal

Paper in Amercan Journal of Psychology

“More efficient brakes on an

automobile will not in themselves

make driving the automobile any

safer.”

A Theoretical Field-Analysis of

Automobile Driving, American

Journal of Psychology 1938

Claim that better brakes do not increase safety based on reason alone

But is it possible to address empirically?

Did not happen in

1940s

1950s

1960s

1970s

1980s

then opportunity occurred!

Dramatic advance in brake technology

Increases rollover risk by (39+16)%

Large numbers of GM popular vehicles:

1991 MY – NONE had ABS

1992 MY – ALL had ABS

Otherwise, no important differences

ABS (antilock brakes)

Engineering factors affecting survival in crashes

Biomechanics - the science of relationships between injuries and the mechanical forces that produce them:

Penetrating trauma

Blunt trauma

To reduce severity of blunt trauma – reduce force by reducing deceleration of body

Spread stopping over as much distance, and time, as feasible through

occupant protection devices

vehicle characteristics and design

Scientific study needs data

By far, most reliable data is for fatalities

Even though death just tip of iceberg in numbers, much attention is devoted to it

Fatal Accident Reporting SystemName changed

Feb. 1998

Census of all US traffic crashes in which anyone is killed on a public road

Run by US National Highway Traffic Safety Administration (NHTSA)

Data from 1 January 1975

Over 1.6 million fatalities documented through 2013

Fatality Analysis Reporting System (FARS)

Occupant protection device effectiveness

Occupant protection device Occupant Effectiveness in

preventing fatalities

Airbag plus lap/shoulder belt Car driver (47 4)%

Lap/shoulder belt Car driver ( 42 4)%

Airbag only Car driver (13 4)%

Lap belt Rear-seat passenger (18 9)%

Helmet Motorcycle riders (28 8)%

































The vehicle factor having largest influence on occupant risk is:

Vehicle mass (weight) and size

Large Truck 1 2.7

Large Truck

Medium Truck

Relative Driver Fatality Risk in One Vehicle Crashing into Another Vehicle

Large Truck 1 2.7 16 18

Large Truck

Medium Truck

VanPickup


Large Truck 1 2.7 16 18 22 29 44

Large Truck

Medium Truck

Heavy Car

Medium Car

Light Car

VanPickup


Large Truck 1 2.7 16 18 22 29 44 1997 -

Large Truck

Medium Truck

Heavy Car

Medium Car

Light Car

VanPickup

Motorcycle

Moped


Large Truck

Medium Truck

1 2.7 16 18 22 29 44 1997 -

Large Truck

Medium Truck

Heavy Car

Medium Car

Light Car

VanPickup

Motorcycle

Moped

1 17 10 12 18 34 605 -


Large Truck

Medium Truck

Van

Pickup

1 2.7 16 18 22 29 44 1997 -

Large Truck

Medium Truck

Heavy Car

Medium Car

Light Car

VanPickup

Motorcycle

Moped

1 17 10 12 18 34 605 -

1 1.3 1.7 3.3 9.3 579 -

1 1.3 2.7 7.1 283 253


Large Truck

Medium Truck

Heavy Car

Medium Car

Light Car

Van

Pickup

1 2.7 16 18 22 29 44 1997 -

Large Truck

Medium Truck

Heavy Car

Medium Car

Light Car

VanPickup

Motorcycle

Moped

1 17 10 12 18 34 605 -

1 1.3 1.7 3.3 9.3 579 -

1 1.3 2.7 7.1 283 253

1 2.4 7.7 153 205

1 3.1 85 202

1 42 139


Large Truck

Medium Truck

Heavy Car

Medium Car

Light Car

Van

Pickup

Motorcycle

Moped

1 2.7 16 18 22 29 44 1997 -

Large Truck

Medium Truck

Heavy Car

Medium Car

Light Car

VanPickup

Motorcycle

Moped

1 17 10 12 18 34 605 -

1 1.3 1.7 3.3 9.3 579 -

1 1.3 2.7 7.1 283 253

1 2.4 7.7 153 205

1 3.1 85 202

1 42 139

1 2.8

1


How are R and μ related?

Two key measures:

1. mass ratio, μ = mass of car2

mass of car1

=m2

m1

car2mass m2

car1mass m1

R = probability of driver fatality in car1

probability of driver fatality in car2

2. driver fatality risk ratio, R,

1 1.1 1.2 1.3 1.4 1.5 1.6 1.8 2.0 2.21

2

3

45

7

10

20

R =

15,356 unbelted drivers killed in 13,162 front-impact two car-crashes

R = 3.58

FARS 1975-1998

dri

ve

r fa

tali

tie

s i

n l

igh

ter

ca

rd

riv

er

fata

liti

es

in

he

av

ier

ca

r

mass of heavier carmass of lighter car

1 1.1 1.2 1.3 1.4 1.5 1.6 1.8 2.0 2.21

2

3

45

7

10

20

R =

15,356 unbelted drivers killed in 13,162 front-impact two car-crashes

R = 3.58

FARS 1975-1998

dri

ve

r fa

tali

tie

s i

n l

igh

ter

ca

rd

riv

er

fata

liti

es

in

he

av

ier

ca

r

mass of heavier carmass of lighter car

v of 900 kg car 6% greater than v of 1800 kg car

Risk in 900 kg car 30% greater than risk in 1800 kg lb car due to 6% higher v

900 kg car14,000 kg truck

14,000 kg truck1800 kg car

risk ratio = 44

risk ratio = 22

What is the casual role of mass and size?

Am I safer if I put bricks in my trunk?

Does NOT answer

How does change in RELATIVE risk affect each driver individually?

If cars differ only in mass, R = μu

If cars differ in another attribute, say one carries additional cargo

R = probability of accompanied driver fatality in car1

probability of lone driver fatality in car2 R = A μu

A estimates effect passenger’s presence has on driver risk when car masses are the same

car2 car1

driver +passenger

lone driver

0.5 0.6 0.8 1 1.2 1.5 2

0.1

0.2

0.5

1

2

5

10

R = 0.855 3.36

3692 unbelted drivers killed in 3118 front-impact two-car crashes

FARS 1975-1998

R =

dri

ve

r fa

tali

tie

s i

n c

ar

wit

h p

as

se

ng

er

dri

ve

r fa

tali

tie

s i

n c

ar

wit

h d

riv

er

on

ly

mass of car with passengermass of car with driver only

CONCLUSION

Addition of passenger changes driver fatality ratio by

-(14.5 ± 2.3)%

BUT

We do not know how much of this change is a risk reduction to the accompanied driver and a risk increase to the lone driver

To answer, we model process

r1,2 = xm2

m1 ( )

1.79

net effect = intrinsic size x intrinsic mass

L1 + L2

2.452.45

c

A picture is worth

100 equations

Car and Driver, April 1998

When it comes to vehicle safety, putting on weight is good for your health

Driver performance

Driver behavior

r

acin

g-d

rive

r ra

te

co

mp

aris

on

-dri

ver

rate

0.0

1.0

2.0

3.0Texas

Racing drivers MORE occurrencesthan comparison drivers

Racing drivers FEWER occurrencesthan comparison drivers

Racing drivers same as comparison drivers

rac

ing

-dri

ver

rate

com

par

iso

n-d

rive

r ra

te

0.0

1.0

2.0

3.0Texas




speeding violations

r

acin

g-d

rive

r ra

te

co

mp

aris

on

-dri

ver

rate

0.0

1.0

2.0

3.0Texas




speeding violations

r

acin

g-d

rive

r ra

te

co

mp

aris

on

-dri

ver

rate

0.0

1.0

2.0

3.0Texas

speeding violations REPORTED CRASHES

r

acin

g-d

rive

r ra

te

co

mp

aris

on

-dri

ver

rate

0.0

1.0

2.0

3.0Texas


r

acin

g-d

rive

r ra

te

co

mp

aris

on

-dri

ver

rate

0.0

1.0

2.0

3.0Texas


r

acin

g-d

rive

r ra

te

co

mp

aris

on

-dri

ver

rate

0.0

1.0

2.0

3.0New York

Texas


r

acin

g-d

rive

r ra

te

co

mp

aris

on

-dri

ver

rate

0.0

1.0

2.0

3.0New York

Texas


r

acin

g-d

rive

r ra

te

co

mp

aris

on

-dri

ver

rate

0.0

1.0

2.0

3.0

Florida

New York

Texas


r

acin

g-d

rive

r ra

te

co

mp

aris

on

-dri

ver

rate

0.0

1.0

2.0

3.0

Florida

New York

Texas

Drivers with

Best visual acuity

Fastest reaction times

Most knowledge/interest in vehicles

Driver Performance

-- have highest crash rates!

(What the driver can do)

What is crucial is not what the driver can do -- (Driver Performance)

Driver Behavior

but

What the driver does do

rela

tive

cra

sh r

isk

BAC, %0.00 0.05 0.10 0.15 0.20 0.25

1

10

100Grand Rapids study

rela

tive

cra

sh r

isk

BAC, %0.00 0.05 0.10 0.15 0.20 0.25

1

10


Legal limit inall US States

rela

tive

cra

sh r

isk

BAC, %0.00 0.05 0.10 0.15 0.20 0.25

1

10


Legal limit inall US States

Named for town in MichiganPerformed by Robert Borkenstein

and colleagues

1962-1963

casu

alty

-cra

sh r

isk

at in

dic

ated

sp

eed

risk

at

60 k

m/h

sp

eed

lim

it

travel speed, km/h60 65 70 75 80 85

1

10

100urban roads in

Adelaide, Australia

60

U. of Adelaide data

casu

alty

-cra

sh r

isk

at in

dic

ated

sp

eed

risk

at

60 k

m/h

sp

eed

lim

it


1

10

100urban roads in

Adelaide, Australia

60

U. of Adelaide data

casu

alty

-cra

sh r

isk

at in

dic

ated

sp

eed

risk

at

60 k

m/h

sp

eed

lim

it


1

10

100urban roads in

Adelaide, Australia

60

U. of Adelaide data

casu

alty

-cra

sh r

isk

at in

dic

ated

sp

eed

risk

at

60 k

m/h

sp

eed

lim

it


1

10

100urban roads in

Adelaide, Australia

60

U. of Adelaide data

casu

alty

-cra

sh r

isk

at in

dic

ated

sp

eed

risk

at

60 k

m/h

sp

eed

lim

it


1

10

100urban roads in

Adelaide, Australia

60

U. of Adelaide data

casu

alty

-cra

sh r

isk

at in

dic

ated

sp

eed

risk

at

60 k

m/h

sp

eed

lim

it


1

10

100urban roads in

Adelaide, Australia

60

U. of Adelaide data

Effects of speed

1. Risk of crashing increases with increasing travel speed

2. If crash occurs, risk of injury increases with increasing speed

3. If injury occurs, risk that it is fatal increases with travel speed

1% increase in travel speed increases the risk of a fatal crash by at least 4%

Speed

Belt wearing

Drunk driving

Benefits only relevant occupant

Affects all road usersAffects all road users, although victim is usually the drunk driver (plus similarly drunk passengers)

Affects ALL road users – is central

International comparisons offer insights into best ways to reduce harm in traffic

US

A t

raff

ic f

atal

itie

s/ye

ar (

tho

usa

nd

s)

1900

1910

1920

1930

1940

1950

1960

1970

1980

1990

2000

2010

0

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60

US

A t

raff

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atal

itie

s/ye

ar (

tho

usa

nd

s)

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1910

1920

1930

1940

1950

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2000

2010

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30

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50

60

Because fatalities reach a maximum number, we can define a simple ratio:

Dimensionless (no units) No arbitrary assumptions Depends ONLY on fatalities

Fatalities in a given yearMaximum yearly fatalities

Plot* how this ratio varies in time after maximum is reached

-------------*on logarithm scale, and x100 to express as %

US

A t

raff

ic f

atal

itie

s/ye

ar (

tho

usa

nd

s)

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1910

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1940

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1980

1990

2000

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years since reaching MAXIMUM0 5 10 15 20 25 30 35 40 45

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USA

data thru 2013

USAGBCanadaAustraliaNetherlandsSwitzerlandFinland GermanySpainS. KoreaSwedenFranceJapanItalyPolandGreeceBelgium Czech Republic HungaryAustriaIsraelDenmarkNorway IrelandNew ZealandPortugal









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USA

data thru 2013









2013 value is 40%below 1972 maximum

(32,719 down from 54,589)


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USACanada

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USAGBCanadaAustraliaItalySpainPolandS. KoreaSwitzerlandFranceJapanGermanySwedenNetherlandsAustriaDenmark


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Finland GreeceBelgium PortugalCzech Rep.HungaryIsraelNorway IrelandNew Zealand

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USAGBCanadaAustraliaItalySpainPolandS. KoreaSwitzerlandFranceJapanGermanySwedenNetherlandsAustriaDenmark


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USANetherlands

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This is 83.7% below The Netherlands’ all time high of 3,506 in 1972

The Netherlands had 570 traffic deaths in 2013

If US total had fallen by 83.7% from its high, US total in 2013 would be 8,875

(instead of 32,719 observed)

More than 20,000 additional Americans are killed annually because US fails to match decline in Netherlands (+ 10 other countries)

USA disaster lies in ignoring basic scientific finding - which is:

Vehicle factors are important


Vehicle factors are important, but less important than roadway factors



Roadway factors are important



Roadway factors are important, but less important than driver performance factors





Driver performance factors are importantctors




Driver performance factors are important, but less important than driver behavior factorsfactors

Predictions

Never make predictions —

especially about the future

Never make predictions

15 May 2015

Are already safer than human-controlled cars

Cannot become universal for many decades

System consisting exclusively of self-driving cars can approach perfect safety

This study, in agreement with earlier research, implies that there are over 200,000 annual traffic deaths in China.

How can this number be reduced?

Two recommendations

Conclusion

1 Create data-collecting agency

USA data set FARS is good model

2 Create traffic-safety research organization

Goal - accuracy and completeness

Supported by government, but largely independent of government

Best model is SWOV in the Netherlands

Make solicited and unsolicited science-based recommendations

Evaluate safety programs (implementation and evaluation must be kept separate)

Goal – highest quality objective scientific research

40+ years of ongoing improvement Free, comprehensive, and simple on web

Concluding comments

Traffic causes enormous numbers of injuries and deaths

Traffic-safety science can sharply reduced these numbers

Reliable data

“Disinterested” quality analysis

This requires

Summarizes what science has taught about traffic safety

www.ScienceServingSociety.com

Documents

Leonard Evans President, Science Serving Society President-Emeritus, International Traffic Medicine Association Bloomfield Hills, Michigan USA Devoted