P3
P29
P47
P79

Transportation Safety and Operator Sleepiness:
Where Biology Needs Technology
Professor David F. Dinges, PhD
Division of Sleep & Chronobiology, Department of Psychiatry
Perelman School of Medicine
University of Pennsylvania
Philadelphia, Pennsylvania USA“Traffic Safety in the Future”
20 September 2012
International Association of Traffic and Safety Sciences (IATSS)
2012 International Workshop
Tokyo Japan© David F. Dinges—may not be copied or used without permission

Transportation Safety and Operator Sleepiness:
Where Biology Needs Technology
Four key points
I.

Transportation systems involve continuous operations.

II. Healthy sleep is essential to operate a motor vehicle safely.
III. Driving sleepy is common and a risk to transportation safety.
IV. Driver incapacitation from sleep loss requires novel solutions.

© David F. Dinges—may not be copied or used without permission

5

Transportation Safety and Operator Sleepiness:
Where Biology Needs Technology
I. Transportation systems involve continuous operations.
A. 24-hour operations in transportation modalities
B. Inadequate sleep has been associated with majortransportation accidents
C. The commute conundrum: Evidence that time spent driving
can affect sleep time

© David F. Dinges—may not be copied or used without permission

Sleep need and circadian timing are often in conflictwith the work demands of industrialized societies
Manufacturing, banking,transportation, mining,
health care, public safety,
power plants are some ofmany industries that now
operate 24/7.

© David F. Dinges—may not be copied or used without permission

6

Contributors to human behavior 24/7
• global economy (investment markets, banking, etc.)• proliferation of around-the-clock industries• widespread use of nonstop automated systems• increased exposure to night shift work
• growing trend toward prolonged work hours• overnight and just-in-time delivery• emergency operations• physical access to entertainment, shopping, etc.
• internet access around the clock• early school start times coupled with later bed times• life style chronic sleep restriction• 24-h vigilance by police and military• increased international commercial aviation© David F. Dinges—may not be copied or used without permission

Human activity often exceeds human sleep requirements

Commercial airplane flights in a 12-h period—each yellow dot is an airplane

Earth is rotating on its axis from left to right.

© David F. Dinges—may not be copied or used without permission

7

Driving with inadequate sleep results in fatigue,
sleepiness, and drowsiness that pose a significant risk
 Fatigue can be a risk to safety in general, and driving in particular.
(Mitler et al., 1988; Dinges, 1995; Lyznicki et al., 1998; Stutts et al., 2003; Barger et al., 2005)

 Fatigue is the physiological consequence of inadequate sleep.

(Dinges et al., 1997; Belenky et al., 2003; Van Dongen et al., 2003; Banks et al., 2010, 2011)

 Sleep loss degrades the ability to remain awake, alert and reactive.
(Lim & Dinges, 2008, 2010; Basner & Dinges, 2011; Roehrs et al., 2011)

 Sleep loss induced performance deficits equivalent to alcohol limits.
(Dawson & Reid, 1997; Williams & Feyer, 2000; Williams et al., 2001; Roehrs et al., 2003).

 Driving drowsy is common and frequently results in injury and fatality.
(Pack et al., 1995; Philip et. al., 2001; Connor et. al., 2002; Flatley et al., 2004).

 Driving drowsy had a 4-6 times higher crash risk relative to driving
alert, and a higher crash risk than distracted driving. (Klauer et al., 2006)© David F. Dinges—may not be copied or used without permission

Excessive sleepiness is a common and serious
problem due primarily to life style decisions andsecondarily to medical disorders and medications• Most common cause—Insufficient sleep syndrome• Shift work and jet lag disorders• Obstructive sleep apnea syndrome• Narcolepsy and hypersomnolence syndromes• Certain insomnias© David F. Dinges—may not be copied or used without permission

8

Americans exchange sleep time for compensatedwork time, travel and prime time television
Wake up times
Work time and travel time were theprimary activities that were reciprocallyrelated to sleep time among 47,731
Americans (Basner et al., 2007)
Work time(p < 0.0001)

Travel time(p < 0.0001)

Bed times

Evening
television
programmingand morning
alarm clocks
were theprimaryfactors
predicting
sleep onset
and offset,
respectively(Basner etal., 2009)© David F. Dinges—may not be copied or used without permission

Transportation Safety and Operator Sleepiness:
Where Biology Needs Technology
II. Healthy sleep is essential for the alertness required
to operate a motor vehicle
A. Evidence for the biological basis of sleep need
B. Evidence on how acute and chronic sleep loss affectalertness and performance
C. Evidence that sleep need can pose a performance risk
equivalent to alcohol© David F. Dinges—may not be copied or used without permission

9Sleep has not been eliminated by evolutionary
adaptation. It is ubiquitous in the animal kingdom
when defined by behavioral criteria (sans EEG)

• behavioral quiescence• stereotypical posture• reduced response to stimulation• spontaneously reversed in <24h• resists deprivation• increased following deprivation• no EEG criteria required
On the basis of these criteria, we can conclude that "sleep" is present throughout the
animal kingdom. It has been identified in alligators, turtles, lizards, frogs, salamanders,bees, wasps, flies, dragon flies, grasshoppers, butterflies, scorpions, and the primitive
invertebrate sea hare. Its presence in simpler animal models (C elegans, Zebrafish,
Drosophila melanogaster).
© David F. Dinges—may not be copied or used without permission

Sleep continuity, intensity and duration provide the“recovery” that restores alertness: Sleepinessincreases when any of these aspects are denied.

© David F. Dinges—may not be copied or used without permission

10Brain areas and receptors that maintain wake and sleep
are increasingly identified and targeted for medications
The human brain AWAKE

The human brain ASLEEP

Wafford & Ebert (2008)© David F. Dinges—may not be copied or used without permission

Earth’s orbital mechanics are instantiated in (and entrain) a
circadian genetic “clock” and sleep need in the human brain
Genes enforce the imperative of daily sleep and its timing
Human brain

24-hr period
Sunset over North
America Feb.1, 2003

SCN

Melatonin receptor binding on thehuman suprachiasmatic nucleus (SCN)(courtesy of David Weaver)

The SCN is the masterbiological (circadian) clock© David F. Dinges—may not be copied or used without permission

11

SCN neuron

Humanbehavior

Circadian clocks are based on
negative feedback loops:
Factors stimulate transcription ofgenes encoding proteins.
As the proteins accumulate they
act as transcriptional repressors of
their own genes.
From Moore, Science (1999)

Our circadian clock also has strong influence over
the timing of our sleep periods (sleep duration)

Duration of
247 layover
sleeps inlong-haulcommercial
pilots flying
Pacific
routessleep duration (actigraphy + diary)

Circadian timing from home dictates
sleep duration in long-haul pilots.

00
Rosekind et al. (1994)

06

12

18
00
06
time of day

12

18

00

© David F. Dinges—may not be copied or used without permission

Meta-analysis of the impact of 24-48h total
sleep deprivation on cognitive performance
Impact of 48h total sleep
deprivation on speed and accuracy
measures in 6 cognitive categories:
70 articles (147 cognitive tests) met
inclusion criteria.
Both speed and accuracy wereaffected across cognitive domains.
Effect sizes were largest for lapses
in simple attention, and smallest(nonsignificant) for reasoning
accuracy)*p<.01, **p<.001
Lim & Dinges (2010)© David F. Dinges—may not be copied or used without permission

12Illustration of wake state instability due to sleep loss:
PVT lapses of attention and uneven performance
Stable responses after an 8-hr sleep opportunity

Doran et al. (2001); Lim & Dinges (2008)50

stability = 0 lapses

frequency

40
30
20

1.5

>1.5

1.4

1.3

1.2

1.1

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0

0.2

10

rt (seconds)

Unstable responses after a night without sleep
50

frequency

40

instability = 33 lapses

30
20© David F. Dinges—may not be copied or used without permission

rt (seconds)

No matter what humans are doing—sleepiness canintrude into wakefulness even in highly motivated and welltrained individuals engaged in safety-sensitive activities
B747 transoceanic flights

Rosekind et al. (1994).

© David F. Dinges—may not be copied or used without permission

13

>1.5

1.5

1.4

1.3

1.2

1.1

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0

0.2

10

Stable wake state

Lapses areerrors ofomission andwhen theyoccur errorsof commission
can increase

Wake state instability due to inadequate sleep

Doran et al. ( 2001) ; Lim & Dinges (2008)© David F. Dinges—may not be copied or used without permission

Drummond et al. (2005); Chee et al. ( 2008)

Drowsy driving crash risk varies across the day in a mannerreflecting (nonlinear) circadian and sleep need dynamics
USA National Highway Traffic Safety Administration (NHTSA) estimates driver
fatigue annual costs to be: $12.5 billion,
100,000 police-reported crashes
1,550 deaths (4% of fatalities)
71,000 injuries

Time of day of 4,333 highway crashes in which the driver was judged to be asleep but not intoxicated.
(Pack et al., 1995)© David F. Dinges—may not be copied or used without permission

14

A drowsy driving crash requires a lapse of
only a few seconds to result in a crash© David F. Dinges—may not be copied or used without permission

Sleep loss is cumulative and people are often not awareof how much it is affecting alertness and performance
Vigilance lapses occur more
frequently with each day of sleep
duration below 7 hours

Vigilance lapses increased acrossdays of sleep restriction, but ratingsof fatigue changed much less24-40 hr TSD

Van Dongen et al. (2003)

40-64 hr TSD
24-40 hr TSD

Coefficients for cognitive
functions were near linear

worsening

Sleepiness and Lapsing

40-64 hr TSD

Coefficients for subjective
impressions were saturating

Consecutive days of sleep
restriction

Belenky et al. (2003)© David F. Dinges—may not be copied or used without permission

15

Studies equating the effects of alcohol on
performance to those of time awake on
performance have found 18h awake ≈ 0.05 g%(8 other studies also equate prolonged
wakefulness with BAC >0.04 g%)

In the USA fall asleep crashes areoften as lethal as alcohol crashes

Pack et al. (1995)
Dawson & Reid (1997)© David F. Dinges—may not be copied or used without permission

Transportation Safety and Operator Sleepiness:
Where Biology Needs Technology
III. Driving sleepy is common enough to be a concern
in transportation safety
A. Evidence that driving sleepy is common
B. Evidence that driving sleepy increases crash risk

© David F. Dinges—may not be copied or used without permission

16

USA National Survey of Distracted and Drowsy
Driving Attitudes and Behaviors: 2002
 Telephone interviews with nationally representative survey of 4,010
drivers (age ≥ 16 yr) 37% of the driving population reports having nodded off or fallen
asleep while driving at some time in their life. Males (49%) are
more likely to report this than female drivers (26%).
 About 22% of male drivers who have nodded off at the wheel reporthaving done so within the past month, compared to 19% of females.
 Among drivers who had a drowsy driving event in the past 6 months• 28% reported it occurred between midnight and 6:00 a.m.
• 35% reported it occurred between 6:00 a.m. and 5:00 p.m.
• 17% reported it occurred between 5:00 p.m. and 9:00 p.m.
National Survey of Distracted and Drowsy Driving Attitudes and Behaviors: 2002. Volume 1-Findings Report.
Submitted to the National Highway Traffic Safety Administration by The Gallup Organization.
http://www.nhtsa.dot.gov/people/injury/drowsy_driving1/survey-distractive03/index.htm© David F. Dinges—may not be copied or used without permission

National Survey of Distracted and Drowsy
Driving Attitudes and Behaviors: 2002
 Average of 6 hours sleep reported the night prior to a drowsy
driving experience• 24% reported having just ≤4 hours of sleep the prior night• 26% reported having 6 hours sleep the prior night• 33% reported having ≥7 hours of sleep the prior night Drowsy drivers under age 30 reported an average of 5.5 hours of
sleep the night before they nodded off at the wheel. The average
sleep time of drowsy drivers increased with age. Those ≥ 65yr
reported episode after an average of 7.7 hours of sleep
 Relatively few drivers who nod off at the wheel report having had
consumed alcohol (2%) or allergy or other medications (12%) prior
to their trip
National Survey of Distracted and Drowsy Driving Attitudes and Behaviors: 2002. Volume 1-Findings Report.
Submitted to the National Highway Traffic Safety Administration by The Gallup Organization.
http://www.nhtsa.dot.gov/people/injury/drowsy_driving1/survey-distractive03/index.htm© David F. Dinges—may not be copied or used without permission

17National Survey of Distracted and Drowsy
Driving Attitudes and Behaviors: 2002
 When feeling sleepy while driving, 43% say they pull over and nap(especially males); 26% open a window to get air; 17% get a coffee orsoda to drink; 14% turn on the radio or increase its volume; 3% sing/talk 92% of drivers who have nodded off while driving within the past 6months report that they startled awake.
• 33% wandered into another lane or onto the shoulder• 19% crossed the centerline• 10% ran off the road
 While it happened in only about 2% of the most recent drowsy
driving episodes, it is estimated that approximately 292,000
drivers were involved in some type of crash within the past six
months as a result of nodding off at the wheel.
National Survey of Distracted and Drowsy Driving Attitudes and Behaviors: 2002. Volume 1-Findings Report.
Submitted to the National Highway Traffic Safety Administration by The Gallup Organization.
http://www.nhtsa.dot.gov/people/injury/drowsy_driving1/survey-distractive03/index.htm© David F. Dinges—may not be copied or used without permission

National Survey of Distracted and Drowsy
Driving Attitudes and Behaviors: 2002
NHTSA (2002)“NHTSA data indicate that in recent years there have been about 56,000
crashes annually in which driver drowsiness/fatigue was cited by police.
Annual averages of roughly 40,000 nonfatal injuries and 1,550 fatalities
result from these crashes. It is widely recognized that these statistics
underreport the extent of these types of crashes. These statistics also
do not deal with crashes caused by driver inattention, which is believed
to be a larger problem.”

NHTSA (2002)

While the proportion of drivers involved in a crash as a result of nodding
off at the wheel is very small, the actual numbers of drivers involved insuch crashes over the past five years is sizable. An estimated 1.35 million
drivers have been involved in a drowsy driving related crashes in the past
five years (270,000 crashes annually). About seven in ten of these drivers,or 972,000 were males, while 379,000 were females.
National Survey of Distracted and Drowsy Driving Attitudes and Behaviors: 2002. Volume 1-Findings Report. Submitted
to the National Highway Traffic Safety Administration by The Gallup Organization.
http://www.nhtsa.dot.gov/people/injury/drowsy_driving1/survey-distractive03/index.htm© David F. Dinges—may not be copied or used without permission

18

Driving sleepy has been found to be a significant factor
in injury-related and fatal crashes in many countries• New Zealand: “There was an eightfold increased risk if drivers
reported sleepiness and almost a threefold risk for drivers who
were driving after five hours or less of sleep.” (Connor et al.,2002)
• France: A survey of 67,671 crashes in France determined 10%
were fatigue related. (Philip et al., 2001)• United Kingdom: The authors of a recent study that examined1828 crashes in the UK reported that 17% of the accidents
resulting in injury or death were sleep related. (Flatley et al.,2004)

© David F. Dinges—may not be copied or used without permission

Drowsy driving in metropolitan Washington, DC, USA wasfound to be as common as distracted driving, and it
occurred more often during daylight/lighted conditions.
Secondary task-related epochs
Total epochs

Drowsiness-related epochs“It appears driving drowsy
during the daylight may beslightly riskier than driving
drowsy in the dark. While it iscommonly thought that mostdrowsiness-related crashes
occur at night, a majority of thedrowsiness-related crashes inthis study occurred during thedaytime in heavy traffic (duringmorning and evening
commutes). Thus, the risks ofdriving drowsy during the day
may be slightly higher than atnight due to higher traffic
density.” (p. 41)

Klauer SG et al. The Impact of Driver Inattention on Near-Crash/Crash Risk: An Analysis Using the
100-Car Naturalistic Driving Study Data. USA DOT HS 810 594 IS NHTSA, pp1-224, April, 2006
© David F. Dinges—may not be copied or used without permission

19

People often believe they can drive and work (even on
safety-sensitive tasks) when they have a sleep debt

video
© David F. Dinges—may not be copied or used without permission

Truck drivers are at risk for drowsy driving crashes
from sleep disorders and work-rest schedules
Drowsy driver crashes
cost $12 billion andcontribute to a third ofthe ∼4,000 annual
truck driver deaths in
the US.

Study of 406 commercial truck drivers found increases insubjective sleepiness (ESS), MSLT, and performance (PVT,
DADT) were linearly associated with shorter sleep durations,but associations with severity of sleep apnea were not as
robust and not strictly monotonic. Severe sleep apnea (AHI
>29/h) was found in 4.7% of drivers, while sleep duration<5h/night was found in 13.5% , and these conditions weresimilar in their impact on objective sleepiness.
Pack A. et al. Impaired Performance in Commercial Drivers: Role of Sleep
Apnea and Short Sleep Duration; AJRCCM, 174:446–454, 2006

Pennsylvania, USA (2000)
Hazmat crash (sulfuric acid)
Closed one of the busiest highways in the US for 24 h

© David F. Dinges—may not be copied or used without permission

20

Bus drivers are at risk for drowsy driving crashes
from sleep disorders and work-rest schedules
Bus driver with sleep debt anduntreated sleep complaint(could sleep only 3-4h)
Pennsylvania, USA (1998)
7 killed, 16 injured

Bus driver had <4h sleep in
51h, stayed awake to gamble,
New York, USA (2002)
5 killed, 42 injured© David F. Dinges—may not be copied or used without permission

Sleep-related crash involving two modes of transportation

UK (2001): A motor vehicle operator who had been awake all night began driving his Land Rover at
05:00 h. He fell asleep at the wheel, veered off the motorway and lodged his vehicle on thesouthbound East Coast railway line. After exiting his vehicle, a commuter train traveling 125 mph
smash into his vehicle. The southbound train was derailed, only to collide with a northbound freighttrain running at 60 mph. The crash killed 10 and injured >60. The driver was convicted of convicted of© David F. Dinges—may not be copied or used without permission
10 counts of causing death by dangerous driving.

21

Sleep loss has contributed to serious maritime catastrophes
People have difficulty believing that a human can make a fatigue-related error
while performing an over-learned task under highly motivated (even lifethreatening) conditions. But it happens because fatigue is a risk state that
degrades behavioral efficiency. These maritime allisions illustrate this point.
Grounding of the oil super tanker Exxon Valdez
Prince William Sound, Alaska, USA (1989)
Severe environmental damage and costs in thetens of billions of dollars

Staten Island Ferry rams into pier
New York City, USA (2003)
10 killed, 34 injured∼25 million passengers a year

© David F. Dinges—may not be copied or used without permission

Transportation Safety and Operator Sleepiness:
Where Biology Needs Technology
IV. Are there solutions to driver incapacitation fromsleep need?
A. Is education to avoid sleepy driving likely to be effective?
B. Are increased rest stops a cost-effective solution without
unintended consequences?
C. Are vehicle technologies feasible that safely inform, warn
and/or alert sleepy drivers?

Using technology to help manage fatigue© David F. Dinges—may not be copied or used without permission

22

Maintaining Human Behavioral Capability:
Where Biology Needs Technology
Why technologies can help humans cope behaviorally Performance is dynamically nonlinear (C+S)—work rules aren’t Large differences among people in neurobehavioral vulnerability Lack of awareness of relationship between “fatigue” and risk
 Need to inform people of when recovery is essential & how much
Accurate feedback regarding an individual’s sleepiness level• evaluate clinically for treatment needs• to prevent/reduce imminent risk
• to manage fatigue from life styleSleep and circadian drives in the brain interact tocontrol performance and alertness: Mathematicalmodels attempt to predict this performance timing
Two-process model:
oscillator interacting with aquasi-linear process
Increased
behavioral
capability
Performance, alertness,threat detection,risk taking,mood and morale,
behavioral efficiency

Resulting behavioral
alertness from
nonlinear interaction
Van Dongen & Dinges (2000)

Reducedbehavioral
capability© David F. Dinges—may not be copied or used without permission

23

Tracking astronaut alertness with the PVT-B(Reaction Self Test) during 6-month missions
on the International Space Station (ISS)© David F. Dinges—may not be copied or used without permission

Study of effects of feedback on driver sleep and sleepiness
WRAIR SleepWatch

SafeTRAC lane-tracking monitor
PVT-192

CoPilot infrared retinal reflectance monitor
Howard Power Center
Steering System

Eye images from
CoPilot
Dinges DF et al (2005)© David F. Dinges—may not be copied or used without permission

24

Objective feedback (FMT) on drowsiness/performance whiledriving at night led to reductions in driver drowsiness andlane tracking variability, and more sleep on days off duty
Technologies

Actigraphy

sleep (h) from actigraphy

provided

feedback onalertnessduring nightdriving

Lane tracker

Perclos

APP+
black box
recorderPVT perf. test

Streeringstability

Dinges DF et al. J Transportation Res Board No. 1922,
National Academies, Wash. DC, 175-182 (2005).

© David F. Dinges—may not be copied or used without permission

During night driving, fatigue feedback
decreased lane tracking variability (p < 0.0001)
Expected “alertness” decreased after hour 8 of night driving.

Dinges et al. J Transportation Res Board No. 1922, TRB of the National Academies, Washington, DC, 175-182, 2005.
© David F. Dinges—may not be copied or used without permission25

Feedback improved lane tracking at nightin commercial truck drivers
Feedback by driving time interaction was significant P<0.0001

ns
P<0.01

Dinges et al.J Transportation Res Board No. 1922, TRB of the National Academies, Washington, DC, 175-182, 2005.
© David F. Dinges—may not be copied or used without permission

Feedback to truck drivers about their
sleepiness increased sleep time on days off

Dinges et al. J Transportation Res Board No. 1922, TRB of the National Academies, Washington, DC, 175-182, 2005.
© David F. Dinges—may not be copied or used without permission

26

Drowsiness has a characteristic neurobehavioral profile

Pack et al. (1995)© David F. Dinges—may not be copied or used without permission

Changes in neurobehavioral markers can reflect
sleepiness—tracking ocular sleepiness(PERCLOS)PERCLOS refers to the percent of timeslow eyelid closures cover the pupil.
PERCLOS was the best predictor of
PVT lapses of attention© David F. Dinges—may not be copied or used without permission

27

Dinges et al. (1998); Dinges et al. (2002)

D Metaxas, PhD

Measure of sleepiness based on
optical computer recognition(OCR) of eyelids (levator
palpebrae superioris muscle)

No sleep deprivation
PVT lapses = 0 in 1-min video below
4 in 20-min test boutEyes closed epochs = 125 (4.1 sec)
Avg. blink duration = 132 ms

Sleep deprivation
PVT lapses = 4 in 1-min video below
42 in 20-min test boutEyes closed epochs =308 (10.2 sec)
Avg. blink duration = 205 ms (+54%)© David F. Dinges—may not be copied or used without permission

Research supported by:
USA National Institutes of Health (NINR, NHLBI, NCRR)
NASA & National Space Biomedical Research InstituteDepartment of Transportation; Department of Defense
Colleagues,
collaborators,
trainees andtechnical staff

Americas 1st
medical school© David F. Dinges—may not be copied or used without permission

28Traffic Safety in Japan and Germany –Success, Deficiencies, Future Potentials
Director and Professor a.D.
Dr.-Ing. Ekkehard Brühning

Similarities in motorization and roadsafety in 2010

•
•
•
•
•

•
•
•
•
•

Capital: Tokyo
128 million inhabitants
646 vehicles / 1000 inh.
5 745 road fatalities
4.5 fatalities / 100 000 inh

Capital: Berlin
81.8 million inhabitants
614 vehicles / 1 000 inh.
3 648 road fatalities
4.5 fatalities / 100 000 inh
IRTAD (2011)231

Downward trend in fatality figures
Fatalities
Fatalities / 100 000 inhabitants

Fatalities / billion vehicle-km
Motorization (mot. veh. / 1000 inh.)

1990

2010

% changeJ

14 5955745- 60 %

G

11046

3648

- 67 %

J

11.8

4.5

- 62 %

G

14.0

4.5

- 68 %

J

23.2

7.7

- 67 %

G

20.0

5.2

- 74 %

J

216

646

+ 299 %

G

529

614

+ 116 %IRTAD (2011)3

Reasons for safety improvements• Engineering(road, vehicle, traffic planning, …)• Legal measures(speed, alcohol, safety belt, …)• Education(driver training, pedestrian behaviour, …)• Enforcement(police …)• Emergency Medical Service at road accidents
432Fatalities by road type / location in 2010
3500

3121

Number of fatalities

3000
2500

2472

2207

Rural roads

2000

Built-up areas

1500
1000
500

Motorways

1011
430

152

0

Japan

Germany
IRTAD (2011)
5

The German Road Safety Programme 2011
requires for Rural Roads• Preventing accidents involving a collision with a roadside
obstacle• Motorcycle-friendly safety systems• Providing additional overtaking lanes to prevent overtaking
accidents• Enhancing road safety at junctions• Deploying speed monitoring at accident blackspots• Evaluating measures to prevent accidents involving wildlife

33Tree-lined roads in Germany
Example: Dangerous road segment- Before treatment- After treatment

Weber (2003)
7

Fatally injured pedestrians and cyclists
by age group in 2010
under 65

Pedestrian - J

28.4

Pedestrian - G

65-74
22.2

52.1

Cyclist - J

27.2

48.3
0%

20%

49.5
14.9

37.7

Cyclist - G

75 and older

35.1
27.6

40%

32.8

60%

24.1
80%

100%

National Police Agency (2011)
Statistisches Bundesamt (2011)

34

8

Proportion of driving license holders
by age and gender
％

90
80
70
60
50

40
30

G

20
10

J

0

Al ages 65-74 75-84

G

Men

J
Women

85+

Japanese data derivefrom 2010 (Ministry of Health, Labour &Welfare/National Police Agency)
Germany data derive from 2004 (Kalinowska et al, 2007)(Okamura, 2011)

Bicycle crossing at a main arterial street
in Tokyo35

9The Japanese Traffic Safety Programme has
3 strategic objectives and 8 pillars.
The 3 strategic objectives are:

1. Safety for the elderly and children,
2. Pedestrian and bicycle safety,
3. Ensuring safety on roads serving the community andon main roads.

Among the 8 pillars are:

1. Improvement of the road traffic environment,
2. Dissemination and reinforcement of traffic safety messages,
3. Safe driving.
There are a great number of possible measures outlined in detail

Improving road traffic environment

Small streets in a residential area nearby a school

Photos: Nishida (2012)36

Fatalities
caused by alcohol-impaired drivers
Alcohol is tolerated in most countries/societies –in Germany and Japan, too

Alcohol-related road fatalities
J - 6.0 % of all fatalities in 2010
G - 9.4 % of all fatalities in 201037

Alcohol-impaired drivers (involved in crashes)per 1 000 driving licenses
Japan in 2006

Germany in 2005
4.5

4.0
3.5

Male
Female

3.0
2.5
2.0
Male

0.6
0.4
0.2
0.0

1.5

Female1.0
0.5
0.0
18 - 21 - 25 - 45 - 55 - 65+ All
20 24 44 54 64
ages
Okamura (2012)15

Trend in number ofconvicted alcohol-impaired drivers
300000250000200000Japan
Germany

15000010000050000
02000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
National Police Agency (2011)
Statistisches Bundesamt (2011)

38

16

Proportion of fatalities
caused by alcohol-impaired drivers in 2010
Australia (BAC >=0.05%, 2006)

29

USA (BAC >= 0.08%)

31

France (BAC >= 0.05%)

31
16

Sweden (BAC >= 0.02%)

14

Great Britain (BAC >= 0.08%)
9

Germany (BAC >= 0.03%)
Japan (BAC >= 0.03%)

6
0

5

10

15

20

25

30

%

35

Austroads (2010), European Transport Safety Council (2012),
NHTSA (2012), National Police Agency (2012)17

Emergency service at road accidents
in Germany• Arrivals of ambulance vehicle on the accident spot
average = 9.0 min
95 % < 18.4 min• Arrival of rescue physician on the spot by vehicle
average = 12.0 min
95 % < 26.6 min• HEMS – Helicopter Emergency Medical Service
at 2.5% of road accident emergency cases
Unfallverhütungsbericht Straßenverkehr 2008/2009

39

HEMS: Helicopter Emergency Medical Service
Ca. 100 air rescue helicopters in G
for medical emergencies of any kind
System established in the 1970s and 1980s
HEMS provided by different organizations1913

道北（旭川赤十字病院）

ドクターヘリの配備状況○ ○○30道府県35箇所
秋田（秋田赤十字病院）
栃木（獨協医大病院）
群馬（前橋赤十字病院）

沖縄（浦添総合病院）

長野東（佐久総合病院）

大阪（大阪大学病院）○

道東（釧路市立総合病院）
道央（手稲渓仁会病院）
青森（八戸市立市民病院）
岩手（岩手医大病院）

長野西（信州大学病院）
岐阜（岐阜大学病院）
三重（三重大学病院）

○
○
○
○
○○○
○
○ ○
○○
○ ○
○
○
○
○○
○
○ ○ ○
○

兵庫（公立豊岡病院）
岡山（川崎医科大学病院）
島根（島根県立中央病院）

福島（福島県立医大病院）
茨城（水戸済生会総合病院/
水戸医療センター）

埼玉（埼玉医大総合医療センター）
千葉北（日本医大千葉北総病院）
山口（山口大学病院）
千葉南（君津中央病院）
神奈川（東海大学医学部付属病院）
山梨（山梨県立中央病院）
高知（高知医療センター） 静岡東（順天堂大学静岡病院）
福岡（久留米大学病院）
静岡西（聖隷三方原病院）
愛知（愛知医科大学病院）
熊本（熊本赤十字病院）
和歌山（和歌山県立医大病院）
2012年5月現在
宮崎（宮崎大学医学部付属病院）
HEM Net (2012)
長崎（長崎医療センター）
鹿児島（鹿児島市立病院）

40

Progress in vehicle safety- Great success in the past throughimprovements in passive safety- New horizons through accident avoiding
electronic (driver) assistance systems

Passive safety – state of the art• Stiff Passenger Compartment Cell
• Belt Pretensioner• Belt Load Limiter• Multi-Stage Airbags• “Soft“ Interior Design• Crash-Design: “Self Protection“41Pre-Crash-Safety(Crosslinking with systems of the Active Safety)
Benefit for Passive Safety:– Collision mitigation– Time for optimization of parameters– Pre-deployment of airbag

Conclusion:
Future Improvements of Passive Safety –significant, substantial improvement, but
not a new “dimension“

42Accident avoiding electronic(driver) assistance systems
For many years on the market:- Anti-lock Braking System (ABS)- Electronic Stability Control (ESC)- Brake Assist System (BAS)

Evaluation of (driver) assistance systems– Reduction of serious injuries in the EUIntelligent Speed Adaptation

11.0

Advanced Adaptive Cruise Control

11.0

Collision Avoidance

9.1

Collision Warning

6.6

Traffic Sign Recognition

5.8

Lane Keeping Assistant

5.7

Night Vision

4.8

Blind Spot Detection

4.0

Lane Changing Assistant

3.1

Alcolock Key

3.0

Drowsy Driver Detection System

2.9

TRACE (2009)

0

4

43

8

12 %

“Forward collision avoidance systems,
particularly those that brakeautonomously, show some of thebiggest crash reductions.”

IIHS (2012)

How to increase the market
penetration of driver assistancesystems?

44

Mandatory Fitment Requirements for
Active Safety Systems in the EU
Year

SystemType approval for

1991

ABS Anti-lock Breaking System

Trucks >7.5 t

2009

BAS Brake Assist System

Cars

2011

ESC Electronic Stability Control
DRL Daytime Running Light

Cars

2012

TPM Tire Pressure Monitoring System

Cars

2013

AEBS Advanced Emergency Breaking System
LDWS Lane Departure Warning System

Trucks >7.5 t

2014

ESC Electronic Stability Control

Trucks >3.5 t

2016

AEBS Advanced Emergency Breaking System
LDWS Lane Departure Warning System

Trucks 3.5 – 7.5 t

AEBS Increased speed reduction

Trucks >7.5 t

ABS Anti-lock Breaking System

Motorcycles >50ccm

2016/17?

(EU Directives / Regulations)

29Euro NCAP Driver Assist(Decision of 12 June 2012)

Fitment requirements in EU

2012

2013

2014

2015

2016

2017

SBR Seatbelt Reminder

100 %

100 %

100 %

100 %

100 %

100 %

ESC Electr. Stability Controle(= EU Regulation, 2011)

100 %

100 %

100 %

100 %

100 %

100 %

50 %

50 %

70 %

100 %

100 %

AEB Advanced Emergency
Braking (Inter Urban > 40km/h)

50 %

50 %

70 %

100 %

AEB (City < 50km/h)

100 %

100 %

100 %

100 %

100 %

100 %

70 %

100 %

SAS Speed Assist Systems

AEB (Pedestrian)

LDW/LKD Lane Departure
Warning / Lane Keeping Device

50 %Euro NCAP (2012)

50 %

30

45

Arigato / Acknowledgements
for close co-operation and valuable assistance to- Kazuko Okamura, Dr. phil, National Research Institute of

Police Science (Kashiwa)

for useful information and photos received from- Hirotoshi Ishikawa, Dr. Eng., HEM Net (Tokyo)- Yasushi Nishida, Institute of Traffic Accident Research andData Analysis (Tokyo)- Nobuaki Takubo, PhD, National Research Institute of Police

Science (Kashiwa)

46

Reliability of Motorway Operation

Prof.(em.) Dr.-Ing. Werner Brilon

Ruhr-University Bochum / Germany
and BPS GmbH Karlsruhe / Germany
Tokyo Sept. 21st 2012

1

Reliability of Motorway Operation
1. Introduction:
What is reliability? Why do we use this term?
2. How do we describe reliability?
3. How to improve reliability?
4. What is the advantage of reliability concepts?

2

49

1

German„Autobahn“ 3Objectives

Traditional objectives forhighway design and operation:
Safetyaccident cost rates

traffic efficiency

speed

economic efficiency
environmental compatibility

ratio: benefit / costs
miscellaneous indicators

4

50

2

Classic macroscopic description of traffic flow : qq-v-diagram

140

capacityv [km/h](km/h)
average speed

120
100
80
60
40
20
0
0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

q [Kfz/h]
volume(veh/h)5Classic macroscopic description of traffic flow : qq-v-diagram

e.g. German HBS 2001 : 33-lane freeway
6

2

51

3

Highway Design Process

Traditional:
Choice of a specific single peak hour (e.g. 30th hour).
Comparison of this traffic demand and capacity
to assess the quality of traffic flow.

7

Highway Design Process

Traditional:

Reality:source of pictures: FHWA

8

52

4

Highway Design Process

Limitations of traditional analysis:•

A single peak hour can not reflect the whole life cycleof a road infrastructure.

•

Highest demands are not considered.

•

Average Speed is not of too much importanceto the drivers.
Small increase of speed
does not produce economic benefit.
Only applicable for proper operation;
no consideration of disturbance due toworkwork-zones, accidents, incidents, weather
No assessment of overloaded conditions (LOS F).

•
•
•

9

Highway Design Process

Consequences:•

We need a modified scale
to evaluate traffic performance.

•

The concept should focus
on the intrinsic purpose of the highway infrastructure.

•

The concept must consider
incidents, accidents, workwork-zones, etc.

•

This concept should be interrelated with traffic safety.

10

4

53

5

More timely Approach to express Traffic Efficiency

Objective of the road user (both passengers and cargo):•

to arrive within a time marginwhich can reasonably expected.

Scale for traffic efficiency important to the road user:•

risk of a remarkable delay.

Æ Reliability

11

Future Parameters of Traffic Performance

Reliability =Probability that the motorway
operates at a performance level
better than a defined minimum standard(i.e. a still satisfactory service quality; e.g. LOS D)

Indicators for reliability:

probability of congestion
delays per year due to freeway overload
duration of all congestions during a year
ratio of real travel time to average travel time
....
12

54

6

Disfunctioning of motorways

Potential reasons for breakdowns on motorways:•

failure of infrastructure•

accidents•

incidents (vehicle malfunction, road closure, …)•

demand exceeds capacity•

workwork-zones with reduced capacity•

bad weather (storm, snow, heavy rain, bad visibility…
visibility…)•

other events: like festivals, sporting events, catastrophes, …

13

Disfunctioning of motorways

Observed reasons for breakdowns on motorways:

14

6

55

7

Reliability is a function of:•basic capacity of the infrastructure•

maintenance of the infrastructure•

performance of control systems•

qualification of operational staff•

quality of vehicles•

behavior of drivers•

weather•…

15

Two basic features of transportation systems:

Delay

1. NonNon-linearity• Up to ≈ 60% of capacity
traffic systems are not sensible to moderate disturbances.
• atat-capacity:
800
Small incidents
cause
severe congestion.
600
400

200

0

0,0

0,2

0,4

0,6

0,8

1,0

1,2

1,4

degree of saturation
16

56

8

Two basic features of transportation systems:
2. Normal operation (like designed) is happening very seldom.
(always more than 10 % of the network are workwork-zones.)source of picture: FHWA

17

2. How to measure reliability?
variability of travel times•

variance of travel times•

95th percentile of travel time•

traveltravel-time index (TTI)••=average travel time
travel time ( free flow speed )planning time index (PTI)=

95% travel time
travel time ( free flow speed )buffer index=

expected max. lost time
⋅ 100
average travel timepercent of onon-time arrivals
lost times due to congestion

probability that a driver experiences congestion;i.e. percent failure based on a target minimum speed.
18

8

57

9

average speed [km/h]

90
80
70
mph

Mittlere Pkw-Reisegeschwindigkeit [km/h]

150

dreistreifig, außerhalb von Ballungsräumen, s≤2%

140
130
120
110

capacity

100
90
80

SV-Anteil [%]:20 10% trucks : 20 10 0

70

5399

60

0

5401

50
0

1000

2000

3000

4000

Gesamtverkehrsstärke [Kfz/h]Volume [veh/h]

5000

54006000
19

Randomness of Capacityv [km/h]q [veh/h]Pattern over time for traffic volume and speed(1-minute-intervals)
for a whole day with several breakdowns

70 km/htime [minutes]
20

58

10

10

Randomness of Capacity

space mean speed (km/h)

140
120
100
80
60
40
20
0
0

1000

2000

3000

4000

5000

6000

7000

volume (veh/h)21

Randomness of Capacity
Variability of traffic volumes preceding a breakdown

Intervals just before the breakdownq [veh/h]
22

59

11

Randomness of Capacity

23

WeibullWeibull-Distribution for the Breakdown Capacity
Density functionf ( x) =

α
β

α

x

⎛x⎞
− ⎜⎜ ⎟⎟
α −1 ⎝ β ⎠Distribution functionαe

β = scale parameterF( x ) = 1 − e⎛x⎞− ⎜⎜ ⎟⎟⎝β⎠α

α = form parameter

Maximum-Likelihood Estimation with Weibull-distributionδ⎡⎛α 1− δi ⎤α i ⎛⎛ qi ⎞ ⎞⎟⎛ qi ⎞ ⎞⎢⎥⎜⎜− ⎜⎜ ⎟⎟− ⎜⎜ ⎟⎟ ⎟
n
β⎠ ⎟
β⎠ ⎟
α −1
−α
⎢
⎥
⎝
⎝
⎜
⎜
L = ∏ α ⋅ β ⋅ qi
⋅ e
⋅e
⎢⎜
⎥
⎟ ⎜
⎟
i =1 ⎢⎜
⎥
⎟
⎟ ⎜
⎠
⎠ ⎝
⎢⎣⎝
⎥⎦
24

60

12

12

Distribution Function of Freeway Capacity (3 Lanes, 55-Minute Intervals)

0,85

0,15

25

Deterministic versus Stochastic Capacity

90 %

26

61

13

Comparison :dry / wet road surface

3-lane motorway (3 lanes per direction)
daylight
5-minute-intervals
distribution function

dry

wet

volume [veh/h]27

Whole year analysis (WYA) of traffic performance
A year is generally long enoughto capture nearly all of the variability
caused by various kinds of breakdown
and, thus,
thus, to represent also longer periods:
periods:
Congested situations:situations:
How often?
often?
Worst situation to be expected?
expected?
Total impacts?
impacts?

28

62

14

14

Whole year analysis (WYA) of traffic performancecapacity
demand29

Whole year analysis (WYA) of traffic performance
Taken into account :•random variation of capacity and of demand•

capacity drop•

accidents and incidents•

wet road surface capacity reduction

Method:Monte-Carlo-simulation with mutliple evaluation ofdelays etc. for a whole year
+ subsequent calculation of expectations
30

63

15

Whole year analysis (WYA) of traffic performance
Results :duration of congestion
sum of all delays
number of vehicles involved
percentage of vehicles involved
economic value of delays(all as expectation per year)
Travel time index, Planning time index, BufferBuffer-index…
can be combined with evaluation of ecological parameters(e.g. fuel consumption,…
consumption,…)31

Whole year analysis (WYA) of traffic performance

Anzahl der Überlastungen [-]Number of oversaturations per year

1000
900

no. of congestions
due to traffic overloads
per year

800
700
600
500
400
300
200
100
0
0

0,2

0,4

0,6

0,8

1

1,2

0,1*DTV/C[-]
O.1 * ADT
/ capacity
mittelaverage
32

64

16

16

Whole year analysis (WYA) of traffic performance
Results from with/without analysis:
effects of accidents + incidents
effects of traffic control devices
effects of organizational improvements(fast accident removal, workwork-zone management,…
management,…)
effects of structural improvements

33

3. How to improve reliability?
capacity and infrastructure•

adequate infrastructural capacity•

active traffic control•

temporary hardhard-shoulder running•workwork-zone management•

emergency management (accidents & incidents)•

highhigh-quality construction of infrastructure Æ less maintenance

34

65

17

Adequate capacity of the infrastructure

35

Optimization of efficiency [veh*km/h]
veh*km/h]
Maximum efficiency
in veh*km/h
Average speed [km/h]

maximum efficiency
is achieved at 90 %of the classical capacity
Classical
capacity

volume [veh/h]
36

66

18

18

Appraisal of motorway design schemes by WYA

example: restructuring of an urban motorway (A620):
Existing
infrastructure

Direction MA
Direction Lux

new layout
value of travel time [€/year]
0

40
20
80
60
1.
1.
00
20
0.0
0.0
0.0
0.0
0.
0.
00
00
00
00
00
00
0
0

reduced delays:
delays:76 600 vehveh-h/year

reduced cost of time:
570 000 €/year

justifies an investment of

8.4 Mio €+ improved safety
37

Active traffic control

Motorway traffic control center(with manpower,
manpower,
video supervision,
supervision, …)+
mandate to take action(police,emergency services,traffic control devices,road workers)
38

67

19

Temporary hard shoulder runningÆ

only during peak hours

Æ

always with a speed limit of 100 km/h

Æ

+ 25 % capacityÆ

no additional risks
39

WorkWork-zone management
WorkWork-zones reduce capacity Æ reduced reliability

40

68

20

20

Freeway Sections with workwork-zone (5(5-Minute Intervals)

Freeway A3, 4+2 scheme
1,0

1,0

with construction zone
without construction zone

0,8

with construction zone
without construction zone

0,9
probability of breakdown (-)

0,9probability of breakdown (-)

Freeway A5, 5+1 scheme

0,7
0,6
0,5
0,4
0,3
0,2
0,1

0,8
0,7
0,6
0,5
0,4
0,3
0,2
0,1

0,0
3000

4000

5000

6000
7000
flow rate (veh/h)

8000

0,0
3000

9000

Median Capacity -9.4%

4000

5000

6000
7000
flow rate (veh/h)

8000

9000

Median Capacity -16.7%

Standard deviation is significantly lower
Median of capacity distribution of a construction zone
(3-lane carriageway) is in the range of 6000 to 6300 veh/h
41

WorkWork-zone managementa) timing of construction works and maintenance(e.g. during holiday season; in offoff-peak periods;…
periods;…)b) reduction of workwork-zone duration
by rewarding construction firms for work acceleration
to be tested by WYA

42

69

21

Emergency management (incidents & accidents)
accidents)
less accidents Æ more reliabilty
Everything which avoids accidents
will improve the reliability of the system.

43

Emergency management (incidents & accidents)
accidents)
Reduction of the duration of lane closures due to accidents
 modified strategies for the police presence of towtow-trucks during peaks at bottlenecks
Charging drivers (accidents & incidents)
according to the degree of congestion caused (conceptual)

44

70

22

22

3. How to improve reliability?
demand• time dependent tolls• demand management(e.g. rewards for offoff-peak travel; (e.g. NL: Sitsmijden)
Sitsmijden)
better information about expected travel times,…
times,…)

Seattle freeway reliability
schemesource of picture: WS-DOT

45

3. How to improve reliability?
demand• demand management(e.g. better information about expected travel times,…
times,…)

Best time to leave

Where are you starting from:

SeattleWhere are you going?

Redmont

When do you need to et there?

8:25

Your 95% travel time is 31 minutes.
95% of the time
you would need to leave at 7:54 AM to arrive by 8:25 AM.
Seattle freeway reliability
schemesource of picture: WS-DOT

46

71

23

3. How to improve reliability?
smoothening traffic flow•

traffic adaptive speed control•

truck overtaking restrictions(above specified levels of traffic flow)•ramp metering•

integration of inin-vehicle and stationary guidance systems•

driver education

47

Active adaptive speed control

with additional temporary
truck overtaking prohibition
48

72

24

24

Impact of dynamic speed control

49

Impact of dynamic speed control on safety
on average:
form 17.1 Æ 12.2

accident rate [acc./1 Mio veh*km]

30
25
20
15
10
5
0
A43

A4

A8

A61

A44

A3

before

A1/61

A10

A5

A9

after

Accident rate: before/after analysis at 10 traffic actuated speed control sites(Siegener e.a. 2000)
50

73

25

Ramp metering

Bochum / Germany

UK

51

Travel time indication

Frankfurt / Germany

Paris

52

74

26

26

Travel time indication

Travel time indication by navigation systems
teaches drivers that aggressive driving
does not save travel time.
53

Traditional concept

Reliability concept

source of pictures: FHWA

54

75

27

Focus on Reliability in the USA

source of picture: FHWA

55

Advantage of Reliability Concepts
Reliability is more important than speed
both for travelers and cargo
Reliability paves the way towards traffic performancebased oninfrastructure improvements
traffic control measuresorganizational input
Full integration of overloaded situations (LOS F)
into the system of performance assessment.
More reliability Æ more safety
These integrated concepts meet today’
today’s necessities
56

76

28

28

Conclusion
Safety is target #1
beyond safety the central objective for motorway
design and operation Æ Reliability
mathematical description of breakdown probabilities= key to reliability management
WYA (whole year analysis)= adequate method for analysis
In addition to infrastructureorganizational (soft) measures provide a significant
contribution to improved reliability.
Reliability and safety complement each other:= 2 sides of the same medal.
57

Thank you for listening

58

77

29

Researchon the territorial approach to safety
D. Fleury
IFSTTAR - France
IATSS 2012 International Workshop
20 – 21 September

Présentation Ifsttar 04012011

The trend of safety in France: from 8,253 deathsin 2001 to 3,963 in 2011
Research on the territorial approach to safety• The evolution of the territorial approach tosafety• Safety as an area of complex systemmanagement.
• The conditions for improvement81I - The evolution of the territorial
approach to safety
How safety had structured traffic network design••

19th century: the development of motorised transportation has a tremendous
impact.
Great specialisation of traffic areas (according to speed)

Cerda, Henard, Le Corbusier, ..

Principles of segregating modes of transportation and the hierarchy of roads

How safety had structured traffic network design• Buchanan• The SCAFT guide of 1968
-Reduce traffic by localising activities-Separate modes of transportation-Differentiate the network by functions-Differentiate the various traffic flows-Clarify, simplify and standardise the design

Principle of environmental area

-Design a safe road side82

How safety had structured traffic network design
The "Woonerf" in the 70’s
Integrating modes and functions"traffic calming" principles

The dynamic of design resulting from an “Island Strategy”

Controversies
30-km/h city
• In Great Britain, Living Streets has launched a campaign to reduce speed in London
to 20 mph.
• In Switzerland, ATE (Association of Transports and the Environment) pushed for avote on a popular initiative held on 4 March 2001 (rejected by 79.7%)• In France : Fontenay aux Roses, Nogent sur Marne, Sceaux, Clamart, Sèvres, Clichy
la Garenne, Lorient, Neuilly-les-Dijon… but…
• In 2011, 54.9% of the population of Strasbourg rejected the project to turn thecity center into a 30 km/h zone
Naked Street• “A street or public space where vehicle movement and other activities are
combined through informal social protocols, negotiation and design solutions
rather than through formal regulations and controls.” (Living Streets, 2009).
• Many towns have experimented with this concept.
• But there is no consensus : Blind People, Deaf People, Cyclists

83II - Safety as an area of complex
system management
The actual design• Road safety not the main challenge in public space layouts• other considerations : accessibility, urban quality,
sociability, etc…
Concerns sometimes contradictory:• fewer cars in front of houses but greater accessibility• lower speeds and rerouted lorry traffic• shopkeepers want more parking spaces and better vehiclerotation• associations want more cycling paths• less nuisance and fewer traffic jams
But all constraints involving private transportation arepolitically difficult to promote.

In practice
A safety diagnosis is carried out, soon forgotten
Thesis of Frédérique Hernandez (2003) on Local
Transport Plan in Marseille.
• An action scene with the decision-making actors• confrontation between possible solutions• precise projects and more general technicalnotions

84

Relatiogram(Hernandez, 2003)

A process:• certain projects disappear from the technical landscape• relations become clearer• coherence arises• the Local Transport Plan scheme takes form
an “island strategy”:• automobile traffic bypasses the central areas• dense zones are connected by public transport• the primary network is requalified with the tramway,
reducing room for private travel modes• high-performance cycling network is created…

85

“islandstrategy”
atdifferentscale

A current practice

INSECURITY

Reference
to

OPERATIONAL
TOOLS

86

Laid down
in

TECHNICALDESIGN

Complexity• Because of the adaptability of users, drivers, pedestrians – users of public
spaces
The road system is a complex system and is therefore unpredictable.
• The relationship between the decision maker and the population using
traffic spaces is a two-player game.
• the user will adapt his behavior in a way that is more effective for him, andnot necessarily in a way that is better for collective safety••••

improvements to visibility that reduce attention
road resurfacing that increases speed
creating cycling lanes used by powered two-wheelers
misuse of on-board systems …

All decisions are taken in a context of uncertainty. It is then necessary tomeasure the results of actions

But let us imagine that safety could
become a priority objective…
proj

SAFETYOBJECTIVES

Transcribed into

Via

TECHNICALPRINCIPLES

Used forOPERATIONALTOOLSTECHNICALDESIGN
Technical evaluation“Conceptual” evaluation
Project evaluation

87This use of objectives, then technical principles, andthen tools for integration, requires a real evaluation
effort in return• The technical evaluation measures the impact of a
project’s implementation on safety• The conceptual evaluation provides feedback
used to apply a particular tool in several• The project evaluation widens the viewpoint to
the entire decision-making process

III - The conditions for improvement
Training in road safety
Ezra Hauer (2007) describes two styles of thought on road safety• The first is “pragmatic”, based on beliefs and the immediate interests oforganizations.
• The second style defined by Ezra Hauer is “rational”
Four reasons explain the shift from the first style to the second:• The first is that humanity has always evolved that way• what remains to be done requires more serious knowledge• legislation requires safety to be taken into account when planning• many initiatives go in the right direction
But little demand for people with road safety training, which pleads in favorof the third condition, i.e. resorting to legal obligation

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The conditions for improvement
Availability of accident data.
• In 2004 in France, the transmission of current judicial proceedings
to IFSTTAR• after text recognition, automatic requests are performed• geolocation software is used to spatialise the information
Geographic Information Systems• Data: geographical, economic, socioeconomic, demographic or
financial, networks, notably transportation networks, business orrecreational areas, built-up areas by function, etc…
• The link between these two sources of information lead to themeasure of risk (group of inhabitants)• This created a change of perspective in the foundation of local
public policies on road safety

Example : the relative risk of depraved areas

Estimation of the Ajusted Relative Risk : 1,363, interval [1,238 ; 1,502].

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The conditions for improvement
Accident prototypical scenarios• “A prototypical traffic accident scenario can be defined
as a prototype of an accident process corresponding toa group of accidents with overall similarities in terms ofthe chain of events and causal relationships in the
different phases leading to the collision”• The construction of a real accident nosology in theform of prototypical scenarios• It makes it possible to target actions to specific users,
vehicles and environments

In conclusion
Who is responsible for safety, the urban layout designer or the user?
• avoiding all driver errors and, if an accident does occur minimal
consequences.
-> responsibility lies with the engineer (see “Vision Zero” in Sweden)• calling for “civic behavior” or “good manners”-> responsibility lies with the user (see the “Naked Street” )Coming back to the second diagram• a good evaluation of the design processes and the layout tools• well-documented and well-evaluated feedback
Effectiveness depends on :• The location• The quality of the layout• The kinds of users present• we need a good evaluation of the design processes and therefore toevaluate projects, rather than only evaluating layout tools independentlyof their location.
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In conclusion
For a higher level of safety:• the progress of knowledge and its dissemination,• the development of technical tools for the design as well as for
accident analysis and safety diagnosis,
But• the lack of involvement of local politician and of the public, when
they stress already made solution and “common sense” approach,not taking into account the complexity of the problem

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