applications in traffic accident research to improve ...€¦ · position movement video. 31...

Verkehrsunfallforschung

ein Unternehmen der

an der TU Dresden GmbH

APPLICATIONS IN TRAFFIC ACCIDENT

RESEARCH TO IMPROVE VEHICLE SAFETY

MathWorks, Automotive Conference 2019, Europe

Dipl.-Ing. Florian SpitzhüttlInstitute for Traffic Accident Research

at Dresden University of Technology

2

Structure

1. Necessity of traffic accident research

2. Application assisted accident investigation

3. Data analyses for research on traffic safety

4. Pre-crash simulation to enhance traffic safety

5. Conclusion





5. Conclusion

3

Accident research in the 1920s

Applications in Traffic accident research to improve vehicle safety

Necessity of traffic accident research

Source: YoutubeEarly “accident research” in Dresden

4

Accident scenario in Germany

o Car occupants benefit from

active and passive safety

o Numbers of accidents &

casualties are stagnating

since some years

o In 2017 persons:

• Fatalities 3,186

• Seriously injured 66,495

• Slightly injured 323,659



- 10 %

- 14 %

- 41 %

+ 17 %

0%

20%

40%

60%

80%

100%

120%

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

Source: DESTATIS, Fachserie

6



General information

Accident sketch

Technical investigation

Medical investigation

≈ 2.000

accidents/year

GIDAS – German In-Depth Accident Study, since 1999

Ø 3.500 single

information/accident

7



Source: Google Maps & GIDAS

Accident level

Vehicle level

Personal level

…

~34.500accidents

~62.000vehicles

~85.000persons

Only accidents with

personal damage

Criteria Investigation area Database

Hanover

Dresden

8





5. Conclusion

Structure

9

Some examples


Application assisted accident investigation

OpenStreetMap (OSM)

for accident sketch

Coding of injuries Signal processing

of measurements

10





5. Conclusion

Structure

11


Data analyses for research on traffic safety

Databases Access and processing

Source: ESV 2017 – Bakker, Spitzhüttl et al.:

“IGLAD - International harmonized in-depth accident data”

13

0 ... n – regression coefficients

x1 ... xn – independent variables

Mathematical models – Injury Risk Functions (IRF); example: pedestrians in car accidents



p(slightly injured) = 28 %

p(seriously injured) = 34 %

p(slightly injured) = 46 %

p(fatally injured) = 21 %

p(seriously injured) = 33 %

p(fatally injured) = 38 %

Real accident:

vcoll = 50 km/h

Accident with system

(e.g. AEB):

vcoll = 40 km/h

14

Mathematical models – Injury Risk Functions (IRF)

Multidimensional



15

Calculation of deformation frequencies

o Normalized car dimensions

and discretization into voxel

o Accumulation of accident deformations

for 1,000 passenger cars

Analyzation of potentially safe

places for sensitive and/or

dangerous energy storage

(e.g. battery or gas)



16





5. Conclusion

Structure

17

ACEA Safety Model


Pre-crash simulation to enhance traffic safety

Phase 4

In-Crash-Phase

Phase 1

Normal driving

Phase 5

Post-Crash-Phase

𝑡𝑢collision unavoidable

Phase 3

Pre-Crash-Phase

Sequence of a traffic accident

𝑡0collision

𝑡𝑐𝑟𝑖𝑡critical event

Phase 2

Incident-Phase

Tertiary safetyActive safety Integral safety Passive safety

19



VUFO Accident Simulation Toolbox (VAST)

Sketch

External data

Virtual camera images

sent back to Simulink.

Source: Mathworks.com

20



Evaluation of opponent‘s position at specific TTC

* 400 ms before crash

· 200 ms before crash

21



VUFO Accident Simulation Toolbox (VAST)

Sketch

External data

22



Example accident – Sketch Accident scene

23

Example accident – Simulation



real accident situation real accident situation

with ADAS System

24



Point of no return tu when a collision is unavoidable

o Severity of damages as a function of time

• continuous

• differentiable

o No knowledge about the exact function

o f(tu) = 0

• no analytical solution possible

25




Source: Winner et al., H. (2015). „Handbuch Fahrerassistenzsysteme,

Grundlagen, Komponenten und Systeme für aktive Sicherheit und Komfort“

Circle of forces / „Kamm‘scher Kreis“

26


o Severity of damages as a function of time

• continuous

• differentiable

o No knowledge about the exact function

o f(tu) = 0

• no analytical solution possible

• approximation by iterative process

and variable integration step size



27

Point of no return tu when a collision is unavoidable – Generic rear-end collision



tu = f(∆v, μ); vobj = 40 km/h

∆v = 2 …100 km/h , μ = 0,1... 1,0 tu comparison of simulation and literature

28

Point of no return tu when a collision is unavoidable – real accident’s rear-end collision



real accident situation tu simulation

29

Naturalistic driving study (NDS) Incidents and Events



30

Naturalistic driving study (NDS)

Real scenario



Recording

o Camera

o Accelerometer

o Rotation rate sensor

o GPS

o Sender and receiver device

o Processor und ring memory

Position Movement Video

31


Real scenario Simulation



32




0 50 100 150 200 250-1

0

1

2Anfahrverhalten

Zeit in s

Längsbeschle

unig

ung m

/s²

0 50 100 150 200 2500

20

40

60

GP

S G

eschw

indig

keit k

m/h

33




Source: GDV, VUFO (2016): „Unfälle mit Beteiligung von Wohnmobilen in Deutschland“

Driver 1 Driver 2 Driver 3

Pas

sern

ger

car

Cam

pin

g v

an

Driver 1:o Large scatter range

o Significant difference between

passenger car and camping van

o High accelerations

Driver 2:o Marginal difference between

passenger car and camping van

o Experienced driving

Driver 3:o Low scatter range

o Higher acceleration in passenger car

34




VW Caddy:

Responsibility for children

Renault Espace:

Marital-problems

Suzuki Swift:

Divorce

Renault Megane:

New relationship

Renault Megane:

Crisis in relationship

Renault Laguna:

On-Off relationship20

17

20

15

20

16

36


Ground truth labeling with



37

Naturalistic driving study (NDS) vs. Real world accident



38





5. Conclusion

AGENDA

39

o Assurance of traffic safety must be a very high society target.

Human errors must not lead to fatalities in a modern traffic environment!

o In contrast to past trends, recent statistics show a

stagnation in the accident numbers.

o The development of Highly Automated Driving

needs some more efforts to ensure a

safe and modern concept of movement.

o Therefore it is very important to improve on

crucial aspects of

• ensuring functional safety

• study real world scenarios

• progress on perception infrastructure to support vehicle systems.


Conclusion

???

Verkehrsunfallforschung

ein Unternehmen der

an der TU Dresden GmbH

THANK YOU

FOR YOUR ATTENTION!

Florian Spitzhüttl

Data analyses and simulation

[email protected]

Tel.: +49 351 43 89 89 22
mailto:[email protected]

applications in traffic accident research to improve ...€¦ · position movement video. 31...

Documents