driver aggressiveness analysis using multisensory data fusion a thesis submitted to the graduate ...

97 Pages·2016·8.54 MB·English

DRIVER AGGRESSIVENESS ANALYSIS USING MULTISENSORY DATA
FUSION
A THESIS SUBMITTED TO
THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES
OF
MIDDLE EAST TECHNICAL UNIVERSITY
BY
(cid:214)M(cid:220)RCAN KUMTEPE
IN PARTIAL FULFILLMENT OF THE REQUIREMENTS
FOR
THE DEGREE OF MASTER OF SCIENCE
IN
ELECTRICAL AND ELECTRONICS ENGINEERING
JANUARY 2016

Approval of the thesis:
DRIVER AGGRESSIVENESS ANALYSIS USING MULTISENSORY
DATA FUSION
submitted by (cid:214)M(cid:220)RCAN KUMTEPE in partial ful(cid:28)llment of the require-
ments for the degree of Master of Science in Electrical and Electronics
Engineering Department, Middle East Technical University by,
Prof. Dr. G(cid:252)lbin Dural (cid:220)nver
Dean, Graduate School of Natural and Applied Sciences
Prof. Dr. G(cid:246)n(cid:252)l Turhan Sayan
Head of Department, Electrical and Electronics Eng.
Prof. Dr. G(cid:246)zde Bozda§(cid:25) Akar
Supervisor, Elec. and Electronics Eng. Dept., METU
Examining Committee Members:
Prof. Dr. A. Ayd(cid:25)n Alatan
Electrical and Electronics Engineering Department, METU
Prof. Dr. G(cid:246)zde Bozda§(cid:25) Akar
Electrical and Electronics Engineering Department, METU
Assoc. Prof. Dr. Alptekin Temizel
Modeling and Simulation Department, METU
Assoc. Prof. Dr. (cid:157)lkay Ulusoy
Electrical and Electronics Engineering Department, METU
Asst. Prof. Dr. Osman Serdar Gedik
Computer Engineering Dept., Y(cid:25)ld(cid:25)r(cid:25)m Beyaz(cid:25)t University
Date: January 22, 2016
I hereby declare that all information in this document has been ob-
tained and presented in accordance with academic rules and ethical
conduct. I also declare that, as required by these rules and conduct,
I have fully cited and referenced all material and results that are not
original to this work.
Name, Last Name: (cid:214)M(cid:220)RCAN KUMTEPE
Signature :
iv
ABSTRACT
DRIVER AGGRESSIVENESS ANALYSIS USING MULTISENSORY DATA
FUSION
Kumtepe, (cid:214)m(cid:252)rcan
M.S., Department of Electrical and Electronics Engineering
Supervisor : Prof. Dr. G(cid:246)zde Bozda§(cid:25) Akar
January 2016, 77 pages
Every year a vast number of tra(cid:30)c accidents occur globally. These tra(cid:30)c acci-
dents cause fatalities, severe injuries and huge economical cost. Most of these
tra(cid:30)c accidents occur due to aggressive driving behaviour. Therefore, detection
of driver aggressiveness could help reducing the number of tra(cid:30)c accidents by
warning related authorities to take necessary precautions. Although aggressive-
ness is a psychological phenomenon, driver aggressiveness can be analysed by
monitoring certain driving behaviour such as abrupt lane changes, unsafe fol-
lowing distance and excess acceleration and deceleration. In this thesis work,
a method is introduced in order to detect aggressive driving behaviour using a
system on vehicle. The proposed method is based on fusion of visual and other
sensor information to characterize related driving session and to decide whether
the session involves aggressive driving behaviour. Visual information is used to
detect road lines and vehicle images; whereas CAN bus information provides
certain driving data such as vehicle speed and engine speed. Both information
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is used to obtain feature vectors which represent a driving session. These feature
vectorsareobtainedbymodellingtimeseriesdatabyGaussiandistributions. An
SVM classi(cid:28)er is utilized to classify the feature vectors in order for aggressive-
ness decision. The proposed system is tested by real tra(cid:30)c data and it achieved
an aggressive driving detection rate of 94.0%.
Keywords: Driver behavior, driver aggressiveness, road safety, line detection,
vehicle detection, CAN bus
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(cid:214)Z
˙OKLU SENS(cid:214)R VER(cid:157)S(cid:157) KAYNA(cid:147)TIRIMI KULLANARAK S(cid:220)R(cid:220)C(cid:220)
AGRES(cid:157)FL(cid:157)(cid:135)(cid:157) ANAL(cid:157)Z(cid:157)
Kumtepe, (cid:214)m(cid:252)rcan
Y(cid:252)ksek Lisans, Elektrik ve Elektronik M(cid:252)hendisli§i B(cid:246)l(cid:252)m(cid:252)
Tez Y(cid:246)neticisi : Prof. Dr. G(cid:246)zde Bozda§(cid:25) Akar
Ocak 2016 , 77 sayfa
Her y(cid:25)l d(cid:252)nya (cid:231)ap(cid:25)nda b(cid:252)y(cid:252)k say(cid:25)da tra(cid:28)k kazas(cid:25) ger(cid:231)ekle‡mektedir. Bu tra(cid:28)k
kazalar(cid:25) can kay(cid:25)plar(cid:25)na, ciddi sa§l(cid:25)k problemlerine ve b(cid:252)y(cid:252)k ekonomik mali-
yete yol a(cid:231)maktad(cid:25)r. Bu tra(cid:28)k kazalar(cid:25)n(cid:25)n b(cid:252)y(cid:252)k k(cid:25)sm(cid:25) agresif s(cid:252)r(cid:252)‡ davran(cid:25)‡(cid:25)
kaynakl(cid:25) olarak meydana gelmektedir. Bu nedenle, s(cid:252)r(cid:252)c(cid:252) agresi(cid:29)i§inin tespit
edilip ilgili kurumlar taraf(cid:25)ndan (cid:246)nlem al(cid:25)nmas(cid:25)n(cid:25)n sa§lanmas(cid:25) tra(cid:28)k kazalar(cid:25)-
n(cid:25)n say(cid:25)s(cid:25)n(cid:25) (cid:246)nemli (cid:246)l(cid:231)(cid:252)de azaltacakt(cid:25)r. Agresi(cid:29)i§in psikolojik bir olay olmas(cid:25)na
kar‡(cid:25)n, ani ‡erit de§i‡ikilikleri, g(cid:252)vensiz takip mesafesi ve ani ivmelenme gibi
s(cid:252)r(cid:252)‡ davran(cid:25)‡lar(cid:25)n(cid:25)n g(cid:246)zlemlenmesi ile analiz edilmesi m(cid:252)mk(cid:252)nd(cid:252)r. Bu tez (cid:231)a-
l(cid:25)‡mas(cid:25)nda, s(cid:252)r(cid:252)c(cid:252) agresi(cid:29)i§inin tespit edilmesi i(cid:231)in ara(cid:231) (cid:252)zerinde (cid:231)al(cid:25)‡acak bir
sistem sunulmu‡tur. Sunulan sistem, g(cid:246)rsel veri ve sens(cid:246)r verisinin ilgili s(cid:252)r(cid:252)‡(cid:252)
tan(cid:25)mlamak (cid:252)zere kayna‡t(cid:25)r(cid:25)lmas(cid:25) ve ilgili s(cid:252)r(cid:252)‡(cid:252)n agresif s(cid:252)r(cid:252)‡ davran(cid:25)‡(cid:25) i(cid:231)e-
rip i(cid:231)ermedi§ine karar verilmesine dayanmaktad(cid:25)r. Kameradan al(cid:25)nan veri yol
(cid:231)izgilerinin ve yoldaki ara(cid:231)lar(cid:25)n tespiti i(cid:231)n kullan(cid:25)lmakta, denetleyici alan(cid:25) a§
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veriyolundan ise ara(cid:231) ve motor h(cid:25)z(cid:25) bilgisi elde edilmektedir. Elde edilen bu bil-
giler, s(cid:252)r(cid:252)‡leri tan(cid:25)mlayan (cid:246)znitelik vekt(cid:246)rlerini elde edilmek i(cid:231)in kullan(cid:25)lmakta-
d(cid:25)r. Bu (cid:246)znitelik vekt(cid:246)rleri zaman serisi ‡eklindeki verilerin Gaussian da§(cid:25)l(cid:25)mlar
olarak modellenmesi ile elde edilmektedir. Bir destek vekt(cid:246)r makinesi (SVM) s(cid:25)-
n(cid:25)(cid:29)ay(cid:25)c(cid:25)s(cid:25) (cid:246)znitelik vekt(cid:246)rlerinin agresi(cid:29)ik i(cid:231)eri§i hakk(cid:25)nda s(cid:25)n(cid:25)(cid:29)and(cid:25)r(cid:25)lmas(cid:25) i(cid:231)in
kullan(cid:25)lmaktad(cid:25)r. Sistem ger(cid:231)ek tra(cid:28)k verisi ile test edilmi‡ ve %94.0 oran(cid:25)nda
do§ruluk pay(cid:25) ile ba‡ar(cid:25) g(cid:246)stermi‡tir.
Anahtar Kelimeler: S(cid:252)r(cid:252)c(cid:252) davran(cid:25)‡(cid:25), s(cid:252)r(cid:252)c(cid:252) agresi(cid:29)i§i, yol g(cid:252)venli§i, (cid:231)izgi tes-
piti, ara(cid:231) tespiti, CAN bus
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In memory of my father Duran Kumtepe,
who was always proud of me
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ACKNOWLEDGMENTS
First of all, I would like to present my sincere gratitude to my supervisor Prof.
G(cid:246)zde Bozda§(cid:25) Akar for her guidance from the very (cid:28)rst day of my academic
career. I feel myself very lucky for being student of such a gentle person and a
experienced academic. No matter what the problem is, any time I got stuck at a
point, she encouraged and provided me insightful ideas to overcome the problem
by her wisdom, accompanied with a full understanding manner. She brought
forward a wide variety of research alternatives and helped me to discover my
interests and to shape my future.
I would like to thank to Prof. A. Ayd(cid:25)n Alatan for sharing a huge knowledge
on computer vision and machine learning topics and whenever I asked for his
advise he never left my questions unanswered.
One of the biggest motivation in my graduate studies is being a member of
Multimedia Research Group. It has always been a great pleasure for me to work
with the members of the best research group of METU. I am thankful to each
and every current and former member for their valuable friendship. I would
like to thank to Emrecan Bat(cid:25) for sharing all his technical knowledge without
hesitation any time I ask for his help; Beril Be‡b(cid:25)nar for all long conversations
we had about life, hobbies and travelling; Ece Selin B(cid:246)nc(cid:252) for her energy and
making the atmosphere colourful with her energy; (cid:157)lker Buzcu for being my
companion during the courses that we took; Ak(cid:25)n ˙al(cid:25)‡kan for reminding me to
be always positive with his sincere smiles; Yeti Ziya G(cid:252)rb(cid:252)z for the TA tasks
we did together and being an enjoyable friend; Emin Zerman for helping me to
feel comfortable in the lab environment during my (cid:28)rst days and teaching me
research methods and academical approach to the problems. I am also grateful
to Dr. Alper Koz for his wisdom, advises and support during my research
activities. I would like to thank to the new members of our group O§ul Can
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