İyileştirilmiş dizi kararlı heterojen araç katarları için dağıtılmış oluşum kontrol algoritması geliştirilmesi
Distributed formation control algorithm development for improved string stability in heterogen vehicle platoons
Yazar: HAKAN SERT
Danışman: DOÇ. DR. SERHAT İKİZOĞLU
İstanbul Teknik Üniversitesi / Fen Bilimleri Enstitüsü / Kontrol ve Otomasyon Mühendisliği Ana Bilim Dalı / Kontrol ve Otomasyon Mühendisliği Bilim Dalı
Derece: Yüksek Lisans, 2018
Konu: Elektrik ve Elektronik Mühendisliği = Electrical and Electronics Engineering ; Ulaşım = Transportation

Özet:
Trafik sıkı¸sıklı˘gının azaltılması ve enerji verimlili˘ginin artırılması günümüz karayolu
ta¸sımacılı˘gında en önemli konuların ba¸sında gelmektedir. Aynı güzergah üzerinde
seyreden araçların aralarında koordine olarak bir düzen dahilinde katar olu¸sturmaları
bu iki konunun her ikisine birden fayda sa˘glamaktadır. Otomobil gibi görece küçük
araçlarda kısa takip mesafeli araç katarlarının olu¸smasıyla birlikte yolun kullanım
oranı ve trafi˘gin akı¸s hızı artarken otobüs, kamyon, çekici gibi a˘gır ticari araçların
katar olu¸sturmasıyla birlikte olu¸san rüzgar koridoru neticesi yakıt tüketimi de kayda
de˘ger derecede dü¸smekte, bu sayede enerji verimlili˘gi artmaktadır.
Bu konuda literatür çok eskilere gitmekle birlikte uygulama projeleri 90'lı yılların
sonunda ba¸slamı¸s, teknolojik altyapının geli¸smesiyle günümüzde oldukça hız
kazanmı¸stır. Buna paralel olarak araç katarlarının beraberinde getirdi˘gi sorunların
çözümü için gittikçe daha fazla sayıda çalı¸sma yapılmakta, ara¸stırma sonuçları
yayınlanmaktadır.
Araç katarlarıyla ilgili yukarıda bahsedilen problemlerin ba¸sında dizi kararlılı˘gı
gelmektedir. Dizi kararlı˘gı en basit haliyle lider araç ve hemen ardından gelen takip
aracı arasındaki pozisyon, hız veya ivme cinsinden hata i¸saretinin katar içinde geriye
do˘gru gidildikçe azalması, bir ba¸ska deyi¸sle sönümlenmesidir. Dizi kararlılı˘gı sa˘glayan
bir araç katarında kopmalar yahut çarpı¸smaların ve olası kazaların önüne geçilmi¸s olur.
Katarı olu¸sturan araçlar e¸slenik veya dinamik davranı¸sları ihmal edilebilecek seviyede
ise buna homojen araç katarı denir. Farklı türde araçların olu¸sturdu˘gu araç katarları
ise heterojen olarak adlandırılır. Bu tez çalı¸smasında heterojen araç katarlarında
dizi kararlılı˘gının iyile¸stirilmesine çalı¸sılmı¸stır. Bunun için katarı olu¸sturan araçların
dinamik farklarını gözönüne alan bir katar olu¸sum kontrol algoritması geli¸stirilmi¸stir.
Her ne kadar güvenlik açısından heterojen araç katarlarında araç dinamiklerinden
kaynaklanan davranı¸s farklılıklarını araç seviyesinde bertaraf etmek, araç seviyesi
kontrolcüye eklenecek ön düzenleyiciler vasıtasıyla mümkün olsa da, bu durum toplam
katar performansını ideal noktadan uzakla¸stırmaktadır. Çalı¸smada öne çıkan özellik,
benzer çalı¸smalardan farklı olarak heterojen katarlarda olu¸sum kontrol algoritmasında
her aracın dinamiklerini katar içindeki di˘ger araçlarla mukayese etmesi, bu sayede
her aracın katar içindeki optimum yerinin dizi kararlılı˘gını maksimize edecek ¸sekilde
belirlenmesidir. ˙Iyile¸stirilmi¸s dizi kararlılı˘gı sayesinde araçlar arasında daha yakın
takip aralı˘gı mümkün olmakta, bu sayede yol kullanım oranı ve yakıt ekonomisinde
iyile¸sme sa˘glanmaktadır. Çalı¸sma sonucunda ortaya çıkan algoritmanın iyile¸sme
sa˘gladı˘gı simülasyonlar e¸sli˘ginde kar¸sıla¸stırmalı olarak ortaya konmu¸stur. Bir di˘ger
dikkate de˘ger husus ise algoritmanın merkezi de˘gil, her araç içerisinde ba˘gımsız olarak
ko¸suyor olmasıdır. Bu sayede modüler biçimde araçlara entegrasyonu mümkün olup
herhangi merkezi bir i¸slemciye veya yöneticiye ihtiyaç duymamaktadır.

Abstract:
Traffic congestion and energy saving have been the utmost major subjects in road
transportation. Vehicle platooning is already proved to have potential to improve both.
Literature goes back few decades while experiments started as early as late 90s. Basic
idea of platooning is to have a string of vehicles with closer gap than normal driving
with use of automation. The automation is in simplest form a coordinated adaptive
cruise control (CACC) in which constant time gap following strategy is implemented.
Platooning is different from CACC that it has constant distance following strategy
rather than time gap.
Benefits of platoons comes from its vehicle following strategy. Closer inter vehicle
gaps means more vehicle per kilometer which leads to better usage of the road and less
traffic jam. It also improves aerodynamics of the whole platoon reducing fuel cost and
emission in parallel. One can also tell that it helps safety because of reaction times of
automation is much less than that of human driver.
While adaptive cruise control is based on distance measurement with the preceeding
vehicle with use of a front looking radar, CACC needs vehicle to vehicle
(V2V) communication as well. This is done by wireless Radio Frequency (RF)
communication, namely IEEE 802.11p protocol over 5.9GHz base frequency. There
are some challenges with vehicle platoons along with opportunities described above.
The literature on this subject mostly focuses on string stability (SS). SS is that the error
signal between the leader and the follower must attenuate as it propogate along the
string. SS ensures there is no collision between the members of the platoon or no split
under accelaration. Thus not only each vehicle needs to exhibit stability individually
but also platoon or vehicle strings in other words needs to be stable as well.
This work starts with building basics of SS, definitions, boundary conditions, how to
reach SS analysis with using input output position errors and transfer functions, why
a transfer function impuls response is important to tell if the system is SS or not, how
to use norms from linear system theory for SS analysis and so on. There is also an
appendix for the definition, theory and proof of norm concept. Another appendix is
dedicated to impuls response of a transfer function and how it is related to inverse
Laplace transformation of the system transfer function. This is to help reader to better
understand some in text concepts.
There are many papers on how to achieve SS and/or improve it. This work focuses on
improving SS of a heterogenous platoon. Heterogeneous platoon means each member
of the platoon has different dynamics contrast to homogenous platoon in which each
vehicle is considered to have the same dynamic behaviour or identical in other words.
One can ask why it is important to improve SS if the platoon is already string stable.
Improving SS provides more margin between the vehicles thus allows shorter time
headway for CACC or inter vehicle follow distance for platooning. Shorter time
headway or intervehicle means better road usage and less fuel consumption. Ideally,
this leads to road trains (touch condition) which is not possible in practice because of
marginal SS behaviour under physical constraints.
There are different approaches to compansate different dynamics of each member
of the platoon like adaptive controllers or implementing low level controller at each
vehicle working as gain scheduler (or pre-compasators) based on dynamics and
position of the vehicle in the platoon. This kind of approaches have disadvantage
of limiting overall performance of the platoon and at an operating margins far from
ideal. When we say dynamics, we refer to acceleration and deceleration capability
of a vehicle. This is basically depends on vehicle mass, drive train and braking
performance.
This work has taken a different approach than those of in the literature. Rather
than compansating dynamic differences by means of low level control schemes
implementing pre-compansators, it is preferred to improve SS at a higher level control;
platoon formation. To achieve this, it is mandatory to ensure each vehicle is in the
optimum position in the platoon based on its dynamics for highest string stability. This
generally leads to the vehicle with highest inertia leads the platoon and lowest as the
follower at the end. In order to do that, a platoon formation algorithm is developed and
run on each vehicle leading to an optimum overall string structure.
To show effectiveness of the algorithm, a simulation environment is needed. Matlab
Simulink by Mathworks is used for this purpose. It is started with a state space model
of a vehicle. A generic state-space vehicle model is created first from the literature
then it is customized to differentiate each vehicle thus creating a heterogenous vehicle
platoon. Then vehicles are linked to each other in an arbitrarly in simulink, by means of
states, in such a way that the preceding vehicle's output is followers's input to simulate
RF link. A reasonable transmission delay of 100 miliseconds also introduced at each
couple.
Second step is to create a drive cycle for which simulation can run over. Signal builder
function is a powerful tool in simulink and can be used to create a drive cycle. It is used
as speed reference (m/s) for drive cycle. To build the algorithm, state-flow diagrams
are used in Simuling environment. State-flow diagrams is a powerfull tool and easy to
implement to build logical diagrams and flow charts at high level. Operation modes,
interfaces, transition rules and actions for each state are necessary build blocks for
implementing state-flow diagrams. The good thing about the algorithm is that it is
vehicle built-in thus no need for a cental control base for platoon management.
Vehicle platoon run over drive cycle built in simulation environment with different
vehicle order each time. Vehicle speeds, positions, and vehicle spacing in meters are
measured and plotted to have insight about string stability. With a four vehicle platoon,
it is shown that formation algorithm reaches the optimum vehicle platoon with each
vehicle is in ideal position within the platoon.
It is believed that this work paved the way for heterogen platoons with better overall
performance thanks to improved string stability. One can question how much benefit
to get with this approach while it is still safe with heterogen platoons SS already.
However it should be noted that not only safety but also it is marginal gains at the end
to reach maximum efficiency along the route which would typically be a highway. So
it is reasonable to allow for manouvering to get ideal vehicle string at the beginning or
along the route to maximize benefit from platoon thanks to closer headway or vehicle
spacing, both fuel efficiency and road usage.
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