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International Journal of Advanced Research in Engineering and
Technology (IJARET) Volume 11, Issue 6, June 2020, pp. 731-739,
Article ID: IJARET_11_06_066 Available online
athttp://iaeme.com/Home/issue/IJARET?Volume=11&Issue=6 ISSN
Print: 0976-6480 and ISSN Online: 0976-6499 DOI:
10.34218/IJARET.11.6.2020.0 66
© IAEME Publication Indexed Scopus
AUTONOMOUS VEHICLE REVERSE PARKING SYSTEM
Nareshbabu G, Keerthana D, Nivethitha S.B, I Leando Assistant
Professor, Department of Mechatronics Engineering,
Rajalakshmi Engineering College, Chennai, India
ABSTRACT This paper presents the design of autonomous reverse
parking system where
vehicle is going to park in its identified vacant slot. The slot
identification has been done through hue saturation technique which
identifies the hue value of the RGB
colors. The hue saturation signals are controlled by PID control
signals. These control signals actuate the vehicle into the vacant
slot. The Simulink model of the PID controller is being designed
and various response of the system are being analyzed.
The Response of the PID controller signals and the simulation
results for identification of vacant slots are being discussed.
Key words: Autonomous vehicle, Hue saturation value, Vacant slot
detection, Simulink PID model.
Cite this Article: Nareshbabu G, Keerthana D, Nivethitha S.B and
I Leando, Autonomous Vehicle Reverse Parking System, International
Journal of Advanced
Research in Engineering and Technology, 11(6), 2020, pp.
731-739.
http://iaeme.com/Home/issue/IJARET?Volume=11&Issue=6
1. INTRODUCTION Parking is considered to be the highest stress
maneuver for the drivers while driving the
vehicle. In the major cities many kind of difficulties such as
traffic congestion, air pollution etc. are faced in parking the
vehicle. In large parking environment, it is difficult for the
driver to identify the vacant parking slot. During peak hours, it
is impossible for the driver to find
the slots that have become vacant few minutes/seconds before.
Also, the driver becomes unluck or irritated if the empty slot gets
filled before the driver could reach the slot.
Thus, to meet the parking demands and in order to reduce the
traffic congestion innovative parking systems are developed. With
intelligent Control and wireless communications, the
vehicle parking space utilization can be improved. Recent
Advances in autonomous vehicle parking has made an immense
attention among the people. Till now, many commercial cars have
developed self-parking system up to certain extent. However, most
of them still require certain degree of human decision making. In
new end cars like TOYOTA PRIUS, BMW 7
series, the driver needs to control the speed of the car with
the help of brake pedal. The
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system, only takes control of the steering wheel. Researchers
are working to fill the gap to produce a complete self-parking
car.
2. SIMULINK MODEL FOR CONTROL OF WHEELED RO BOTDC Motor is the
most common basic actuator in control system. The purpose of the DC
motor is to provide either rotary or translational motion. In DC
Motor, the torque that is generated is
directly proportional to both strength of magnetic field as well
as armature current. The physical parameters considered for the
design of the design as shown in figure 1 are as
follows: (J) moment of inertia of the rotor 0.01 kg.m^2 (b)
motor viscous friction constant 0.1 N.m.s (Ke) electromotive force
constant 0.01 V/rad/sec (Kt) motor torque constant 0.01 N.m/Amp (R)
electric resistance 1 Ohm (L) electric inductance 0.5 H
In MATLAB, PID Tuner block is used to design the controller for
controlling the speed of the motor. The difference in setpoint and
measured process variable is calculated as error
value by PID Controller. PID controller adjusts the process
control inputs thus the error gets minimized.
Generally the PID tuner turning depends on the following three
steps. Launch the PID Tuner. When launching, the software
automatically computes a linear
plant model from the SIMULINK model and designs an initial
controller. Tune the controller in the PID Tuner by manually
adjusting design criteria in two
design modes. The tuner computes PID parameters that robustly
stabilize the system. Export the parameters of the designed
controller back to the PID Controller block and
verify controller performance in SIMULINK.
Figure 1 Simulink model for two-wheel Robot system
2.1. Design of Two Wheel Robot System The robot system is
developed with the help of the 12V dc motor by specifying the
parameters as required and supplying the necessary input step
signal. The PID controller from the control system tool box is
mainly utilized to eliminate the error and to get the good
response for varying voltage levels. Once the PID tuner block is
being launched with the help of above-mentioned steps as shown in
figure 2, then PID values are generated for the
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designed two-wheel robot system. By changing the step time in
the slider, the corresponding tuned values for the PID controller
are obtained.
The corresponding response of speed in rpm for constant voltage
and varying voltage levels are obtained and the variations can be
viewed in the graph as shown in figure 3 where x-axis and y-axis
are defined as speed and voltage.
Figure 2 PID values for the designed system
Figure 3 Response curve of the designed system
3. VACANT SLOT IDENTIFICATION 3.1. Entropy Minimization for
Shadow Removal The shadows present in the colour images can be
removed by investigating a special direction
in a 2D chromaticity feature space. The direction of the vehicle
is assumed to be a single color. The same image when projected into
1D image, it gives a greyscale image of varying
intensity. The unexpected shadows during the image processing is
removed by different lighting methods. The quadratic entropy method
is preferred to get an effectual explanation of the entropy. The
observed pixels are replaced with the kernel method of density
probability
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distribution which can be examined using efficient Fast Gauss
Transform. As a result, a shadow less, reliable color image is
produced.
Thus the heart of this test of the entropy-minimization idea
using real data, is as follows: Form a 2D log-chromaticity
representation of the image. For θ = 1-180
(i) Form greyscale image I: the projection onto 1D direction.
(ii) Calculate entropy. (iii) Min-entropy direction is correct
projection for shadow removal.
3.2. Invariant Image A method to develop a common illumination
image is formed by determining the entropy
minimization. When a 3-D coloured image is transformed in to a
2-D image, the illuminations are scattered on straight lines, that
is shown in figure5. A grey scale image which is of
intrinsic type, shows only the inherent reflectance properties
in the image. The standard definition of chromaticity, i.e., color
contents without intensity:
R = {r,g,b} ≡ {R,G,B}/(R+ G + B)
Figure 4 Input Image for shadow removal
Figure 5 Output Image Obtained after shadow removal
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4. HUE SATURATION TECHNIQUE Hue Saturation Value (HSV)
represents the points in the cylindrical coordinates of the RGB
value. It is similar to that of the Cartesian representation. In
each cylindrical coordinates hue represents the angle around the
central vertical axis, saturation represents the corresponding
distance from the axis and the distance along the axis represents
the lightness. HSL and HSV
are both cylindrical geometries (fig. 1), with colour, the
angular dimension is at 0 degree which is the red primary and
passing at 120 degree which is the green primary and at 240 degrees
for blue primary, and then wrapping back to red at 360° as shown in
figure 6. In every geometry, the axis at the centre will comprise
of the three, neutral, Gray colour ranging from 0 to 1 and
achromatic.
.
Figure 6 Hue values for RGB
Now with the help of these technique vehicle identifies whether
the slot is vacant or not. For each colour different values are
being given (ie) each RGB colour has different hue
saturation value. When the vehicle identifies that the value of
the particular colour is being obtained it takes the decision to
move the vehicle to the next parking slot. If the Hue value of the
particular colour is not obtained then the slot is vacant and the
vehicle decides to park in
the identified vacant slot. Now in order to check the length of
the parking slot the wall is made of the black colour and the hue
saturation value of it is being determined. With the help of these
technique numerous numbers of slots can be identified whether it is
vacant or not. The vehicle can be parked without any disturbance to
the other vehicle.
4.1. of Computer Aided Tool for Control of Vehicle Use Before
testing the vehicle in the parking environment by utilizing above
technique, at first the hardware components such as motors and
camera are being controlled with the help of the GUI window.
Whenever the raspberry pi is being connected with the laptop it
loads the new
OS. By selecting the user window one can able to allocate the
necessary push buttons for various functioning of the system. Also
with the clear definition of the pin configuration the vehicle is
controlled for various functions such as moving the vehicle forward
or backward, turning the vehicle and camera in left side direction
or right side direction. By just clicking the buttons shown in the
GUI window as shown in figure 7 corresponding functions are
being
performed. The vehicle can able to identify the presence of
vacant slot without human intervention. With the help of the
above-mentioned technique one can able to park the vehicle
autonomously for n number of parking slots available provided the
end wall is made up of black color.
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Figure 7 GUI windows for Vehicle Control
4.1.1. Conversion of RGB Value HSV Value toGiven three numbers
R,G and B (each between 0 and 255), at first m and M are defined
M=max{R,G,B} ....(1) m=min{R,G,B} ….(2)Then Value and Saturation
are defined by the equations V = M/255 ....(3) S = 1 if M > 0 –
m/M ….(4)S = 0 if M = 0 ….(5)Hue h is defined by the equation H =
cos-1[(R – - G
B) /
] if G >= B (6)
H = 360 cos– -1 [(R - - G B) /
] if B > G (7) With the help of this conversion Raspberry pi
takes the necessary decision to park the
vehicle. If particular hue value of RGB color is obtained within
the given threshold, then the slot is occupied. As of now vehicle
with three different colors such as red, blue and green are
placed in the respective slot and if their HSV values with
certain range are coded by the processor. If the input from the
image sensor does not satisfy the given HSV range then no component
of RGB colors are present over there, hence the slot is vacant.
Suppose the slot is not vacant the vehicle has to move further with
respect to the black color present in the end wall. Once the
distance between the last slot and the end wall becomes closer the
vehicle decides to turn left and searches for the empty slot on the
other side in the similar way.
4.1.2. Functions Performed after Capturing the Input Image At
first the vehicle is placed in the parking environment and the
reset key is pressed. The Logitech camera which is utilized as
image sensor for autonomous system will be actuated to turn
leftward. Now the camera captures the input video and performs the
various functions as stated above. Filter such as range filter is
used to eliminate the noise and various operations such as dilation
and erosion are performed to obtain the clear definition of edges.
Then the threshold value coded by the processor is being compared
and it takes the necessary decision
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Figure 8 Flow diagram for the process
Figure 9 Block Diagram of the Conversion Process
Figure 9 shows the block diagram of the autonomous reverse
parking system and the interconnections of each hardware module
connected to the entire system. Raspberry pi is the decision taking
module which takes the decision based upon the input from the image
sensor
and it regulates the functioning of the actuating system. With
the help of this system the vehicle can able to park in numerous
numbers of slots and without any noise being amplified in the
system.
Figure 10 Vehicle near the wall
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Nareshbabu G, Keerthana D, Nivethitha S.B and I Leando
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If the predetermined value of the black colour is met then the
vehicle turns left as shown in figure 10 and it scans for the black
colour in the other end of the wall. Now the vehicle moves forward
and reaches the other side of the parking environment and the same
procedure repeats in the other end of the parking side also. With
these kind of techniques the vehicle can able to identify and park
autonomously in more number of parking environments and other
advantage of using hue saturation value is that in case of
underground parking environments illuminations plays the major role
and these illumination defects and shadows of any colour light are
easily eliminated with the help of this technique.
5. RESULTS The following are the response that are obtained
based on the decision made by the Raspberry pi model. The designed
vehicle first checks whether the slot is vacant or not in the first
slot which is stated as the initial starting point. If no vehicle
is present then the vehicle decides to park in the first slot
itself and the results are shown in the figure 11.
Figure 11 Vehicle in the vacant slot
Suppose if some other vehicle is present in the parking slot
then the vehicle decides to move forward and searches for the empty
vacant slot. At instance, if the vehicle arrives the end of the
wall, it travels onto the opposite side of the parking slot and
again searches for a free slot for parking. If the free parking
slot is detected by the vehicle, it parks the vehicle in reverse
parking process. The empty slots are identified by using the hue
saturation value.
Figure 12 Vehicle parked at the empty slot.
6 CONCLUSION . The above described system can be used to park
the vehicle in numerous number of slots without causing any
disturbance to the other vehicle present in their slot. The hue
saturation technique mainly focused in order to eliminate the
shadows that are present in case of
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underground parking environment or parking the vehicle in the
night time. Thus the system parks the vehicle autonomously without
any human intervention required and if all the
parking slot are occupied the vehicle keeps on searching the
vacant slot autonomously and parks the vehicle once the slot is
vacant.
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