Relative Location Estimation of Vehicles in
Parking Management System
Mohammad Shaifur Rahman, Youngil Park, and Ki-Doo Kim*
Dept. of Electronics Engineering, Kookmin University, Seoul, Korea
E-mail: [email protected]*
Abstract ⎯ In this paper, an automatic parking management
system is designed using active Radio Frequency Identification
technology along with WiFi wireless LAN. An algorithm is also
developed for the localization of the cars parked inside the
parking area. The localization process is done in two steps using
Time Difference of Arrival and Received Signal Strength
measurements, respectively. The system can automatically
monitor, guide and localize the cars inside the parking space.
Keywords ⎯ Relative location estimation, Active RFID, RSSI,
TDOA, WiFi.
1. Introduction
Parking area is one of the key installations found in most
major cities. Conventional parking systems employ only a
simple barrier to track the number of vehicles currently
occupying the parking area. Typically, only the information
about the number of empty spaces is conveyed to the drivers
via some displays installed at the entrance and on nearby
streets. Information about the location of the empty spaces is
not provided. In addition, location of a particular occupying
car can not be known in the existing system. In the present
systems, the drivers have to find out the empty space and/or
their parked cars without sufficient guidance which sometimes
becomes difficult for them if the parking area is large and busy.
The objective of our research is to develop an indoor
location-sensing system for the parking area. The goal is to
design an automatic parking management system which would
locate the existing cars, the empty parking spaces and convey
that information to the management server. It would guide the
incoming car drivers to their nearest/most convenient and
empty parking spaces. In addition, it would provide the
management authority some additional information such as
vehicle ID and duration of stay etc. This paper proposes a
wireless sensor network based parking management system
using RFID and WiFi wireless LAN, which automates parking,
monitoring, guiding, and managing services. For parking
management systems, wireless sensor networks can be
deployed in existing parking areas without having to install
new cabling for network and electricity to reach each sensing
device and it significantly lowers the installation costs,
especially for existing car-parks. In recent years, several types
of location sensing systems for indoor and outdoor
environments are suggested [1]-[5], each having their own
strengths and weaknesses. Global Positioning System, Radio
Frequency, Ultrasonic, Infrared, active RFID are some
examples of these systems. However, our target is to use
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off-the-shelf products that are suitable for the indoor
environment of parking area. Active RFID system draws our
attention for this purpose due to several useful features of it
such as non-line-of-sight operation, high speed detection,
good transmission range and performance in dense sensor
environment. In recent years, RFID systems have evolved as a
fast growing technology in the fields like identification,
location sensing, logistics, health care, pharmacy etc. RFID
will become one of the key technologies in near future for the
deployment of ubiquitous communications. We have studied
the important features of several RFID systems manufactured
by different companies [6]-[8] and selected AeroScout Active
RFID system for the proposed car parking management
system. We also suggest a new algorithm for localization of
cars using Time Difference of Arrival (TDOA) and Received
Signal Strength Indication (RSSI).
The remaining of this paper is structured as follows. Section
2 describes the proposed parking management system.
Summary of the comparative study among RFID systems
manufactured by different companies is given in section 3. In
section 4, the proposed localization algorithm is explained.
Section 5 describes the architecture and operation of the
proposed system. Finally, in section 6, we draw the conclusion
of the paper and indicate the future research directions.
2. System Overview
The proposed parking system, shown in Fig. 1, contains four
kinds of nodes such as verifying, monitoring, guiding and sink
nodes. All the cars will contain active RFID tags. The
functions of the nodes are as follows:
Verifying node - It contains the RFID reader, exciter and a
camera. When a car passes beside it, the RFID tag inside it is
turned on by the RFID exciter and detected by the reader. At
the same time, the system triggers a small camera, which takes
a picture of the license plate of the car. The number is matched
with the RFID tag number for the verification purpose.
Monitoring node - WiFi Active RFID readers are installed
in the monitoring nodes. These readers read all the tags within
their radio range. Monitoring nodes are arranged in such a
way that each RFID tag should be read by at least 4 readers.
Monitoring node transmits or receives messages through
standard WiFi communication. It also receives commands
from the management station to carry out some procedures
such as time synchronizing, debugging, working status
reporting and so on.
Feb. 15-18, 2009 ICACT 2009
Furthermore, it can also serve in the ad-hoc network of the
monitoring nodes.
Sink node - The sink node collects parking status reports
and delivers them to the management station. It acts as a
gateway between wireless sensor network and the
management server. In our system, the sink node connects
directly to the management server through an RS-232
interface.
Management server - The management server takes
charge of managing and maintaining the whole system. It
processes the data received from the sink node, counts parking
fees, and displays necessary information on the monitor. The
management server also sends parking-space guiding
messages to guiding nodes and updates the display screen at
the entrance of the parking lot at regular intervals of time.
Entrance
& Exit
Management
Station
Varifying Node
Guiding Node
3. RFID System Selection
Monitoring Node
Figure 1. Automatic parking management system overview. Each car
contains active RFID tag of which the location has to be estimated. Fixed
reference tags are placed inside the parking area. The monitoring nodes
contain RFID location receivers with WiFi wireless LAN. Relative
locations of the cars with respect to the reference tags are estimated
processing the TDOA and RSSI information collected from the
reference and tracking tags.
Guiding node - This node is equipped with a WiFi
communication module and a display module. The guiding
node receives guiding information from the management
station and shows it on the LED display. This can help guiding
vehicles to find idle parking spaces with less time and effort.
After careful study of the specifications of different
available systems [6]-[8], we have chosen the system
manufactured by AeroScout. AeroScout Visibility system
consists of AeroScout location receiver, Wi-Fi based active
RFID tags, AeroScout Engine, and AeroScout Exciter. The
AeroScout location receiver is the core component of the
system. It provides sophisticated TDOA and RSSI
measurement capabilities. It is to be mentioned here that active
RFID systems designed by RF Code [6] and IDENTEC
SOLUTIONS [7] were used in [5] and [9], respectively. Some
important features of each system are compared in the
following table:
Table 1: Comparison of different RFID systems
AeroScout
Reading range
(outdoor/indoor)
200 m/60 m
IDENTEC
SOLUTIONS
100 m
RSSI/TDOA
measurability
Tag transmission
interval
Radio
Tag programmability
Possible
Not possible
Not possible
128 ms ~ 3.5 h
0.5 s ~ 60 s
2 s/12.5 s
802.11 b/g
Transmission interval
programmable
Available
Available
Replaceable
868 MHz/915 MHz
Transmission interval
programmable
Not available
Not available
Not replaceable
433.92 MHz
Not programmable
Choke point detection
On board motion sensor
Battery
Even though the indoor reading range of AeroScout RFID is
lower than that of the other two systems, this system is found
to be advantageous in case of RSS/TDOA measurability, tag
transmission interval, tag programmability, and choke-point
detection. AeorScout offers to use Time Difference of Arrival
(TDOA) and Received Signal Strength Indication (RSSI)
algorithms to accurately and reliably determine location.
These are the key factors for selecting the RFID system. Using
the AeroScout exciter, the tags can be turned on and off at the
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RF Code
100 m
Not available
Available
Not replaceable
entry and exit of the car to the parking area, respectively, when
the car passes through a choke-point. This can reduce energy
consumption of the tag to a great extent.
4. Algorithm for Location Estimation
In the last few years, we have witnessed a burgeoning
amount of research and commercial interest in the area of
location-aware technologies. For the location estimation
Feb. 15-18, 2009 ICACT 2009
process several techniques are studied namely, RSSI, Time of
Arrival (TOA), TDOA, Angle of Arrival (AOA), etc. Among
them, RSSI and TDOA are suitable for our purpose of short
range localization. For range measurement, RSSI is attractive
for device simplicity and cost effectiveness but is traditionally
seen as a coarse means of range. On the other hand, TDOA
gives better accuracy compared to RSSI. AeroScout RFID
location readers have the ability to read the RSS and TDOA of
the signal emitted from the RFID tags. Hence, it can be used
for reliable localization with the accuracy of 3-10 meters
(RSSI) and 3-5 meters (TDOA) [8]. However, the dynamic
radio channel behavior is still one of the main reasons for
increasing measurement errors, as we can never guarantee the
same distance would give the same signal strength at different
time and channel condition. Similarly, TDOA accuracy is
limited by the Non-line-of-sight condition. In order to cope
with these problems, LANDMARC [5] was proposed which
improved the overall accuracy of locating objects by utilizing
the concept of reference tags. The presence of active RFID
tags in some known reference points allow to eliminate the
off-line phase, since measurements are updated continuously
in each interrogation from the RFID readers. LANDMARC
was based on indirect RSSI estimations due to the hardware
limitations of measuring RSSI or TDOA directly at that time.
In the present study, we propose using AeroScout active RFID
system which supports localization by RSSI and TDOA.
Let us consider that we have n RFID location receivers along
wit p reference tags and q tracking tags. The location
receivers are continuously reporting the tags that are within
their radio range. The localization process is done in two steps.
In the first step, four nearest-neighbor reference tags are
determined, using TDOA, which subtend a rectangle around
the tracking tag. In the next step, the coordinate of the tracking
tag is estimated. For this purpose, difference of RSSI between
each of the four reference tags and the tracking tag is used to
calculate the weighting factors of the reference tags. Reason
for choosing TDOA instead of RSSI in the first step is its
lesser vulnerability to radio channel condition [9]. Let the
coordinates of the reference tags be ( xi , yi ) where
i = 1,2, " , p and the coordinate of the tracking tag is
determined by TDOA to be ( x, y ) . Hence, the linear distance
between each of the reference tags and the tracking tag is
d i = ( x − x i ) 2 + ( y − y i ) 2 , where i = 1,2, " , p . Now, the
four nearest reference tags that create a rectangle around the
tracking tag can be found comparing the distances. For the
next step, suppose the RSSI vector of a tracking tag is
G
S = ( S1 , S 2 , " , S 4 ) where S i denotes the signal strength of
the tracking tag reported by the ith reader (i = 1,2, " , n ) . For
the reference tags, RSSI vector is denoted by
G
θ = (θ1 , θ 2 , " , θ n ) where θ i denotes the signal strength of the
reference tag reported by the ith reader. Average Euclidian
1
distance in terms of RSSI, E j =
k
k
∑ (θ
i
− Si )
2
where
i =1
j = 1,2,3,4 and k is the total number of readers which can
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read both the reference and tracking tag pairs under
investigation. Here, E represents the location relationship
between the tracking and reference tags. The closer the
tracking and reference tags are, the smaller E value is found. A
G
tracking tag will have its E vector as E = (E1, E2 , E3 , E4 ) . The
tracking tag’s coordinate ( x, y ) is obtained by:
4
( x, y ) =
∑ w ( x , y ) , where w is the weighting factor for the
i
i
i
i
i =1
ith neighboring reference tag. Weighting factor wi will be
determined depending on E value:
1
E2
wi = 4 i
1
2
i =1 Ei
∑
5. System Architecture and Operation
This section describes the implementation details of the
system. Placement of RFID readers and reference tags plays
an important role in location estimation accuracy. In the
present study, we consider only the indoor scenario of parking
area. We design the system for our experiments using 4 RFID
location receivers, 8 reference tags and 4 tracking tags, all
manufactured by AeroScout. We build our two-dimensional
grid of reference tags as shown in Fig. 2. The location
receivers are also installed in grid arrangement. Distance
between two RFID location receivers in the practical
installation should not be more than the maximum reading
range (90 meters, in case of AeroScout system). This will
ensure that all the tags would be read by at least 4 readers.
Many parameters related to the location algorithms and the
deployment scenarios affect the location performance.
Followings are the key parameters that have greater influence
on the location accuracy:
Number of reference tags, p is one of the key issues that
determine the location accuracy. Since, we are arranging the
6m
10 m
Reference tags
Tracking tags
RFID location
readers
Figure 2. Placement of RFID location receivers, reference and tracking
tags.
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reference tags in two-dimensional rectangular grids,
p = 4 would be the optimum reference tag number. Here,
4-nearest neighbor reference tags surrounding the tracking tag
would be selected for location estimation.
Spacing between reference points is another important
factor in this system. Assuming each parking space to be
3m × 5m , we consider the distance between two reference tags
in a line is 6m . However, the spacing would have to be
adjusted depending on the experimental results.
Spacing between RFID location receivers should be less
than their reading range, since minimum of three location
receivers are needed to enable TDOA processing in AeroScout
system.
In the proposed system, the parking cars are classified into
two categories, cars using the parking area frequently
(registered cars) and guest cars (unregistered cars). Active
RFID tags should be permanently tagged at the windscreen of
the registered cars. On the other hand, RFID tags will be
supplied to the unregistered cars temporarily from the
monitoring room. When a car arrives at the entry of the
parking area, the AeroScout RFID exciter turns the tag on
inside the car and the RFID reader reads it. It also triggers a
small camera to take the photo of the number plate. The
number plate is read by image processing technique and
verified. If it is identified then the main entrance is opened
otherwise it will have to collect the RFID tag from the
monitoring room. The management server will send the
guiding information to the guiding node through the sink node.
The incoming car will then be guided to the empty parking
space. The RFID location receiver at the monitoring nodes
will read the tags and estimate their location by TDOA and
RSSI features continuously with certain time intervals. At first,
four nearest-neighbors of each incoming tracking tags would
be determined by the TDOA analysis. Then, signal strength
differences between the tracking tag and reference tags would
be used to estimate the coordinate of the tracking tag. The
detail algorithm of the relative location estimation is already
explained in a previous section. The RFID location receivers
also create WiFi wireless LAN which is used to transmit data
to the sink node hop by hop. The sink node collects the report
messages and delivers them to the management server, and
then drivers can get the visual status information of the whole
parking area on the monitor screen. Upon arrival of an
incoming car, the management server prepares the guiding
information for each guiding node and sends the guiding
messages to them via the sink node. The guiding nodes receive
the messages and display the guiding indication.
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6. Conclusion
This paper proposes a WiFi wireless sensor network based
parking management system using AeroScout RFID location
sensing system, which automates the car park monitoring,
localizing, managing, and guiding services. Localization
process is done in two steps using the TDOA and RSSI
features of AeroScout RFID system. At first, four
nearest-neighbor reference tags, around the tracking tag, are
selected using TDOA measurement. Then, the coordinate of
the tracking tag is estimated depending on the difference of
RSSI between each of the four reference tags and the tracking
tag. Future research work would be the implementation of the
proposed system in real parking area and the performance
evaluation.
ACKNOWLEDGEMENT
This work was supported by the Basic Science Program
[R01-2008-000-20570-0] of Korea Science & Engineering
Foundation, and the IT R&D program of MKE/IITA
[2008-S-041-01].
REFERENCES
[1] N. Patwari, A. O. Hero, M. Perkins, N. S. Correal, and R. J. O’Dea,
“Relative Location Estimation in Wireless Sensor Networks,” IEEE
Trans. on Sig. Process., vol. 51, no. 8, August 2003, pp. 2137-2148.
[2] M. Youssef and A. Agrawala, “The Horus WLAN Location
Determination System,” in Proceedings of MobiSys, 2005, pp. 205-218.
[3] P. Bahl and V. N. Padmanabhan, “RADAR: An In-Building RF-Based
User Location and Tracking System,” in Proceedings of IEEE INFOCOM,
2000, pp. 775-784.
[4] U. Bandara, M. Hasegawa, M. Inoue, H. Morikawa, and T. Aoyama,
“Design and implementation of a Bluetooth Signal Strength Based
Location Sensing System,” in Proceedings of the IEEE Radio and
Wireless Conference, 2004, pp. 319-322.
[5] L. M. Ni, Y. Liu, Y.C. Lau, and A. P. Patil, “LANDMARC: Indoor
Location Sensing Using Active RFID,” Springer Wireless Networks,
2004, vol. 10, pp. 701-710.
[6] RF Code, http://www.rfcode.com/
[7] IDENTEC SOLUTIONS, http://www.identecsolutions.com/
[8] AeroScout, http://www.aeroscout.com/
[9] S. Polito, D. Biondo, A. Iera, M. Mattei, and A. Molinaro, “Performance
Evaluation of Active RFID Location Systems Based on RF Power
Measures,” in proceedings of the IEEE PIMRC, 2007.
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