Evaluation of parking search using sensor network

Evaluation of Parking Search using Sensor Network Shun Miura, Yi Zhan, and Tadahiro Kuroda

Department of electronics and electrical engineering, Keio University,

3-14-1, Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan

Phone: +81-45-566-1779 Email : {shun,yizhan} @kuro.elec.keio.ac.jp, [email protected]

Abstract- A new parking search system using wireless sensor network is described, and simulated with a C++ based microscopic simulator. With the proposed system, information of

the real time parking state, vacant or occupied can be obtained through the deployed network. For propagating useful information, a new network system "Information Exchanging System" is proposed which realizes ad hoc network in Inter Vehicle Communication by using only single hops. For more useful information propagation, some more arrangements are

proposed. As a result of the simulation, average Searching Time decreases 50% in crowded condition.

I. INTRODUCTION Since cars have been prevailed, difficulty in parking search at metropolitan area, such as Tokyo, has been serious social issue due to traffic congestion caused by slow driving for parking search and illegal parking on the street. The reason of this problem is not only shortage of parking lots, but also shortage of the information of vacant parking lots. In recent years car navigation system using GPS is prevailed widely and it enabling user to see parking lots location. However, in urban area, where the issue is serious, the possibility that these parking lots are occupied is high, so the information is not enough to solve the issue. Hence, there has been a requirement for the efficient parking search system, and has been researched in [1] and [2], in which parking systems using signboard which shows vacant or occupied parking state have developed. Moreover, the development of a key technology Wireless Sensor Network (WSN) enables to solve the issue by its great advantages in real time detection. A. Wireless Sensor Network

Wireless Sensor Network is the technology to gather information through the deployed network. Typical construction of WSN is comprised of sensors, wireless communication units, processor units, and batteries. WSN is a

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network which can "sense" the real world on time by sampling distributed sensors in the real world and self-organized by using wireless communication. Therefore, when application needs real-time information, such as environmental monitoring, . . .

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B. Network Topology The network topology of WSN is strongly influenced by its target application and a lot of research on this area is going on. Ad hoc network with multi hop is hotly discussed for its flexibility and scalability [3]. The mobile network known as Mobile Ad hoc Network (MANET) has difficulty in keeping network connected, since mobiles easily move out of the wireless ranges. With the mobiles moving faster, keeping network connected becomes more difficult. Consequently, not much of research has been done on MANET with car-to-car communication. Although some results are achieved in [4] and [5], both are specialized in highway where there is no crossing and cars move much more regularly compared with those in city area where the movement of cars differs at crossing, which makes it difficult to keep multi hop network through the same route. On the other hand, Ad hoc network with just Single hop network has also been studied in [6]. They built up ad hoc network for man-to-man communications, the target application of which is searching certain person inside buildings. Because the mobility of men is low, information is spread slowly. Moreover, the random movement of men causes the possibility ofbringing the information to the needing person low.

II. INFORMATIoN ExcHANGING SYSTEM A. Topology ofIES In this paper, we propose a new network system called Information Exchanging System (IES) which is organized of ad hoc network with just single hop. This system is developed for car-to-car communication. Although high mobility of cars is bottleneck in multi hop network, it is not drawback in single hop network because the latter doesn't need to keep the information route. In fact, the high mobility just helps spreading information faster in IES. The needing information for cars is usually the forward information, which can be obtained easily from cars which come from front side. Moreover, the possibility to cross and obtain the forward information is quite high, because all cars move along the street. B. Parking Search with JES WSN can manage real time information and IES can propagate the information efficiently. Consequently, efficient Parking Search system can be succeeded by using IES. The proposed system has great advantages in some points. The first advantage is "real time information". Because cars can get the needing information from who detects parking in real time, the car can obtain the just real time parking lots information, vacant or occupied. The second advantage is "Simplicity". Although, Multi hop network in car-to-car communication has lots of technical challenging to keep routing path, proposed system needs just simple algorithm and protocols. The last reason is its "scalability". Because the system uses ad hoc network and needs low infrastructure, the system can offers scalability.

III. SIMULATION A. Simulation Set Up 1) Simulation Field In order to prove the effect of IES for parking search, the microscopic traffic simulator is developed by based on C++ language. In the simulator, we simulate the real traffic situation of 'Ginza' in Tokyo where has heavy traffic and many small parking lots. Since 'Ginza' is located in central part of Tokyo, traffic situation is always crowded. Besides the area is very popular for shopping on weekend, the number of cars waiting for parking is higher on weekend than that of on weekday. 'Ginza' is rectangular shaped and all the streets in the area are crossed in right angle. Therefore, we assumed the area as rectangular shape (lkmx0.5km) of which is separated into 8X10 grid alignments. The border of the simulator is cyclic border, so cars which go out to the end of the field appear from the opposite side of the field, as new cars. As the parking lots in the simulator, we just focus on curb parking lots along the street everywhere in 'Ginza'. The numbers and location ofthese curb parking lots are based on the

real condition in 'Ginza' area. 2) Simulation Condition The simulation condition is mostly followed the real situation at 'Ginza', the number of parking for instance. Because 'Ginza' is crowded area, cars average velocity is set to 20km/h in our simulator. Cars in the simulation can be classified into two states: Cs and Cd, which are shown below. The ratio of Cs against total number of cars is set to constant value. Because the ratio of cars which want to park this area for shopping is higher than that on weekday, the ratio of Cs is set to 10%: assuming weekday (conditionl), and 20%: assuming weekend (condition2). Car Set {CO, C1, .., Cn} Cars that search parking lots (Cs) Cars that don't search parking lots (Cd) Total number of cars 420 is calculated as crowded condition in 'Ginza', which is calculated from the value in [7], though Cn is used as a variable in the simulation. Since most cars in the real world drive toward own destination, Cd takes the shortest way towards the direction, and never go back, though the crossing where Cd turns are random in the simulation. Parking time for each car is set to 60 minutes. Summary of the simulation condition is shown in the Tablet.

B. Algorithm 1) Information Exchange We assume that every car has sensor node which can detect four kinds of information. (a) "Vacant curb parking lots": puts RFID on each curb parking lot which shows the parking state whether it's vacant or occupied. (b) "Time to find parking lot": what time Cd find parking lots by using clock which is equipped on each car. (c) "Direction to turn": which direction, right or left, to turn at crossing by putting strain sensor on handle. (d) "Distance after turning": distance from the crossing where Cd turns the last time using distance detection equipment on each car. Radio transmissions are equipped in the sensor nodes with which cars exchange the information when they cross against each other. The combination of the information (c) and (d) can be transmitted from Cd to Cs or from Cd to Cd. This transmitted information indicates the relative location of vacant parking lots.

Figure 1 shows the algorithm to find out vacant parking lot from the information. (a) Cdl detects a empty parking lot, and record "Time to find parking lot", (b) Cdl starts recording "Direction to turn", and "Distance after turning". The information shows the way trace back to the vacant parking lot. (c)Cdl transmits information to Cd2 when they cross against each other. (d)Repetition of exchanging information carries information to Cs. Then Cs can calculate the absolute location from the relative location, and track back to the vacant parking lot by following to the information.

2) Simulation Flow Because purpose of Cs and Cd is different, the ways they move are different. Fig.2 (a) shows the flow of Cd, and Fig.2 (b) shows the flow of Cs. Cd can get parking information under two conditions (1) when it passes the vacant parking lot. (2) Exchange of parking information when Cds cross each other. Cs moves randomly at first, then go towards the parking lot after crossing parking information carrier Cd. If Cs meets another Cd on the way to the target parking, it selects the newest information according to "Time to find parking lot" and follows that way. C. Evaluation In the simulation, taken one of Cs (CsO as an example), time from CsO starts searching to CsO arrives at a parking lot is defined as Searching Time. We simulated 1000 times in each condition and calculated average Searching Time as evaluation criteria.

IV. SIMULATION RESULT A. Searching Time Figure3 shows how Average Searching Time is changed with and without IES on weekday (conditionl). When the number of cars is increased, under this more crowded situation, Searching Time is increased without using IES. In contrast, Searching Time is decreased drastically as the number of cars increases after IES is applied. It is because increase in cars accelerates car-to-car communications. Thus, the efficiency of the spreading information is improved and leads to decreased Searching Time.

Figure4 shows how Average Searching Time is changed with and without IES on weekend (condition2). IES proves the effectiveness in Searching Time decrease even in case of weekend. As the number of cars increase, Searching Time decrease at first, like in case of weekday. On the contrary, Searching Time increases, as the number of cars increases continuously. With the number of cars increased the possibility of competence of several Cs for the same vacant parking increases accordingly. At that time the vacant parking can only be occupied by the Cs who reaches earliest. For others, parking information which has been exchanged already becomes useless. Therefore the information can be classified into two groups, useful information or useless information. Figure5 shows the ratio of useless information in the total information in both conditions. AS the number of cars increases, the ratio of useless information increases. The ratio on weekend is much higher than that on weekday. The difference between this ratio on weekday and weekend causes the different result of Searching

Time. Hence, decrease of this ratio makes this system more efficiently.

B. ExpiringdScheme When the condition is competitive represented as weekend, useless information is propagated in high ratio, as shown in Fig.5. The possibility whether the information is useful or useless has relationship with how long Cd has stored the information. Each of Fig.6 shows the reliability of the information by the information stored time on weekend. Two lines show the percentages of both groups of information, useful information and useless information. Both groups of information are separated by information storage time. Each figure shows the result in difference situation, (a)120, (b)240, (c)420, (d)540 of Cds are set for simulation. When the number of cars is small shown in Fig.6 (a), the possibility of useless information is low, however old the information is. As shown in Fig.6 (b)(c)(d), when number of cars increases, the ratio of useless information increases, with having peak at difference point from that of useful information. Hence, the ratio of the useful information can be increased by dividing the information according to information stored time. This method is called Expiring scheme, which set the expiring time. The information stored longer than expiring time is disposed in the scheme. Figure7 shows Searching Time on weekend case and Fig.8 shows the ratio of useless information with Expiring scheme. Expiring time is set to 40sec and 80 sec in those figures. As expiring time increases, the ratio of useless information decreases as shown in Fig.8. Decrease of the ratio causes decrease of Searching Time with the scheme.

C.

Wireless Range

Figure9 shows how average Searching Time varies with the difference in wireless range on both weekday and weekend. Typically, wider wireless range links to higher reliability of the network, but IES doesn't follow as shown in Fig.9, because wider wireless range causes higher useless ratio as shown in Fig. 10. Thus, the appropriate wireless range is optimized as 15m as shown in Fig.9. V. CONCLUSION In this paper, we proposed a new parking search system using wireless sensor network, and new network system IES is proposed for car-to-car communication. As a result of the simulation, proposal parking system succeeds to reduce 5000 of Searching Time at most. Moreover Expiring Scheme is proposed for more efficiency in competitive condition and succeeded 500o of Searching Time reduces from without the Scheme. VI. ACKNOWLEDGEMENTS We would like to express sincere thanks to Dr. K. Yano of Hitachi Corporation.

[1]

[2]

[3] [4]

[5]

[6]

Masataka Imaizumi,, Masatoshi Murai, Hiroshi Yagi, and Takaharu Hino, "Parking -Meter Supervision System", IEEE Vehicle Navigation & Information Systems Conference, 1994

conditionl condition2

Ian C. Hilton, "The Removal of Parking Search Traffic from the Town Centre", Vehicle Navigation and Information Systems Conference, 1989, pp.427 -431 D. K. Kim, "A New Mobile Environment: Mobile Ad Hoc Networks (MANET)", IEEE Vehic. Tech. Soc. News, August 2003, pp. 29-35 S.Y. Wang, "On the Intermittence of Routing Paths in Vehicle-Formed Mobile Ad Hoc Networks on Highways", IEEE Intelligent Transportation Systems Conference, October 2004, Washington DC, USA S.Y. Wang, "On the Effectiveness of Distributing Information among Vehicles Using Inter-Vehicle Communication", IEEE Intelligent Transportation Systems Conference, October 2003, Shanghai, China Mathew Laibowitz, and Joseph A. Paradiso, "The UbER-Badge, A Versatile Platform at the Juncture Between Wearable and Social Computing" , in Fersha, A., Hortner, H.,Kostis, G. (eds), Advances in Pervasive Computing, Oesterreichische Computer Gesellschaft, 2004,

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Shun Miura received the B.S. degree in electrical engineering in 2005 from Keio University where he is currently working toward the M.S. degree. Since 2004, he has been engaged in a research on Wireless Sensor Network.

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Yi Zhan received his M.S. from Beijing Institute of Technology, China in year 2000. He worked as logic design engineer in company VIA technology in Beijing from year 2001 to year 2004. Now, he is pursuing his master in Keio University, Japan.

Tadahiro Kuroda (M'88-SM'00-F'06) received the Ph.D. degree in EE from the University of Tokyo in 1999. In 1982, he joined Toshiba Corporation, where he designed CMOS SRAM, gate arrays and standard cells. From 1988 to 1990, he was a Visiting Scholar with the University of California, Berkeley, where he conducted research in the field of VLSI CAD. In 1990, he was back to Toshiba, and engaged in the research and development of BiCMOS ASIC's, ECL gate arrays, high-speed CMOS LSI's for telecommunications, and low-power CMOS LSI's for multimedia and mobile applications. He invented a Variable Threshold-voltage CMOS (VTCMOS) technology to control VTH through substrate bias, and applied it to a DCT core processor and a gate-array in 1995. He also developed a Variable Supply-voltage scheme using an embedded DC-DC converter, and employed it to a microprocessor core and an MPEG-4 chip for the first time in the world in 1997. In 2000, he moved to the Keio University, and he has been a professor since 2002. His research interests include low-power, high-speed CMOS design for wireless and wireline communications, human computer interactions, and ubiquitous electronics. He has published more than 200 technical publications including 50 invited papers, and 18 books/chapters, and filed more than 100 patents. He served as a conference chair for the Symp. on VLSI Circuits, a vice chair for ASP-DAC, a TPC chair for the Symp. on VLSI Circuits, an invite program chair for A-SSCC, sub-committee chairs for ICCAD and SSDM, and program committee members for Symp. on VLSI Circuits, CICC, DAC, ASP-DAC, ISLPED, SSDM, ISQED, and other international conferences. He is a recipient of 2005 P&I patent of the year award. He is an IEEE Fellow and a Senior member of IEICE.

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