International Journal of Engineering Practical Research (IJEPR), Volume 5 2016 www.seipub.org/ijepr doi: 10.14355/ijepr.2016.05.001
An Intelligent Management System of Vehicle Violation Based on RFID Electronic License Zhengying Caia*, Shi Liub, Jun Chenc College of Computer and Information technology, China Three Gorges University, Yichang, 443002, China a*
master_cai@163.com, b 1432476945@qq.com, c 917136891 @qq.com
Abstract Traditional vehicle management system is popular all over the world which is based on metal plate and mainly identified by the video and image processing techniques which are found to be less accurate and inefficient. Here, the design scheme of the RFID license management system is introduced including its database construction, detecting processing scheme, and anti‐collision algorithm as well. The proposed scheme can be used to build a more effective license identification system and takes incomparable advantages in anti‐counterfeiting, where every electronic license is based on the unique factory‐curing ID number and the vehicle physical binding. Lastly, the prototype of the proposed system was constructed and tested, and the results showed its great advantages over traditional metal plate management system in solving the violation and identification problem more effectively. Keywords Intelligent Management System, Electronic License, RFID, Mobile Internet, Anti‐Collision Algorithm
Introduction Most governments all the round the world require a registration plate to be attached to both the front and the rear of a vehicle, although some jurisdictions or special vehicle types such as motorboats often need only one plate which is usually attached to the rear of the vehicle. For official identification purposes, traditional optical identification technology (Liu et al., 2013) is necessary and often used. However, the traffic control departments have to deal with a large number of unclear pictures or videos of illegal vehicles every day, where the license plate number is mainly identified by manpower and then is fed into the management system. But the whole workload is very big, easily fatigue and miscalculated (Brandwein et al., 2012). Now RFID provides us a new method to overcome the shortcomings of traditional metal plate (Chen et al., 2012), where RFID is referred to Radio Frequency Identification technology. It originated from the 1990s, went through three stages: electromagnetic induction or electromagnetic propagation mode, non‐contact identification of the target tracking and two‐way data communication in the new automatic identification technology (Ali et al., 2014). For example, Lebrun et al. (2015) put forward a model for managing interactions between tangible and virtual agents on an RFID interactive tabletop in traffic simulation. Electronic identification is an automatic vehicle identification (Slapsinskas et al., 2013) that is based on intelligent management system (Yuji, 2014) and radio frequency identification technology unit. Wang et al. (2015) studied a capture‐aware estimation for large‐scale RFID tags identification. Electronic license system includes a database server, the card issuing terminals, terminal management, display terminals(Ali et al., 2015), and is helpful for the automatic detection, identification, access control and information management of the electronic vehicle license, and other related functions (Negny et al., 2014). For remote real‐time monitoring, a well‐operated channel state and managing process are necessary (Tliro, 2014). Choi et al. (2015) proposed a cluster‐based multi‐polling sequencing algorithm for collecting RFID data in wireless LANs. Yan et al. (2015) presented a memoryless binary query tree based on successive scheme for passive RFID tag collision resolution. However, the collision algorithm should be solved before the application of RFID technology in mass identification of vehicle ID (Reza et al., 2014). In this paper, channel collision algorithm of RFID is also analyzed based on UHF (Yun et al., 2015) to provide a vehicle inspection and intelligent traffic management. The scheme and prototype of proposed intelligent management system are illustrated here.
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System Scheme An intelligent vehicle management system of vehicle detection includes central database, management organizations, outer sensor networks, and transfer system especially wireless communication system. To improve the management performance, a closed‐loop of continuous operation is necessary, including RFID license reading, Identification, Check, Act processing, etc. Electronic license is stored as the vehicle identification data after encryption, which can only be read and performed by authorized RFID readers. The transport management bureau can set up many monitoring stations with network security professionals all over the city, which is connected with a central server via WLAN and with Police via PDA (Ruttenberg, 2013). A complete vehicle management system would include accountability and database query, responsibility assignment of driver or vehicle owner, and a monitoring mechanism for manager’s activities. Additionally, auditing tools are also needed to implement corresponding actions in accordance with violation activities, such as alarm, next operation, creating an upward spiral of continuous process, as shown in Fig. 1.
FIG.1 THE PROPOSED SYSTEM SCHEME
Being set in city traffic junctions, the RFID readers can be used to read the RFID license data and further transmit these data to the central database or processing central via ZigBee network. The data processors can determine whether the vehicle is illegal or not by querying and matching the database in electronic vehicle information management system. If a vehicle is not illegal that the alarm equipment will work and can send alarm messages to police or the law enforcement officers nearby. It can also be set for two‐path communication between the inlet channel and the reader device in order to finish the target identification and data exchange of electric vehicle. Then the identifier starts to work to decide whether a vehicle or a driver is illegal or not by different issuing agencies. In RFID vehicle license system, a central database is indispensable because all vehicles have their own unique electronic identifications that a label system should be correspondingly developed in the central database to record all kinds of information of every vehicle. Based on the RFID license data, the proposed system can solve many traditional problems in car monitoring and identification, and improve the traffic situation as well. System Analysis and Design Modules As a license management system, the central database is a basic infrastructure which records the license number and other information depicting the vehicle, such as the Vehicle Identification Number, and the name and address of the vehicleʹs registered owner or keeper, engine size, fuel type, maker, model, color, date of manufacture, mileage recorded, and other related data in jurisdictions. Based on these data, all vehicles can be regularly inspected for roadworthiness every year or more. In the database design, the registration identifier or vehicle ID is a unique numeric or alphanumeric code that can identify the vehicle by the distributed database. In the higher level application design of the intelligent management system, the business process analysis is
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needed to establish a database table for the system to save various data. This database table should cover all kinds of tasks required to manage and monitor the RFID information of vehicle owner and driver. In addition, related information including traffic rules, managing run level scripts is also indispensable, and the basic items are shown in Table. 1. TABLE. 1 BASIC DATA TABLE
Name
Explanation
U_Panel
User Control Panel
U_AddPanel
User additional control panel
U_Groups
User Groups
U_Users
User
U_UserAttr
User Properties
U_System
The basic properties of the system
U_LoginSet
User login settings
U_UseLogin
User login status table
U_UpFileSet
Upload file settings User Group
C_Unit
Vehicle personnel affiliations table
C_Chauffeur
Vehicles person table
C_CarInfo
Vehicle Information Sheet
C_Violation
Vehicle illegal information table
C_Accident
Vehicle Accident Information Sheet
C_YAuditing
Vehicles examined table
Based on the Table 1, the violation management system can manage all kinds of terminals to transmit the vehicle data via UHF RFID readers by micro‐ processors, as shown in Fig. 2. Then the handheld processors are connected with the data center and microcontrollers by ZigBee wireless communication module, which is used to realize necessary communion between the vehicles, drivers and processing center. Apparently, the detecting system is an initialization loop in Fig. 2, which can justify whether the RFID data are effective or not. Then monitoring system can display and transmit the detected effective information to the data center to further justify whether the RFID license entering into the monitored area is illegal or not. Then the justification results can be sent back to the terminals and alarms for the police to dispose. System initialization RFID card?
N
Y Display the information Transmit information to the center Illegal? N
Y Back to the terminal Police dispose
Next
FIG.2 FLOWCHART OF HANDHELD TERMINAL
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Detecting Processing System In the detecting processing system, it is to generate the illegal recording, upload data to the central control subsystem, gather other illegal information, and provide the reference for punishment. Monitoring the Red Light Violation The basic principles for monitoring the red light violation are that when the red light works, the readers installed in the road intersections will start to be operating to detect whether there are cars in the monitoring area or not. If there is a car, then the detecting system will determine whether it is a normal driving, such as turn right. If it is not a normal driving mode, the vehicle will be recorded by its ID number of electronic tag, and other relevant information will also be collected, such as time, place, owner names, road intersections, and others. Then, it begins to transmit the electronic tagʹs ID number to the central database, and precludes the other related illegal information. Monitoring the Over Speed Violation The function is to monitor the over speed phenomenon which is the main cause of many traffic accidents. Over speed violation needs speed radar to work together between two readers in multiple sections, where RFID license is set apart according to a certain interval to easily monitor the vehicle speed in monitored area. Then it can calculate the traveling time by reading the speed of monitored vehicles, and compare it with the corresponding speed limit requirement. Finally, it can also conclude the speed situation of the vehicle according to the regulations and determine whether the vehicle is over speed or not. If the over speed is detected, it would further record vehicle ID number in electronic tag, and collect other related illegal information for the violation disposition by the traffic management department. Monitoring Illegal Parking Illegal parking phenomenon is also popular in many cities, especially bigger metropolis. Although illegal parking behavior is random, it is one of the important causes of urban traffic congestion and some traffic accidents. The basic principle to monitor illegal parking is to monitor parking area by the reasonable set Readers which is prohibited by the traffic management departments. With the rapid development of Chinaʹs economy and society, the ownership rate of private car is greatly increasing. By vehicle monitoring system, it is hopeful to alleviate this congestion situation of our traffic. Anti-Collision Algorithm Because of a large amount of vehicle detecting, the proposed system employs a binary search algorithm for UHF RFID, and the tag readers in the working area continue are divided into P subsets, where P> l. For a subset of the same division, the number of tags within a division is continuously divided into more subsets until the number of tags within a subset is 1, when a successful identification of tag reader is completed. When the read of a tag is finished within a certain subset, the additional waiting period is needed for back manner of readers to read the label. These processes can be seen as a whole diversion process where a tag is grouped in different labels according to the grouping scheme from the root to leaf nodes layer by layer. Only the leaf node labels can be successfully read out. The whole process of anti‐collision algorithms is illustrated as follows. Firstly, it is to seek a separate tab from relatively large number of labels, and the operation process is required to be repeated. The average search step I depends on the number of readers within the total number n of tags, that is I log 2 n 1 (1)
Secondly, it is to find a label search. In the pending identification tag N, the average recognition algorithm requires I times of search for a label. Obviously, the identification tag within the read range tends to be a reduced number of complete tag identification N with total required search cable time:
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IBS (log 2 n 1) [log 2(n 1) 1] ... (log 22 1) (log 21 1) n log 2( N！ ) (2)
The drawbacks of traditional anti‐collision algorithms include the great number of iterations where the readers need a delay to identify any given tag, the complexity of tag circuits with slow response, and uncertain communication among different nodes. On the contrary, the protocol equation (2) lets the tags choose the appropriate chance for their own response. When a collision occurs, the UHF RFID tags in the collision will participate in later iterations until ultimate resolution is finished. The protocol of UHF‐type RFID clearly takes less time to complete a search according to the equation (2). Thirdly, it is to calculate the average recognition. Although in traffic management system there is a probability for a RFID tag of vehicle license to be not read within a given number of iterations. In a defined iteration k, the exception is given as BBS IBS * k (n log 2(n !)) * k (3)
Because each checking request will be passed to the tag reader under the control instruction, the argument is that the length of the entire sequence number is uncertain. So the number of bits to be transmitted to the reader can be assumed as k times of the total number of search algorithms, then it can be labeled as the product serial number length. LBS IBS * k (n log 2(n !)) * k (4)
Lastly, it is to terminate the search algorithm. After several iterations, the intelligent management system of vehicle license can find out whether the detection and transmission of RFID data are successful or a collision takes place by listening to the broadcast. If there is a collision in vehicle identification, the management system can wait a random period. This protocol above makes the reader design simpler where all readers do nothing but listen to the collision. The RFID tags send data packets periodically within random preset periods, and the system can quickly adapts protocol to the varying outer environment. Prototype Test To verify the proposed scheme, a prototype is built where different roles and relationships between services are defined by traffic manager, vehicle owner, and driver. These roles and relationships can be used to provide precise RFID identification, for example, traffic manager can restart all services that are directly affected by a failed identification. Another advantage of the proposed prototype is that the system allows for scalable and reproducible identification processes. For examples, by mounting all of the dependencies, the intelligent and highly parallel management prototype can be controlled, because all independent RFID services can be started in parallel.
FIG.3 SYSTEM LOGIN SCREEN
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The figure 3 shows the landing interface of the prototype system, by which the vehicle owners can visit the primarily information and vehicle violation information of his owner at any time and any place freely. Then, we tested 30‐50 times for the system stability of each module in collision environment respectively, as shown in Table 2. The stability is described by the succeed times and shown in the last column. TABLE 2. SYSTEM TEST TABLE
Test Module User Login User Control Panel Management User Group Management User group permission settings Manage Users Unit Management Personnel management Middle ware
Test Function User login, authentication code update, duplicated user login Add controlled module node, modify the module node, set the fixed module node and the mobile module nodes, remove the module node Adding user groups, modify user Add, modify, save the operating authority of user module Add users, change user, delete user, disable and enable the user to lock and unlock the user Modify the unit, delete unit, disable and enable the unit to lock and unlock the unit Add, modify, delete, disable and enable the staff, lock and unlock the staff Allow multiple processes running on one or more machines to interact across a network.
Stability 50/50(100%) 30/30(100%) 30/30(100%) 30/30(100%) 50/50(100%) 50/50(100%) 50/50(100%) 30/30(100%)
It turned out that all modules were normal and appears good performance in collision environment. The tests showed good data transfer in information exchange between various modules, and rapid response to electronic license detection. For each user in vehicle registration database, the system can operate and display all vehicle information and owner information. To identify the fake cards, deck, theft, and illegal operations, the vehicle authenticity function provides a series of effective tools to prevent the vehicle from counterfeiting, such as illegal vehicles blacklist. These database functions of the intelligent management system above can achieve automatic vehicle identification, and can record continuous use and violation. Anti‐collision algorithm is tested to be effective and the whole system provides us a helpful tool to prevent tax evasion, track car thefts, lessen car snatching, and other criminal activities. Furthermore, the figure 4 shows the user interface of owner information.
FIG.4 INTEGRATION TESTING
As we can see, the user interface can display driving record and electronic license information, and the illegal user can visit all information including Name, Sex, ADD (Address), EXP (Expire Date), Valid From, etc. In the integrated test and system test, the entire system works well, and can successfully meet the predefined requirements and designed capabilities, demonstrating the usability of the intelligent vehicle management system.
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Summary Here, the proposed vehicles management system based on electronic RFID license can more easily identify illegal vehicles and activities by a variety of sensors in real‐time collection based on the unique ID number of vehicles. The proposed system can identify the continuous vehicle traffic, analyze its activity and display related information in real time by the embedded terminal platform. In practice, the most popular vehicle registration plate based on metal or plastic plate identified by graphical technology can be improved by imbedded RFID chip, and its database as well. In future work, artificial intelligent algorithm should be applied to facilitate the interactive analysis, and the shared database should also be established to integrate the intelligent control and human control to improve its intelligence. ACKNOWLEDGEMENTS
This research was supported by the National Natural Science Foundation of China (No. 71471102), and Science and Technology Research Program of Hubei Provincial Department of Education in China (Grant No. D20101203). REFERENCES
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