INTRACS: Intelligent Traffic Control System Based on Ubiquitous Technology Jae-Bong Yoo, Byung-Ki Kim, Ho-Min Jung, Chan-Young Park, Young-Woong Ko Dept. of Computer Engineering, Hallym University, South Korea {yoojaebong, bkkim, chorogiy, cypark, yuko}@hallym.ac.kr Taewan Gu Dept. of Information Technology, Gangwon Human Resource Development Institute, South Korea
[email protected]
Abstract Traffic control system such as detective devices (loop, image, supersonic waves, and high frequency sensor) holds the promise of intelligent traffic information system. However, the traffic control system can not prevent undesirable situations including heavy congestion, a high frequency of crashes, and emergency cases effectively. Furthermore, in dangerous region such as bridges, tunnels, and icy road, drivers might need more useful information about the surrounding environment to avoid an unpredictable accident. To deal with these problems, we adapted a traffic control approach based on ubiquitous technology to our system. In this paper, we describe the design and implementation of INTRACS (Intelligent traffic control system). The key point of INTRACS is a traffic control module which detects a car accident and propagates accident information to neighboring vehicles. INTRACS also collects traffic information such as traffic jam information, accident information and weather information with USN (Ubiquitous sensor network, and RFID. We show that proposed system provides a novel way to manage traffic systems safely and efficiently by complementing these problems in the current traffic system.
1
Introduction
According to the statistics, the number of car registrations jumped from around 18,000 in 1955 to 10 million during the late 1990s, and moreover the number increased to 15.4 million by 2005. Although the technology of automobiles has been improving, the number of car accidents tends to increases. To reduce car accident rate, ITS (Intelligent Transportation System) could be one of the most suitable solutions[1–3]. ITS technologies are a collection of technologies that increase the efficiency and safety of public transportation sys-
tems and offer users greater access to information on system operations[4]. Nowadays, ITS is gradually getting popular as congestion, traffic accidents, air pollution and so on are becoming critical issues. Although it provides useful information about traffic status to the user reliably, accurately, and in a timely manner, ITS can not meet overall requirement of user needs[5]. There are two general types of sensors for traffic surveillance. One is intrusive sensors, the other is non-intrusive sensors. Intrusive sensors are installed directly on the pavement surface by tunneling under the surface such as inductive loops, magnetometers, and micro loop probes. Generally, the drawbacks to their use include disruption of traffic for installation and repair, and failures associated with installation in poor road surfaces. Also, sensors are rarely used these days because of their accuracy[6]. However, non-intrusive sensors do not need any installation on or under the pavement, so that the installation and repair of such a system can be done without disrupting the traffic[7]. Representative non-intrusive devices are video image processing, microwave radar, and laser radar. Video-based vehicle detection is a typical solution for traffic surveillance. It has played an important role in real-time traffic management systems over the past decade. Video-based traffic monitoring systems offer a number of advantages over traditional methods, such as loop detectors. In addition to vehicle counting, more traffic information can be obtained by video images, including vehicle classifications, and lane changes. Furthermore, video cameras can be easily installed and used in mobile environments. However, the disadvantages of the video camera greatly affected by inclement weather so that they can not detect a car accident when there is a thick fog on a bridge or heavy smoke in a tunnel[8]. Considering these limitations, RFID (Radio Frequency Identification) technology can be a good candidate for traffic monitoring system. RFID is an automatic identification technology that can be used to provide electronic identity to
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an item or object[9–11]. RFID is a well-known technology of remotely storing and retrieving data. The main component of RFID system consists of reader and tag. The tag is a small electronic device that consists of a small chip and an antenna. The chip is capable of carrying 2,000 bytes of data or less and the antenna is used to receive and respond to radio-frequency queries from a reader. If we adapt RFID technology to ITS, regardless of the surrounding environment such as fog or smoke, ITS can gather various traffic information effectively. In this paper, we are focusing on traffic surveillance to detect accidents on a bridge and tunnel, therefore RFID and USN can be effectively applied for the traffic surveillance and detection because the coverage of traffic monitoring is limited. The organization of this paper is as follows: In Section 2, we first introduce Related Works. Section 3 presents a System Overview, including system components and system architecture. Next, we present Experimental Environment. Then in Section 5, we propose Event Detection Algorithm to detect a car accident Finally, Section 6 concludes this paper.
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diction of the vehicles path, a model-based description of the traffic environment is presented.
3
System Overview
Proposed system mainly consists of the seven components as illustrated in Figure 1: ITS Server, ITS Client, MCU (Micro Control Unit), Zigbee, RFID Reader, RFID ALE Server, and RFID Client. Assuming that RFID readers can read RFID Tags which are attached to cars moving on the road, the RFID Tag on the ticket is issued at toll gates.
Related Works
There have been many attempts to realize ubiquitous ITS including Fangli[12], VSLS[13], and Aris[14]. Fangli[12] discusses the system architecture and the information service in the RFID-based EPC system. The key idea is the design of EPCIS server applied to ITS using existing EPCIS. The EPSIS system has two working modes for ITS: storing and querying. The storing state refers to the procedure that EPCIS receives real-time information from and to the ITS EPC system, and additionally stores and processes the received data. In the querying state, EPCIS responds querying requests from other terminals in the ITS EPC system and replies with the appropriate results. VSLS (Variable Speed Limit Sign)[13] consists of dynamic message signs which enable transportation managers to dynamically change the posted speed limit in response to prevailing traffic conditions. The purpose of VSLS is to design and evaluate a framework for a candidate VSLS control algorithm on congested freeway, to perform an extensive analysis on a proposed algorithm. The analysis result shows that the relationship between the choice of control strategy parameter values and the resulting safety and operational impacts. Aris[14] suggests path prediction for collision avoidance with sensor fusion technology which integrates several location systems simultaneously and combines sensory data. The resulting information is better than when these sources were used individually. By means of sensor fusion, different sources of information are combined to improve the performance of a system. The benefits of sensor fusion are more accurate, more complete, or more dependable result. In Aris paper, in order to provide sufficient information for an accurate pre-
Figure 1. System Architecture First, the ITS Server (①) collects tag information, atmospheric information such as temperature, humidity and illumination etc. The main responsibility of the server is to detect and propagate car accidents. Secondly, the ITS client (②) enables to help administrators manage their system at ease. It processes messages from the ITS server and displays traffic and atmospheric information on the screen. If any message is considered as a car accident, it notifies a police station or a fire station of an accident, providing emergency medical services and technical rescue for drivers. It can send the server requests for controlling lights, sirens, alerts, gates and LCD in a state of emergency as well. The ITS client plays a role as an ALE client (③) which defines ECSpec. Thirdly, the MCU (④) is able to control lights, sirens, alerts, gates and LCD when the ITS server detects accidents and gives commands to MCU. We made the MCU as an embedded board as shown in Figure 2. Fourthly, each Zigbee Sensor node with a RFID reader sends tag information to a Zigbee sink node by using RF (Radio Frequency). Zigbee (⑤) protocols are intended for use embedded application requiring low data rates and low power consumption. A Zigbee node is divided into a sensor node and a sink node as a role: The sink node collects information from a set of sensor nodes and can sense the event such as temperature, humidity and illumination and so. Fifthly, RFID Readers
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(⑥) read RFID tags and sends them to a Zigbee module by using UART (Universal Asynchronous Receiver and Transmitter). Finally, RFID ALE server (⑦) is communication interface; it also filters and collects RFID tags[15, 16].
Table 1. Development Environment System OS Specification Server Linux Intel Core2 1.86 GHz, Kernel gcc 3.2.2 Compiler, 2.6.x MySQL 5.0.27 Client Windows Visual Studio 2005 (C#) XP RFID TinyOS ATmega 128 13.56MHz 1.x Zigbee TinyOS CC2420 2.4 GHz Base sensors 1.x (temperature, illumination, humidity) MCU Compiler-IAR Embedded workBoard bench ISP downloader : Ponyprog2000
Figure 2. Picture showing main electrical devices such TO-220, ATM 128, LCD driver, and interface connectors. TO-220 as the power control unit supplies power to devices such as LED, LCD, Light and Alert. ATM 128 as the command processing unit is programmed to process command from and to ITS server. The LCD driver displays message on the LCD. There are many interface connectors to link LED, LCD, Light and Alert to the embedded board. Figure 3. Bridge Model
4 4.1
Experimental Environment Experimental Setup
Table 1 summarizes a development environment used in a prototype implementation.
4.2
A Prototype Implementation
We implemented a small test-bed as shown in Figure 3. Its length is 2 meters. Lights and alerts were installed on the left and right guardrail and gates were installed on an exit of the bridge. An LCD on the pier gives traffic information to drivers. Ten 13.56 MHz RFID Readers are attached under the bridge.
4.3
Monitoring Program in ITS Client
The monitoring program consists of Bridge Status, Topology & Statistic, Sensor & Device, Accident History, and Camera Control. As shown in Figure 4, the Bridge Status displays general information such as traffic flow, car
accidents, and the state of devices as well as atmospheric phenomena. The violet arrow under the bridge means a car accident happened at this part. Topology & Statistic displays statistical weather information near the bridge. Sensor & Device controls devices like sirens, alerts, the LCD and gates, and displays the latest information on weather as shown in Figure 5. Accident History displays car accident statistics as shown in Figure 6. Through analysis on occurrence location and occurrence time of the accident, the ITS client reports car accident information to administrators, and helps them to maintain and improve a road. They also give safe driving guidance to drivers. Finally, Camera Control enables administrators to monitor the traffic condition on the bridge as shown in Figure 7. As soon as ITS server detects a car accident on the bridge, cameras are automatically pointed at the scene of an accident.
4.4
Expectable Scenario
The Kim family is going on a picnic by the West Sea. Before arriving at noon, they see the sea and eat shrimp.
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Figure 4. Bridge Status
Figure 6. Accident History
Figure 5. Sensors & Devices Accompanied by a sounding alarm, they see the message, “An accident happened. Slow down while they drive on the Seohae Grand Bridge in a thick fog. They decrease their speed as soon as they get the message. At this time, they see three cars were involved in a car accident 15 meters ahead. However, they avoided the accident thanks to a Safe and Intelligent Bridge System.
Figure 7. Camera Control
INSERT INTO READ TAGDATA (LogicalReader, RFIDTag, CurrTime) VALUES ([Text], [Text], [TimeValue]);
Figure 8 shows the result of the query Q1.
5
Event Detection and Reaction in ITS Server
In this section, we explain Event Detection and Reaction in ITS Server. At first, the ALE server registers logical readers. Next, a logical reader layout is defined as required by the ALE specification. If an event cycle runs, logical readers can read RFID tags. Finally, an ECReports is the output from the event cycle after finishing[16, 17]. After creating the ECReports, ITS server stores the ECReports in Database for Event Detection.
5.1
Queries for Event Detection
The ITS server can also analyze traffic flow using the following query Q2.
The ITS server classifies the ECReport into three fields such as TAGID, Logical Reader, and Register Time, and then it stores it in the Database using the following query Q1. Q1. Input ECReports in the Database.
Figure 8. The query Q1 result on RFID TagECReports input
Q2. Find the location of RFIDTags. SELECT RFIDTag, LogicalReader, CurrTime AS TI FROM READ TAGDATA WHERE CurrTime >= [TimeValue]
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GROUP BY RFIDTag HAVING MAX(CurrTime);
Figure 9 shows the result of the query Q2. For searching for a specific cars current position, the ITS server finds out the RFID Tag which is attached to the car. After looking up the latest updated RFID tag in the table below, its logical reader indicates its current position.
If drivers have a Zigbee device, it has them know accident information in the car. Accident history is available to analyze the accident situation by recording occurrence location and occurrence time of the accident, and atmospheric information such as temperature, illumination and humidity. On the whole, the ITS server helps administrators to decide whether an event is a car accident or not by watching the scene of the expected accident through a camera.
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Figure 9. The query Q2 result on RFID Tag Location Finally, the ITS server is able to detect a car accident using the following query Q3. Q3. Detect a car accident event. SELECT R, T, COUNT(*) AS CNT FROM ( SELECT ReaderID AS R, RFIDTag AS T, CurrTime FROM READ TAGDATA WHERE CurrTime = T2 )
Conclusion
In this paper, we propose Intelligent Bridges System based on ubiquitous technology. This system was designed to detect an event such as a car crash in real-time and propagate accident information as quickly as possible. The evaluation framework consisted of the system equipped with ubiquitous devices (sensor, RFID, and camera), ITS server, ALE client and RFID event generation simulator which generates virtual RFID tags. Experiment result shows that the system can effectively gather various information and control related devices. The client software shows the entire system information with WEB-based GUI display. We believe that proposed prototype can be a great help to drivers and diminish car accidents extremely.
Acknowledgment
GROUP BY R, T;
Figure 10 shows the result of the query Q3 on detecting the accident. A specific RFID tag is read more than 5 times on ExpressHighway15 SehaeBr section3 which means the car with it stopped on the road. It may be considered as a car accident.
This research was financially supported by Korea Industrial Technology Foundation (KOTEF) through the Human Resource Training Project for Regional Innovation.
References [1] Road Traffic Safety Authority, http://www.rtsa.co.kr [2] Ministry of Construction http://www.moct.go.kr
Transportation,
[3] Lee, H., “A Study on ITS in Domestic and Advanced Countries, ETRI Journal, Vol. 14, No. 2, 1999.
Figure 10. The query Q3 result on a car accident
5.2
&
[4] TranSystems corp., “Statewide Transit Intelligent Transportation Systems Deployment Plan, Iowa Department of Transportation, May 2002.
Reaction to Event Detection
When the ITS server detects a car accident, it sends signals to the MCU (Micro Control Unit) which controls sirens, alerts, LCD and gates. By propagating accident information to other drivers quickly, it can prevent additional collisions. Control signals are transmitted through UART and the state of each device is stored in Database.
[5] Reynold, Stuart, “Architectural Trends: A real-time distributed database for Europe, Traffic Technology International, Feb/Mar 1998. [6] Mimbela L. Y., Klein L.A., “A summary of vehicle detection and surveillance technologies used in intelligent transportation systems, New Mexico State University, Tech. Rep., November. 8.
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[7] Sing-Yiu Cheung, Pravin Varaiya, “Traffic Surveillance by Wireless Sensor Networks: Final Report, California PATH Research Report UCB-ITS-PRR-2007-4, Jan. 2007. [8] Xiao-jun Tan, Jun Li, and Chunlu Liu, “A video-based real-time vehicle detection method by classified background learning,” World Transactions on Engineering and Technology Education 2007 UICEE Vol.6, No.1, 2007. [9] WinRFID A Middleware for the enablement of Radio Frequency Identification (RFID) based Applications, B.S. Prabhu, X. Su, H. Ramamurthy, C-C, R. Graph. In Mobile, Wireless and Sensor Networks: Technology, Application and Future Directions, Eds. Rajeev Shorey, et al., John Wiley, 2006, 313-338. [10] RFID Handbook: Fundamentals and Applications in Contactless Smart Cards and Identification, 2ed, Klaus Finkenzeller, Wiley, 2003. [11] Auto-ID Labs, http://www.autoidlabs.org/ [12] Fangli Liu, Huansheng Ning, Huiping Yang, Zhiqiang Xu, Yu Cong, “RFID-based EPC System and Information Services in Intelligent Transportation System”, 6th International Conference on ITS Telecommunications Proceedings, 2006. [13] Allaby, P. Hellinga, B. Bullock, M. “Variable Speed Limits: Safety and Operational Impacts of a Candidate Control Strategy for Freeway Applications”, IEEE Transactions on Intelligent Transportation Systems, pp. 671-680, Dec. 2007. [14] Polychronopoulos, A. Tsogas, M. Amditis, A.J. Andreone, L. , ‘Sensor Fusion for Predicting Vehicles’ Path for Collision Avoidance Systems”, IEEE Transactions on Intelligent Transportation Systems, pp. 549562, Sept. 2007. [15] EPCglobal, The EPCglobal architecture framework, final version, July 1, 2005. [16] EPCglobal. EPC Information Services (EPCIS) Version 1.0 Specification, working draft, June 8, 2006. [17] K. Traub, S. Bent, T. Osinski, S. N. Perertz, S. Rehlinh, S. Rosenthat, and B. Tracey, The Application Level Event(ALE) Specification, ver1.0, 2005.
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