【正文】 的需求，從而取代傳統(tǒng)手工方式和基于定時(shí)器的交通系統(tǒng)。在本文提出的概念涉及利用無(wú)線傳感器網(wǎng)絡(luò)去感應(yīng)交叉路口附近的交通情況，因此依據(jù)交通流量密度規(guī) 劃出所需要的交通路線。 they may range from to at 250 kbps. In general, the ZigBee protocols minimize the time the radio is on, so as to reduce power use. In beaconing works, nodes only need to be active while a beacon is being transmitted. In nonbeaconenabled works, power consumption is decidedly asymmetrical: some devices are always active, while others spend most of their time sleeping. V. PROPOSED ALGORITHM A. Basic Algorithm Consider a left side driving system (followed in UK, Australia, India, Malaysia and 72 other countries). This system can be modified for right side driving system (USA, Canada, UAE, Russia etc.) quite easily. Also consider a junction of four roads numbered as node 1, 2, 3 and 4 respectively. Traffic flows from each node to three other nodes with varied densities. Consider road 1 now given green signal in all directions. Fig. 4 Intersection Under Consideration 1) Free left turn for all roads (free right for right side driving system). 2) Check densities at all other nodes and retrieve data from strip sensors. 3) Compare the data and pute the highest density. 4) Allow the node with highest density for 60sec. 5) Allowed node waits for 1 time slot for its turn again and the process is repeated from step 3. B. Advanced Algorithm Assume road three is currently given green to all directions. All left turns are always free. No signals/sensors for left lane. Each road is given a time slot of maximum 60 seconds at a time. This time can be varied depending on the situation of implementation. Consider 4 levels of sensors Ax, Bx, Cx, Dx with A having highest priority and x representing roads 1 to 4. Also consider 3 lanes of traffic: Left (L), Middle (M) and Right(R) corresponding to the direction of traffic. Since left turn is free, Left lanes do not require sensors. So sensors form 4x2 arrays with 4 levels of traffic and 2 lanes and are named MAx, RAx, MBx, RBx and so on and totally 32 sensors are following flow represents the sequence of operation done by the signal. 1) Each sensor transmits the status periodically to the controller. 2) Controller receives the signals and putes the following 3) The sensors Ax from each road having highest priority are pared. 4) If a single road has traffic till Ax, it is given green signal in the next time slot. 5) If multiple roads have traffic till Ax, the road waiting for the longest duration is given the green. 6) Once a road is given green, its waiting time is reset and its sensor status is neglected for that time slot 7) If traffic in middle lane, green is given for straight direction, based on traffic, either right side neighbor is given green for right direction, of opposite road is give green for straight direction. 8) If traffic in right lane, green is given for right, and based on traffic, left side neighbor is given green for straight or opposite is given green for right. 9) Similar smart decisions are incorporated in the signal based on traffic density and directional traffic can be controlled. C. Implementation and Restrictions This system can be implemented by just placing the sensor nodes beneath the road or on lane divider and interfacing the central controller to the existing signal lights and connecting the sensor nodes to the controller via the proposed wireless protocol. The only restriction for implementing the system is taking the pedestrians into consideration. This has to be visualized for junctions with heavy traffic such as highway intersections and amount of pedestrians is very less. Also major intersections have underground or overhead footpaths to avoid interaction of pedestrians with heavy traffic. VI. CONCLUSION The above proposed system for automated traffic signal routing using Wireless Sensor Networks is advantageous to many existing systems. The wireless sensors nodes create a standalone system at each intersection making it easy to implement in the intersections having heavy density of vehicles. It is also cost inexpensive and does not require any system in the vehicles making it more practical than existing systems. The use of various systems of sensor nodes can be altered based on the requirement and any type of sensor can be used based on the feasibility of the location. ACKNOWLEDGMENT The Authors would like to take this opportunity to thank Ms. P. Sasikala, Assistant Professor, ECE department, Sri Venkateswara College of Engineering, Sriperumbudur, who gave the basic insight into the field of Wireless Sensor Networks. We also thank Mrs. G. Padmavathi, Associate Professor, ECE department, Sri Venkateswara College of Engineering, Sriperumbudur, who with her expertise in the field of works advised and guided on practicality of the concept and provided helpful ideas for future modifications. We also express our gratitude to Dr. S. Ganesh Vaidyanathan, Head of the department of ECE, Sri Venkateswara College of Engineering, Sriperumbudur, who supports us for every innovative project and encourages us “ think beyond” for better use of technology. And finally we express our heart filled gratitude to Sri Venkateswara College of Engineering, which has been the knowledge house for our education and introduced us to the field of Engineering and supports us for working on various academic projects. 基于無(wú)線傳感器網(wǎng)絡(luò)的智能交通信號(hào)控制 摘要： 在所有發(fā)展中國(guó)家和發(fā)達(dá)國(guó)家，不斷增長(zhǎng)的汽車數(shù)量將促使現(xiàn)有的交通信號(hào)系統(tǒng)發(fā)生重大變革。 and active sensors [3]. The sensors are implemented in this system placed beneath