基于无线传感器网络技术的运输网络智能引导及控制系统--中英文翻译.doc
![资源得分’ title=](/images/score_1.gif)
![资源得分’ title=](/images/score_1.gif)
![资源得分’ title=](/images/score_1.gif)
![资源得分’ title=](/images/score_1.gif)
![资源得分’ title=](/images/score_05.gif)
《基于无线传感器网络技术的运输网络智能引导及控制系统--中英文翻译.doc》由会员分享,可在线阅读,更多相关《基于无线传感器网络技术的运输网络智能引导及控制系统--中英文翻译.doc(12页珍藏版)》请在得力文库 - 分享文档赚钱的网站上搜索。
1、英文原文An Intelligent Guiding and Controlling System for Transportation NetworkBased on Wireless Sensor Network Technology AbstractThis paper proposes architecture based on Wireless Sensor Network (WSN) technology for Intelligent Transportation System (ITS) of a transportationnetwork. With the help of
2、WSN technology, the traffic info of the network can be accurately measured in real time. Based on this architecture, an optimization algorithm is proposed to minimize the average travel time for the vehicles in the network. Compared to randomly-chosen algorithm, simulation results show that the aver
3、age speed of the road network is significantly improved by our algorithm, and thus improve the efficiency of the road network. Some extended applications of the proposed WSN system are discussed as well.1. IntroductionTransportation plays an important role in our modern society. How to efficiently e
4、xploit the transportation capacity of the existing transportation infrastructure receives a lot of attention from the researchers across the world. The Intelligent Transportation System (ITS) has been proposed by many researchers to solve the problem.ITS comprises of three main sub-systems. They are
5、 surveillance sub-system, analysis and strategy subsystem and execution sub-system. The execution subsystem can be a traffic control sub-system, a vehicle guiding sub-system, or a navigation sub-system. The surveillance sub-system measures the traffic information such as the vehicles location, speed
6、, number of the vehicles on the road, etc., using certain type of sensor, such as inductive loops 1 or ultrasonic sensor 2. A new method based on video analysis is now under development 1;3.The analysis and strategy sub-system optimizes the traffic flows based on the measurements from the surveillan
7、ce sub-system. Various algorithms are proposed for this purpose, some typical examples follow. Papageorgiou et al. summaries some implementations on fixed-time strategies and trafficresponsive strategies for isolated strategies and coordinated strategies in 4; In 5, Shimizu et al. propose a balance
8、control algorithm to optimize the congestion length of the whole transportation network; in 6, Di Febbraro presents a hybrid Petri Net module to address the problem of intersection signal lights coordination.The control sub-system controls the signal lights on the intersection. The guiding sub-syste
9、m provides the real-time traffic information for the drivers to select the best route. The navigation sub-system uses satellite signal such as GPS to locate the specific vehicle, and with the help of electronic map, select the optimal route for the vehicle.One shortage of the systems mentioned above
10、 is that the sensors can only detect the vehicles in a fixed spot. They can not track the vehicles out of the spot. Clearly, if we can monitor and measure the traffic status dynamically in real time, an efficient traffic control will be easier to realize.With the development of microelectronic and c
11、omputer technologies, the low-power-consumption, low-cost and relatively powerful wireless sensor network (WSN) technology has been applied in many areas7-9. However, the application of WSN in the traffic control system is rarely documented. In 10, we proposed a WSN-based system for an efficient tra
12、ffic control in an isolated road intersection. This paper extends our previous work to a transportation network. A WSN-based traffic control, guiding, and navigation system is proposed to optimize the traffic in a transportation network.The rest of this paper is organized as follows: Section 2 descr
13、ibes the structure of the proposed WSN-based traffic control system. Section 3 describes the optimization algorithm for the traffic network. The simulation results and some discussions are presented in Section 4. Finally, Section 5 concludes this paper.2. System Structure2.1. WSN ModuleWSN module is
14、 a basic component in our traffic control system. As illustrated in Fig. 1, a WSN module comprises of 3 main components, i.e., RF (Radio Frequency), MCU (Micro Control Unit) and Power Supply. The RF encodes, modulates and sends the signal. Also it receives, decodes and demodulates the signal as well
15、. MCU integrates processor and memories, where the programs resides and executes. The Power Supply supplies the power to entire module.In the proposed system, WSN modules are widely distributed on vehicles, roadsides and intersections to collect, transfer and analyze the traffic information. See sec
16、tion 2.3 for details.2.2. Urban Traffic NetworkSeveral different facilities are installed in the urban traffic network to perform their specific functions. For example, the Signal Lights are installed in the road intersection to directly control the vehicle through the intersection; the Variable Mes
17、sage Sign (VMS) is set up along the road side to help drivers to select the optimal route; the Navigation system (electronic-map and satellite-based positioning system) is installed in the vehicle for vehicle locating and navigation.The target of an ITS is to optimize the traffic in a transportation
18、 network by controlling the signal lights in the intersections, by providing the accurate traffic information in the VMS, or by selecting the best route in the e-map.To perform the traffic control, below, we shall first have a look at the configuration of the transportation network. Then, some param
19、eters are introduced to describe traffic information in the network. By optimizing these parameters, the proposed optimization algorithm is expected to optimize the traffic in the transportation network.As a example of a real-life traffic network, Fig. 2 illustrates the road net of Fukuyama city 11.
20、 On the figure some parameters such as the link length, lane numbers, and legal speed are marked on it.In this paper, we consider the traffic system that contains 3 types of basic elements, i.e., intersection (N), Link (L) and Vehicle (V). An Intersection can be described by 2 parameters: 1) the pha
21、se type (the type of the vehicles on different lanes passing through the intersection simultaneously); 2) the duration of every phase. A Link can be described by 4 parameters, i.e., the link length, lane numbers (include every turningdirection), mean speed, vehicle number. A Vehicle can be described
22、 by 5 parameters. They are: 1) the location of the vehicle, 2) the vehicle velocity, 3) the origin, 4) the destination, 5) the length of the route, 6) the total time and, 7) the average speed on the route.Among these parameters, 1) some are fixed, such as the lane numbers and link length; 2) some ar
23、e measured by the surveillance sub-system, such as the mean speed, the number of the vehicles on a link; 3) some are set by an optimization algorithm, such as the intersection signal light and the next link selected by a vehicle.The vehicle velocity, direction, and the number of the vehicles are the
24、 basic variables of the whole system. It is the main task of our algorithm to optimize these parameters.2.3. Data Collection and TransferringAs illustrated in Fig. 3, there are 3 types of WSN nodes installed in our system, i.e., the vehicle unit on the individual vehicle; the roadside unit along bot
- 配套讲稿:
如PPT文件的首页显示word图标,表示该PPT已包含配套word讲稿。双击word图标可打开word文档。
- 特殊限制:
部分文档作品中含有的国旗、国徽等图片,仅作为作品整体效果示例展示,禁止商用。设计者仅对作品中独创性部分享有著作权。
- 关 键 词:
- 基于 无线 传感器 网络技术 运输 网络 智能 引导 控制系统 中英文 翻译
![提示](https://www.deliwenku.com/images/bang_tan.gif)
限制150内