外文翻譯---基于無(wú)線傳感器網(wǎng)絡(luò)技術(shù)的運(yùn)輸網(wǎng)絡(luò)智能引導(dǎo)及控制系統(tǒng)（節(jié)選）

1、<p>　　1500單詞，8300英文字符，2800漢字</p><p>　　出處：International Conference on Computer and Information Technology. IEEE Computer Society, 2005:810-814.</p><p><b>　　英文原文</b></p>&l

2、t;p>　　An Intelligent Guiding and Controlling System for Transportation Network Based on Wireless Sensor Network Technology</p><p>　　C Wenjie ， G Liqiang ， C Zhilei ， C Zhangl

3、ong ， T Shiliang</p><p><b>　　Abstract</b></p><p>　　This paper proposes architecture based on Wireless Sensor Network (WSN) technology for Intelligent Transportation System

4、(ITS) of a transportation</p><p>　　network. With the help of WSN technology, the traffic info of the network can be accurately measured in real time. Based on this architecture, an optimization algorithm is

5、proposed to minimize the average travel time for the vehicles in the network. Compared to randomly-chosen algorithm, simulation results show that the average speed of the road network is significantly improved by our alg

6、orithm, and thus improve the efficiency of the road network. Some extended applications of the proposed WSN </p><p>　　1. Introduction</p><p>　　Transportation plays an important role in our moder

7、n society. How to efficiently exploit the transportation capacity of the existing transportation infrastructure receives a lot of attention from the researchers across the world. The Intelligent Transportation System (IT

8、S) has been proposed by many researchers to solve the problem.</p><p>　　ITS comprises of three main sub-systems. They are surveillance sub-system, analysis and strategy subsystem and execution sub-system. Th

9、e execution subsystem can be a traffic control sub-system, a vehicle guiding sub-system, or a navigation sub-system. </p><p>　　The surveillance sub-system measures the traffic information such as the vehicle

10、's location, speed, 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].&l

11、t;/p><p>　　The analysis and strategy sub-system optimizes the traffic flows based on the measurements from the surveillance sub-system. Various algorithms are proposed for this purpose, some typical examples fo

12、llow. 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 contr

13、ol algorithm to optimize the congestion length of the whole transportation networ</p><p>　　The control sub-system controls the signal lights on the intersection. The guiding sub-system provides the real-time

14、 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

15、 the vehicle.</p><p>　　One shortage of the systems mentioned above 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 monito

16、r and measure the traffic status dynamically in real time, an efficient traffic control will be easier to realize.</p><p>　　With the development of microelectronic and computer technologies, the low-power-co

17、nsumption, low-cost and relatively powerful wireless sensor network (WSN) technology has been applied in many areas[7-9]. However, the application of WSN in the traffic control system is rarely documented. In [10], we pr

18、oposed a WSN-based system for an efficient traffic control in an isolated road intersection. This paper extends our previous work to a transportation network. A WSN-based traffic control, guiding, </p><p>　　

19、The rest of this paper is organized as follows: Section 2 describes the structure of the proposed WSN-based traffic control system. Section 3 describes the optimization algorithm for the traffic network. The simulation r

20、esults and some discussions are presented in Section 4. Finally, Section 5 concludes this paper.</p><p>　　2. System Structure</p><p>　　2.1. WSN Module</p><p>　　WSN module is a basic

21、 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

22、the signal. Also it receives, decodes and demodulates the signal as well. MCU integrates processor and memories, where the programs resides and executes. The Power Supply supplies the power to entire module.</p>&

23、lt;p>　　In the proposed system, WSN modules are widely distributed on vehicles, roadsides and intersections to collect, transfer and analyze the traffic information. See section 2.3 for details.</p><p>　　2

24、.2. Urban Traffic Network</p><p>　　Several different facilities are installed in the urban traffic network to perform their specific functions. For example, the Signal Lights are installed in the road inters

25、ection to directly control the vehicle through the intersection; the Variable Message Sign (VMS) is set up along the road side to help drivers to select the optimal route; the Navigation system (electronic-map and satell

26、ite-based positioning system) is installed in the vehicle for vehicle locating and navigation.</p><p>　　The target of an ITS is to optimize the traffic in a transportation network by controlling the signal l

27、ights in the intersections, by providing the accurate traffic information in the VMS, or by selecting the best route in the e-map.</p><p>　　To perform the traffic control, below, we shall first have a look a

28、t the configuration of the transportation network. Then, some parameters are introduced to describe traffic information in the network. By optimizing these parameters, the proposed optimization algorithm is expected to o

29、ptimize the traffic in the transportation network.</p><p>　　As a example of a real-life traffic network, Fig. 2 illustrates the road net of Fukuyama city [11]. On the figure some parameters such as the link

30、length, lane numbers, and legal speed are marked on it.</p><p>　　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 In

31、tersection can be described by 2 parameters: 1) the phase 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 p

32、arameters, i.e., the link length, lane numbers (include every turningdirection), mean speed, vehicle number. A Vehicle can be described by</p><p>　　Among these parameters, 1) some are fixed, such as the lane

33、 numbers and link length; 2) some are 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 l

34、ight and the next link selected by a vehicle.</p><p>　　The vehicle velocity, direction, and the number of the vehicles are the basic variables of the whole system. It is the main task of our algorithm to opt

35、imize these parameters.</p><p>　　2.3. Data Collection and Transferring</p><p>　　As illustrated in Fig. 3, there are 3 types of WSN nodes installed in our system, i.e., the vehicle unit on the in

36、dividual vehicle; the roadside unit along both sides of the road; and the intersection unit on the intersection.</p><p>　　The main function of intersection unit is to receive and analyze the information from

37、 other units to control the signal light. The main function of roadside unit is to gather the information of the vehicles around, and transfer it to the intersection unit. (Roadside units are installed on the lamp posts

38、along both sides of the road every 50~200m according to the wireless cover range.) The main function of the vehicle unit is to measure the vehicle parameters and transfer them to the roadside uni</p><p>　　Ro

39、adside units broadcast messages every second. A message includes the ID of the roadside unit and its relative location to the intersection (xB, yB). Normally, vehicle unit is in the listening state. When a vehicle comes

40、into the broadcast range of the roadside units and receives the broadcasted message, the vehicle unit switches to the active state. According to the wireless locating method [12;13], if a vehicle unit receives messages f

41、rom more than three nodes, it can calculate its location (</p><p>　　Based on the (x, y, v) from the vehicles, the roadside unit can calculate the mean speed of the vehicles in its scope. The roadside then tr

42、ansfers the calculated information to the intersection unit.</p><p>　　After receiving the messages from the four directions, the intersection unit analyzes the information and makes the decision to control t

43、he signal light, or to send navigate information to the vehicle.</p><p>　　3. Optimization Algorithm for Traffic Network</p><p>　　3.1 Optimization Target</p><p>　　From the point view

44、 of the whole transportation network, the objective of the proposed ITS is to improve the use efficiency of the network, maximize the mean speed of the whole road network, and reduce the traffic congestions and accidents

45、. From the view of an individual driver or passenger, the objective is to arrive at the destination safely with a minimum cost. The cost may be route length, fuel used, payment for taxi, or time spent. Clearly, the minim

46、um length from the origination to the des</p><p><b>　　中文譯文</b></p><p>　　基于無(wú)線傳感器網(wǎng)絡(luò)技術(shù)的運(yùn)輸網(wǎng)絡(luò)智能引導(dǎo)及控制系統(tǒng)</p><p>　　摘要：這篇論文基于運(yùn)輸網(wǎng)絡(luò)的智能運(yùn)輸系統(tǒng)（ITS）的無(wú)線傳感器網(wǎng)絡(luò) (WSN) 技術(shù)提出一種結(jié)構(gòu)。由于WSN技術(shù)的支持, 交

47、通網(wǎng)絡(luò)信息能實(shí)時(shí)正確地測(cè)量出來(lái)?；谶@一個(gè)結(jié)構(gòu),提出一個(gè)最優(yōu)化算法能將交通網(wǎng)絡(luò)平均車(chē)流量減到最低。與隨機(jī)選擇算法相比, 我們的算法摹擬出來(lái)的結(jié)果顯示交通網(wǎng)絡(luò)的公路平均速度和效率有了明顯地改善。許多關(guān)于這個(gè)被提出WSN系統(tǒng)的應(yīng)用也有很好的效果。</p><p><b>　　1．介紹</b></p><p>　　交通運(yùn)輸在我們現(xiàn)代的社會(huì)扮演著重要角色。該如何有效率地開(kāi)發(fā)現(xiàn)

48、有運(yùn)輸系統(tǒng)各部分的運(yùn)輸容量已經(jīng)受到許多國(guó)際上研究員的關(guān)注。而這些研究員都認(rèn)為這個(gè)智能運(yùn)輸系統(tǒng)（ITS）能解決當(dāng)前的問(wèn)題。</p><p>　　ITS包含三個(gè)主要的子系統(tǒng)。他們是偵測(cè)子系統(tǒng)，分析和策略子系統(tǒng)和運(yùn)行子系統(tǒng)。運(yùn)行子系統(tǒng)可以描述為一個(gè)流量控制的子系統(tǒng)，或者是載體的引導(dǎo)子系統(tǒng) , 或者是一個(gè)導(dǎo)航子系統(tǒng)。</p><p>　　偵測(cè)子系統(tǒng)使用確定的傳感器, 運(yùn)用歸納的回路 [1] 或超聲

49、納感應(yīng)器 [2]的方法測(cè)量交通網(wǎng)絡(luò)流量信息，例如是載體位置，速度，交通系統(tǒng)中的車(chē)輛數(shù)等等。同時(shí)，一種以視頻分析為基礎(chǔ)的新方法在迅速發(fā)展 [1;3].</p><p>　　分析和策略子系統(tǒng)根據(jù)偵測(cè)子系統(tǒng)的測(cè)量值來(lái)優(yōu)化交通系統(tǒng)。為了這個(gè)目的，提出了各種不同的算法和一些典型的例子，例如Papageorgiou。在[4]中，摘要關(guān)于一些固定時(shí)間策略和流量回復(fù)策略方面的隔離策略和協(xié)調(diào)策略的工具; 在[5]中，例如Shimi

50、zu，提出了一個(gè)平衡的控制算法。該算法用于優(yōu)化整個(gè)交通網(wǎng)絡(luò)的車(chē)龍長(zhǎng)度。在[6]中,Di Febbraro提出一個(gè)混合的Petri網(wǎng)絡(luò)模型來(lái)確定十字路口的交通訊號(hào)燈調(diào)節(jié)問(wèn)題。</p><p>　　控制子系統(tǒng)控制十字路口交通訊號(hào)燈。導(dǎo)航子系統(tǒng)提供實(shí)時(shí)車(chē)流量信息讓司機(jī)選擇最好的路徑。導(dǎo)航子系統(tǒng)使用宇宙站信號(hào)，如全球定位，來(lái)定位特定的車(chē)輛,和藉由電子地圖的幫忙, 選擇那最佳的行車(chē)路線。</p><p&

51、gt;　　上面提到的系統(tǒng)的一個(gè)不足是傳感器只能在地圖內(nèi)定位一輛固定的車(chē)輛，但不能追蹤地圖外的車(chē)輛。很清楚地，如果我們能實(shí)時(shí)動(dòng)態(tài)地檢測(cè)并測(cè)量交通狀態(tài)，一個(gè)有效率的流量控制將會(huì)更容易地被人了解。</p><p>　　由于微電子和計(jì)算機(jī)技術(shù)的發(fā)展，耗電量低，廉價(jià)及有效的無(wú)線傳感器網(wǎng)絡(luò)(WSN)技術(shù)已經(jīng)在各個(gè)領(lǐng)域廣泛應(yīng)用[7-9]. 然而,WSN的在交通控制系統(tǒng)中的應(yīng)用卻很少被提起。在[10]中,我們?yōu)橐粋€(gè)有效的孤立十字

52、路口的交通控制提出了一個(gè)以WSN為基礎(chǔ)的系統(tǒng)。本論文把我們?cè)缦鹊墓ぷ餮由斓揭粋€(gè)交通運(yùn)輸網(wǎng)絡(luò)中，提出一個(gè)以WSN為基礎(chǔ)的交通控制，引導(dǎo)，及導(dǎo)航系統(tǒng)來(lái)優(yōu)化運(yùn)輸交通網(wǎng)絡(luò)。</p><p>　　本論文的其余部分以下列各項(xiàng)來(lái)組織：第2節(jié)描述這個(gè)以WSN為基礎(chǔ)的交通控制系統(tǒng)的結(jié)構(gòu)。第3節(jié)描述這個(gè)交通網(wǎng)絡(luò)的優(yōu)化算法。在第4節(jié)中，列出摹擬結(jié)果和一些值得討論的問(wèn)題。最后，第5節(jié)總結(jié)本論文。</p><p>

53、<b>　　2．系統(tǒng)結(jié)構(gòu)</b></p><p>　　2.1. WSN模型</p><p>　　圖1 本論文的一個(gè)用于WSN結(jié)點(diǎn)的模型結(jié)構(gòu)</p><p>　　WSN模型是我們交通控制系統(tǒng)的一個(gè)基本的元件。如圖1所示,一個(gè)WSN模型包含3個(gè)主要的元件，包括射頻(無(wú)線電頻率),MCU(微控制單元)和電源。射頻編碼,調(diào)制后發(fā)送信號(hào)。同時(shí)，它也接收

54、信號(hào), 解調(diào)后恢復(fù)信號(hào)。在程序常駐及運(yùn)行的地方，MCU整合了處理機(jī)和存儲(chǔ)器。電源提供能量給整個(gè)的模型。</p><p>　　在這個(gè)提出的系統(tǒng)中，WSN模型廣泛地分配到車(chē)輛，路傍和十字路口上，來(lái)收集,傳遞及分析交通信息。詳見(jiàn)第2.3節(jié)。</p><p>　　2.2. 城市交通網(wǎng)絡(luò)</p><p>　　一些不同的設(shè)備安裝在那城市的交通網(wǎng)絡(luò)中去執(zhí)行他們的特定功能。例如，安

55、裝在十字路口的交通燈直接地控制車(chē)輛經(jīng)過(guò)這個(gè)十字路口；多變的道路消息信號(hào)(VMS)沿著馬路兩旁設(shè)置以幫助司機(jī)選擇最佳的行車(chē)路徑；導(dǎo)航系統(tǒng)(電子地圖和以衛(wèi)星為基礎(chǔ)的定位系統(tǒng))安裝在車(chē)輛中為車(chē)輛提供定位和導(dǎo)航服務(wù)。</p><p>　　ITS的目標(biāo)是通過(guò)控制十字路口的交通信號(hào)燈，使用VMS提供的準(zhǔn)確交通信息，或是在電子地圖中選擇最佳行車(chē)路線來(lái)優(yōu)化運(yùn)輸網(wǎng)絡(luò)的交通狀況。</p><p>　　為了實(shí)現(xiàn)

56、交通控制，以下，首先我們了解一下運(yùn)輸網(wǎng)絡(luò)的配置。然后，認(rèn)識(shí)一些參數(shù)用于描述網(wǎng)絡(luò)的交通信息。通過(guò)優(yōu)化這些參數(shù)，提到的那個(gè)優(yōu)化算法將實(shí)現(xiàn)優(yōu)化那運(yùn)輸交通網(wǎng)絡(luò)的功能。</p><p>　　正如現(xiàn)實(shí)中交通網(wǎng)絡(luò)的例子,圖2，舉例說(shuō)明了Fukuyama城市的道路網(wǎng)絡(luò)[11]。在這個(gè)道路網(wǎng)絡(luò)中的道路參數(shù)，如車(chē)龍長(zhǎng)度,小路數(shù)目,以及合法的速度在圖2上作上記號(hào)。</p><p>　　圖2、在Fukuyama車(chē)

57、站的交通網(wǎng)絡(luò)圖(引證于[11])</p><p>　　在這本論文中，我們考慮的交通系統(tǒng)包含3中類(lèi)型的基本元件,那就是,十字路口(N), 道路連接(L)和車(chē)輛(V)。一個(gè)十字路口能用兩個(gè)參數(shù)描述：1） 狀態(tài)類(lèi)型(同一時(shí)間內(nèi)通過(guò)十字路口的不同方向上車(chē)輛數(shù)的狀態(tài))；2)每一個(gè)狀態(tài)的持續(xù)時(shí)間。 一條連接可以用4個(gè)參數(shù)來(lái)描述，那是，連接長(zhǎng)度，馬路數(shù)目(包括每一個(gè)轉(zhuǎn)角方向)，平均速度, 車(chē)輛數(shù)目。車(chē)輛能用5個(gè)參數(shù)來(lái)描述，他們

58、是: 1)車(chē)輛的位置，2)車(chē)輛速度，3)起始點(diǎn)，4)目的地，5)行車(chē)路程,6)總時(shí)間和7)行駛平均速度。</p><p>　　在這些參數(shù)中，1)一些是固定的,例如馬路數(shù)和連接長(zhǎng)度; 2) 一些是由偵測(cè)子系統(tǒng)測(cè)量, 例如相對(duì)速度,在一個(gè)連接上的車(chē)輛數(shù); 3)一些是可以用優(yōu)化算法設(shè)定,例如那十字路口的交通燈信號(hào)和車(chē)輛選擇的下一個(gè)道路。</p><p>　　車(chē)輛的速度，方向，和車(chē)輛數(shù)量全部都是系

59、統(tǒng)的基本變量。我們的算法的主要任務(wù)是優(yōu)化這些叁數(shù)。</p><p>　　2.3. 數(shù)據(jù)收集與傳遞</p><p>　　如圖3所示，在我們的系統(tǒng)中安裝有3種不同類(lèi)型的WSN結(jié)節(jié)，那就是，在個(gè)別車(chē)輛的車(chē)輛單元；馬路兩旁的路邊單位；和十字路口上的十字路口單位。</p><p>　　圖3 十字路口單位(A)，路邊單位(B)和車(chē)輛單位(C)，以及他們所在公路網(wǎng)絡(luò)的十字路口&l

60、t;/p><p>　　十字路口單位的主要功能是接收并分析來(lái)自其他單位的信息來(lái)控制交通燈。路邊單位的主要功能是收集這附近的車(chē)輛信息,和把它傳送到十字路口單位。(路邊單位是在交通燈上沿著馬路兩旁每50~200米安裝一個(gè)，因?yàn)槠錈o(wú)線覆蓋距離為50~200米)。車(chē)輛單位的主要功能是測(cè)量車(chē)輛參數(shù)并且把他們傳送到路邊單位(車(chē)輛單位是安裝在每一輛車(chē)當(dāng)中的)。那十字路口單位，路傍單位和車(chē)輛單位是</p><p&g

61、t;<b>　　圖3的A，B和C。</b></p><p>　　路邊單位每秒發(fā)送一次信息。該信息包括路邊單位的身份認(rèn)證和它到十字路口的相對(duì)位置(xB,yB)。正常地,車(chē)輛單位是在處于接收狀態(tài)。當(dāng)一輛汽車(chē)進(jìn)入路邊單位的廣播范圍，同時(shí)接收到廣播的信息，車(chē)輛單位就會(huì)進(jìn)入活躍狀態(tài)。依照無(wú)線定位方法[12;13]，如果一個(gè)車(chē)輛單位接收來(lái)自超過(guò)三個(gè)結(jié)點(diǎn)的信息，就能計(jì)算出它的位置(x,y)和速度v。之后,

62、車(chē)輛單位就會(huì)發(fā)送信息(x，y，v)給附近路邊單位。</p><p>　　基于這個(gè)來(lái)自車(chē)輛的信息(x，y，v)，路邊單位就能計(jì)算出在它附近的車(chē)輛的預(yù)期速度。然后，馬路兩旁就會(huì)傳送這個(gè)結(jié)果到十字路口單位。</p><p>　　在接收到來(lái)自四個(gè)方向的信息之后，十字路口單位就會(huì)分析這些信息并且定出交通燈信號(hào)控制方案，或者發(fā)送導(dǎo)航信息到車(chē)輛中。</p><p>　　3. 交通

63、網(wǎng)絡(luò)的優(yōu)化算法</p><p><b>　　3.1 優(yōu)化目標(biāo)</b></p><p>　　整個(gè)的交通網(wǎng)絡(luò)的其中一方面來(lái)看，提出的ITS目標(biāo)是改善網(wǎng)絡(luò)的使用效率，提高整個(gè)的交通網(wǎng)絡(luò)的行駛速度，而且減少交通阻塞和意外事件。從一位個(gè)別的司機(jī)或乘客來(lái)看，該目標(biāo)是以最小的代價(jià)安全地到達(dá)目的地。其代價(jià)可認(rèn)為是車(chē)程，使用的燃料，出租汽車(chē)的費(fèi)用，或者是耗時(shí)。清晰地，從始發(fā)地到目的地的