基于無線傳感器網(wǎng)絡技術(shù)的運輸網(wǎng)絡智能引導及控制系統(tǒng)中英文翻譯

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 vehicle's location,

6、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.the analysis and strategy sub-system optimizes the traffic flows based on the measurements from the surve

7、illance 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 bal

8、ance 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-

9、system 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

10、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 monitor and measure the traffic status dynamically in real time, an efficient traffic control will be easier to realize.with the development of microelectronic

11、and computer 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 efficien

12、t traffic 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

13、describes 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 modu

14、le is 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

15、 well. 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. se

16、e section 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 variabl

17、e message 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 transport

18、ation 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

19、parameters 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 cit

20、y 11. 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) th

21、e 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 parameters, i.e., the link length, lane numbers (include every turningdirection), mean speed, vehicle number. a vehicle can be desc

22、ribed 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) so

23、me 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 light and the next link selected by a vehicle.the vehicle velocity, direction, and the number of the vehicles ar

24、e the 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 alon

25、g both sides of the road; and the intersection unit on the intersection.the main function of intersection unit is to receive and analyze the information from other units to control the signal light. the main function of roadside unit is to gather the information of the vehicles around, and transfer

26、it to the intersection unit. (roadside units are installed on the lamp posts along both sides of the road every 50200m 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 units. (vehicle unit is installe

27、d in every vehicle.) the intersection unit, roadside units and vehicle units are denoted as a, b and c in fig. 2.roadside 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 lis

28、tening state. when a vehicle comes 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 from more than three nodes, it can calculate its

29、 location (x, y) and velocity v. after that, the vehicle unit sends the information (x, y, v) to the roadside unit nearby.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 transfers the calculated information to t

30、he intersection unit.after receiving the messages from the four directions, the intersection unit analyzes the information and makes the decision to control the signal light, or to send navigate information to the vehicle.3. optimization algorithm for traffic network3.1 optimization targetfrom the p

31、oint view 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. from the view of an individual driver or passenger, the objective is

32、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 minimum length from the origination to the destination is a static problem, and is out of our discussion. in this paper, we only consider the minimum-travel

33、-time algorithm. that is, the purpose of our optimization algorithm is to minimize the travel time that a vehicle drives from the origination to the destination.3.2 minimum travel time optimization algorithmthe travel time of a vehicle comprises the running time on the road and the waiting time for

34、the green light at the intersection. for the ease of discussion, the following a few denotations are defined.node: the intersection. it is denoted as ni.(i=0,1,2 )link: the road from an intersection ni to a successive intersection nj. its denoted as li,j. link is one-way.say, lijl,ij.total travel ti

35、me (ttt): the total time spent while a vehicle travels from the origination to the destination along a specified route.link travel time (ltt): the time spent while a vehicle travels from a node to the other node along the link.link average velocity (lav): the average velocity of all the running vehi

36、cles in the link.waiting green-light time (wgt): the time elapsed when a vehicle or a queue waits the right-to-go phase in the front of an intersection. the parameter of wgt includes node, incoming link, outgoing link, and the time when the vehicle reach the intersection. so it can be denoted as wgt

37、(node,lin,lout,time).total travel length (ttl): the total route length that a vehicle traveled.the basic idea of the optimization algorithm is that: before we choose the next link to ride, we firstly predict the time cost of the candidate routes. the route with the minimum cost is then chosen as the

38、 best route. in order to predict the total time cost, we should know the travel time in all links to pass and the waiting time before every intersection.lets see a simple situation. as shown in fig.3, the current time is ; a vehicle c is running on link l1,4 with velocity v; and the destination is n

39、8. then, there are two routes with the approximate length:the total travel time of (ttt()can be calculated as follow:ttt() can be calculated similarly. after that, the path with the minimum ttt is selected.from above algorithm, we can see that ttt is related to link length, d, v and lav(+ t2). link

40、length is fixed; d and v can be detected by the method presented in section 2.3. now, the question is how can we get lav(+ t2)?in 11, the author uses legal velocity to estimate the link average velocity. in 14, the author assumes that if the link is not congested, then the velocity is a constant (sa

41、y, the legal velocity), otherwise, the velocity is zero.in fact, the average velocity of a link is also related to the number of vehicles running on it, or the congestion grade since the vehicle should keep a safe distance between each other. we can construction a function between the average veloci

42、ty and the vehicle number (vn) based on surveillance. thus, if we know the vehicle number on a link, we can get the lav of it.since the system know the target and previous chosen route, it can compute the vehicle number in the special link at time + t2 -1, i.e., vn(l,+ t2 -1).then , we can get lav(l

43、, ,+ t2). so the ttt of a special route can be calculated.4. simulation result and discussionsto demonstrate the effect of the proposed algorithm, some simulations are conducted in the pc using the data of a real urban road network which is reported in 11.the road network is illustrated in fig. 2. v

44、ehicles appear in this network in a random origination to a random destination. the incoming vehicles of the entire network are recorded every 15 minutes, which are illustrated in fig. 5(a).in our algorithm, the mean speed (ms) of the entire road network is calculated, which is defined as follows:wh

45、ere, v is the vehicles that reach the destination in the time period.fig.5 (b) presents the result, curve a indicates the optimized route. as a contrast, curve b represents the results of a randomly-chosen route among several routes with approximately equal length.the proposed wsn system can also be

46、 used for many other transportation applications to improve their efficiency. for examples: 1) a “green wave” along the route of important emergent cars will be easier to implement; 2) parking management will be smarter; 3) electronic toll collection (etc) system can be improved from multilane 15 to

47、 free lane, without any tollgate to limit the vehicle stream. some more complicated functions, such as asymmetric signal phase control and automatic “tide wave” control.the wsn system can also be used as a dual communication network. it can be used for the management center to track and schedule the

48、 vehicles such as taxis, buses and freight carriers.5. conclusionin this paper, a wsn-based architecture is presented for its of a transportation 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 optimiza

49、tion algorithm is proposed to minimize the average travel time for the vehicles in the network. compared to the randomlychosen algorithm, simulation results show that the average speed of the road network is significantly improved by our algorithm, and thus improve the efficiency of the road network

50、. some extended applications of the proposed wsn system is discussed as well.中文譯文基于無線傳感器網(wǎng)絡技術(shù)的運輸網(wǎng)絡智能引導及控制系統(tǒng)摘要：這篇論文基于運輸網(wǎng)絡的智能運輸系統(tǒng)（its）的無線傳感器網(wǎng)絡 (wsn) 技術(shù)提出一種結(jié)構(gòu)。由于wsn技術(shù)的支持, 交通網(wǎng)絡信息能實時正確地測量出來。基于這一個結(jié)構(gòu),提出一個最優(yōu)化算法能將交通網(wǎng)絡平均車流量減到最低。與隨機選擇算法相比, 我們的算法摹擬出來的結(jié)果顯示交通網(wǎng)絡的公路平均速度和效率有了明顯地改善。許多關(guān)于這個被提出wsn系統(tǒng)的應用也有很好的效果。1介紹交通運輸在我們現(xiàn)

51、代的社會扮演著重要角色。該如何有效率地開發(fā)現(xiàn)有運輸系統(tǒng)各部分的運輸容量已經(jīng)受到許多國際上研究員的關(guān)注。而這些研究員都認為這個智能運輸系統(tǒng)（its）能解決當前的問題。its包含三個主要的子系統(tǒng)。他們是偵測子系統(tǒng)，分析和策略子系統(tǒng)和運行子系統(tǒng)。運行子系統(tǒng)可以描述為一個流量控制的子系統(tǒng)，或者是載體的引導子系統(tǒng) , 或者是一個導航子系統(tǒng)。偵測子系統(tǒng)使用確定的傳感器, 運用歸納的回路 1 或超聲納感應器 2的方法測量交通網(wǎng)絡流量信息，例如是載體位置，速度，交通系統(tǒng)中的車輛數(shù)等等。同時，一種以視頻分析為基礎(chǔ)的新方法在迅速發(fā)展 1;3.分析和策略子系統(tǒng)根據(jù)偵測子系統(tǒng)的測量值來優(yōu)化交通系統(tǒng)。為了這個目的，提出

52、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)于一些固定時間策略和流量回復策略方面的隔離策略和協(xié)調(diào)策略的工具; 在5中，例如shimizu，提出了一個平衡的控制算法。該算法用于優(yōu)化整個交通網(wǎng)絡的車龍長度。在6中,di febbraro提出一個混合的petri網(wǎng)絡模型來確定十字路口的交通訊號燈調(diào)節(jié)問題?？刂谱酉到y(tǒng)控制十字路口交通訊號燈。導航子系統(tǒng)提供實時車流量信息讓司機選擇最好的路徑。導航子系統(tǒng)使用宇宙站信號，如全球定位，來定位特定的車輛,和藉由電子地圖的幫忙, 選擇那最佳的行車路線。上面提到的系統(tǒng)的一個不足是傳感器只能在地圖內(nèi)定位一輛固定的車輛，但不能追蹤地圖外

53、的車輛。很清楚地，如果我們能實時動態(tài)地檢測并測量交通狀態(tài)，一個有效率的流量控制將會更容易地被人了解。由于微電子和計算機技術(shù)的發(fā)展，耗電量低，廉價及有效的無線傳感器網(wǎng)絡(wsn)技術(shù)已經(jīng)在各個領(lǐng)域廣泛應用7-9. 然而,wsn的在交通控制系統(tǒng)中的應用卻很少被提起。在10中,我們?yōu)橐粋€有效的孤立十字路口的交通控制提出了一個以wsn為基礎(chǔ)的系統(tǒng)。本論文把我們早先的工作延伸到一個交通運輸網(wǎng)絡中，提出一個以wsn為基礎(chǔ)的交通控制，引導，及導航系統(tǒng)來優(yōu)化運輸交通網(wǎng)絡。本論文的其余部分以下列各項來組織：第2節(jié)描述這個以wsn為基礎(chǔ)的交通控制系統(tǒng)的結(jié)構(gòu)。第3節(jié)描述這個交通網(wǎng)絡的優(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題。最后，第5節(jié)總結(jié)本論文。2系統(tǒng)結(jié)構(gòu)2.1. wsn模型圖1 本論文的一個用于wsn結(jié)點的模型結(jié)構(gòu)wsn模型是我們交通控制系統(tǒng)的一個基本的元件。如圖1所示,一個wsn模型包含3個主要的元件，包括射頻(無線電頻率),mcu(微控制單元