TWI584238B - Optimization Method of Vehicle Coordinated Object Location and Vehicle Coordinate Location Device - Google Patents
Optimization Method of Vehicle Coordinated Object Location and Vehicle Coordinate Location Device Download PDFInfo
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Description
本創作是一種物體定位方法,特別是指一種協同式物體定位(Cooperative positioning)優化方法。 This creation is an object positioning method, especially a cooperative object positioning (Cooperative positioning) optimization method.
在車輛中配置感測器(sensor)以偵測周圍環境的相關技術已發展許久,例如使用全球定位系統(GPS)、雷達(RADAR)、光達(LIDAR)、行車紀錄器等不同感測器可提供多元的環境資訊。但是對車輛本身而言,透過環境資訊感測器所取得的環境資訊仍會受到許多因素的限制,舉例而言,請參考圖9所示,在十字路口的環境中,行駛在縱向車道的第一車輛101可得知該方向之環境資訊,例如可看到有物體200(如行人、車輛、動物)正快速衝出路口,但對於在橫向車道的第二車輛102而言,因受限於其所在位置可能受周圍建築物遮蔽而產生盲點,即使第二車輛102上具有感測器,但仍無法察覺該物體200的突發情況而與其撞擊。因此,若僅單獨依據車輛本身的感測器提供環境資訊,在實際應用時仍存在有盲點。 Related technologies for configuring sensors in vehicles to detect the surrounding environment have been developed for a long time, such as using different sensors such as Global Positioning System (GPS), Radar (RADAR), LIDAR, and Travel Recorder. Provide diverse environmental information. However, for the vehicle itself, the environmental information obtained through the environmental information sensor will still be limited by many factors. For example, please refer to Figure 9, in the environment of the intersection, in the longitudinal lane A vehicle 101 can know the environmental information of the direction. For example, it can be seen that an object 200 (such as a pedestrian, a vehicle, or an animal) is rapidly rushing out of the intersection, but for the second vehicle 102 in the lateral lane, it is limited by The location thereof may be obscured by surrounding buildings to create a blind spot, even if the second vehicle 102 has a sensor, it is still unable to detect the sudden occurrence of the object 200 and collide with it. Therefore, if the environmental information is provided solely on the basis of the sensor of the vehicle itself, there is still a blind spot in actual application.
為此,車輛協同式定位方法遂發展出來,協同式的概念係表示透過周圍其鄰車輛或周圍的感測裝置(例如路側感測單元(Road side unit),RSU)分享各自感測到的資訊,使本車接收其它車輛的資訊而擴增自己的感測範圍,沿用上述圖9的例子說明,若該第二車輛102可接收該第一車輛提供的資訊,便可得知其右方路口將有物體突然出現,有足夠的時間緊急應變。 To this end, the vehicle cooperative positioning method has been developed. The concept of collaborative design means sharing the information sensed by surrounding neighboring vehicles or surrounding sensing devices (such as the road side unit, RSU). Having the vehicle receive information of other vehicles and amplifying its own sensing range. According to the example of FIG. 9 above, if the second vehicle 102 can receive the information provided by the first vehicle, the right intersection can be known. Some objects will suddenly appear and there will be enough time for emergency response.
然而目前協同式定位技術係面臨準確性不佳的技術缺點,請參考圖10所示範例,第一車輛101表示本車,第二車輛102~第四車輛104表示鄰近的其它車輛。以第二車輛102而言,其配備有一商用GPS及一攝影機,而一般商 用GPS的定位誤差約為5~15公尺,攝影機的定位誤差約為5公尺,因此,該第二車輛102利用自身GPS所測得之自身位置具有一GPS誤差範圍A1,第二車輛102利用攝影機感測到第三車輛103之所在位置時,由攝影機所測得之第三車輛103位置具有一攝影機誤差範圍A2;因此,若第二車輛102將其感測到之第三車輛的位置資訊轉傳分享給第一車輛101時,第一車輛101所接收到的第三車輛103的位置資訊即有誤差累積的問題,如GPS及攝影機累加誤差範圍A3所示。 However, the current collaborative positioning technology is faced with technical disadvantages of poor accuracy. Referring to the example shown in FIG. 10, the first vehicle 101 represents the vehicle, and the second vehicle 102 to the fourth vehicle 104 represent other vehicles in the vicinity. In the case of the second vehicle 102, it is equipped with a commercial GPS and a camera, and the general business The positioning error of the GPS is about 5 to 15 meters, and the positioning error of the camera is about 5 meters. Therefore, the second vehicle 102 has a GPS error range A1 measured by its own GPS, and the second vehicle 102 When the position of the third vehicle 103 is sensed by the camera, the position of the third vehicle 103 measured by the camera has a camera error range A2; therefore, if the second vehicle 102 senses the position of the third vehicle When the information transfer is shared to the first vehicle 101, the position information of the third vehicle 103 received by the first vehicle 101 has a problem of error accumulation, as indicated by the GPS and camera accumulation error range A3.
再進一步而言,若第一車輛101將該筆第三車輛103的位置資訊二度轉傳分享給第四車輛104時,將會再進一步加上第一車輛101自身的位置誤差,導致第四車輛104所接收之位置資訊產生更多的累積誤差量。因此,當資訊經過多次的轉傳分享後,對物體的定位準確性將會顯著下降,甚至不具參考價值。 Further, if the first vehicle 101 transmits the position information of the third vehicle 103 twice to the fourth vehicle 104, the position error of the first vehicle 101 itself is further added, resulting in the fourth vehicle. The position information received by the vehicle 104 produces a greater amount of accumulated error. Therefore, when the information is transferred and shared many times, the accuracy of positioning the object will be significantly reduced, and even has no reference value.
鑑於既有協同式定位技術存在有位置資訊精確度不佳的問題,本創作之主要目的是提供一種車輛協同式物體定位優化方法,以擴增車輛的感範圍、提高位置資訊的精準度而提升車輛行駛的安全性。 In view of the problem that the existing collaborative positioning technology has poor positional information accuracy, the main purpose of this creation is to provide a vehicle coordinated object positioning optimization method, which can enhance the sensing range of the vehicle and improve the accuracy of the position information. The safety of the vehicle.
為達到前述目的,本發明之方法係利用一設置在本車內部之協同定位裝置執行,該方法包含有:由本車接收一資訊封包,該資訊封包中包含一鄰車提供的一鄰車車輛原始座標及至少一物體原始座標,該鄰車車輛原始座標及該物體原始座標分別具有各自之定位精準度;對該鄰車車輛原始座標及該物體原始座標進行時間延遲補償,以分別得到鄰車補償後的一車輛補償座標及一物體補償座標;執行一優化程序,其包含: 比對本車的一本車車輛原始座標與鄰車的該車輛補償座標,判斷何者具有較高的定位精準度;優先對具有較高精準度的本車車輛原始座標或鄰車的該車輛補償座標進行一優化運算,再對具有較低定位精準度的本車車輛原始座標或鄰車的該車輛補償座標進行優化運算,其中,該優化運算執行:a)根據本車的本車車輛原始座標與鄰車的車輛補償座標計算出複數個參考位置;及b)根據各參考位置之權重值,分別計算出一本車車輛優化座標及一鄰車車輛優化座標;對物體座標進行優化,係比較鄰車的該鄰車車輛原始座標及鄰車車輛優化座標之間的第一差異量,依據該第一差異量對鄰車提供之物體補償座標進行補償以得到一第一物體優化座標;並比較本車的本車車輛原始座標及本車的本車車輛優化座標之間的第二差異量,依據該第二差異量對本車提供之物體座標進行補償以得到一第二物體優化座標。 To achieve the foregoing objective, the method of the present invention is performed by a co-location device disposed inside the vehicle, the method comprising: receiving, by the vehicle, an information packet, the information packet including an adjacent vehicle provided by an adjacent vehicle. The coordinates and the original coordinate of at least one object, the original coordinates of the adjacent vehicle and the original coordinates of the object respectively have respective positioning accuracy; the original coordinate of the adjacent vehicle and the original coordinate of the object are time-delayed to obtain the compensation of the adjacent vehicle respectively. a subsequent vehicle compensation coordinate and an object compensation coordinate; performing an optimization procedure comprising: Comparing the original coordinates of a vehicle of the vehicle with the compensation coordinates of the vehicle of the adjacent vehicle, determining which has higher positioning accuracy; prioritizing the original coordinate of the vehicle with higher precision or the compensation coordinate of the adjacent vehicle Perform an optimization operation, and then optimize the original coordinate of the vehicle with lower positioning accuracy or the vehicle compensation coordinate of the adjacent vehicle, wherein the optimization operation is performed: a) according to the original coordinates of the vehicle of the vehicle The vehicle compensation coordinates of the adjacent vehicle calculate a plurality of reference positions; and b) according to the weight values of the reference positions, respectively calculate an optimized coordinate of the vehicle and an optimized coordinate of the adjacent vehicle; optimize the coordinates of the object, and compare the adjacent coordinates The first difference between the original coordinate of the adjacent vehicle of the vehicle and the optimized coordinate of the adjacent vehicle, and the object compensation coordinate provided by the adjacent vehicle is compensated according to the first difference amount to obtain a first object optimization coordinate; a second difference between the original coordinate of the vehicle of the vehicle and the optimized coordinate of the vehicle of the vehicle, and the object seat provided to the vehicle according to the second difference amount The target is compensated to obtain a second object optimization coordinate.
藉由本創作的定位優化方法,可獲得本車及鄰車優化後的鄰車車輛優化座標、第一物體優化座標、本車車輛優化座標及第二物體優化座標,該優化後的座標可更加接近實際位置,有助於在行車過程中準確地判斷周圍環境的物體、車輛分佈狀態,提升車輛行駛的安全性。 With the positioning optimization method of the present invention, the optimized coordinates of the adjacent vehicle, the first object optimization coordinate, the vehicle optimization coordinate and the second object optimization coordinate of the vehicle and the adjacent vehicle can be obtained, and the optimized coordinates can be closer. The actual position helps to accurately determine the surrounding objects and vehicle distribution status during the driving process and improve the safety of the vehicle.
10‧‧‧車輛協同定位裝置 10‧‧‧Vehicle co-location device
11‧‧‧無線傳輸介面 11‧‧‧Wireless transmission interface
12‧‧‧延遲修正模組 12‧‧‧Delay correction module
13‧‧‧位置優化模組 13‧‧‧Location Optimization Module
14‧‧‧定位比對模組 14‧‧‧ Positioning comparison module
15‧‧‧車身感知器 15‧‧‧Body Sensor
21‧‧‧第一部分 21‧‧‧Part 1
22‧‧‧第二部分 22‧‧‧Part II
101‧‧‧第一車輛 101‧‧‧First vehicle
102‧‧‧第二車輛 102‧‧‧Second vehicle
103‧‧‧第三車輛 103‧‧‧ Third vehicle
104‧‧‧第四車輛 104‧‧‧fourth vehicle
200‧‧‧物體 200‧‧‧ objects
A1‧‧‧GPS誤差範圍 A1‧‧‧GPS error range
A2‧‧‧攝影機誤差範圍 A2‧‧‧ camera error range
A3‧‧‧GPS及攝影機累加誤差範圍 A3‧‧‧GPS and camera accumulator error range
H‧‧‧本車 H‧‧‧Car
R‧‧‧鄰車 R‧‧‧ neighboring car
H1~H4‧‧‧第一參考位置~第四參考位置 H1~H4‧‧‧first reference position~fourth reference position
R1‧‧‧基準位置 R1‧‧‧ reference position
M1~M4‧‧‧第一涵蓋範圍~第四涵蓋範圍 M1~M4‧‧‧First Coverage~Fourth Coverage
圖1:本創作協同定位裝置的架構方塊圖。 Figure 1: Architecture block diagram of the authoring co-location device.
圖2:本創作車輛協同式物體定位優化方法的流程圖。 Figure 2: Flow chart of the collaborative vehicle positioning optimization method for the author vehicle.
圖3:本創作BSM資料封包格式示意圖。 Figure 3: Schematic diagram of the BSM data packet format of this creation.
圖4:本創作對車輛原始位置執行時間延遲補償的示意圖。 Figure 4: Schematic diagram of the implementation of time delay compensation for the original position of the vehicle.
圖5:本創作位置優化模組所執行之優化程序流程圖。 Figure 5: Flow chart of the optimization program executed by the creative location optimization module.
圖6A:本創作取得第一參考位置H1的示意圖。 FIG. 6A is a schematic diagram of the first reference position H1 obtained by the present creation.
圖6B:本創作取得第一參考位置H2的示意圖。 FIG. 6B is a schematic diagram of the first reference position H2 obtained by the present creation.
圖6C:本創作取得第一參考位置H3的示意圖。 FIG. 6C is a schematic diagram of the first reference position H3 obtained by the present creation.
圖6D:本創作取得第一參考位置H4的示意圖。 FIG. 6D is a schematic diagram of the first reference position H4 obtained by the present creation.
圖7:本創作利用多個參考位置計算車輛優化座標之示意圖。 Figure 7: This creation uses a plurality of reference locations to calculate a schematic diagram of the vehicle's optimized coordinates.
圖8:本創作中多台車輛之資訊分享示意圖。 Figure 8: Schematic diagram of information sharing for multiple vehicles in this creation.
圖9:車輛行經交叉路口之示意圖。 Figure 9: Schematic diagram of a vehicle passing through an intersection.
圖10:協定式定位之誤差累積示意圖。 Figure 10: Schematic diagram of the cumulative error of the contracted positioning.
請參考圖1所示,本創作利用配備在各車輛上的一車身感知器15,包含GPS接收器及其它多種感測器,例如雷達、攝影機等設備取得本車座標與車輛周圍之環境資訊,並透過無線通訊技術將本車座標與環境資訊轉傳分享給周圍的鄰近車輛。因此,就任何一台車輛而言,係與周圍車輛進行接收及傳輸的雙向無線通訊。 Referring to FIG. 1 , the present invention utilizes a vehicle body sensor 15 provided on each vehicle, including a GPS receiver and various other sensors, such as radars, cameras, and the like to obtain environmental information of the coordinates of the vehicle and the surroundings of the vehicle. And through the wireless communication technology, the car coordinates and environmental information will be transferred to the surrounding neighboring vehicles. Therefore, in any vehicle, it is a two-way wireless communication that receives and transmits with surrounding vehicles.
本創作在車輛內部設置一車輛協同定位裝置10,該車輛協同定位裝置10包含有一無線傳輸介面11、一延遲修正模組12、一位置優化模組13及一定位比對模組14。該車輛協同定位裝置10係執行一車輛協同式物體定位優化方法,該方法如圖2所示,包含有以下步驟:S10:接收一資訊封包,該資訊封包中包含鄰車的一鄰車車輛原始座標及至少一物體原始座標以及該鄰車車輛原始座標與物體原始座標各自之定位精準度;S20:對該鄰車車輛原始座標及該物體原始座標進行時間延遲補償,以分別得到鄰車補償後的一車輛補償座標及一物體補償座標; S30:執行一優化程序;S40:座標比對融合。 The vehicle co-locating device 10 is disposed in the vehicle. The vehicle co-location device 10 includes a wireless transmission interface 11 , a delay correction module 12 , a position optimization module 13 , and a positioning comparison module 14 . The vehicle co-location device 10 performs a vehicle coordinated object positioning optimization method. The method includes the following steps: S10: receiving an information packet, where the information packet includes an adjacent vehicle original of the adjacent vehicle. Coordinates and at least one original coordinate of the object and the positioning accuracy of the original coordinates of the adjacent vehicle and the original coordinates of the object; S20: time delay compensation for the original coordinates of the adjacent vehicle and the original coordinates of the object, respectively, to obtain compensation for the adjacent vehicle respectively a vehicle compensation coordinate and an object compensation coordinate; S30: Perform an optimization procedure; S40: coordinate comparison fusion.
在步驟S10:該無線傳輸介面11負責本車與鄰車之間的資料雙向傳輸,在本實施例中是採用一短距無線通訊介面(DSRC),於車輛之間週期性地收發資料封包,資料封包格式是採用基本安全訊息(Basic Safety Message,BSM)封包,請參考圖3,該資料封包的訊息格式大致上包含一msgID欄位、第一部分21(Part I)及第二部分22(Part II),其中第一部分21係定義為必要資訊,包含基本的安全訊息內容,為每個資料封包必然包含的部分,但第二部分22為非必要部分(optional),可由使用者視應用需求將所需的資訊加入在第二部分22,屬於自行定義的範圍。 In step S10, the wireless transmission interface 11 is responsible for bidirectional transmission of data between the vehicle and the adjacent vehicle. In this embodiment, a short-range wireless communication interface (DSRC) is used to periodically send and receive data packets between vehicles. The data packet format is a Basic Safety Message (BSM) packet. Please refer to FIG. 3. The message format of the data packet generally includes a msgID field, a first part 21 (Part I), and a second part 22 (Part II), wherein the first part 21 is defined as the necessary information, including the basic security message content, and the part that is inevitably included for each data packet, but the second part 22 is optional, which can be viewed by the user depending on the application requirements. The required information is added to the second part 22, which is a self-defined range.
在BSM資料封包的第一部分21中,即必然存在有車輛的經緯度資訊,也就是車輛的原始座標,表示利用車輛內的GPS接收器所測得的本車位置。 In the first part 21 of the BSM data packet, there is necessarily a latitude and longitude information of the vehicle, that is, the original coordinates of the vehicle, indicating the position of the vehicle measured by the GPS receiver in the vehicle.
在BSM資料封包中的第二部分22中,本創作加入兩類資訊,第一類資訊為輸出該車輛原始座標的感測器種類(例如RTK、GPS)及該感測器的定位精準度。第二類資訊包含有物體(object)原始座標、產生該物體原始座標的感測器種類、或進一步包含該感測器的精準度,該物體原始座標是指利用本車之其它感測器(例如radar,lidar,camera等)感測本車以外的其它物體的資訊,該物體可能是車輛、行人、移動物或固定物等。各車輛可將本車的本車車輛原始座標與物體原始座標對外發送,供周圍鄰車利用;而本車同樣可接收來自周圍鄰車提供的車輛原始座標與物體原始座標。 In the second part 22 of the BSM data package, the author adds two types of information. The first type of information is the sensor type (such as RTK, GPS) that outputs the original coordinates of the vehicle and the positioning accuracy of the sensor. The second type of information includes the original coordinates of the object, the type of sensor that produces the original coordinates of the object, or the accuracy of the sensor. The original coordinate of the object refers to the use of other sensors of the vehicle ( For example, radar, lidar, camera, etc.) sense information about objects other than the vehicle, which may be vehicles, pedestrians, moving objects or fixtures. Each vehicle can send the original coordinates of the vehicle of the vehicle and the original coordinates of the object to the surrounding neighboring vehicles for use; and the vehicle can also receive the original coordinates of the vehicle and the original coordinates of the object provided by the surrounding neighboring vehicles.
在步驟S20:該延遲修正模組12透過該無線傳輸介面11接收鄰車傳輸出來的BSM資料封包,獲得鄰車的鄰車車輛原始座標與物體原始座標,此外,該位置優化模組13也進一步接收本車的感測器提供的各種感測結果,例如 車輛座標(GPS)、物體座標。該延遲修正模組12針對鄰車提供的鄰車車輛原始座標與物體原始座標進行時間延遲補償,請參考圖4所示,一第一車輛101表示本車,在其附近的一第二車輛102表示鄰車,當第一車輛101接收到第二車輛102發出的資料封包時,第一車輛101可根據紀錄在封包內的一封包發出時間及該第一車輛101本身接收到該封包時的一封包接收時間,計算出該封包發出時間及封包接收時間之間的一時間延遲量n。因為第二車輛102在送出封包後,仍持續行駛前進由原始位置PA到位置PB,因此第一車輛101所接收到的第二車輛102原始座標只是代表原始位置PA,而延遲修正模組12即根據該時間延遲量n推算第二車輛102所移動的一補償距離,加上該補償距離而得知即時位置PB,其推算公式可表示如下:PB=PA+V×n,其中,V代表第二車輛102的車速。 In step S20, the delay correction module 12 receives the BSM data packet transmitted by the adjacent vehicle through the wireless transmission interface 11, and obtains the original coordinate of the adjacent vehicle of the adjacent vehicle and the original coordinate of the object, and further, the position optimization module 13 further Receive various sensing results provided by the sensors of the vehicle, such as vehicle coordinates (GPS), object coordinates. The delay correction module 12 performs time delay compensation on the original coordinates of the adjacent vehicle and the original coordinate of the object provided by the adjacent vehicle. Referring to FIG. 4, a first vehicle 101 represents the vehicle, and a second vehicle 102 in the vicinity thereof. Representing an adjacent car, when the first vehicle 101 receives the data packet sent by the second vehicle 102, the first vehicle 101 may be based on a time when the packet is recorded in the packet and a time when the first vehicle 101 itself receives the packet. The packet receiving time calculates a time delay amount n between the packet sending time and the packet receiving time. Since the second vehicle 102 continues to travel forward from the original position P A to the position P B after the packet is sent out, the original coordinates of the second vehicle 102 received by the first vehicle 101 are only representative of the original position P A , and the delay correction mode The group 12 estimates a compensation distance moved by the second vehicle 102 according to the time delay amount n, and adds the compensation distance to know the instantaneous position P B , and the calculation formula can be expressed as follows: P B =P A +V×n Where V represents the vehicle speed of the second vehicle 102.
當延遲修正模組12推算出第二車輛102的即時位置PB,可根據兩位置PA、PB之補償距離,一併對第二車輛102提供的物體原始座標加入該補償距離。在鄰車車輛原始座標、物體原始座標都經過時間補償後,即分別得到一車輛補償座標及一物體補償座標,提供給該位置優化模組13進行後續處理。 When the delay correction module 12 estimates the instantaneous position P B of the second vehicle 102, the compensation distance can be added to the original coordinate of the object provided by the second vehicle 102 according to the compensation distance of the two positions P A , P B . After the original coordinate of the adjacent vehicle and the original coordinate of the object are time-compensated, a vehicle compensation coordinate and an object compensation coordinate are respectively obtained, and are provided to the position optimization module 13 for subsequent processing.
在步驟S30:該位置優化模組13接收到經時間補償後之鄰車的車輛補償座標及物體補償座標,並接收本車的本車車輛原始座標及本車的感測器測得之物體座標,並執行一優化程序如圖5所示,該優化程序包含有以下流程S31~S33: In step S30, the position optimization module 13 receives the vehicle compensation coordinate and the object compensation coordinate of the time-compensated adjacent vehicle, and receives the original coordinate of the vehicle of the vehicle and the object coordinates measured by the sensor of the vehicle. And executing an optimization program as shown in FIG. 5, the optimization program includes the following processes S31~S33:
S31:比較定位精準度,係比較本車的本車車輛原始座標與鄰車的車輛補償座標,判斷何者的精準度較高。舉例而言,若本車的本車車輛原始座標是利用一即時動態測量(RTK)裝置所得到的座標,而鄰車的車輛補償座標是利用一般GPS接收器接收,則可判斷RTK提供的座標具有較高精準度;又例如本車與鄰車皆是利用相同等級的GPS接收器提供座標,則可根據兩GPS信號 中的信任度來判斷何者精準度較高,例如根據GPS信號中包含的GGA訊息判斷兩GPS信號何者的信任度較高。 S31: Comparing the positioning accuracy, compare the original coordinates of the vehicle and the vehicle compensation coordinates of the adjacent car to determine which one has higher accuracy. For example, if the original coordinates of the vehicle of the vehicle are coordinates obtained by using a real-time dynamic measurement (RTK) device, and the vehicle compensation coordinates of the adjacent vehicle are received by a general GPS receiver, the coordinates provided by the RTK can be determined. With high precision; for example, the car and the neighboring car are all using the same level of GPS receiver to provide coordinates, then according to the two GPS signals The degree of trust is used to determine which one has higher accuracy. For example, according to the GGA message included in the GPS signal, it is judged whether the two GPS signals have higher trust.
S32:車輛定位優化,在判斷出本車的本車車輛原始座標與鄰車的車輛優化座標何者精準度較高後,將先針對精準度較高者進行優化運算,其次再對精準度較低者進行優化運算。無論是針對本車或鄰車的位置資訊進行優化運算,其作法是:a)根據本車的車輛原始座標與鄰車的車輛補償座標計算出複數個參考位置;b)根據各參考位置之權重值,分別計算出一本車車輛優化座標及一鄰車車量優化座標。 S32: Optimization of vehicle positioning. After judging whether the vehicle's original coordinates of the vehicle and the vehicle's optimized coordinates of the neighboring vehicle are higher in accuracy, the operator with higher accuracy will be optimized first, and then the accuracy will be lower. Perform optimization operations. Whether it is optimized for the position information of the vehicle or the neighboring car, the method is: a) calculating a plurality of reference positions according to the original coordinates of the vehicle and the vehicle compensation coordinates of the adjacent vehicle; b) weighting according to each reference position The value of each vehicle is calculated as an optimized coordinate of the vehicle and an optimized coordinate of the adjacent vehicle.
在本實施例中,係假設本車與鄰車皆配備有GPS接收器及其它感測器,並根據四個參考位置計算出車輛優化座標,且當判斷本車H的車輛座標與鄰車的車輛座標後,得知本車H的車輛座標具有較高的精準度,故以本車H為中心,優先對本車的本車車輛原始座標進行優化,其步驟詳述如後。首先,請參考圖6A所示,本車及鄰車分別以H、R表示,兩車可根據自身之GPS接收器得知自己的車輛座標,其中,本車H根據GPS接收器得知的車輛座標作為第一參考位置H1,該第一參考位置H1與本車H的實際位置有差異是因為GPS接收器之誤差量導致,鄰車R之GPS接收器感測出的車輛座標作為一基準位置R1。 In this embodiment, it is assumed that the vehicle and the adjacent car are equipped with a GPS receiver and other sensors, and the vehicle optimized coordinates are calculated according to the four reference positions, and when the vehicle coordinates of the vehicle H and the neighboring vehicles are judged After the coordinates of the vehicle, it is known that the vehicle coordinates of the vehicle H have a high degree of precision. Therefore, with the vehicle H as the center, the original coordinates of the vehicle of the vehicle are preferentially optimized, and the steps are as follows. First, please refer to FIG. 6A, the vehicle and the adjacent car are respectively represented by H and R, and the two vehicles can know their own vehicle coordinates according to their own GPS receivers, wherein the vehicle H is known according to the GPS receiver. The coordinate is used as the first reference position H1, and the difference between the first reference position H1 and the actual position of the vehicle H is caused by the error amount of the GPS receiver, and the GPS receiver sensed by the GPS receiver of the neighboring vehicle R serves as a reference position. R1.
請參考圖6B所示,鄰車R的感測器因為可感知本車H的存在,因此可得知鄰車R與本車H與之間的相對距離D1與相對角度θ1,即得知本車H的相對座標。鄰車R即以自已的基準位置R1為參考基準,根據距離D1及角度θ1將本車H的相對座標轉換為一經緯度座標,該經緯度座標即作為第二參考位置H2。由鄰車R發出的資料封包,即包含有該第二參考位置H2的經緯度座標。 Referring to FIG. 6B, the sensor of the neighboring vehicle R can know the existence of the vehicle H, so that the relative distance D1 between the neighboring vehicle R and the vehicle H and the relative angle θ1 can be known. The relative coordinates of the car H. The neighboring vehicle R converts the relative coordinates of the vehicle H into a latitude and longitude coordinate according to the distance D1 and the angle θ1 with the reference position R1 of the own vehicle as the reference reference, and the latitude and longitude coordinates serve as the second reference position H2. The data packet sent by the neighboring vehicle R, that is, the latitude and longitude coordinates of the second reference position H2.
請參考圖6C所示,本車H的感測器因為可感知鄰車R的存在,因此可得知本車H與鄰車R與之間的相對距離D2與相對角度θ2。本車H取得與鄰車R之間的相對距離D2及相對角度θ2之後,以鄰車R的基準位置R1作為參考基準反推出本車H的經緯度座標,可得到一第三參考位置H3。 Referring to FIG. 6C, the sensor of the vehicle H can know the relative distance D2 between the vehicle H and the neighboring vehicle R and the relative angle θ2 because the presence of the neighboring vehicle R can be perceived. After the vehicle H obtains the relative distance D2 and the relative angle θ2 from the neighboring vehicle R, the latitude and longitude coordinates of the vehicle H are reversely derived using the reference position R1 of the neighboring vehicle R as a reference reference, and a third reference position H3 is obtained.
請參考圖6D所示,鄰車R與本車H之間以無線信號傳輸資料封包,因此,可根據無線信號收、發之間的強度衰減程度,推估兩車之間的相對距離D3,例如鄰車R發射出的無線信號功率預設為-10dBi,而本車H接收到的無線信號功率己成為-30dBi,即顯示兩車之間的距離讓無線訊號衰減了20dBi,因為衰減幅度與距離成正比且可預先建立一衰減關係表,因此根據該20dBi的衰減量可推測或查表得知兩車之間的相對距離D3。另一方面,因為本車H與鄰車R利用GPS接收器測知的車輛座標為已知,即第一參考位置H1及基準位置R1均為已知,可根據兩位置之間的一直向延伸線推測出本車H相對於鄰車R的所在方向。因此,以鄰車R的基準位置R1為基準,根據相對距離D3及方向算出一第四參考位置H4。 Referring to FIG. 6D, the adjacent vehicle R and the vehicle H transmit data packets by wireless signals. Therefore, the relative distance D3 between the two vehicles can be estimated according to the intensity attenuation between the wireless signals. For example, the wireless signal power emitted by the neighboring vehicle R is preset to -10 dBi, and the wireless signal power received by the vehicle H has become -30 dBi, that is, the distance between the two vehicles is shown to attenuate the wireless signal by 20 dBi because of the attenuation amplitude and The distance is proportional to and a decay relationship table can be established in advance, so that the relative distance D3 between the two vehicles can be estimated or looked up based on the attenuation amount of the 20dBi. On the other hand, since the vehicle coordinates detected by the host vehicle H and the neighboring vehicle R using the GPS receiver are known, that is, the first reference position H1 and the reference position R1 are known, and can be extended according to the direction between the two positions. The line infers the direction of the vehicle H relative to the neighboring car R. Therefore, based on the reference position R1 of the neighboring vehicle R, a fourth reference position H4 is calculated based on the relative distance D3 and the direction.
請參考圖7,當取得第一參考位置H1~第四參考位置H4後,以各參考位置H1~H4為圓心相當於可決定出第一涵蓋範圍M1~第四涵蓋範圍M4,每個涵蓋範圍的大小係根據其參考位置之來源感測器的精準度而定,假設本車H的GPS接收器具有最好的精準度,則第一參考位置H1的涵蓋範圍最小,且精準度越高者,該參考位置也會具有一較高的權重值ω,其中GPS接收器會提供其本身的精準度。若其它感測器無法提供自身精準度,可根據該感測器推知後的位置其所在距離而決定其權重值,距離越遠,其權重越低。而本創作即是在第一涵蓋範圍M1~第四涵蓋範圍M4之交集區域(如斜線區域表示)計算出一車輛優化座標H(x,y)。 Referring to FIG. 7, after obtaining the first reference position H1 to the fourth reference position H4, the first coverage range M1 to the fourth coverage range M4 may be determined by using the reference positions H1 to H4 as the center, each coverage area. The size of the sensor is based on the accuracy of the source sensor of the reference position. If the GPS receiver of the vehicle H has the best accuracy, the first reference position H1 has the smallest coverage and the higher accuracy. The reference position will also have a higher weight value ω, where the GPS receiver will provide its own accuracy. If other sensors are unable to provide their own accuracy, the weight value may be determined according to the distance of the position after the sensor is inferred. The farther the distance is, the lower the weight is. The present invention calculates a vehicle optimization coordinate H(x, y) in the intersection area of the first coverage range M1 to the fourth coverage area M4 (as indicated by the slanted area).
在步驟b)中,係根據各參考位置之權重值ω,計算出一車輛優化座標H(x,y),計算方式可表示如下:,其中, In step b), a vehicle optimization coordinate H(x, y) is calculated according to the weight value ω of each reference position, and the calculation manner can be expressed as follows: ,among them,
在上式中,有m表示參考位置的數目,故本實施例m=4;(xi,yi)分別表示第一~第四參考位置H1~H4的座標;權重值ωi的其中一種計算方式可採用Adaboost演算法或其它演算法。 In the above formula, m denotes the number of reference positions, so m=4 in the present embodiment; (x i , y i ) denote coordinates of the first to fourth reference positions H1 to H4, respectively; one of the weight values ω i The calculation method can adopt Adaboost algorithm or other algorithms.
除了Adaboost演算法,在此提供一種權重值的計算方式。首先,假設第一參考位置H1~第四參考位置H4的誤差值分別為3、6、4、5公尺,可利用一誤差反比演算法計算四個不同的權重值,計算方式如下:計算總誤差量,Σiεi=3+4+5+6=18 In addition to the Adaboost algorithm, a way to calculate the weight value is provided here. First, assuming that the error values of the first reference position H1 to the fourth reference position H4 are 3, 6, 4, and 5 meters, respectively, an error inverse ratio algorithm can be used to calculate four different weight values, and the calculation manner is as follows: Error amount, Σ i ε i =3+4+5+6=18
分別計算總誤差量與各誤差值的差異量,φ1=Σiεi-ε1=18-3=15 Calculate the difference between the total error amount and each error value, φ 1 = Σ i ε i - ε 1 = 18-3 = 15
計算差異量的總量,Σiφi=15+13+12+14=54 Calculate the total amount of difference, Σ i φ i =15+13+12+14=54
四個權重值分別為:
本車H的車輛優化座標其中(xi,yi)分別表示四個參考位置的座標;H(x,y)代表車輛優化座標。 Vehicle optimization coordinates of the vehicle H Where (x i , y i ) represent the coordinates of the four reference positions, respectively; H(x, y) represents the vehicle optimized coordinates.
當完成本車H的車輛座標的優化運算之後,其次再以鄰車R為中心,對鄰車R的車輛座標進行優化運算,其運算過程如同上述,只是互換本車與鄰車之間的角色,換言之,將鄰車資料視為是上述運算中的本車資料,並將 本車資料視為是上述運算中的鄰車資料。因此,同樣可以得到代表鄰車之車輛優化座標R(x,y)。 After the optimization of the vehicle coordinates of the vehicle H is completed, the vehicle coordinates of the neighboring vehicle R are optimized based on the neighboring vehicle R. The calculation process is the same as above, but the role between the vehicle and the adjacent vehicle is exchanged. In other words, the adjacent car data is regarded as the vehicle information in the above calculation, and The vehicle information is regarded as the adjacent vehicle data in the above calculation. Therefore, the vehicle optimized coordinates R(x, y) representing the neighboring cars can also be obtained.
S33:物體定位優化,即針對鄰車R、本車H之感測器所測得的物體座標皆進行優化。在本車H部分,因為已得知本車H優化後之車輛優化座標H(x,y),故根據本車H感測器所測得的物體座標,可以比較本車H的車輛原始座標及其車輛優化座標H(x,y)之間的第二差異量,於計算本車H感測器測得之物體的物體優化座標時,即根據該第二差異量對本車H感測器測得之物體座標進行補償,而得到一第二物體優化座標,完成對本車H測得之物體座標的優化運算。同理,在鄰車R部分,因為已得知鄰車R優化後之車輛優化座標,故根據鄰車R感測器所測得的物體座標,可以比較鄰車R的車輛原始座標及其車輛優化座標之間的第一差異量,在重新計算該對鄰車R感測器測得之物體的物體優化座標時,即根據該第一差異量對鄰車R感測器測得之物體補償座標進行補償,而得到一第一物體優化座標。 S33: Object positioning optimization, that is, the object coordinates measured by the sensor of the neighboring vehicle R and the vehicle H are optimized. In the H part of the car, since the vehicle optimized coordinate H(x, y) after the vehicle H optimization has been known, the original coordinates of the vehicle H can be compared according to the object coordinates measured by the vehicle H sensor. And a second difference between the vehicle optimization coordinates H(x, y), when calculating the object optimization coordinate of the object measured by the vehicle H sensor, that is, according to the second difference amount, the vehicle H sensor The measured object coordinates are compensated, and a second object optimization coordinate is obtained to complete the optimization operation of the object coordinates measured by the vehicle H. In the same way, in the R part of the neighboring car, because the optimized coordinates of the vehicle after the optimization of the neighboring vehicle R have been known, the original coordinates of the vehicle of the neighboring vehicle R and its vehicle can be compared according to the coordinates of the object measured by the neighboring vehicle R sensor. Optimizing the first difference amount between the coordinates, and recalculating the object optimization coordinate of the object measured by the neighboring vehicle R sensor, that is, the object compensation measured by the neighboring vehicle R sensor according to the first difference amount The coordinates are compensated to obtain a first object optimized coordinate.
在步驟S40,本創作可利用該定位比對模組14融合來自不同鄰車R的多筆座標。舉例來說,請參考圖8所示,對第一車輛101而言,其它任一車輛102~104均會感測到周圍的物體並分享給第一車輛101,第一車輛101會接收到多筆關於同一物體(例如第二車輛102)的座標並暫存在一緩衝器(buffer)內,因此,第一車輛101內的定位比對模組14會從緩衝器內取出相似物體的座標,並加以融合成單一個位置資料,不同的物體座標則單獨新增。其中一種融合方式是透過K-Means分群演算法將多筆座標計算出一平均值,將同一車輛的車輛優化座標平均計算出一車輛代表座標,將同一物體的物體優化座標平均計算出一物體代表座標。 In step S40, the author can use the positioning comparison module 14 to fuse multiple coordinates from different neighboring cars R. For example, referring to FIG. 8, for the first vehicle 101, any other vehicle 102-104 will sense surrounding objects and share it with the first vehicle 101, and the first vehicle 101 will receive more. The coordinates of the pen about the same object (for example, the second vehicle 102) are temporarily stored in a buffer, so that the positioning comparison module 14 in the first vehicle 101 takes the coordinates of the similar object from the buffer, and They are combined into a single location data, and different object coordinates are added separately. One of the fusion methods is to calculate the average value of multiple coordinates by K-Means grouping algorithm, calculate the vehicle representative coordinates of the same vehicle on average, and calculate the object representative coordinates of the same object on average. coordinate.
綜上所述,本創作車輛協同式物體定位優化方法係具備有下述優點: In summary, the collaborative vehicle object positioning optimization method of the present invention has the following advantages:
1.利用本車與鄰車之間交換各自感測出的資料,可擴增各車輛的感測範圍,取得更多的環境資料。 1. By using the information exchanged between the vehicle and the neighboring car, the sensing range of each vehicle can be amplified to obtain more environmental information.
2.透過協同定位裝置重新校正車輛及周圍物體的座標資料,相較於單獨參考GPS接收器測知的座標資料,本創作可以得到更精準的座標,無論是應用於自動駕駛系統,或是用於提前警示駕駛者周圍環境之現況,均可提升行車安全性。 2. Recalibrate the coordinate data of the vehicle and surrounding objects through the co-location device. Compared with the coordinate data measured by the GPS receiver alone, the creation can obtain more precise coordinates, whether it is applied to the automatic driving system or Driving safety can be improved by warning the driver of the surrounding environment in advance.
3.利用本創作的協同定位方法,當本車完成優化運算後,可以得到優化完成後之本車定位資料、鄰車定位資料和一或多個物體定位資料,這三份資料會以BSM資料封包的格式傳送給周圍的鄰車,這時候的鄰車接收到BSM資料封包時,亦可以單獨執行本發明之優化運算,因此,周圍各車可分散運算,隨著時間的逐漸累積,車輛彼此之間的定位資料亦會漸漸提高精準度。 3. Using the collaborative positioning method of this creation, after the vehicle completes the optimization calculation, the vehicle positioning data, the adjacent vehicle positioning data and one or more object positioning data after optimization can be obtained, and the three materials will be BSM data. The format of the packet is transmitted to the surrounding neighboring car. When the neighboring car receives the BSM data packet, the optimization operation of the present invention can also be performed separately. Therefore, the surrounding vehicles can be distributed and calculated, and the vehicles accumulate with each other over time. The positioning data between them will gradually improve the accuracy.
H‧‧‧本車 H‧‧‧Car
H1~H4‧‧‧第一參考位置~第四參考位置 H1~H4‧‧‧first reference position~fourth reference position
M1~M4‧‧‧第一涵蓋範圍~第四涵蓋範圍 M1~M4‧‧‧First Coverage~Fourth Coverage
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