TWI490496B - Vehicle motion analysis device, vehicle motion analysis program, and driving recorder - Google Patents
Vehicle motion analysis device, vehicle motion analysis program, and driving recorder Download PDFInfo
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0841—Registering performance data
- G07C5/085—Registering performance data using electronic data carriers
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/12—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to parameters of the vehicle itself, e.g. tyre models
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/10—Longitudinal speed
- B60W2520/105—Longitudinal acceleration
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/12—Lateral speed
- B60W2520/125—Lateral acceleration
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Description
本發明是有關於一種車輛動作分析裝置或車輛動作分析程式(program)等，該車輛動作分析裝置在事故發生時，或在如險情之類的雖未致使發生事故卻有可能成為事故時，對車輛的動作或周圍狀況等進行記錄，以可事後適當地對導致如上所述的狀況的原因進行分析等。The present invention relates to a vehicle motion analysis device, a vehicle motion analysis program, or the like. The vehicle motion analysis device may become an accident when an accident occurs, or if an accident such as a dangerous situation does not cause an accident, The operation of the vehicle, the surrounding conditions, and the like are recorded so that the cause of the above-described situation can be appropriately analyzed afterwards.
近年來，作為車輛動作資料(data)收集裝置，已開發出如下的車輛搭載型的行車記錄器(drive recorder)，該車輛搭載型的行車記錄器例如自動地對駕駛中的車輛(汽車)的外部或內部的影像進行記錄，從而可對發生事故或出現險情等時的客觀狀況、甚至駕駛人(driver)的駕駛傾向進行事後分析。而且，例如對於計程車(taxi)等而言，亦已出現如下的動向，即，例如為了藉由對日常駕駛進行事後分析來預防事故，或為了在發生事故時，客觀地證明、查明事故的原因，搭載如上所述的行車記錄器。In recent years, a vehicle-mounted drive recorder has been developed as a vehicle operation data collection device. The vehicle-mounted drive recorder automatically drives a vehicle (automobile), for example. External or internal images are recorded so that post-analysis can be performed on the objective conditions in the event of an accident or danger, and even the driving tendency of the driver. Moreover, for example, for taxis and the like, the following trends have also occurred, that is, for example, to prevent accidents by performing post-mortem analysis on daily driving, or to objectively prove and ascertain accidents in the event of an accident. The reason is to carry the driving recorder as described above.
具體而言，如上所述的車輛動作資料收集裝置例如按照時間序列，逐步依序將行駛中的內外部圖像資料、加速度資料、速度資料、以及位置資料等的狀況資料記錄至記憶體(memory)內。接著，事後由其他裝置來對上述記憶體內的狀況資料進行參照，藉此，可客觀地對事故等進行分析(參照專利文獻1)。Specifically, the vehicle motion data collecting device as described above records the status data of the internal and external image data, the acceleration data, the velocity data, and the position data in a stepwise manner, for example, in time series, to the memory (memory). )Inside. Then, the situation information of the memory is referred to by another device, and the accident or the like can be objectively analyzed (see Patent Document 1).
然而，當事後欲對以上述方式記錄的狀況資料進行分 析時，由於上述狀況資料中包含如下的狀況資料，該狀況資料除了表示險情等的特定的車輛動作之外，亦表示各種動作，因此，必須對已收集的多個狀況資料進行分類，自已收集的多個狀況資料中，將所期望的表示車輛動作的狀況資料予以抽出。However, afterwards, I want to divide the status data recorded in the above manner. In the case of the above-mentioned situation data, the following status data is included, and the status data indicates various actions in addition to the specific vehicle actions such as the dangerous situation. Therefore, it is necessary to classify the collected plurality of status data and collect the self-collection. Among the plurality of status data, the expected status information indicating the vehicle operation is extracted.
此處，先前是進行如下的作業，即，藉由目視來逐個地對已收集的多個狀況資料進行確認，將各狀況資料例如分類為碰撞事故、險情、與險情無關的急刹車(brake)、以及單純的雜訊(noise)等。Here, the previous work is performed by visually checking a plurality of collected status data one by one, and classifying each status data into, for example, a collision accident, a dangerous situation, and a brake that is not related to a dangerous situation. And simple noise (noise).
然而，對於藉由目視來逐個地對狀況資料進行確認且進行分類的作業而言，存在如下的問題，即，不僅會導致對一個狀況資料進行確認的作業時間過長，而且難以根據使用者(user)的隨意的判斷來正確地進行分類。又，存在如下的問題，即，對使用者造成的肉體負擔以及精神負擔亦大。However, in the case of visually confirming and classifying the status data one by one, there is a problem that not only the work time for confirming one status data is too long, but also it is difficult to be based on the user ( User's arbitrary judgment to classify correctly. Further, there is a problem that the physical burden and the mental burden on the user are also large.
另一方面，如專利文獻2所示，可考慮如下的裝置，該裝置為了減輕使用者的負擔，自動地將狀況資料分類為由雜訊引起的狀況資料、與用以對險情等的動作進行分析的狀況資料。具體而言，上述裝置構成為基於加速度資料的波形的波高以及脈寬(pulse width)，將由雜訊引起的多餘的狀況資料予以排除。On the other hand, as shown in Patent Document 2, a device that automatically classifies the status data into status data caused by noise and actions for the danger or the like can be considered in order to reduce the burden on the user. Status information for analysis. Specifically, the above-described apparatus is configured to exclude redundant condition data caused by noise based on the wave height and pulse width of the waveform of the acceleration data.
然而，若如上述裝置般，使用臨限值來對由雜訊引起的多餘的狀況資料、與用以對險情等的動作進行分析的狀況資料進行判別，則存在如下的問題，即，分類精度會因 臨限值的設定方法而大不相同。又，即便可使用臨限值來將由雜訊引起的資料予以除去，亦必須藉由目視來逐個地對剩餘的狀況資料進行確認且進行分類。However, if the threshold value is used to discriminate between the excess status data caused by the noise and the status data for analyzing the operation such as the dangerous situation, the following problem occurs, that is, the classification accuracy Will The setting method of the threshold is very different. Moreover, even if the threshold value can be used to remove the data caused by the noise, it is necessary to visually confirm and classify the remaining status data one by one.
例如，若將臨限值設定為低臨限值，則根據全部的狀況資料，候補險情事例的抽出件數會增加，但抽出的資料中的險情事例的準確率變低，包含多餘的資料的比例變大。另一方面，若將臨限值設定為高臨限值，則根據全部的狀況資料，候補險情事例的抽出件數會減少，但抽出的狀況資料中的險情事例的準確率變高，包含多餘的資料的比例變小。然而，於該情形時，險情事例的遺漏率變高。亦即，對於利用臨限值來統一地進行分離的方法而言，準確率與遺漏率之間存在取捨關係(trade off)。又，雖說使臨限值提高而提高準確率，但與藉由目視來進行分類的情形相比較，上述準確率相當低且不實用。因此，為了正確地根據狀況資料來對險情事例進行分類，目前依然需要利用目視的作業。For example, if the threshold value is set to the low threshold value, the number of extractions of the candidate danger case will increase according to the entire situation data, but the accuracy rate of the dangerous case in the extracted data becomes low, and the excess information is included. The proportion becomes larger. On the other hand, if the threshold value is set to the high threshold value, the number of pieces of the candidate danger case will be reduced according to all the status data, but the accuracy rate of the dangerous case in the extracted status data becomes high, including redundant The proportion of the information becomes smaller. However, in this case, the miss rate of the dangerous case becomes high. That is, there is a trade off between the accuracy rate and the missing rate for the method of uniformly separating using the threshold value. Further, although the threshold value is increased to improve the accuracy, the accuracy is relatively low and impractical compared to the case of sorting by visual observation. Therefore, in order to correctly classify dangerous cases based on status data, it is still necessary to use visual operations.
專利文獻1：日本專利特開2007-11909號公報Patent Document 1: Japanese Patent Laid-Open Publication No. 2007-11909
專利文獻2：日本專利第4238293號公報Patent Document 2: Japanese Patent No. 4238293
因此，本發明是本申請案發明人進行仔細研究之後，著眼於如下的內容才獲得的發明，該內容是指針對車輛的每個動作，各加速度資料的特徵量存在特有的相對關係， 本發明的主要的預期課題在於：並不僅藉由目視來對狀況資料所示的車輛的動作進行分類，而是自動地且以高可靠性來鑑定狀況資料所示的車輛動作。Accordingly, the present invention has been made in view of the following contents after careful study by the inventors of the present application, and the content is a unique relative relationship between the characteristics of each acceleration data for each movement of the vehicle. A main and expected problem of the present invention is to not only classify the movement of the vehicle indicated by the situation data by visual observation, but to automatically and reliably identify the vehicle behavior indicated by the situation data.
亦即，本發明的車輛動作分析裝置的特徵在於包括：狀況資料接收部，接收包含作用於車輛的前後加速度、左右加速度及上下加速度的各加速度資料的狀況資料、或包含作用於車輛的傾側角(roll angle)加速度、螺距角(pitch angle)加速度及偏航角(yaw angle)加速度的各角加速度資料的狀況資料中的至少一種狀況資料；以及車輛動作鑑定部，使用已接收的狀況資料中的前後加速度、左右加速度及上下加速度的各加速度資料的特徵量的相對關係、或傾側角加速度、螺距角加速度及偏航角加速度的各角加速度資料的特徵量的相對關係中的至少一個特徵量的相對關係，對上述狀況資料所示的車輛動作進行鑑定。In other words, the vehicle behavior analysis device according to the present invention includes: a status data receiving unit that receives status information including acceleration data of the longitudinal acceleration, the left and right acceleration, and the vertical acceleration acting on the vehicle, or includes a tilt angle acting on the vehicle. (roll angle) at least one of status data of acceleration, pitch angle acceleration, and yaw angle acceleration angular acceleration data; and vehicle motion identification section using the received status data At least one of a relative relationship between the feature quantities of the acceleration data, the left and right accelerations, and the acceleration data of the vertical acceleration, or the relative relationship between the tilt angular acceleration, the pitch angular acceleration, and the feature amount of each angular acceleration data of the yaw angular acceleration The relative relationship is identified by the vehicle behavior shown in the above situation data.
如此，可使用各加速度資料的特徵量或各角加速度資料的特徵量，且藉由上述特徵量的相對關係來鑑定車輛動作，因此，可不依賴於目視而鑑定狀況資料所示的車輛動作。藉此，不僅可將使用者的隨意的判斷予以排除而客觀地鑑定車輛動作，而且可減輕使用者的時間負擔、肉體負擔以及精神負擔。又，由於可根據各加速度資料的特徵量或各角加速度資料的特徵量的相對關係來鑑定車輛動作，因此，與僅利用臨限值來進行判別的情形相比較，可獲得可靠性高的鑑定結果。In this manner, the feature amount of each acceleration data or the feature amount of each angular acceleration data can be used, and the vehicle motion can be identified by the relative relationship of the feature amounts. Therefore, the vehicle behavior indicated by the situation data can be identified without depending on the visual observation. Thereby, not only the user's arbitrary judgment can be excluded, but also the vehicle behavior can be objectively identified, and the time burden, the physical burden, and the mental burden of the user can be alleviated. Further, since the vehicle behavior can be identified based on the relative relationship between the feature amount of each acceleration data or the feature amount of each angular acceleration data, it is possible to obtain a highly reliable identification as compared with the case where the discrimination is performed only by using the threshold value. result.
具體而言，本申請案發明人進行仔細研究之後，已知： 於以下(1)~(3)的車輛動作中，前後加速度、左右加速度以及上下加速度的各加速度資料的特徵量存在特有的相對關係。亦即，當上述已接收的狀況資料包含前後加速度、左右加速度以及上下加速度的各加速度資料時，考慮由上述車輛動作鑑定部使用前後加速度、左右加速度以及上下加速度的各加速度資料的特徵量的相對關係，將上述狀況資料所示的車輛動作鑑定為以下的(1)~(3)中的任一種動作。Specifically, after careful study by the inventors of the present application, it is known that: In the following (1) to (3) vehicle operation, there is a unique relative relationship between the feature amounts of the acceleration data of the longitudinal acceleration, the left and right acceleration, and the vertical acceleration. In other words, when the received condition data includes the acceleration data of the front-rear acceleration, the left-right acceleration, and the vertical acceleration, the relative amount of the feature amounts of the acceleration data using the longitudinal acceleration, the left-right acceleration, and the vertical acceleration by the vehicle motion identification unit is considered. In the relationship, the vehicle behavior indicated by the above-mentioned situation data is identified as any one of the following (1) to (3).
(1)表示碰撞事故、與碰撞事故相關聯的險情或該險情以外的急刹車的險情等動作。(1) Indicates a collision accident, a danger associated with a collision accident, or a danger of sudden braking other than the dangerous situation.
(2)表示單輪碾壓至路緣石或車輪脫入至側溝的碾壓等動作。(2) indicates a single-wheel rolling operation to the curb or the rolling of the wheel into the side groove.
(3)表示因兩輪通過車道上的凹凸而產生的顛簸(bound)的顛簸動作。(3) indicates a bumpy movement caused by the two-round passage of the unevenness on the lane.
更詳細而言，較佳為當前後加速度資料的特徵量大於左右加速度資料及上下加速度資料的特徵量時，上述車輛動作鑑定部將上述狀況資料所示的車輛動作鑑定為上述險情等動作，當上述左右加速度資料的特徵量大於前後加速度資料及上下加速度資料的特徵量時，上述車輛動作鑑定部將上述狀況資料所示的車輛動作鑑定為上述碾壓等動作，當上下加速度資料的特徵量大於前後加速度資料及上述左右加速度資料的特徵量時，上述車輛動作鑑定部將上述狀況資料所示的車輛動作鑑定為上述顛簸動作。More specifically, when the feature quantity of the current post-acceleration data is greater than the feature quantity of the left-right acceleration data and the vertical acceleration data, the vehicle motion identification unit identifies the vehicle motion indicated by the status data as the dangerous situation or the like. When the feature quantity of the left and right acceleration data is greater than the feature quantity of the longitudinal acceleration data and the vertical acceleration data, the vehicle motion identification unit identifies the vehicle motion indicated by the situation data as the rolling operation, and the feature quantity of the vertical acceleration data is greater than When the front-back acceleration data and the feature amount of the left and right acceleration data are used, the vehicle motion identifying unit identifies the vehicle motion indicated by the situation data as the bump operation.
對於上述險情等動作而言，為了更細化地鑑定碰撞事 故以及險情以外的急刹車，較佳為上述狀況資料包含方向燈資料(winker data)，該方向燈資料表示上述車輛的方向燈的作動資訊，當鑑定為上述險情等動作的狀況資料中包含上述方向燈資料時，上述車輛動作鑑定部將上述方向燈資料所示的車輛動作，鑑定為表示用以靠著車道的路肩停車的急刹車的動作。For the above-mentioned dangers and other actions, in order to more accurately identify the collision Therefore, it is preferable that the sudden braking other than the dangerous situation includes the above-mentioned situation data including winker data, and the directional light data indicates the operation information of the directional light of the vehicle, and the above-mentioned situation information including the above-mentioned dangerous situation includes the above-mentioned information. In the case of the directional light data, the vehicle motion identifying unit identifies the vehicle operation indicated by the directional light data as an operation indicating a sudden braking for stopping the shoulder of the lane.
又，本發明的車輛動作分析程式的特徵在於：使電腦(computer)具有作為狀況資料接收部與車輛動作鑑定部的功能，上述狀況資料接收部接收包含作用於車輛的前後加速度、左右加速度及上下加速度的各加速度資料的狀況資料、或包含作用於車輛的傾側角加速度、螺距角加速度及偏航角加速度的各角加速度資料的狀況資料中的至少一個狀況資料，上述車輛動作鑑定部使用已接收的狀況資料中的前後加速度、左右加速度及上下加速度的各加速度資料的特徵量的相對關係、或傾側角加速度、螺距角加速度及偏航角加速度的各角加速度資料的特徵量的相對關係中的至少一個特徵量的相對關係，對上述狀況資料所示的車輛動作進行鑑定。Further, the vehicle motion analysis program according to the present invention is characterized in that the computer has a function as a status data receiving unit and a vehicle motion identifying unit, and the status data receiving unit receives the longitudinal acceleration, the left and right acceleration, and the upper and lower accelerations acting on the vehicle. At least one of the status data of each acceleration data of the acceleration or the status data of each angular acceleration data including the tilt angular acceleration, the pitch angular acceleration, and the yaw angular acceleration of the vehicle, the vehicle motion identification unit uses the received The relative relationship between the front-back acceleration, the left-right acceleration, and the feature quantity of each acceleration data of the vertical acceleration in the status data, or the relative relationship between the tilt angular acceleration, the pitch angular acceleration, and the feature quantity of each angular acceleration data of the yaw angular acceleration The relative relationship of at least one feature quantity is used to identify the vehicle action indicated by the above status data.
上述車輛動作分析裝置自搭載於車輛的行車記錄器取得狀況資料，對該狀況資料進行分析。亦可將上述車輛動作分析裝置的功能賦予行車記錄器。亦即，本發明的行車記錄器的特徵在於包括：狀況資料接收部，接收包含作用於車輛的前後加速度、左右加速度及上下加速度的各加速度資料的狀況資料、或包含作用於車輛的傾側角加速度、 螺距角加速度及偏航角加速度的各角加速度資料的狀況資料中的至少一個狀況資料；以及車輛動作鑑定部，使用已接收的狀況資料中的前後加速度、左右加速度及上下加速度的各加速度資料的特徵量的相對關係、或傾側角加速度、螺距角加速度及偏航角加速度的各角加速度資料的特徵量的相對關係中的至少一個特徵量的相對關係，對上述狀況資料所示的車輛動作進行鑑定。The vehicle motion analysis device analyzes the status data from the driving recorder of the vehicle. The function of the above-described vehicle motion analysis device can also be given to the driving recorder. That is, the drive recorder of the present invention includes: a status data receiving unit that receives condition data including acceleration data of a longitudinal acceleration, a left-right acceleration, and an up-and-down acceleration acting on the vehicle, or includes a tilt angular acceleration acting on the vehicle , At least one condition data in each of the angular acceleration data of the pitch angular acceleration and the yaw angular acceleration; and the vehicle motion identification unit, using the acceleration data of the longitudinal acceleration, the left and right acceleration, and the vertical acceleration in the received condition data The relative relationship of the feature quantity, or the relative relationship of at least one feature quantity in the relative relationship between the feature values of the angular acceleration of the tilt angle, the pitch angular acceleration, and the angular acceleration of the yaw angle acceleration, and the vehicle behavior indicated by the above condition data Identification.
如此，於行車記錄器將狀況資料儲存於記憶體的階段，可對各狀況資料所示的車輛動作進行鑑定，因此，可無需對之後收集的狀況資料進行分類的作業，或可使該作業減輕。又，可僅選擇特定的動作來儲存於行車記錄器的記憶體，從而可有效率地利用記憶體。In this way, when the driving recorder stores the status data in the memory, the vehicle behavior indicated by each status data can be authenticated, so that it is not necessary to classify the later collected status data, or the operation can be reduced. . Further, only a specific action can be selected to be stored in the memory of the drive recorder, so that the memory can be utilized efficiently.
根據以上述方式構成的本發明，可不使用如下的方法而自動地且以高可靠性來鑑定狀況資料所示的車輛動作，上述方法是指藉由目視來對狀況資料所示的車輛的動作進行分類，或使用臨限值來對狀況資料中所含的例如加速度資料進行判別且進行分類。According to the present invention configured as described above, the vehicle behavior indicated by the situation data can be automatically and highly reliably determined without using the following method, which means that the motion of the vehicle indicated by the situation data is visually observed. Classification, or use of thresholds to discriminate and classify, for example, acceleration data contained in the status data.
以下，參照圖式，對本發明的車輛動作分析系統(system)的一個實施形態進行說明。Hereinafter, an embodiment of a vehicle behavior analysis system (system) of the present invention will be described with reference to the drawings.
如圖1所示，本實施形態的車輛動作分析系統包括：行車記錄器100，對汽車(車輛)V的外部前方進行拍攝 等；以及車輛動作分析裝置200，例如取得上述行車記錄器100所拍攝的動態影像資料等，基於該動態影像資料所示的動態影像來鑑定汽車V是否表現出規定的動作。As shown in FIG. 1, the vehicle behavior analysis system according to the present embodiment includes a driving recorder 100 that photographs an exterior front side of a car (vehicle) V. And the vehicle motion analysis device 200 obtains, for example, motion picture data captured by the drive recorder 100, and identifies whether the vehicle V exhibits a predetermined operation based on the motion picture indicated by the motion picture data.
行車記錄器100是車輛搭載型的行車記錄器，該行車記錄器100黏著於擋風玻璃(front glass)，或者設置於儀錶板(dash board)附近或安裝於車輛內的適當的位置，例如當發生事故時或出現雖未致使事故發生卻有可能成為事故的險情時，對前後固定期間中的汽車V的動作或周圍狀況等進行記錄，上述行車記錄器100採用一體的構成，即，將基本構成要素即圖2所示的偵測單元3、資訊處理單元8、報告單元4、輸入單元5、通信單元6、以及裝脫式記錄單元7等収容於單個或多個外殼(casing)內。The driving recorder 100 is a vehicle-mounted driving recorder that is attached to a front glass or is disposed near a dash board or at an appropriate position in the vehicle, for example, when In the event of an accident or a danger that may occur as an accident without causing an accident, the operation of the vehicle V in the front and rear fixed periods or the surrounding conditions is recorded, and the above-described driving recorder 100 adopts an integrated configuration, that is, basic The detecting unit 3, the information processing unit 8, the reporting unit 4, the input unit 5, the communication unit 6, and the detachable recording unit 7 shown in Fig. 2 are housed in a single or a plurality of casings.
偵測單元3對與汽車V的動作或周圍狀況等相關的狀況進行感測(sensing)，且將表示該狀況的狀況資料予以輸出，此處，至少使用有拍攝單元31、加速度感測器(sensor)32、以及位置感測器33該3種裝置。拍攝單元31例如是電荷耦合元件(Charge Coupled Device，CCD)相機(camera)，對自身車輛前方的車外狀況進行拍攝，且將表示車外狀況的圖像的狀況資料(動態影像資料)予以輸出。加速度感測器32例如是利用壓電(piezo)電阻效應而構成的加速度感測器，該加速度感測器32對作用於車輛的三維的加速度進行感測，且將表示上述加速度的狀況資料(加速度資料)予以輸出。具體而言，加速度感測器 32對作用於車輛V的前後方向的前後加速度、作用於車輛V的左右方向的左右加速度、以及作用於車輛V的上下方向的上下加速度進行感測。位置感測器33例如為全球定位系統(Global Positioning System，GPS)接收機，該GPS接收機接收(catch)來自多個衛星的電波而對車輛V的位置進行感測，且將表示該位置的狀況資料(位置資料)予以輸出。再者，於狀況資料中，亦存在自車輛V的車速感測器發送而來的車速資料、或表示車門(door)的開閉的車門開閉資料、或表示刹車的ON/OFF的刹車資料、以及表示車輛V的方向燈的作動資訊的方向燈資料等，經由連接器(connector)CN來接收上述資料。又，上述連接器CN亦用作電源。The detecting unit 3 senses a situation related to the operation of the automobile V, the surrounding condition, and the like, and outputs status information indicating the situation. Here, at least the imaging unit 31 and the acceleration sensor are used ( The sensor 32 and the position sensor 33 are the three devices. The imaging unit 31 is, for example, a charge coupled device (CCD) camera, and captures an outside situation of the vehicle in front of the vehicle, and outputs status information (moving image data) of an image indicating the situation outside the vehicle. The acceleration sensor 32 is, for example, an acceleration sensor configured by a piezo resistance effect, and the acceleration sensor 32 senses a three-dimensional acceleration acting on the vehicle, and displays status information indicating the acceleration ( Acceleration data) is output. Specifically, the acceleration sensor 32 senses the longitudinal acceleration acting in the front-rear direction of the vehicle V, the left-right acceleration acting in the left-right direction of the vehicle V, and the vertical acceleration acting on the vertical direction of the vehicle V. The position sensor 33 is, for example, a Global Positioning System (GPS) receiver that catches radio waves from a plurality of satellites to sense the position of the vehicle V and will indicate the position. Status data (location data) is output. Further, in the status data, there are also vehicle speed data transmitted from the vehicle speed sensor of the vehicle V, or door opening and closing data indicating the opening and closing of the door, or brake data indicating ON/OFF of the brake, and The directional light data or the like indicating the operation information of the directional light of the vehicle V is received via the connector CN. Further, the above connector CN is also used as a power source.
報告單元4包含露出至外殼的表面的發光體即LED41、或者內置於外殼的蜂鳴器(buzzer)或揚聲器(speaker)等的聲音輸出體(未圖示)等。The report unit 4 includes an LED 41 that is an illuminant exposed to the surface of the casing, or a sound output body (not shown) such as a buzzer or a speaker built in the casing.
此處，所謂輸入單元5，是指設置於外殼的表面的按鈕開關(button switch)。Here, the input unit 5 refers to a button switch provided on the surface of the casing.
此處，所謂通信單元6，是指內置於外殼，且與基站或後述的車輛動作分析裝置200之間收發電波的例如無線區域網路(Local Area Network，LAN)或行動電話等的通信用的硬體(hardware)。Here, the communication unit 6 is a communication device such as a wireless area network (LAN) or a mobile phone that is built in the casing and transmits and receives radio waves between the base station or the vehicle motion analysis device 200 to be described later. Hardware.
此處，所謂裝脫式記錄單元7，是指可拔脫地安裝於插槽(slot)的例如緊密快閃(Compact Flash，CF)記憶卡(memory card)或安全數位(Secure Digital，SD)記憶 卡，上述插槽於外殼的側方形成開口。Here, the detachable recording unit 7 refers to, for example, a compact flash (CF) memory card or a secure digital (SD) that is detachably mounted in a slot. memory The card has an opening formed in a side of the outer casing.
就構造而言，資訊處理單元8是包括中央處理單元(Central Processing Unit，CPU)81、內部記憶體82(例如非揮發性記憶體)、以及I/O緩衝(buffer)電路(有時亦包含類比數位(Analog Digital，AD)轉換器(converter)等)83等的常說的電腦電路，該資訊處理單元8內置於外殼。而且，上述CPU81根據儲存於記憶體82的規定區域的程式來進行動作，藉此，進行上述各單元的控制或資訊處理。In terms of structure, the information processing unit 8 includes a central processing unit (CPU) 81, internal memory 82 (for example, non-volatile memory), and an I/O buffer circuit (sometimes also included A computer circuit such as an analog digital (AD) converter (such as a converter) 83 or the like, and the information processing unit 8 is built in a casing. Further, the CPU 81 operates based on a program stored in a predetermined area of the memory 82, thereby performing control or information processing of each unit described above.
簡單地進行說明，CPU81經常一面逐個地對行駛中的各種狀況資料即加速度資料或位置資料、動態影像資料等進行更新，一面逐步將上述資料暫時保存至設定於記憶體82內的暫時(temporary)區域(以下亦稱為暫時資料儲存部)，並且當產生如下的現象時，將該現象的前後固定期間中的上述狀況資料移送且記錄至記憶體82內的正規區域(以下亦稱為正規記錄資料儲存部)，上述現象間接地表示險情或事故、異常發生等的發生。Briefly, the CPU 81 constantly updates the various status data, that is, the acceleration data, the position data, the moving image data, and the like, while gradually storing the above data to the temporary (temporary) set in the memory 82. The area (hereinafter also referred to as a temporary data storage unit), and when the following phenomenon occurs, the situation data in the period before and after the phenomenon is transferred and recorded in the normal area in the memory 82 (hereinafter also referred to as a regular record) The data storage unit), the above phenomenon indirectly indicates the occurrence of danger, accident, abnormality, and the like.
加速度資料所示的加速度(減速度)超過規定基準值的情形、或加速度(減速度)的時間持續固定時間以上的情形、車門開閉的情形、以及車輛的電源關閉的情形等相當於上述現象。此處，根據已產生的現象，只有當車速為上限速度以上時，當車速為加速度或減速度以下時，以及當表示是否已刹車等的其他的若干個條件同時成立時，才以該情形為契機而進行資料記錄，從而可儘可能地不記錄 無用的資料。The case where the acceleration (deceleration) indicated by the acceleration data exceeds the predetermined reference value, or the time when the acceleration (deceleration) continues for a fixed time or longer, the case where the door is opened and closed, and the case where the vehicle is turned off is equivalent to the above phenomenon. Here, according to the phenomenon that has occurred, only when the vehicle speed is equal to or higher than the upper limit speed, when the vehicle speed is below the acceleration or deceleration, and when several other conditions indicating whether the brake has been established or the like are simultaneously established, Data recording for the opportunity to record as much as possible Useless information.
又，就防止記錄無用的資料的觀點而言，上述行車記錄器亦具有學習功能。亦即，於進行資料記錄之前，必定藉由上述報告單元來向駕駛人報告是否已出現險情或發生事故等，且採納來自駕駛人的表示正確與否的輸入(例如，上述按鈕開關5的ON/OFF)。將上述動作予以重複，藉此來某種程度地掌握駕駛人的駕駛傾向，例如，將加速度的規定基準值予以變更等，學習間接地表示事故等的該駕駛人所特有的現象。Further, the above-described driving recorder also has a learning function from the viewpoint of preventing the use of unnecessary data. That is, before the data recording is performed, it is necessary to report to the driver by the above-mentioned reporting unit whether or not a dangerous situation or an accident has occurred, and the input from the driver indicating whether it is correct or not is adopted (for example, the above-mentioned button switch 5 is ON/ OFF). By repeating the above-described operation, the driving tendency of the driver is grasped to some extent, for example, the predetermined reference value of the acceleration is changed, and the phenomenon unique to the driver such as an accident is indirectly learned.
而且，根據已記錄的狀況資料被記錄時的狀況，對該已記錄的狀況資料進行加權，根據應記錄的重要度來分類。接著，例如，當記憶體容量已滿時，自重要度低的狀況資料起，將狀況資料予以刪除，接著記錄新的狀況資料。Further, based on the status at the time of recording of the recorded status data, the recorded status data is weighted and classified according to the importance level to be recorded. Next, for example, when the memory capacity is full, the status data is deleted from the status data with low importance, and then the new status data is recorded.
以上述方式正規地被記錄的狀況資料於特定場所，被無線地發送至分析中心(center)(未圖示)，或者被移送至裝脫式記錄單元7，將該裝脫式記錄單元7取下，接著移入至分析中心，用於使用車輛動作分析裝置200來進行事後的分析。The status data that is normally recorded in the above manner is wirelessly transmitted to an analysis center (not shown) or transferred to the loading and unloading recording unit 7 to take the detachable recording unit 7 Next, it is moved to the analysis center for performing post-mortem analysis using the vehicle motion analysis device 200.
車輛動作分析裝置200按照規定的各車輛動作，對多個搭載於汽車V的行車記錄器100所獲得的狀況資料群進行分類，從而支援事後的分析。上述車輛動作分析裝置200的具體的機械構成是包括CPU、記憶體、輸入輸出介面(interface)、以及AD轉換器等的通用或專用的電腦，該 通用或專用的電腦依照記憶於上述記憶體的規定區域的車輛動作來分析程式，使CPU、周邊設備等協作，藉此，如圖3所示，發揮作為狀況資料接收部201、狀況資料儲存部D1、車輛動作鑑定部202、以及分析資料儲存部D2等的功能。The vehicle behavior analysis device 200 classifies the status data groups obtained by the plurality of driving recorders 100 mounted on the automobile V in accordance with the predetermined vehicle operations, thereby supporting the subsequent analysis. The specific mechanical configuration of the vehicle motion analysis device 200 described above is a general-purpose or dedicated computer including a CPU, a memory, an input/output interface, and an AD converter. The general-purpose or dedicated computer analyzes the program in accordance with the vehicle motion stored in the predetermined area of the memory, and causes the CPU, the peripheral device, and the like to cooperate, thereby functioning as the status data receiving unit 201 and the status data storage unit as shown in FIG. D1, the vehicle motion identification unit 202, and the analysis data storage unit D2 and the like.
以下，使用圖4，一併對各部分D1、201、202、D2以及各部分的動作進行說明。Hereinafter, the operation of each of the portions D1, 201, 202, D2 and each portion will be described with reference to Fig. 4 .
狀況資料接收部201採納行車記錄器100的正規記錄資料儲存部中所儲存的包含動態影像資料及各加速度資料的狀況資料，將該狀況資料儲存於狀況資料儲存部D1(圖4、步驟(step)S1)。狀況資料接收部201可包含接收狀況資料的接收機，上述狀況資料是設置於行車記錄器100的通信單元(發送機)6使用無線LAN等來發送的狀況資料，上述狀況資料接收部201亦可經由設置於行車記錄器100的裝脫式記錄單元7即例如CF卡來取得狀況資料。The status data receiving unit 201 adopts the status data including the moving image data and the acceleration data stored in the normal recording data storage unit of the drive recorder 100, and stores the status data in the status data storage unit D1 (FIG. 4, step (step) )S1). The status data receiving unit 201 may include a receiver that receives the status data, and the status data is status information transmitted by the communication unit (transmitter) 6 provided in the drive recorder 100 using a wireless LAN or the like, and the status data receiving unit 201 may also be used. The status data is acquired via a detachable recording unit 7 provided in the drive recorder 100, that is, for example, a CF card.
狀況資料儲存部D1儲存且蓄積著包含上述行車記錄器100所拍攝的動態影像資料等的狀況資料(圖4、步驟S2)。再者，於本實施形態中，狀況資料儲存部D1構成為例如針對每輛汽車V，系統地儲存多輛汽車V所獲得的多個狀況資料。The status data storage unit D1 stores and stores status data including the moving image data captured by the drive recorder 100 (FIG. 4, step S2). Further, in the present embodiment, the status data storage unit D1 is configured to systematically store a plurality of status data obtained by a plurality of vehicles V for each vehicle V.
車輛動作鑑定部202取得儲存於上述狀況資料儲存部D1的狀況資料，對每個上述狀況資料中所含的前後加速度、左右加速度以及上下加速度的各加速度資料的特徵量進行計算(圖4、步驟S3)。本實施形態的車輛動作鑑定 部202對各加速度資料所示的加速度波形的振幅或不均的尺度即例如標準偏差進行計算，作為各加速度資料的特徵量。The vehicle behavior identifying unit 202 acquires the status data stored in the status data storage unit D1, and calculates the feature quantity of each acceleration data including the longitudinal acceleration, the left and right acceleration, and the vertical acceleration included in each of the status data (FIG. 4, Steps). S3). Vehicle motion identification of this embodiment The unit 202 calculates, for example, a standard deviation of the amplitude or unevenness of the acceleration waveform indicated by each acceleration data as the feature amount of each acceleration data.
接著，車輛動作鑑定部202使用各加速度資料的特徵量即例如標準偏差的相對性大小關係，來鑑定狀況資料所示的車輛動作(圖4、步驟S4)。具體而言，車輛動作鑑定部202使用前後加速度、左右加速度以及上下加速度的各加速度資料的標準偏差的相對性大小關係，將狀況資料所示的車輛動作至少鑑定為以下的(1)~(3)中的任一個動作。Next, the vehicle behavior identifying unit 202 identifies the vehicle motion indicated by the situation data using the feature magnitude of each acceleration data, that is, the relative magnitude relationship of the standard deviation, for example (FIG. 4, step S4). Specifically, the vehicle motion identifying unit 202 uses the relative magnitude relationship of the standard deviations of the acceleration data of the longitudinal acceleration, the left and right acceleration, and the vertical acceleration, and identifies the vehicle behavior indicated by the situation data as at least the following (1) to (3). Any one of the actions.
(1)表示碰撞事故、與碰撞事故相關聯的險情或該險情以外的急刹車的險情等動作。(1) Indicates a collision accident, a danger associated with a collision accident, or a danger of sudden braking other than the dangerous situation.
(2)表示單輪碾壓至路緣石或車輪脫入至側溝的碾壓等動作。(2) indicates a single-wheel rolling operation to the curb or the rolling of the wheel into the side groove.
(3)表示因兩輪通過車道上的凹凸而產生的顛簸的顛簸動作。(3) indicates a bumpy movement caused by two rounds of bumps on the lane.
更詳細而言，如圖5所示，當前後加速度資料的加速度波形的標準偏差，大於左右加速度資料的加速度波形的標準偏差及上下加速度資料的加速度波形的標準偏差時，車輛動作鑑定部202將上述狀況資料所示的車輛動作鑑定為上述險情等動作。原因在於：由於碰撞時的衝擊或急刹車時的衝擊，各加速度中的前後加速度會最大幅度地發生變動，從而前後加速度波形的不均變得最大。再者，圖5是模式圖，藉由目視來將上述行車記錄器100所獲得的多 個狀況資料分類為上述(1)~(3)，針對上述每個動作而對狀況資料進行排列，表示各狀況資料的各加速度波形的標準偏差。圖5的橫軸表示各狀況資料，縱軸表示各加速度波形的標準偏差。More specifically, as shown in FIG. 5, when the standard deviation of the acceleration waveform of the current post-acceleration data is greater than the standard deviation of the acceleration waveform of the left and right acceleration data and the standard deviation of the acceleration waveform of the upper and lower acceleration data, the vehicle motion identification unit 202 The vehicle behavior indicated by the above situation data is identified as the above-mentioned danger and the like. The reason is that the front-back acceleration in each acceleration changes greatly due to the impact at the time of collision or the impact at the time of sudden braking, and the unevenness of the longitudinal acceleration waveform becomes maximum. Furthermore, FIG. 5 is a schematic view of the above-described driving recorder 100 obtained by visual inspection. The status data is classified into the above (1) to (3), and the status data is arranged for each of the above operations, and the standard deviation of each acceleration waveform of each status data is indicated. The horizontal axis of Fig. 5 indicates each status data, and the vertical axis indicates the standard deviation of each acceleration waveform.
又，當上述左右加速度資料的加速度波形的標準偏差，大於前後加速度資料的加速度波形的標準偏差及上下加速度資料的加速度波形的標準偏差時，車輛動作鑑定部202將上述狀況資料所示的車輛動作鑑定為上述碾壓等動作(參照圖5)。原因在於：在碾壓等動作中，僅車輛V的前輪中的單輪會急遽地發生變動，藉此，各加速度中的左右加速度會最大幅度地發生變動，從而左右加速度波形的不均變得最大。Further, when the standard deviation of the acceleration waveform of the left and right acceleration data is greater than the standard deviation of the acceleration waveform of the longitudinal acceleration data and the standard deviation of the acceleration waveform of the vertical acceleration data, the vehicle behavior identification unit 202 operates the vehicle indicated by the situation data. It was identified as the above-described operation such as rolling (see Fig. 5). The reason is that in the operation such as rolling, only the single wheel in the front wheel of the vehicle V is violently changed, whereby the left and right accelerations in the respective accelerations are changed to the maximum extent, and the unevenness of the left and right acceleration waveforms becomes maximum.
而且，當上下加速度資料的加速度波形的標準偏差，大於前後加速度資料的加速度波形的標準偏差及上述左右加速度資料的加速度波形的標準偏差時，車輛動作鑑定部202將上述狀況資料所示的車輛動作鑑定為上述顛簸動作(參照圖5)。原因在於：在顛簸動作中，車輛V的兩個前輪大致同時地發生變動，即，大致同時地上下運動，藉此，各加速度中的上下加速度會最大幅度地發生變動，從而上下加速度波形的不均變得最大。Further, when the standard deviation of the acceleration waveform of the vertical acceleration data is larger than the standard deviation of the acceleration waveform of the longitudinal acceleration data and the standard deviation of the acceleration waveform of the left and right acceleration data, the vehicle behavior identification unit 202 operates the vehicle indicated by the situation data. It is identified as the above-described bumping action (refer to FIG. 5). The reason is that in the bumping motion, the two front wheels of the vehicle V change substantially simultaneously, that is, move up and down substantially simultaneously, whereby the vertical acceleration in each acceleration changes to the maximum extent, so that the vertical acceleration waveform does not They all become the biggest.
而且，當鑑定為上述險情等動作的狀況資料中包含上述方向燈資料時，車輛動作鑑定部202將上述方向燈資料所示的車輛動作，鑑定為表示用以靠著車道的路肩停車的急刹車的動作(路肩停止動作)(參照圖5)。以上述方式 進行鑑定，藉此，能夠自動且更細化地對險情等動作進行分類。再者，於圖5中，在圖的下部以縱向細線來表示方向燈的有無。又，利用影線(hatching)來表示方向燈信號的密集部分。Further, when the situation data identifying the operation such as the dangerous situation includes the directional light data, the vehicle motion identifying unit 202 identifies the vehicle motion indicated by the directional light data as a sudden braking indicating that the road shoulder is parked against the lane. The action (shoulder stop action) (see Figure 5). In the above way By performing the identification, it is possible to automatically and more accurately classify actions such as dangers. Further, in Fig. 5, the presence or absence of the directional light is indicated by a longitudinal thin line at the lower portion of the figure. Further, hatching is used to indicate a dense portion of the direction light signal.
接著，車輛動作鑑定部202使作為鑑定結果的動作鑑定資料與以上述方式對車輛進行動作鑑定的狀況資料相關聯，將該動作鑑定資料儲存於分析資料儲存部D2(圖4、步驟S5)。Next, the vehicle behavior identifying unit 202 associates the motion identification data as the identification result with the situation data for identifying the behavior of the vehicle as described above, and stores the motion identification data in the analysis data storage unit D2 (FIG. 4, step S5).
分析資料儲存部D2針對各車輛的動作，系統地對動作已被上述車輛動作鑑定部202鑑定的狀況資料、以及與該狀況資料相對應的動作鑑定資料進行分類且進行儲存。具體而言，分析資料儲存部D2將相對應的狀況資料以及動作鑑定資料，儲存於針對險情等動作、碾壓等動作、以及顛簸動作而設定的儲存資料夾(folder)內。例如於分析資料儲存部內，設定有險情等動作資料夾、碾壓等動作資料夾、以及顛簸動作資料夾，上述險情等動作資料夾儲存著被鑑定為險情等動作的狀況資料，上述碾壓等動作資料夾儲存著被鑑定為碾壓等動作的狀況資料，上述顛簸動作資料夾儲存著被鑑定為顛簸動作的狀況資料，於各資料夾內，儲存有相對應的狀況資料以及動作鑑定資料。The analysis data storage unit D2 systematically classifies and stores the situation data that has been authenticated by the vehicle behavior identification unit 202 and the operation identification data corresponding to the situation data for the operation of each vehicle. Specifically, the analysis data storage unit D2 stores the corresponding status data and the operation identification data in a storage folder set for an operation such as a dangerous situation, a rolling operation, and a jolting operation. For example, in the analysis data storage unit, an action folder such as a dangerous situation, an action folder such as a crushing force, and a bumping action folder are set, and the action folder such as the dangerous situation stores status information that is identified as a dangerous situation, the above-described crushing, and the like. The action folder stores status data identified as actions such as crushing, and the bump action folder stores status data identified as bumps, and corresponding status data and action identification data are stored in each folder.
而且，分析資料儲存部D2對上述險情等動作資料夾進行細化或階層化，從而設定路肩停止動作資料夾，該路肩停止動作資料夾用以自險情等動作進一步分類出上述路肩停止動作且儲存著該路肩停止動作。Further, the analysis data storage unit D2 refines or stratifies the operation data folder such as the dangerous situation, thereby setting a shoulder stop operation data folder for further classifying the shoulder stop operation and storing the operation from a dangerous situation or the like. The shoulder of the road stops moving.
操作員(operator)對例如鍵盤(key board)或滑鼠(mouse)等的輸入單元進行操作，藉此，僅選擇以上述方式儲存於分析資料儲存部D2的狀況資料中的被分類為特定的車輛動作的狀況資料，將該狀況資料輸出至例如顯示器(display)等的輸出單元。或者，同樣地僅選擇被分類為特定的車輛動作的狀況資料，將該狀況資料傳送至其他分析裝置或記憶體等。An operator operates an input unit such as a keyboard (key board) or a mouse, whereby only the status information stored in the status data of the analysis data storage unit D2 in the above manner is classified as specific. The status data of the vehicle operation is output to the output unit such as a display. Alternatively, only the status data classified as the specific vehicle operation is selected, and the status data is transmitted to another analysis device, memory, or the like.
根據以上述方式構成的本實施形態的車輛動作分析系統，可根據前後加速度資料、左右加速度資料及上下加速度資料所示的前後加速度波形的標準偏差、左右加速度波形的標準偏差及上下加速度波形的標準偏差的大小關係，來鑑定車輛動作。因此，可不依賴於目視而鑑定狀況資料所示的車輛動作，從而不僅可將使用者的隨意的判斷予以排除而客觀地鑑定車輛動作，而且可減輕使用者的時間負擔、肉體負擔以及精神負擔。又，可不使用臨限值而根據前後加速度波形的標準偏差、左右加速度波形的標準偏差以及上下加速度波形的標準偏差的大小關係來鑑定車輛動作，因此，可獲得可靠性高的鑑定結果。According to the vehicle behavior analysis system of the present embodiment configured as described above, the standard deviation of the longitudinal acceleration waveform, the standard deviation of the left and right acceleration waveforms, and the standard of the vertical acceleration waveform can be used based on the longitudinal acceleration data, the left and right acceleration data, and the vertical acceleration data. The magnitude of the deviation is used to identify vehicle motion. Therefore, it is possible to identify the vehicle motion indicated by the situation data without depending on the visual observation, thereby not only eliminating the user's arbitrary judgment but also objectively identifying the vehicle motion, and reducing the time burden, the physical burden, and the mental burden of the user. Further, the vehicle operation can be identified based on the standard deviation of the longitudinal acceleration waveform, the standard deviation of the left and right acceleration waveforms, and the magnitude deviation of the standard deviation of the vertical acceleration waveform without using the threshold value. Therefore, a highly reliable identification result can be obtained.
再者，本發明並不限於上述實施形態。Furthermore, the present invention is not limited to the above embodiment.
例如，於上述實施形態中使用有各加速度資料，但若行車記錄器100包括陀螺儀感測器(gyrosensor)，則亦可使用作用於車輛的傾側角加速度、螺距角加速度以及偏航 角加速度的各角加速度資料的特徵量來鑑定車輛動作。For example, in the above embodiment, each acceleration data is used. However, if the driving recorder 100 includes a gyro sensor, the tilting angular acceleration, the pitch angular acceleration, and the yaw acting on the vehicle may be used. The feature quantity of each angular acceleration data of the angular acceleration is used to identify the vehicle motion.
又，於上述實施形態中，分析資料儲存部包括針對險情等動作、碾壓等動作、以及顛簸動作而設定的儲存資料夾，之後，簡單地選擇規定動作，但不限於此。例如，車輛動作分析裝置亦可更包括狀況資料抽出部，該狀況資料抽出部自儲存於分析資料儲存部內的狀況資料中，將表示規定的車輛動作的狀況資料予以抽出。而且，狀況資料抽出部亦可基於賦予狀況資料的動作鑑定資料，將如下的狀況資料予以抽出，該狀況資料是由操作員對例如鍵盤或滑鼠等的輸入單元進行操作來選擇，且表示規定的車輛動作。Further, in the above-described embodiment, the analysis data storage unit includes a storage folder set for an operation such as a dangerous situation, an operation such as rolling, and a jolting operation, and then simply selects a predetermined operation, but is not limited thereto. For example, the vehicle motion analysis device may further include a status data extracting unit that extracts status information indicating a predetermined vehicle motion from the status data stored in the analysis data storage unit. Further, the status data extracting unit may extract the following status data based on the action identification data of the status data, which is selected by the operator to operate the input unit such as a keyboard or a mouse, and indicates the regulation. Vehicle action.
而且，於上述實施形態中，將行車記錄器100所獲得的狀況資料收集至車輛動作分析裝置之後，藉由該車輛動作分析裝置來鑑定狀況資料所示的車輛動作，但於行車記錄器100中，亦同樣可鑑定狀況資料所示的車輛動作。例如，行車記錄器100包括狀況資料接收部以及車輛動作鑑定部，亦可僅將由上述車輛動作鑑定部鑑定為規定的動作(例如險情等動作)的狀況資料，移送且記錄至記憶體內的正規區域(正規記錄資料儲存部)。Further, in the above-described embodiment, after the situation data obtained by the drive recorder 100 is collected in the vehicle motion analysis device, the vehicle motion analysis device identifies the vehicle motion indicated by the situation data, but in the drive recorder 100. It is also possible to identify the vehicle action indicated by the status data. For example, the driving recorder 100 includes a status data receiving unit and a vehicle motion identifying unit, and may transfer and record only the status data identified as a predetermined operation (for example, an operation such as a dangerous situation) by the vehicle motion identifying unit to a regular area in the memory. (Regular Record Data Storage Department).
而且，亦可使用規定的臨限值，將被分類為險情等動作的狀況資料予以細化。例如，可考慮根據如下的值與臨限值的關係，將上述狀況資料予以細化，上述值是自加速度感測器所獲得的3軸合成加速度的最大值減去上下加速度最大值所得的值。Furthermore, it is also possible to use a predetermined threshold to refine the situation data classified as dangerous. For example, it is conceivable to refine the above-mentioned situation data according to the relationship between the value and the threshold value, which is a value obtained by subtracting the maximum value of the vertical acceleration from the acceleration of the 3-axis synthetic acceleration obtained by the acceleration sensor. .
又，為了更細化地鑑定碰撞事故，較佳為將險情等動 作鑑定為表示如下的值的動作，該值的左右加速度資料、上下加速度資料及前後加速度資料的特徵量，顯著地大於由通常的刹車引起的路面與輪胎(tyre)的接地面的摩擦力的特徵量。Moreover, in order to more accurately identify the collision accident, it is preferable to move the dangerous situation. The operation is identified as a value indicating a value of the left and right acceleration data, the vertical acceleration data, and the front and rear acceleration data of the value, which is significantly larger than the friction between the road surface and the ground surface of the tire caused by the normal brake. Feature amount.
而且，車輛動作分析裝置亦可使狀況資料與地圖資訊鏈結(link)。具體而言，車輛動作分析裝置使用狀況資料中所含的位置資料，將地圖資訊與狀況資料予以鏈結。藉此，例如可根據被鑑定為顛簸動作的狀況資料來推測出道路資訊(例如路面的劣化狀態等)，從而進行道路分析。Moreover, the vehicle motion analysis device can also link the status data to the map information. Specifically, the location information included in the usage status data of the vehicle motion analysis device links the map information and the status data. Thereby, road analysis can be performed by estimating road information (for example, deterioration state of the road surface, etc.) based on the situation data identified as the bump operation.
此外，亦可使用前後加速度資料的變動形態，對碰撞事故中的與其他車輛或構造物等發生碰撞時的動作、及與其他車輛發生碰撞的動作進行分類。亦即，對於上述險情等動作而言，為了鑑定追尾事故或被追尾事故，較理想的是根據左右加速度資料、上下加速度資料及前後加速度資料的特徵量的正負來進行鑑定。Further, it is also possible to classify the operation when a collision occurs with another vehicle or a structure or the like and the collision with another vehicle in a collision form in which the longitudinal acceleration data is changed. In other words, in order to identify the rear-end accident or the rear-end collision, it is preferable to perform the identification based on the positive and negative characteristics of the left and right acceleration data, the vertical acceleration data, and the longitudinal acceleration data.
而且，除了上述實施形態之外，亦可使用表示碾壓等動作的狀況資料中所含的方向燈資料，以如下的方式來對該狀況資料進行處理。亦即，亦可根據方向燈資料來對車輛的左拐或右拐進行判別，例如，確認在車輛V左拐時或右拐時是否已碾壓至路緣石等。Further, in addition to the above-described embodiment, the directional light data included in the status data indicating the operation such as rolling may be used to process the status data as follows. That is, it is also possible to discriminate the left or right turn of the vehicle based on the direction light data, for example, to confirm whether the curb has been crushed to the curb when the vehicle V turns left or when the right turn.
又，當判斷是已右拐且已碾壓至路緣石，還是已左拐且已碾壓至路緣石時，無方向燈資料，對左右加速度的波形的正負的順序進行觀察，藉此，可分清左右的輪胎的碾壓順序，因此，可進行判斷。Moreover, when it is judged that it has been turned right and has been crushed to the curb, or has been turned left and has been crushed to the curb, there is no direction lamp data, and the positive and negative sequence of the waveform of the left and right acceleration is observed, thereby The order of rolling of the left and right tires is distinguished, and therefore, the judgment can be made.
藉此，可容易地對駕駛人的駕駛傾向進行分析，該駕駛人的駕駛傾向例如是指在左拐時容易碾壓至路緣石，或在右拐時容易碾壓至路緣石。Thereby, the driving tendency of the driver can be easily analyzed, and the driving tendency of the driver is, for example, that it is easy to be crushed to the curb when turning left, or to be crushed to the curb when turning right.
又，亦可藉由對左右加速度的波形進行觀察來判斷出U形轉彎(turn)，因此，例如亦可判斷出是否為進行U形轉彎時的事故或險情。Further, it is also possible to determine the U-turn by observing the waveform of the right and left acceleration. Therefore, for example, it is also possible to determine whether or not an accident or a danger is caused when the U-turn is performed.
上述實施形態的加速度資料的特徵量為加速度波形的標準偏差，但可使用其他加速度波形的變異數(variance)，亦可使用加速度的平均值。此外，對於各加速度，亦可使用表示各動作特有的大小關係的運算值。The feature amount of the acceleration data in the above embodiment is the standard deviation of the acceleration waveform, but the variation of the other acceleration waveform may be used, and the average value of the acceleration may be used. Further, for each acceleration, an arithmetic value indicating a magnitude relationship unique to each operation may be used.
而且，本發明並不限於上述實施形態，當然可於不脫離本發明的宗旨的範圍內進行各種變形。It is to be understood that the invention is not limited thereto, and various modifications may be made without departing from the spirit and scope of the invention.
根據如上所述的構成的本發明，並不僅藉由目視來對狀況資料所示的車輛的動作進行分類，而是可自動地且以高可靠性來鑑定狀況資料所示的車輛動作。According to the present invention configured as described above, not only the movement of the vehicle indicated by the situation data is classified by visual observation, but the vehicle behavior indicated by the situation data can be automatically and highly reliably identified.
3‧‧‧偵測單元3‧‧‧Detection unit
4‧‧‧報告單元4‧‧‧Reporting unit
5‧‧‧輸入單元5‧‧‧Input unit
6‧‧‧通信單元(發送機)6‧‧‧Communication unit (transmitter)
7‧‧‧裝脫式記錄單元7‧‧‧ Loading and unloading unit
8‧‧‧資訊處理單元8‧‧‧Information Processing Unit
31‧‧‧拍攝單元31‧‧‧ Shooting unit
32‧‧‧加速度感測器32‧‧‧Acceleration sensor
33‧‧‧位置感測器33‧‧‧ position sensor
41‧‧‧發光體(LED)41‧‧‧Lighting body (LED)
81‧‧‧中央處理單元/CPU81‧‧‧Central Processing Unit/CPU
82‧‧‧內部記憶體/記憶體82‧‧‧Internal memory/memory
83‧‧‧I/O緩衝電路83‧‧‧I/O buffer circuit
100‧‧‧行車記錄器100‧‧‧ Driving recorder
200‧‧‧車輛動作分析裝置200‧‧‧Vehicle motion analysis device
201‧‧‧狀況資料接收部/部分201‧‧‧Status Data Receiving Department/Part
202‧‧‧車輛動作鑑定部/部分202‧‧‧Vehicle Action Identification Department/Part
CN‧‧‧連接器CN‧‧‧Connector
D1‧‧‧狀況資料儲存部/部分D1‧‧‧ Status Data Storage Department / Part
D2‧‧‧分析資料儲存部/部分D2‧‧‧Analytical data storage/part
S1~S5‧‧‧步驟S1~S5‧‧‧Steps
V‧‧‧車輛/汽車V‧‧‧Vehicles/Cars
圖1是模式性地表示本實施形態的車輛動作分析系統的圖。Fig. 1 is a view schematically showing a vehicle behavior analysis system according to the embodiment.
圖2是表示本實施形態的行車記錄器的構成要素的圖。Fig. 2 is a view showing the components of the drive recorder of the embodiment.
圖3是本實施形態的車輛動作分析裝置的功能構成圖。Fig. 3 is a view showing the functional configuration of a vehicle behavior analysis device according to the present embodiment.
圖4是表示本實施形態的車輛動作分析裝置的動作的 流程圖。4 is a view showing the operation of the vehicle behavior analysis device according to the embodiment; flow chart.
圖5是表示本實施形態中的車輛動作與各加速度的特徵量的對應關係的圖。Fig. 5 is a view showing a correspondence relationship between vehicle behavior and feature amounts of respective accelerations in the embodiment.
100‧‧‧行車記錄器100‧‧‧ Driving recorder
200‧‧‧車輛動作分析裝置200‧‧‧Vehicle motion analysis device
V‧‧‧車輛/汽車V‧‧‧Vehicles/Cars
Claims (6)
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| JP2010215479 | 2010-09-27 |
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| JP6027743B2 (en) | 2016-11-16 |
| SG188578A1 (en) | 2013-04-30 |
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| WO2012043388A1 (en) | 2012-04-05 |
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