TW201404636A - 遠程識別機動車輛及監測駕駛員行爲之電子感測器資料的評估 - Google Patents
遠程識別機動車輛及監測駕駛員行爲之電子感測器資料的評估 Download PDFInfo
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Abstract
一個計算裝置連接到一個機動車輛的診斷埠或通訊埠,以獲取車輛感測器資料,舉例而言,是從為了其他原因而典型安裝在機動車輛上之多樣的壓力、溫度、氧、燃料和其他的感測器來獲取。獲取的感測器資料乃無線傳送到一個遠程伺服器,在此則獲取的感測器資料可以與儲存之感測器資料的資料庫比較以識別機動車輛。描述的額外功能性則是權衡上傳的感測器資料。感測器資料可以接近即時地上傳到伺服器,及/或局部緩衝並且藉由週期性或片段之推或拉的通訊協定而上傳。
Description
本揭示關於動力車輛,更特別而言是關於機動車輛,並且關於車輛和中央伺服器之間的資料通訊而能夠做到多樣有利的應用。
相關申請案
本申請案係主張於2012年6月8日所提申之美國臨時專利申請案第61/657,192號的一個非臨時案,並且以引用方式納入本文中。
版權聲明
© 2012到2013艾比奎特公司。此專利文件之揭示內容的一部分係含有受到版權保護的資料。該版權所有人不反對任何人對該專利文件或該專利揭示內容進行複印重製,如同在專利暨商標局的專利檔案或記錄中,但是在其他方面無論如何皆保有所有的版權。37 CFR§ 1.71(d)。
普遍的控制器區域網路(controller area network,CAN)匯流排是車輛匯流排標準,其設計成允許微控制器和裝置彼此在車輛裡通訊而不用主電腦。CAN匯流排是用於OBD-II車輛診斷標準之五種協定中的一種。OBD-II標準自從1996年便已強制用於美國境內販售的所有汽車和輕型卡車,並且EOBD標準自從2001年便已強制用於歐盟境內販售的所有汽油車
輛以及自從2004年已強制用於歐盟境內販售的所有柴油車輛。CAN是用於連接電子控制單元(electronic control unit,ECU)的多主式廣播串列匯流排標準。
雖然每個節點能夠發送和接收訊息,但不是同時的。訊息主要由ID(identifier,識別符)所構成,其代表訊息的優先次序,並且高達八個資料位元組。它是串列傳送到匯流排上。這訊號樣式乃編碼成不歸零(non-return-to-zero,NRZ)並且由所有的節點來感測。由CAN網路所連接的裝置典型是感測器、致動器和其他控制裝置。一般而言,這些裝置不是直接連接到匯流排,而是經由主處理器和CAN控制器。無論如何,CAN網路乃限制在機動車輛。
以下是本發明的綜述以便提供對本發明某些態樣的基本理解。這綜述不打算識別本發明的關鍵/緊要的元件或限制本發明的範圍。其單純目的是要以簡化形式來呈現本發明的某些概念,而做為稍後提出之更詳細描述的序言。
一般而言,雖然機載電子通訊於機動車輛中持續演變,但是它們仍受限於車輛中。本揭示的一個特色將機載網路、感測器和其他節點的多個態樣延伸到遠程伺服器位置。
於本揭示的另一態樣,遠程伺服器可以從機動車輛獲取資料,包括機載感測器資料。
於再一態樣,感測器資料可以用於在遠程伺服器來遠程識別機動車輛。
於又一態樣,感測器資料可以用於在遠程伺服器來遠程識別機動車輛的目前駕駛員。
本發明的額外態樣和優點將從底下參考附圖所詳細敘述的較佳實施例而變得明顯。
100‧‧‧機動車輛的資料通訊埠
104‧‧‧智慧型手機
110‧‧‧蜂巢式資料通訊網路
120‧‧‧遠程伺服器
122‧‧‧歷史資料
130‧‧‧供備管理器
202~250‧‧‧從遠程車輛收集電子感測器資料的過程步驟
圖1是簡化方塊圖,其示範與本揭示一致的車隊管理監測系統之一範例的選擇構件。
圖2示範基於伺服器的過程,其從遠程車輛收集電子感測器資料。
一個問題起源於某些車輛上的資料通訊埠不提供車輛識別號碼(vehicle identification number,VIN),其係獨特的識別符。無獨特地識別車輛之能力,則車隊管理系統便嚴重受限。舉例而言,它無法實施自動化供備系統以將校正參數快速供備於車輛系統。於某種情形,此種參數可以是車輛行為所獨有的。下載的參數或其他資料可以由機載軟體所使用。於某些實施例中,機載軟體或系統可以利用駕駛員行為演算法來監測駕駛員行為。此外,若不藉由某些其他方式而手動的將資料關聯於車隊車輛(如果可能的話),自動化系統就無法從車輛收集資料。若能獨特地識別每個車輛,則可以從遠程伺服器實施多樣的有利功能。
於實施例中,計算裝置可以連接到機動車輛的診斷埠或通訊埠以獲取車輛感測器資料,舉例而言是從為了其他原因而典型安裝在機動車輛上之多樣的壓力、溫度、氧、燃料和其他的感測器來獲取。計算裝置
可以是行動裝置,例如智慧型手機。該裝置可以連接到埠,舉例而言為OBD埠。該裝置可以藉由纜線或短程無線連接(譬如Bluetooth®連接)而連接到機載網路。
獲取的感測器資料可以經由智慧型手機而無線傳送到遠程伺服器,在此則獲取的感測器資料可加以儲存和/或與儲存之感測器資料的資料庫比較,以識別機動車輛和用於其他功能。獲取的感測器資料也可以經由機載式或嵌入式網路存取裝置(network access device,NAD)來傳送。
感測器資料可以接近即時地上傳到伺服器,以及/或者局部緩衝並且藉由週期性或片段之推或拉的通訊協定而上傳。獲取的感測器資料可以儲存在中央伺服器。獲取的資料可以儲存在耦合於中央伺服器的資料庫。它可以用於形成儲存的基線資料。判定的車輛ID可以由後端伺服器系統所使用來比較車輛的歷史操作,以判定是否有關聯於其行為的任何異常。附帶而言,車輛ID可以用於判定是否有任何異常可能是由操作車輛的駕駛員所引起的,如下面所進一步解釋。此外,車輛ID可以用於從伺服器供備資料或軟體到車輛,特別是使之適用於目前條件。
於圖1,簡化方塊圖示範了車隊管理或駕駛員行為監測系統之一範例的主要構件。於此範例,機動車輛的資料通訊埠100或其他介面乃經由纜線或無線連接而耦合到計算和通訊裝置,例如使用者的「智慧型手機」104。舉例而言,雖然可以在可攜式裝置和車輛埠/轉接器之間使用Bluetooth®連接或類似的短程無線連接,但是這連接可以經由任何可得的方式來為之。
於實施例中,智慧型手機104經由蜂巢式資料通訊網路110
(亦稱為「行動網路」)以及IP閘道器(若需要的話)而與遠程伺服器(「後端系統」)120來通訊,該伺服器接收、儲存和維持幾種資料。一種資料可以是歷史資料122。歷史資料122可以包括但不限於以下範例:(a)用於車輛識別的感測器資料;(b)駕駛員和車輛行為的歷史資料;(c)用於下載到車輛的校正參數和其他資料;以及(d)地理位置資料,舉例而言是由內部或外部GPS感測器所提供。除了歷史資料,伺服器系統還可以包括供備管理器130以在車輛中供備計算裝置。車輛中的計算裝置可以包括可攜式裝置(如所示範),或者於另一實施例則是為了多樣目的而嵌入車輛的一或更多個處理器(未顯示)。
於某些實施例中,儲存的基線感測器資料包括從對應的機動車輛於至少一已知穩定狀態條件期間所獲取的感測器資料。為了示範,「第一穩定狀態條件」可以定義在預定時間窗裡,舉例而言為在車輛引擎從冷發動而啟動之後的5秒。這可以稱為冷條件。
「第二穩定狀態條件」可以定義在車輛引擎連續操作了至少預定最小時間到期之後。舉例而言,這時間可以是在5或10分鐘的等級。它可以稱為「熱」或運作條件。於某些實施例中,儲存的基線感測器資料包括從對應的機動車輛於冷條件期間所獲取的感測器資料。於某些實施例中,儲存的基線感測器資料包括從對應的機動車輛於熱或運作條件期間所獲取的資料。一組多個感測器讀數(舉例而言為來自三或四個不同感測器的讀數)可以儲存在伺服器並且用於識別遠程車輛。於某些實施例中,感測器讀數可以是冷條件、熱條件或此二種的組合。
舉例示範而非限制而言,用於提供資料的車輛感測器可以包
括如下:
‧引擎冷媒溫度
‧引擎空氣溫度
‧燃料軌壓力
‧機油溫度
‧絕對油門位置極限
‧引擎怠速下的每分鐘轉數(RPM)
‧λ排放氧感測器電壓
那麼舉例來說,引擎怠速下的每分鐘轉數可以在冷條件下以及相同度量在熱條件下來獲取。相同的資料(熱和冷)可以獲取於燃料軌壓力和機油溫度,而總共有九個測量。這種資料組可以用於識別車輛。流逝的時間可以用來將冷描述為熱。或者,改變速率可以用於指出運作(穩定狀態)條件。可以使用其他的感測器以附加或取代所述者。較大量的感測器一般將更能分辨不同的車輛。獲取之資料與先前儲存之基線資料的比較則可以使用已知的資料庫查詢科技來完成。可以使用模糊匹配。
於某些實施例,從遠程車輛獲取感測器資料乃包括獲取感測器資料於至少三個前述穩定狀態的感測器輸出值;以及其中該比較步驟包括比較至少三個穩定狀態的感測器輸出值與對應的儲存基線資料。
因此,於本揭示的某一態樣,識別車輛的方法可以包括以下的組合:定出感測器資料值的特徵,該資料值係在已知穩定狀態的車輛條件下而讀取自車輛資料通訊埠;以及隨著車輛的狀態係以先前定出特徵的速率和改變方向而正在改變,定出特定感測器值的特徵。車輛感測器測量
的正確度最好是在≦+/- 1正確度的等級。
其他的度量可以包括動態測量條件。動態測量的範例可以包括而不限於以下:
‧映對到先前記錄之引擎冷發動溫度的引擎啟動怠速
‧在指定之熱引擎溫度的引擎怠速
‧引擎溫度從冷發動改變到熱溫度的時間,其係相對於先前記錄的從冷溫度改變到熱溫度所花之時間的平均引擎負載
‧GPS位置以區別具有類似感測器資料值的二個車輛。
於實施例中,我們提議部分基於穩定狀態的感測器輸出值來定出車輛的特徵。這會涉及測量在穩定狀態之車輛連接下由資料通訊埠所提供的車輛感測器資料,例如但不限於以下:「引擎冷媒溫度」。其典型測量於-40℉到419℉(-40℃到215℃)的範圍。這感測器典型具有+/- 5%的正確度,其等於相對於真實的冷媒溫度而言導致不同的感測器輸出有+22.95℉(+5℃)到-22.95℃(-5℃)的偏差。由於有這來自不同感測器的輸出偏差,該輸出可以連同其他類型的感測器輸出來使用以發展出車輛的「指紋」。
「引擎空氣溫度」。其典型測量於-40℉到419℉(-40℃到215℃)的範圍。這感測器典型具有+/- 5%的正確度,其等於相對於引擎吸入空氣的真實溫度而言可以導致不同的感測器有+22.95℉(+5℃)到-22.95℉(-5℃)的偏差。由於有這來自不同感測器的輸出偏差,該輸出可以連同其他類型的感測器輸出來使用以發展出車輛的「指紋」。
「燃料軌壓力」。不同品牌和樣式的車輛將大大變化。對於相
同品牌和樣式的車輛而言,不同的車輛將會有偏差,其係燃料壓力調節器和燃料壓力感測器之正確度的函數。即使這二個裝置是1%的正確,總正確度將會是+/- 2%。這是可測量的感測器輸出而為特定車輛所獨有的。
「機油溫度」。不同品牌和樣式的車輛將大大變化。對於相同品牌和樣式的車輛而言,不同的車輛將會有偏差,其係機油黏滯度、引擎區塊質量、熱逸散的函數,並且機油溫度的正確度典型為+/- 5%。這是可測量的感測器輸出而為特定車輛所獨有的。
「絕對油門位置」。其測量於0到100%的最大油門開口。對於相同的車輛品牌和樣式或對於不同的車輛品牌和樣式而言,最小值或可是獨特的。這是由於機械關閉的油門極限之緣故,其通常是由空氣怠速設定螺絲或油門鑄造關閉位置止擋所控制。
「引擎每分鐘轉數」。這值經常是在真實之引擎每分鐘轉數的1%裡;然而,引擎每分鐘轉數是在任何穩定狀態條件下影響引擎每分鐘轉數之許多車輛特定變數的因素。這些車輛特定的變數包括引擎和空氣在穩定狀態條件下的溫度、油門上游空氣壓降(由於空氣過濾器清潔度的緣故)、每個引擎汽缸於燃料和空氣燃燒過程期間正在如何適當產生汽缸壓力、閉路引擎怠速下的每分鐘轉數(在此已藉由引擎管理系統而獲得想要之測量的空氣燃料比例,其係相對於所用燃料類型在想要之引擎每分鐘轉數下的計量空氣燃料比例)。這所想要的引擎每分鐘轉數可以是引擎管理系統學習輸出的產物,其導致引擎在該穩定狀態條件下有最佳的排放輸出,並且它將隨著不同的車輛而變化。
「λ感測器」。對於用於車輛的特定燃料來說,λ感測器電
壓輸出範圍可以隨著不同的感測器而變化,這是由於感測器老化、感測器正確度、氧參考電池之感測器製造技術的緣故。可以測量之作用λ感測器的數目可以用於判定具有不同汽缸數目之引擎的車輛品牌和樣式的差異,或判定負責控制相對於引擎排放的引擎輸出之引擎管理系統的複雜差異。於實施例中,幾種前述的度量乃組合使用以判定車輛的獨特識別符或概況。
於另一態樣,我們定出車輛動態狀態改變的特徵以判定感測器輸出值的改變速率概況。舉例而言:
1.隨著車輛溫度從冷發動改變到預先定義的熱操作溫度之引擎怠速下的每分鐘轉數。
2.機油溫度改變,其相對於引擎冷媒溫度從冷發動引擎溫度改變到預先定義的熱引擎溫度。
某些實施例因此可以綜述如下:識別機動車輛之電腦實施的方法包括:於車輛的第一穩定狀態操作條件期間,從車輛獲取第一感測器資料;於相同車輛的第二穩定狀態操作條件期間,從車輛獲取第二感測器資料;其中第一和第二感測器資料各包括從車輛所機載安裝之不少於三個感測器所獲取的資料,而第一和第二資料係在不同的時間而獲取自相同感測器;以及儲存獲取的第一和第二感測器資料,如此以形成基線感測器資料以用於後續識別車輛。
與本揭示一致的方法可以進一步包括:比較第一和第二感測器資料與儲存的基線感測器資料;以及基於該比較步驟而形成車輛的識別符。
圖2是簡化流程圖,其示範基於伺服器的過程200而從遠程
車輛收集電子感測器資料。於該圖,無線通訊鏈路202乃形成在中央伺服器(舉例而言為車隊管理系統)和遠程車輛之間。鏈路可以是在無線遠距通訊網路上。鏈路可以利用合規頻帶發信而在聲音頻道上傳送資料。鏈路可以利用資料服務。
如果感測器資料是在車輛緩衝並且就緒(決定204),則它被上傳(方塊206)。如果它未就緒,則過程可以在208形成迴圈。上傳的資料可以在過程中經歷錯誤修正,並且可選用的被取消以幫助確保有正確的資料(方塊210)。
在資料就緒之後,耦合於伺服器的資料庫(舉例而言為基線資料庫)可加以查詢以找出匹配資料(方塊220)。匹配的基線感測器資料可以用於識別車輛。如果發現獨特的匹配(決定222),則資料可以添加到資料庫(方塊230)。該過程於某些情況下可以經由240形成迴路以獲取額外的資料。如果起初在222並未發現獨特的匹配,則舉例而言可以基於獲取每個車輛的對應位置資料而努力弄清楚這些報告類似感測器值的多個車輛。位置資料可以從車輛中的GPS接收器而獲取。GPS接收器可以耦合於機載網路,如此則位置資料是可存取的。於使用行動裝置(例如智慧型手機)來與伺服器通訊的情況,智慧型手機嵌入式GPS接收器可以用於獲取車輛的位置。如果弄清楚做得不成功(決定方塊232),則可以要求額外的感測器資料(方塊250),並且經由迴圈252而重複匹配過程。
<駕駛員行為>
本揭示的另一特色涉及獲取感測器資料,其可以接近即時的加以緩衝、儲存或傳送,並且分析該感測器資料以推論駕駛員行為的特徵。
對於給定的駕駛員,資料可以隨著時間而累積以形成概況。偏離於概況可以指出駕駛員由於生理或其他因素而受損。基於感測器資料的概況也可以用於推論目前車輛駕駛員的身分。
<燃料效率>
本揭示的另一特色涉及獲取感測器資料,並且基於儲存的資料來計算機動車輛的英里率或燃料效率。英里率是指每加侖的液態燃料或每千瓦-小時的電能(對於電動車輛而言)所行駛的英里數。使用上述技術,則可以判定每個車輛在多樣條件下的燃料效率。偏離正常的燃料效率可以指出須要注意的保修問題。如果不存在保修問題,則計算出的平均燃料效率差異也可以用於獨特的識別車輛(如果駕駛員行為可以排除而不是燃料效率變化之原因的話)。
於某些情況,如感測器資料所反映的車輛效能改變可能是由於駕駛員行為而非保修問題所造成。這二個原因之間的分辨可以藉由分析隨著時間所獲取的資料而達成。於其他情況,極不同的車輛導致極不同的讀數,而非駕駛員。
熟於此技術者將明顯知道可以對上述實施例的細節做出許多改變,而不偏離本發明背後的原理。本發明的範圍因此應該僅由下面的申請專利範圍來決定。
100‧‧‧機動車輛的資料通訊埠
104‧‧‧智慧型手機
110‧‧‧蜂巢式資料通訊網路
120‧‧‧遠程伺服器
122‧‧‧歷史資料
130‧‧‧供備管理器
Claims (20)
- 一種遠程識別機動車輛的方法,其包括:(a)從安裝於車輛的多個電子感測器而電子獲取感測器資料;(b)經由無線鏈路而從車輛傳送獲取的感測器資料到遠程伺服器;(c)在遠程伺服器中,接收獲取的感測器資料並且比較獲取的感測器資料與儲存的基線資料;以及(d)基於該比較而識別機動車輛。
- 根據申請專利範圍第1項的方法,其中儲存的基線資料包括先前獲取自多個機動車輛的每一者所機載之多個感測器的感測器資料。
- 根據申請專利範圍第2項的方法,其中對於選擇的車輛而言,儲存的基線資料包括從選擇自以下感測器所構成的群組中之至少三個感測器所獲取的資料:‧引擎冷媒溫度‧引擎空氣溫度‧燃料軌壓力‧機油溫度‧絕對油門位置極限‧引擎怠速下的每分鐘轉數‧λ排放氧感測器電壓。
- 根據申請專利範圍第3項的方法,其中對應於至少一所選感測器之儲存的基線資料包括在對應機動車輛之第一操作條件下所獲取的第一資料,以及包括在對應機動車輛之第二操作條件下所獲取的第二資料。
- 根據申請專利範圍第4項的方法,其中對應機動車輛的第一操作條件是冷條件,並且對應機動車輛的第二操作條件是穩定狀態操作條件。
- 根據申請專利範圍第5項的方法,其中穩定狀態操作條件乃定義成在車輛啟動之後的預定時間。
- 根據申請專利範圍第3項的方法,其包括定出車輛動態狀態改變的特徵,以判定給定車輛之至少一所選感測器的改變速率概況,並且將動態狀態改變概況添加到儲存的基線資料以識別對應的車輛。
- 根據申請專利範圍第7項的方法,其中動態狀態改變是從冷發動條件到預先定義的熱操作溫度而判定。
- 根據申請專利範圍第3項的方法,其中該識別機動車輛包括基於獲取每個車輛的對應位置資料,而弄清楚這些報告類似感測器值的多個車輛。
- 根據申請專利範圍第9項的方法,其中該獲取每個車輛的對應位置資料是從位於個別車輛的GPS接收器來獲取。
- 一種電腦實施的方法,其包括:從遠程機動車輛獲取電子感測器資料;重複獲取步驟,以隨著選擇的時間而累積電子感測器資料;將累積的電子感測器資料關聯於基線感測器資料的資料庫,以識別對應的機動車輛;分析用於對應車輛駕駛員之累積的電子感測器資料,以形成關聯於識別之機動車輛和對應車輛駕駛員的駕駛員概況;以及將駕駛員概況儲存於多個駕駛員概況的中央伺服器資料庫。
- 如申請專利範圍第11項的方法,其中電子感測器資料是從機動車輛 無線傳送到中央伺服器。
- 如申請專利範圍第12項的方法,其中電子感測器資料乃獲取於機動車輛的機載網路上以傳送到中央伺服器。
- 如申請專利範圍第12項的方法,其中電子感測器資料乃經由連接到機動車輛的OBD埠而獲取,以透過無線遠距通訊鏈路傳送到中央伺服器。
- 如申請專利範圍第14項的方法,其包括在耦合於機動車輛之OBD埠的行動裝置中獲取資料,並且於無線遠距通訊鏈路中將獲取的資料從行動裝置實質立即的傳送到中央伺服器。
- 如申請專利範圍第14項的方法,其包括實質即時傳送電子感測器資料到中央伺服器。
- 如申請專利範圍第11項的方法,其進一步包括:從遠程機動車輛獲取目前的電子感測器資料;以及比較新的電子感測器資料與多個駕駛員概況的中央伺服器資料庫,以識別目前車輛的駕駛員。
- 如申請專利範圍第11項的方法,其進一步包括比較新的電子感測器資料與資料庫中先前儲存的感測器資料,以偵測駕駛員的行為改變。
- 如申請專利範圍第11項的方法,其中對於選擇的車輛而言,駕駛員概況包括從選擇自以下感測器所構成的群組中之至少三個感測器所獲取的資料:‧引擎冷媒溫度‧引擎空氣溫度‧燃料軌壓力 ‧機油溫度‧絕對油門位置極限‧引擎怠速下的每分鐘轉數‧λ排放氧感測器電壓。
- 如申請專利範圍第11項的方法,其進一步包括比較新的電子感測器資料與資料庫中先前儲存的感測器資料,以偵測對應車輛的保修問題。
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WO2013184877A2 (en) | 2013-12-12 |
CN104364827B (zh) | 2016-06-08 |
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