TWI820471B - Vehicle driving risk assessment system - Google Patents
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Abstract
一種車輛駕駛風險評估系統,包含行車時間分析單元、駕駛行為分析單元,及風險評估單元。該行車時間分析單元可分析行車資訊以得到手動駕駛與自動駕駛的所有時間區段。該駕駛行為分析單元可分析行車資訊以取得手動駕駛行為參數與自動駕駛行為參數。該風險評估單元可分析手動駕駛行為參數與自動駕駛行為參數,以評估駕駛人的行車事故風險,藉此設計,使得本發明車輛駕駛風險評估系統適用於導入駕駛行為車險應用服務,而能用於對駕駛具備自動駕駛功能之車輛的駕駛人進行更合理的車險保費估算。A vehicle driving risk assessment system includes a driving time analysis unit, a driving behavior analysis unit, and a risk assessment unit. The driving time analysis unit can analyze driving information to obtain all time segments of manual driving and automatic driving. The driving behavior analysis unit can analyze driving information to obtain manual driving behavior parameters and automatic driving behavior parameters. The risk assessment unit can analyze manual driving behavior parameters and automatic driving behavior parameters to assess the driver's driving accident risk. This design makes the vehicle driving risk assessment system of the present invention suitable for introducing driving behavior car insurance application services, and can be used for Provide more reasonable auto insurance premium estimates for drivers who drive vehicles with autonomous driving capabilities.
Description
本發明是有關於一種風險評估系統,特別是指一種用於評估交通事故風險之車輛駕駛風險評估系統。 The present invention relates to a risk assessment system, and in particular, to a vehicle driving risk assessment system for assessing traffic accident risks.
駕駛行為車險應用服務(Usage Based Insurance,簡稱UBI)是一種伴隨著車輛監控感測科技的發展所衍生出來的新型車輛保險機制,UBI車險的評估設計,是根據車輛上之感測設備所記錄的行車資訊,來分析駕駛人的駕駛行為,並根據分析得到的各種駕駛行為來評估該為駕駛人的事故風險,藉以訂定車險保費。 Driving behavior car insurance application service (Usage Based Insurance, referred to as UBI) is a new vehicle insurance mechanism derived from the development of vehicle monitoring and sensing technology. The evaluation design of UBI car insurance is based on the data recorded by the sensing equipment on the vehicle. Driving information is used to analyze the driver's driving behavior, and based on the various driving behaviors analyzed, the driver's accident risk is assessed to set auto insurance premiums.
但近年來,許多車輛都已經開始導入自動駕駛技術,例如定速巡航、自動跟車、自動導航駕駛與自動停車等,以致於在駕駛人開車期間,可能有部分時間是採取手動駕駛模式,而部分時間是採取自動駕駛模式,如何有效評估具有自駕功能之車輛的駕駛人的事故風險,是目前保險業界亟待解決的問題。 However, in recent years, many vehicles have begun to introduce automatic driving technologies, such as cruise control, automatic car following, automatic navigation driving and automatic parking, etc., so that the driver may be in manual driving mode part of the time while driving. Self-driving mode is used part of the time. How to effectively assess the accident risk of drivers of vehicles with self-driving functions is an urgent issue in the insurance industry.
因此,本發明的目的,即在提供一種能改善先前技術的 至少一個缺點的車輛駕駛風險評估系統。 Therefore, the object of the present invention is to provide a method that can improve the prior art. At least one shortcoming of the vehicle driving risk assessment system.
於是,本發明車輛駕駛風險評估系統,適用於分析一車輛之一個行車資訊,以評估該車輛之駕駛人的行車事故風險。該車輛駕駛風險評估系統包含一個行車時間分析單元、一個駕駛行為分析單元,及一個風險評估單元。 Therefore, the vehicle driving risk assessment system of the present invention is suitable for analyzing a piece of driving information of a vehicle to evaluate the driving accident risk of the driver of the vehicle. The vehicle driving risk assessment system includes a driving time analysis unit, a driving behavior analysis unit, and a risk assessment unit.
該行車時間分析單元可用以分析該行車資訊以得到對應手動駕駛的所有手駕時間區段、對應自動駕駛的所有自駕時間區段、一個由所有手駕時間區段加總得到之手動駕駛總時間(TH),及一個由所有自駕時間區段加總得到之自動駕駛總時間(TM)。 The driving time analysis unit can be used to analyze the driving information to obtain all hand-driving time sections corresponding to manual driving, all self-driving time sections corresponding to automatic driving, and a total manual driving time obtained by summing up all hand-driving time sections. (T H ), and a total autonomous driving time ( TM ) obtained by summing up all self-driving time segments.
該駕駛行為分析單元可用以分析該行車資訊,以取得每一手駕時間區段所存在的所有手動駕駛行為參數,以及取得每一自駕時間區段所存在的所有自動駕駛行為參數。 The driving behavior analysis unit can be used to analyze the driving information to obtain all manual driving behavior parameters that exist in each manual driving time segment, and to obtain all automatic driving behavior parameters that exist in each self-driving time segment.
該風險評估單元具有一個透過機器學習建立的風險評估模型,且包括一個事故風險評估模組,該事故風險評估模組可透過該風險評估模型分析所有手駕時間區段之所有手動駕駛行為參數、所有自駕時間區段的所有自動駕駛行為參數、該手動駕駛總時間,及該自動駕駛總時間,以得到對應該駕駛人與車輛的一個手駕事故發生機率(PH)、一個手駕事故損失估值(LH)、一個自駕事故發生機率(PM),及一個自駕事故損失估值(LM)。 The risk assessment unit has a risk assessment model established through machine learning, and includes an accident risk assessment module. The accident risk assessment module can analyze all manual driving behavior parameters in all driving time periods through the risk assessment model, All self-driving behavior parameters of all self-driving time segments, the total manual driving time, and the total self-driving time are used to obtain the probability of a hand-driving accident (P H ) and the loss of a hand-driving accident corresponding to the driver and the vehicle. valuation (L H ), a self-driving accident probability (P M ), and a self-driving accident loss valuation (L M ).
本發明之功效在於:透過對該車輛於啟動該自動駕駛模 式期間與該手動駕駛模式期間的行車資訊進行分析,藉以取得在自動駕駛模式期間與手動駕駛模式期間之各種自動駕駛行為參數的設計,使得本發明車輛駕駛風險評估系統適用於導入駕駛行為車險應用服務(Usage Based Insurance,UBI),而能用於對駕駛具備自動駕駛功能之車輛的駕駛人進行更合理的車險保費估算。 The effect of the present invention is: by activating the automatic driving mode for the vehicle The driving information during the automatic driving mode and the manual driving mode is analyzed to obtain the design of various automatic driving behavior parameters during the automatic driving mode and the manual driving mode, so that the vehicle driving risk assessment system of the present invention is suitable for introducing driving behavior auto insurance applications. Service (Usage Based Insurance, UBI), which can be used to provide more reasonable auto insurance premium estimates for drivers who drive vehicles with autonomous driving capabilities.
200:車輛駕駛風險評估系統 200: Vehicle driving risk assessment system
3:行車時間分析單元 3: Driving time analysis unit
4:駕駛行為分析單元 4: Driving behavior analysis unit
5:風險評估單元 5:Risk Assessment Unit
501:取得行車資訊 501: Obtain driving information
502:資料分類 502: Data classification
503:手動駕駛模式風險評估 503: Manual driving mode risk assessment
504:自動駕駛模式風險評估 504: Autonomous driving mode risk assessment
505:綜合風險評估 505: Comprehensive Risk Assessment
506:保險費用估算 506: Insurance cost estimate
507:最佳駕駛模式的分析與建議 507: Analysis and suggestions for optimal driving modes
51:事故風險評估模組 51:Accident Risk Assessment Module
52:事故等級評估模組 52:Accident Level Assessment Module
53:保費估算模組 53: Premium estimation module
6:駕駛模式推薦單元 6: Driving mode recommendation unit
701:車輛 701:Vehicle
702:行動裝置 702:Mobile device
801:即時行車資訊資料庫 801: Real-time driving information database
802:歷史交通事故資訊資料庫 802: Historical traffic accident information database
900:電子裝置 900: Electronic devices
901:顯示器 901:Display
本發明的其他的特徵及功效,將於參照圖式的實施方式中清楚地呈現,其中:圖1是一個架構示意圖,說明本發明車輛駕駛風險評估系統的一個實施例實施建構在一個電子裝置,且搭配一個即時行車資訊資料庫與一個歷史交通事故資訊資料庫使用時的情況:圖2是該實施例的功能方塊圖;及圖3是一個步驟流程圖,說明該實施例進行車輛駕駛風險評估時的步驟。 Other features and effects of the present invention will be clearly presented in the embodiments with reference to the drawings, in which: Figure 1 is an architectural schematic diagram illustrating an embodiment of the vehicle driving risk assessment system of the present invention implemented on an electronic device; And when used with a real-time driving information database and a historical traffic accident information database: Figure 2 is a functional block diagram of this embodiment; and Figure 3 is a step flow chart illustrating vehicle driving risk assessment in this embodiment time steps.
參閱圖1、2,本發明車輛駕駛風險評估系統200的一個實施例,適用於透過電子電路、韌體及/或程式軟體實施建構在一個電子裝置900上,可用以取得一具備自動駕駛功能之車輛701經由網際網路及/或行動通訊網路傳送至一個即時行車資訊資料庫
801的行車資訊,可分析該行車資訊以評估該車輛701之駕駛人的行車事故風險與該駕駛人所應繳交的車險保費,以及分析適用於該駕駛人之駕駛模式,並對該駕駛人持用之行動裝置702發送分析得到之駕駛模式建議。該電子裝置900具有一個顯示器901。所述行車資訊彙整有安裝在該車輛701上之各種感測器所測得之資料,以及各種記錄器所記錄之資料,所述行車資訊之資料例如但不限於在自動駕駛模式與手動駕駛模式下之行車影像資料、前車車距資料、後車車距資料、油門踩踏資料、煞車踩踏資料,以及行車速度資料等。
Referring to Figures 1 and 2, one embodiment of the vehicle driving
該車輛駕駛風險評估系統200包含一個行車時間分析單元3、一個駕駛行為分析單元4、一個風險評估單元5,及一個駕駛模式推薦單元6。
The vehicle driving
該行車時間分析單元3可用以分析該行車資訊,以得到對應手動駕駛模式的所有手駕時間區段、對應自動駕駛模式的所有自駕時間區段、一個由所有手駕時間區段加總得到之手動駕駛總時間(TH),及一個由所有自駕時間區段加總得到之自動駕駛總時間(TM)。
The driving
該駕駛行為分析單元4可用以分析該行車資訊,以取得每一手駕時間區段所存在的所有手動駕駛行為參數,以及取得每一自駕時間區段所存在的所有自動駕駛行為參數。本實施例中,該駕駛
行為分析單元4是根據預先透過機器學習所建立之駕駛行為分析模型,藉由影像分析技術與大數據統計分析等方式,取得該駕駛人在手動駕駛該車輛701之每一個手駕時間區段內所做出的各種手動駕駛行為,以及各種手動駕駛行為的發生次數與頻率,藉以得到所述手動駕駛行為參數。並取得該車輛701於每一個自駕時間區段內所做出的各種自動駕駛行為,以及各種自動駕駛行為的發生次數與頻率,藉以取得所述自動駕駛行為參數。
The driving
在本實施例中,所述手動駕駛行為參數與所述自動駕駛行為參數中的所述手動駕駛行為與自動駕駛行為,例如但不限於行車速度變化、緊急煞車、重踩油門、前車車距、後車車距、車道變換、車道偏移,以及闖紅燈等。 In this embodiment, the manual driving behavior and the automatic driving behavior among the manual driving behavior parameters and the automatic driving behavior parameters include, but are not limited to, changes in driving speed, emergency braking, heavy accelerator pedal, and distance from the vehicle in front. , distance between vehicles behind, lane changes, lane deviations, and running red lights, etc.
該風險評估單元5包括一個事故風險評估模組51、一個事故等級評估模組52,及一個保費估算模組53,且具有透過機器學習建立的一個風險評估模型與一個事故等級評估模型。
The
在本實施例中,該風險評估單元5會經由該電子裝置900訊號連接一歷史交通事故資訊資料庫802以得取多筆交通事故資料,且會藉由對每一交通事故資料中自發生前一預定時間至事故發生當下的這段期間,例如事故發生前一天、前三天或前一週,至事故發生當下的這段期間,所記錄之前述各種手動駕駛行為參數與各種自動駕駛行為參數,以及各交通事故所導致之駕駛與乘客的傷亡
程度、現場周遭人員傷亡程度、事故車輛損壞程度與周遭環境破壞程度等進行大數據統計分析,並以機器學習演算法進行演算訓練,藉以建立該風險評估模型與該事故等級評估模型。由於建立該等模型的機器學習演算法類型眾多,例如但不限於類神經網路系統、支持向量機、決策樹...等,因此不再詳述。
In this embodiment, the
該事故等級評估模組52會透過該風險評估模型,對所有手駕時間區段之所有手動駕駛行為參數、所有自駕時間區段的所有自動駕駛行為參數、該手動駕駛總時間及該自動駕駛總時間進行演算,以得到一個代表該駕駛人可能發生之駕車事故的事故等級。
The accident
該事故風險評估模組51可透過該風險評估模型,對所有手駕時間區段之所有手動駕駛行為參數、所有自駕時間區段的所有自動駕駛行為參數、該手動駕駛總時間、該自動駕駛總時間,以及該事故等級進行演算,以得到對應該駕駛人的一個手駕事故發生機率(PH)、一個手駕事故損失估值(LH)、一個自駕事故發生機率(PM),及一個自駕事故損失估值(LM),並於該顯示器901顯示出該手駕事故發生機率(PH)、該手駕事故損失估值(LH)、該自駕事故發生機率(PM),及該自駕事故損失估值(LM)。
The accident
該保費估算模組53會根據公式P]利用駕駛時間加權的計算方式分析得到一個綜合事故風險(P),且會根據公式分析得到一個綜合損失金
額(L)。並根據公式[P×L=N]計算得到對應該駕駛人與該車輛701的該車險保費(N),並於該顯示器901顯示出該車險保費(N)。
The
該駕駛模式推薦單元6會根據該手駕事故發生機率(PH)與該手駕事故損失估值(LH)預估計算得到一個手駕事故財損金額,並會根據該自駕事故發生機率(PM)與該自駕事故損失估值(LM)預估計算得到一個自駕事故財損金額,且該駕駛模式推薦單元6會於判斷該手駕事故財損金額大於該自駕事故財損金額時,產生一個推薦自駕模式訊息,而於判斷該手駕事故財損金額小於該自駕事故財損金額時,產生一個推薦手駕模式訊息。實施時,該駕駛模式推薦單元6可經由該電子裝置900之通訊功能設計,將該推薦自駕模式訊息或該推薦手駕模式訊息傳送至駕駛人所攜帶的行動裝置702,或者是直接傳送至該車輛701,而於該車輛701配備之顯示器(圖未示)顯示出,藉以提醒駕駛人採用推薦的駕駛模式。但在本發明之其它實施態樣中,該駕駛模式推薦單元6產生之該推薦自駕模式訊息或該推薦手駕模式訊息的輸出方式不以上式方式為限。
The driving
參閱圖1、2、3,本發明車輛駕駛風險評估系統200進行車輛駕駛風險評估時,包含以下步驟:
Referring to Figures 1, 2, and 3, the vehicle driving
步驟501。取得行車資訊。使該車輛駕駛風險評估系統200經由該電子裝置900連線該即時行車資訊資料庫801,以取得該
車輛701當前已上傳之所有行車資訊。
步驟502。資料分類。使該行車時間分析單元3與該駕駛行為分析單元4分析該行車資訊,針對手動駕駛模式與自動駕駛模式進行資料分類,以分別取得對應手動駕駛模式之所有手駕時間區段、該手動駕駛總時間(TH)與所有手動駕駛行為參數,以及對應自動駕駛模式之所有自駕時間區段、該自動駕駛總時間(TM)與所有自動駕駛行為參數。
接著,分別執行步驟503之手動駕駛模式風險評估,以及與步驟504之自動駕駛模式風險評估。於步驟503,該風險評估單元5會分析得到對應手動駕駛模式之該手駕事故發生機率(PH)與該手駕事故損失估值(LH)。於步驟504,該風險評估單元5會分析得到對應自動駕駛模式之該自駕事故發生機率(PM)及該自駕事故損失估值(LM)。
Then, the manual driving mode risk assessment in
然後,執行步驟505。綜合風險評估。該風險評估單元5會彙整該手駕事故發生機率(PH)、該手駕事故損失估值(LH)、該自駕事故發生機率(PM),及該自駕事故損失估值(LM),以對該車輛701之該駕駛人進行綜合風險評估,以得到該手駕事故財損金額與該自駕事故財損金額。
Then, step 505 is performed. Comprehensive risk assessment. The
接著,分別執行步驟506之保險費用估算,與步驟507之最佳駕駛模式的分析與建議。於步驟506,會進行該車輛701之該
駕駛人的保險費用估算,於步驟507會進行,會將分析得到之該推薦自駕模式訊息或該推薦手駕模式訊息傳送至駕駛人所攜帶的行動裝置702。
Then, the insurance cost estimation in
綜上所述,透過對該車輛701於啟動該自動駕駛模式期間與該手動駕駛模式期間的行車資訊進行分析,藉以取得在自動駕駛模式期間之各種自動駕駛行為參數,以及取得在手動駕駛模式期間之各種手動駕駛行為參數的設計,以及透過該風險評估模型與該事故等級評估模型來分析取得該手駕事故發生機率(PH)、該手駕事故損失估值(LH)、該自駕事故發生機率(PM)及該自駕事故損失估值(LM),並進一步分析得到對應該駕駛人之車險保費的設計,使得本發明車輛駕駛風險評估系統200適用於導入駕駛行為車險應用服務(Usage Based Insurance,簡稱UBI),而能用於對駕駛具備自動駕駛功能之車輛701的駕駛人進行更合理的車險保費估算。
In summary, by analyzing the driving information of the
此外,還可進一步透過分析該手駕事故財損金額與該自駕事故財損金額差異,而對駕駛人提供該推薦自駕模式訊息或該推薦手駕模式訊息的設計,可根據該駕駛人駕駛該車輛701時的手動駕駛行為,以及該車輛701進行自動駕駛時的自動駕駛行為,對該駕駛人推薦適用於該車輛701且相對安全的駕駛模式,而有助於降低交通事故風險。因此,本發明車輛駕駛風險評估系統200確實是
一種相當創新的創作,確實能達成本發明的目的。
In addition, by further analyzing the difference between the amount of financial losses in the hand-driving accident and the amount of financial losses in the self-driving accident, the recommended self-driving mode message or the design of the recommended hand-driving mode message can be provided to the driver according to the driver driving the vehicle. The manual driving behavior of the
惟以上所述者,僅為本發明的實施例而已,當不能以此限定本發明實施的範圍,凡是依本發明申請專利範圍及專利說明書內容所作的簡單的等效變化與修飾,皆仍屬本發明專利涵蓋的範圍內。 However, the above are only examples of the present invention and should not be used to limit the scope of the present invention. All simple equivalent changes and modifications made based on the patent scope of the present invention and the content of the patent specification are still within the scope of the present invention. within the scope covered by the patent of this invention.
200:車輛駕駛風險評估系統 200: Vehicle driving risk assessment system
3:行車時間分析單元 3: Driving time analysis unit
4:駕駛行為分析單元 4: Driving behavior analysis unit
5:風險評估單元 5:Risk Assessment Unit
51:事故風險評估模組 51:Accident Risk Assessment Module
52:事故等級評估模組 52:Accident Level Assessment Module
53:保費估算模組 53: Premium estimation module
6:駕駛模式推薦單元 6: Driving mode recommendation unit
900:電子裝置 900: Electronic devices
901:顯示器 901:Display
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Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
TW201741898A (en) * | 2016-05-27 | 2017-12-01 | 勝捷光電股份有限公司 | System and method for UBI or fleet management by utilizing cloud driving video recording information |
CN108469806A (en) * | 2018-03-26 | 2018-08-31 | 重庆邮电大学 | Alternative expression is man-machine to drive middle driving power transfer method altogether |
TWM601415U (en) * | 2020-05-14 | 2020-09-11 | 泰安產物保險股份有限公司 | Vehicle damage prevention underwriting claims system |
TW202101344A (en) * | 2019-05-17 | 2021-01-01 | 美商愛和誼日生同和保險服務美國公司 | Systems And Method For Calculating Liability Of A Driver Of A Vehicle |
CN113095889A (en) * | 2021-04-28 | 2021-07-09 | 中国第一汽车股份有限公司 | Insurance pricing method, device, server and storage medium |
US20210224917A1 (en) * | 2017-09-27 | 2021-07-22 | State Farm Mutual Automobile Insurance Company | System and Method for Evaluating a Driving Behavior |
CN113257023A (en) * | 2021-04-13 | 2021-08-13 | 哈尔滨工业大学 | L3-level automatic driving risk assessment and takeover early warning method and system |
-
2021
- 2021-08-19 TW TW110130707A patent/TWI820471B/en active
Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
TW201741898A (en) * | 2016-05-27 | 2017-12-01 | 勝捷光電股份有限公司 | System and method for UBI or fleet management by utilizing cloud driving video recording information |
US20210224917A1 (en) * | 2017-09-27 | 2021-07-22 | State Farm Mutual Automobile Insurance Company | System and Method for Evaluating a Driving Behavior |
CN108469806A (en) * | 2018-03-26 | 2018-08-31 | 重庆邮电大学 | Alternative expression is man-machine to drive middle driving power transfer method altogether |
TW202101344A (en) * | 2019-05-17 | 2021-01-01 | 美商愛和誼日生同和保險服務美國公司 | Systems And Method For Calculating Liability Of A Driver Of A Vehicle |
TWM601415U (en) * | 2020-05-14 | 2020-09-11 | 泰安產物保險股份有限公司 | Vehicle damage prevention underwriting claims system |
CN113257023A (en) * | 2021-04-13 | 2021-08-13 | 哈尔滨工业大学 | L3-level automatic driving risk assessment and takeover early warning method and system |
CN113095889A (en) * | 2021-04-28 | 2021-07-09 | 中国第一汽车股份有限公司 | Insurance pricing method, device, server and storage medium |
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