WO2015184578A1

WO2015184578A1 - Adaptive warning management for advanced driver assistance system (adas)

Info

Publication number: WO2015184578A1
Application number: PCT/CN2014/079053
Authority: WO
Inventors: Carsten Isert; Sebastian Granzow; Sam Lai
Original assignee: Bayerische Motoren Werke Aktiengesellschaft
Priority date: 2014-06-03
Filing date: 2014-06-03
Publication date: 2015-12-10
Also published as: DE112014006721T5; CN106463054B; CN106463054A

Abstract

An advanced driver assistance system (100) for a vehicle comprises: a risk map section (110) configured to maintain a risk map (112)including risk information associated with respective geographic positions; a positioning section (120) configured to obtain a current geographic position of the vehicle; a calculating section (130) configured to calculate a risk level from at least the risk information associated with the current geographic position and/or a near future position of the vehicle; and a warning management section (140) configured to adjust a warning strategy of the advanced driver assistance system (100) based on the calculated risk level. Also a vehicle equipped with the advanced driver assistance system, a method for warning management in the advanced driver assistance system (100) for a vehicle, and a computer readable medium with computer executable instructions stored thereon for performing the method are provided. The system and method are applicable in various markets including but not limited to the western markets like European and American and the eastern markets like China and India.

Description

ADAPTIVE WARNING MANAGEMENT FOR ADVANCED DRIVER ASSISTANCE SYSTEM(ADAS)

FIELD OF THE INVENTION

The present invention generally relates to advanced driver assistance system(ADAS)for vehicles,and in particular,to adaptive warning management of the ADAS system.

BACKGROUND

In recent years,with the rapid development of vehicle industry, there is an increasing trend for developing advanced driver assistance systems (ADAS).These systems are designed with the intent of improving the safety, intelligence,efficiency,comfort,and overall satisfaction of driving,supporting the driver in critical traffic situations,and helping avoid accidents or mitigate the effect of crashes.There are already several systems available on the market, including,for example,adaptive cruise control,lane keeping,intelligent speed adaptation,traffic sign recognition,objects(pedestrian and vehicle)detection, and the like.

In general,ADAS can be classified into three categories as information provision,warning and control.Information provision may be achieved by use of a plurality of sensors,such as cameras,range sensor,speed sensor,accelerometer,or the like,deployed in or on the vehicle,such that the vehicle can know the status of itself and the surrounding environment.Some information may also be presented to the driver by means of a head up display (HUD).When the vehicle deviates from normal driving or runs into an emergence situation,warning signals may be generated to inform the driver of the situation and thus to elicit an appropriate avoidance response.Control systems may be configured to improve the ease of control during normal driving and help avoid accidents and/or mitigate the crash severity in critical situations, for example,by braking.

One of the major disadvantages is that the ADAS systems available on the market are mainly developed for the western countries,for example, European and American.These markets have a completely different traffic behavior than other markets like China and India.China has become the world's largest automobile market since the year about2009,and the market is still growing fast by about fifteen percentages on average.Unfortunately,most ADAS systems designed for western markets are not suitable for the markets like China.When implementing the ADAS systems to the vehicles to be sold or used in China,drivers'behavior and traffic situation in China need to be taken into consideration.However,there is a lack of comprehensive studies on drivers' behavior and traffic situation in China and their application in the design of the ADAS systems in the prior art.

In general,Chinese traffic means a lot more moving objects and obstacles,including but not limited to cars,scooters,pedestrians,bicycles,and the like.These objects themselves also behave differently and unpredictably, like closer distances,frequent and fast lane changes,or even ignoring the traffic lights.All this results in the problem that a completely normal Chinese traffic situation looks a lot more difficult/complex and dangerous than in the western countries.It means that you have to adapt the ADAS systems,for example, changing the algorithms for the ADAS systems including the warning strategy implemented in the ADAS system,so that they can work properly in this market. If the ADAS systems are implemented to vehicles to be sold or used in China without adaption,warning signals may become frequent but unnecessary and annoying to the drivers.This might cause the drivers to lose confidence in the warning signals,ignore them or even turn off the ADAS system.

This leads to a problem that it is very difficult to find the right balance between the goal of providing greater road safety and the occurrence of a lot of false or nuisance warnings.

The approaches described in this section are approaches that could be pursued,but not necessarily approaches that have been previously conceived or pursued.Therefore,unless otherwise indicated,it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.

SUMMARY

To address one or more of the above and other problems,the present invention provides methods and systems for adaptive warning management in an advanced driver assistance system(ADAS)which are applicable in various markets including but not limited to the western markets like European and American and the eastern markets like China and India.

According to an aspect of the present invention,an advanced driver assistance system(ADAS)is provided for a vehicle.The ADAS system may comprise:arisk map section configured to maintain a risk map including risk information associated with respective geographic positions；a positioning section configured to obtain a current geographic position of the vehicle；a calculating section configured to calculate a risk level from at least the risk information associated with the current geographic position and/or a near future position of the vehicle；and a warning management section configured to adjust a warning strategy of the advanced driver assistance system based on the calculated risk level.

In an exemplary embodiment of the present invention,the warning management section is further configured to change one or more of following aspects of the warning strategy:priority；sensitivity；type of warning signal； intensity of warning signal；length of warning signal；and frequency of warning signal.

In an exemplary embodiment of the present invention,the risk information associated with respective geographic positions comprises one or more of:how many accidents and/or dangerous situations happened in the past； kind of accident and/or dangerous situation；lane or driving path of accident and/or dangerous situation；maneuver associated with accident and/or dangerous situation；traffic density；number of other participants in the traffic；intervals of traffic lights；and maneuver that the driver will do.

In an exemplary embodiment of the present invention,the advanced driver assistance system further comprises a personal information section configured to maintain personal information of one or more drivers.In addition to the risk information associated with respective geographic positions, the calculating section is further configured to calculate the risk level from the personal information.

In an exemplary embodiment of the present invention,the personal information of one or more drivers comprises one or more of:gender；age； yearly travelled miles；totally travelled miles；driving behavior；and accident history.

In an exemplary embodiment of the present invention,the risk information and the personal information are assigned with respective weights in calculation of the risk level.

In an exemplary embodiment of the present invention,the near future position of the vehicle is provided by a navigating system based on the current geographic position of the vehicle.

In an exemplary embodiment of the present invention,the risk map section also serves as a navigating map module in the navigating system.

In an exemplary embodiment of the present invention,the calculated risk level is further used to control or configure other components of the vehicle.

Another aspect of the present invention also provides a vehicle equipped with the advanced driver assistance system as recited in any one of the above exemplary embodiments.

According to a further aspect of the present invention,amethod for warning management in an advanced driver assistance system for a vehicle is provided.The method for warning management comprises at least following steps:preparing a risk map including risk information associated with respective geographic positions；determining a current geographic position of the vehicle； calculating a risk level from at least the risk information associated with the current geographic position and/or a near future position of the vehicle；and adjusting a warning strategy of the advanced driver assistance system based on the calculated risk level.

In an exemplary embodiment of the present invention,the step of adjusting a warning strategy of the advanced driver assistance system comprises changing one or more of following aspects of warning:priority；sensitivity；type of warning signal；intensity of warning signal；length of warning signal；and frequency of warning signal.

In an exemplary embodiment of the present invention,the step of calculating a risk level comprises calculating a risk level from,in addition to the risk information associated with respective geographic positions,personal information of the driver.

In an exemplary embodiment of the present invention,the personal information of the driver comprises one or more of:gender；age；yearly travelled miles；totally travelled miles；driving behavior；and accident history.

In an exemplary embodiment of the present invention,the method for warning management further comprises:obtaining,from a navigating system,the near future position of the vehicle based on the current geographic position.

In an exemplary embodiment of the present invention,the risk map is also used as a navigating map in the navigating system.

In an exemplary embodiment of the present invention,the method for warning management further comprises:controlling or configuring other components of the vehicle based on the calculated risk level.

Astill aspect of the present invention provides a computer readable medium with computer executable instructions stored thereon for performing the method for warning management as recited in any one of the above exemplary embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features,aspects,and advantages of the present invention will become better understood when the following detailed description of certain exemplary embodiments is read with reference to the accompanying drawings in which like characters represent like parts throughout the drawings,wherein:

Fig.1is a block diagram that illustrates an advanced driver assistance system in accordance with an exemplary embodiment of the present invention；

Fig.2is a picture of intersection that shows traffic situation in the intersection；and

Fig.3is a flow chart that illustrates a method for warning management in an advanced driver assistance system in accordance with an exemplary embodiment of the present invention.

DETAILED DESCRIPTION

In the following description,for the purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the present invention.It will be apparent,however,that the present invention may be practiced without these specific details.In other instances,well-known structures,devices and methods are simplified or omitted in exemplary embodiments set forth below in order to avoid unnecessarily obscuring the present invention.

Fig.1is a block diagram that illustrates an advanced driver assistance system(ADAS)100in accordance with an exemplary embodiment of the present invention.The ADAS system100may be implemented in a vehicle so as to provide comfortable interaction for the driver and enhance road safety. As shown in the block diagram of Fig.1,the ADAS system100according to the embodiment may include at least a risk map section110,a positioning section120,a calculating section130and a warning management section140, which may be connected with each other by a bus160.

The risk map section110may have or maintain a risk map112 stored therein.The risk map section110may comprise a device for data storage, such as a hard disk,an optical medium(such as a CD-ROM,a DVD,or a Blue-Ray Disc),a magneto-optical medium,a memory device(such as a Dynamic Random-Access Memory(DRAM),Static RAM(SRAM),or other type of Random-Access Memory(RAM)),a Read-Only Memory(ROM),a flash memory(based on,e.g.,EEPROM flash memory technology or NAND flash memory technology),or other type of non-transitory device for electronic data storage.

Although the risk map section110is shown in Fig.1as a local device of the ADAS system100,it may also be a remote storage device that is accessible by the ADAS system100via wireless connections such as3G,4G,or WiFi communications.In another embodiment,the risk map section110may be a local device,and it can update the risk map112periodically from a remote host via wireless connections.

The risk map112may be stored in a predetermined format or in a database in the risk map section110.The risk map112may include various risk information associated with respective geographic positions or regions.As discussed below in more detail,the risk map112may be used to decide or adjust the warning strategy of the driver and the behavior of the ADAS system 100.

The risk information contained in the risk map112may include a risk and accident history of the respective geographic positions or regions.For example,the risk information may indicate,for a certain position or area,how many accidents or dangerous situations happened in the past or in a recent period of time.In particular,it may also include a more detailed description of the accidents or dangerous situations,like the kind,time,lane or driving path, maneuver of accidents or dangerous situations.The kind of accidents or dangerous situations may be defined by two parties involved in the accident or dangerous situation,for example,motor vehicle-to-motor vehicle accident, motor vehicle-to-non-motor vehicle accident,and motor vehicle-to-pedestrian accident.The time of accidents or dangerous situations may be the day in a month or week or the time in a day when the accident or dangerous situation happens.The lane or driving path indicates an accurate position where the accident or dangerous situation happens.The maneuver may include,for example,lane change,turning left or right,and the like that cause the accident or dangerous situation to happen.

In other embodiments,the risk information may further include traffic density,the number of other participants such as pedestrians,scooters and bicycles,for a certain position or area.The information of the traffic density and the number of other participants may include real time information which is available from a plurality of sources.For example,the real time traffic information may be collected by road monitoring cameras that have already been provided in the road network by the traffic management department.The collected real time traffic information may be processed in an information center and then distributed to vehicles by wireless communication.In another example,the real time traffic information may be collected by cameras implemented in the vehicles and then shared between the connected vehicles.It will be appreciated that the information of the traffic density and the number of other participants may also include non-real-time history information,which indicates average values of the traffic density and the number of other participants in the past or in a recent period of time.

Fig.2is a picture of an intersection that shows a traffic situation in the intersection.Referring to Fig.2,alot of pedestrians and non-motor vehicles such as bicycles and scooters participate in the traffic.This is a typical case especially in the rush hour in China.It is very difficult to predict behavior of pedestrians,bicycles and scooters,because they move flexibly and seldom provide any signal to indicate their next movement.They are more prone to ignore the traffic signal controls since there is much less punishment to them if compared with motor vehicles breaking the traffic rules,which in turn results in a large number of traffic conflicts(potential accidents and dangerous situations).

In general,traffic conflict means an observable situation in which two or more traffic participants approach each other in space and time to such an extent that there will be a risk of collision if their movements remain unchanged.Referring to Fig.2,there may be following typical conflicts between traffic participants:MTM conflict,which occurs between motor vehicles,MTN conflict,which occurs between a motor vehicle and a non-motor vehicle,and MTP conflict,which occurs between a motor vehicle and a pedestrian.The number or density of conflicts that occur in the intersection may indicate the risk level of the intersection.

What may be further inferred from Fig.2includes traffic density, the number of other participants in the traffic,lane or driving path of dangerous situations,maneuver associated with dangerous situations,or the like.So,the data contained in Fig.2may serve as one part of the above mentioned risk information to create the risk map112of the present invention.One or more pictures as shown in Fig.2may be captured by one or more monitoring cameras disposed around the intersection.Then,the pictures may be processed for example by computer to extract the above information.

Further information that may serve as risk information may include intervals of the traffic lights at intersections.As generally known,the probability for accidents rises dramatically at about the time when the light changes from one color to another.The on-vehicle cameras may recognize the traffic light,or status of the traffic light may be acquired via wireless communications,which may be used in combination with the interval information to calculate remaining seconds to a change or countdown.

Typically,a vehicle is equipped with a navigation system,which may provide a route planning for the driver to a destination.From the navigation system the vehicle may knows the next maneuver the driver will do in the near future,for example,a left crossing at the next intersection.In an exemplary embodiment,the vehicle can retrieve risk information associated with the next maneuver from the risk map section110and evaluate a risk level based on the risk information,as discussed below in more detail.If there is not information from the navigation system,in another embodiment,the vehicle can check whether the driver is driving a typical way for the current daytime,for example,the way to or back from the office.This also allows the vehicle to predict the route and thus the next maneuver.

Examples for the risk information have been provided as above.It is to be understood,however,that the above examples are not intended to be exhaustive nor limiting of the invention,but are given for purpose of illustration. Those skilled in the art can understand that the present invention may be implemented with more or less risk information,if necessary.

It is possible to collect all the above information by a plurality of ways.For example,the traffic management department may collect the risk information by using road monitoring cameras that have already been deployed in the road network,and the collected information may be processed and stored in a centre server.Then,the risk information may be distributed to vehicles by request,or be broadcasted in a near real time manner.In another example, cameras implemented on vehicles may be used to collect the risk information and the collected information may be shared between connected vehicles.Other possibilities are over a crowd sourcing approach where people get paid for uploading accident positions and descriptions over an app or internet side.This crowd sourcing approach can be enhanced to Taxi drivers and Taxi companies. Other sources are police traffic reports or traffic surveillance cameras.The traffic light information can be obtained by car2x communication or using already existing cameras.The present invention is not limited to the above ways, and many other ways are also possible.

Referring back to Fig.1,the positioning section120is provided to determine the current geographic position of the vehicle.The positioning section120may receive information from satellites such as US GPS,Russia GNNS,European Galileo and China Beidou to perform positioning such that the vehicle can know the current geographic position where the driver is driving. The positioning section120may also determine the current geographic position by other means such as through wireless network positioning technique.The positioning section120may also serve as a part of the navigation system disclosed above.From the current geographic position in combination with the map information or the route planning,the navigation system may further determine a near future position where the vehicle will arrive in a near future, for example,in ten seconds,thirty seconds,one minute,two minutes,and so on.

Combining all available information,the calculating section130 may calculate a risk level that indicates how high the probability for an accident or dangerous situation is currently or in the near future.Specifically,according to the current geographic position or the near future position,the calculating section130may acquire corresponding risk information,such as those discussed above,from the risk map section110.Then,such risk information may be used to calculate the risk level associated with the current geographic position or the near future position.

Beside the risk information disclosed above,it is also possible to include some additional personal information about the driver of the vehicle in calculation of the risk level.As generally known,the driver is also a very important factor of accidents.In an exemplary embodiment,the ADAS system 100may further include a personal information section150that maintains personal information of one or more drivers.A facial recognition camera may be provided in the vehicle so as to recognize the driver who is driving and thus the personal information section150can maintain or automatically update personal information of the driver,if necessary,by using various other sensors provided in or on the vehicle.Some personal information of the driver may also be provided to the personal information section150by manual input.Personal information maintained by the personal information section150may include but not limited to gender of the driver,age of the driver,yearly travelled miles, totally travelled miles,driving behavior(for example,aggressive or conservative levels),and accident history of the driver,or any other personal information that has an influence on the risk factor.

When the calculating section130calculates the risk level using the risk information and the personal information,the risk information and the personal information may be assigned with respective weights that indicate a degree the information contributes to the risk level.Amodel may be established empirically for calculation of the risk level.In an exemplary embodiment,the calculating section130may also include an intelligent unit(not shown)to adjust the calculation of the risk level dynamically and intelligently.That is,the intelligent unit can learn and improve itself over time.For example,as more personal information is gathered,the intelligent unit can optimize the model and/or adjust parameters such as weights of the risk and personal information according to driving behavior of the driver derived from the personal information.For another example,the intelligent unit can also optimize the parameters and the model as more actual accident statistics are collected,so that a more accurate risk level may be calculated for respective positions.

Then,the calculated risk level may be used by the warning management section140to determine or change a warning strategy of the ADAS system100,including adjusting algorithms for the ADAS system.

A sequence of events leading up to a crash includes normal driving, deviation from normal driving,emerging situation,critical situation and crash unavoidable.From deviation from normal driving to just before the crash, warning signals may be provided to inform the driver of the situation and elicit an appropriate avoidance response.Warnings may be classified into a plurality of priority levels.In an example,there may be provided three levels of warning priority:Low-level,the driver prepares action or decision within10seconds to 2minutes；Mid-level,it requires action or decision within around2to10 seconds；and High-level,it requires the driver to take immediate action or decision(0to around2seconds)to avoid a potential accident.

In the intersection as shown in Fig.2,warnings are prone to be triggered frequently,especially those of low priority or even false warnings.If too many warnings are generated,it may disturb the driver'sattention and reduce the driver'strust in the ADAS system,which in turn can reduce response time or even lead to the driver wanting to turn the ADAS system off.In one embodiment of the present invention,when the vehicle enters a region of high risk level,such as the intersection shown in Fig.2,the warning management section140may adjust priority level of warnings accordingly.For example,a mid-priority warning may be adjusted to be a low-priority warning,while a low-priority warning may be deactivated.Thus,many or all of the low-priority warnings may be eliminated when the vehicle is in the high risk region,and the driver may focus his/her attention to real critical situations.It may help maintain the driver'strust and confidence in the system.

It is important to note that high priority warnings should not be degraded because safety must not be compromised by the adjustment of the warning strategy.

An exemplary embodiment of the present invention also provides another way to adjust the warning strategy,i.e.,to change sensitivity of warnings in response to the calculated risk level.It relates to adaption of existing algorithms of the ADAS system.For example,reaction times,distances from objection,tolerances may be adapted such that warnings,especially those of low or mid priorities,may become less sensitive.So,unnecessary or false warnings may be reduced,especially in a region of high risk level.Also, warnings of high priority should be maintained sensitive in order for safety and reliability.

Generally,warnings of different priorities are represented by different signals.For example,alow priority warning is represented by a lower sound,while a high priority warning by a higher sound,or even accompanied with a visual or haptic signal.Another way to adjust the warning strategy is to change type,intensity,length and/or frequency of warning signals.For example, an auditory signal for a low priority warning may be changed into a visual signal presented for example on the HUD.For another example,an auditory signal for a mid priority warning may be adjusted to have a lower intensity.For yet another example,warning signals of low or mid priority may be assigned with a reduced length and frequency.By doing so,these warnings may less disturb the driver'sattention on the critical situation.Also,those skilled in the art can understand that warning signals of high priority should be maintained noticeable in the driving environment in order to ensure safety and reliability.

Those skilled in the art can understand from the above disclosure that the present invention is not limited to the above specific aspects for adjustment of the warning strategy,which are provided merely for illustration of the principle of the invention.In other words,those skilled in the art may also adjust the warning strategy in a different way in compliance with their practice and special design requirements.All the ways to adjust the warning strategy by using of the risk level will fall within the scope of the present invention as defined in the claims and its equivalents.

In a further embodiment,a dynamic intelligent system may be implemented in the warning management section140for adjustment of the warning strategy and adaption of the algorithm for the ADAS system.The dynamic intelligent system can learn and improve itself over time.For example, the dynamic intelligent system can analyze a history of warning signals and the driver'sresponse to the signals.If a warning signal is generated frequently while the driver never or seldom makes any response to the signal,the dynamic intelligent system can determine that the warning signal is less useful and thus weaken this signal.For example,the priority of the warning signal may be downgraded,and intensity,length and/or frequency of the warning signal may be reduced.On the other hand,if the driver usually responds to a warning signal, the dynamic intelligent system can determine that the warning signal is highly useful.Then,the warning signal may be maintained or even strengthened.The algorithm for the ADAS system may be adapted accordingly.By the dynamic intelligent system,the ADAS system100may be trained such that useful warning signals are maintained or strengthened,and useless warning signals are reduced or eliminated.

In an exemplary embodiment of the present invention,information about the calculated risk level may also be used to control or configure other equipments or components of the vehicle.For example,when a high risk level is determined,the cameras or other sensors implemented on the vehicle may be instructed to for example analyze a more specific area/field of view with a higher resolution or frequency such that more precise information may be obtained about a critical situation.

Using the above described risk map,the ADAS system100may provide an adaptive warning management that may be adapted in accordance with traffic information for a certain position or region.The adaptive warning management can suit various different traffic behaviors.So,the ADAS system 100may be applicable in both western market(European and American)and eastern market(China and India).

An example for the benefit of the ADAS system100is the object detection system.The actual system warns the driver if there is an object (pedestrians and motorized or non-motorized vehicles)in the front of the vehicle equipped with the object detection system.In the intersection as shown in Fig.2,for example,it is completely normal that pedestrians and non-motorized vehicles move or crowd before or around the vehicle,even if there is very narrow space therebetween.A frequent warning in this situation is not necessary or understandable for the driver.By using a specific risk map, many false or unnecessary warning can be reduced or eliminated.The system now mainly supports the driver in situations which appear in probably dangerous areas or complex street situations with a high likelihood of accident.

The block diagram of the ADAS system100configured in accordance with an exemplary embodiment of the present invention has been shown in Fig.1.Those skilled in the art can understand that the functional blocks of the ADAS system100may be implemented by hardware,software,or a combination of hardware and software to carry out the principles of the invention.It is also understood that the functional blocks described in Fig.1 may be combined or separated into sub-blocks to implement the principles of the invention as described above.For example,the calculating section130and the warning management section140may be integrated as a single unit such as a processor or CPU that is programmed to perform functions of the calculating section130and the warning management section140.For another example,the risk map section110may also serves as a navigating map module in the navigating system.Therefore,the description herein may support any possible combination or separation or further definition of the functional blocks described herein.

Turning to Fig.3,there is shown a flow chart that illustrates a method200for warning management in an advanced driver assistance system (ADAS)in accordance with an exemplary embodiment of the present invention. Since many specific details of the method200for warning management are the same as or similar to those disclosed above with reference to the ADAS system 100shown in Fig.1,repetitive description thereof will be omitted below.

Referring to Fig.3,the method200for warning management begins with the block210.In the block220,a risk map may be prepared.The risk map may include risk information,such as those discussed above in detail, associated with respective geographic positions.In an example,the risk map may be maintained in a local device of the vehicle equipped with the ADAS system.In another example,the risk map may be stored in a remote device and the preparing of the risk map comprises downloading the risk map from the remote device via wireless communications.

In the optional block230,personal information of the driver may be obtained from,for example,the personal information section150as disclosed above.In the block240,a current geographic position of the vehicle is determined by,for example,the positioning section120.Further,in the optional block250,a near future position may be determined based on the current geographic position.

Then,in the block260,a risk level may be calculated by using the risk information associated with the current geographic position and/or the near future position in combination with the personal information of the driver.In calculation of the risk level,the risk information and the personal information of the driver may be assigned with respective weights.Thus,in the block270,the calculated risk level may be used to adjust a warning strategy of the ADAS system and/or configure other sensors of the vehicle.The method200ends in the block280.

Although the above steps are described in sequence,those skilled in the art can understand that certain steps may be performed in other order or sequence,or even performed in parallel.For example,the steps220,230and 240may be performed in parallel or in other order.Other steps may be added or steps may be omitted depending upon the embodiment.For example,the optional steps230and250may be omitted,and an additional step of configuring other components of the vehicle by using the risk level calculated in the step260may be added.Those skilled in the art can make any modification to the method200within the principles of the present invention as disclosed.

In other embodiments,the present invention may also be implemented in a computer readable medium with computer executable instructions stored thereon for performing the steps as discussed above.

The foregoing descriptions of various embodiments have been presented only for purposes of illustration and description.They are not intended to be exhaustive or to limit the present invention to the exact forms disclosed.Accordingly,many modifications and variations will be apparent to practitioners skilled in the art.Additionally,the above disclosure is not intended to limit the present invention.

Claims

An advanced driver assistance system for a vehicle,comprising:

a risk map section configured to maintain a risk map including risk information associated with respective geographic positions；

a positioning section configured to obtain a current geographic position of the vehicle；

a calculating section configured to calculate a risk level from at least the risk information associated with the current geographic position and/or a near future position of the vehicle；and

a warning management section configured to adjust a warning strategy of the advanced driver assistance system based on the calculated risk level.
The advanced driver assistance system as recited in claim1,wherein the warning management section is further configured to change one or more of following aspects of the warning strategy:

priority；

sensitivity；

type of warning signal；

intensity of warning signal；

length of warning signal；and

frequency of warning signal.
The advanced driver assistance system as recited in claim1,wherein the risk information associated with respective geographic positions comprises one or more of:

how many accidents and/or dangerous situations happened in the past；

kind of accident and/or dangerous situation；

lane or driving path of accident and/or dangerous situation；

maneuver associated with accident and/or dangerous situation；

traffic density；

number of other participants in the traffic；

intervals of traffic lights；and

maneuver that the driver will do.
The advanced driver assistance system as recited in claim1,further comprising a personal information section configured to maintain personal information of one or more drivers,

wherein,in addition to the risk information associated with respective geographic positions,the calculating section is further configured to calculate the risk level from the personal information.
The advanced driver assistance system as recited in claim4,wherein the personal information of one or more drivers comprises one or more of:

gender；

age；

yearly travelled miles；

totally travelled miles；

driving behavior；and

accident history.
The advanced driver assistance system as recited in claim4,wherein the risk information and the personal information are assigned with respective weights in calculation of the risk level.
The advanced driver assistance system as recited in claim1,wherein the near future position of the vehicle is provided by a navigating system based on the current geographic position of the vehicle.
The advanced driver assistance system as recited in claim7,wherein the risk map section also serves as a navigating map module in the navigating system.
The advanced driver assistance system as recited in claim1,wherein the calculated risk level is further used to control or configure other components of the vehicle.
A vehicle equipped with the advanced driver assistance system as recited in any one of claims1-9.
A method for warning management in an advanced driver assistance system for a vehicle,comprising:

preparing a risk map including risk information associated with respective geographic positions；

determining a current geographic position of the vehicle；

calculating a risk level from at least the risk information associated with the current geographic position and/or a near future position of the vehicle；and

adjusting a warning strategy of the advanced driver assistance system based on the calculated risk level.
The method for warning management as recited in claim11,wherein adjusting a warning strategy of the advanced driver assistance system comprises changing one or more of following aspects of warning:

priority；

sensitivity；

type of warning signal；

intensity of warning signal；

length of warning signal；and

frequency of warning signal.
The method for warning management as recited in claim11,wherein the risk information associated with respective geographic positions comprises one or more of:

how many accidents and/or dangerous situations happened in the past；

kind of accident and/or dangerous situation；

lane or driving path of accident and/or dangerous situation；

maneuver associated with accident and/or dangerous situation；

traffic density；

number of other participants in the traffic；

intervals of traffic lights；and

maneuver that the driver will do.
The method for warning management as recited in claim11,wherein calculating a risk level comprises calculating a risk level from,in addition to the risk information associated with respective geographic positions,personal information of the driver.
The method for warning management as recited in claim14,wherein the personal information of the driver comprises one or more of:

gender；

age；

yearly travelled miles；

totally travelled miles；

driving behavior；and

accident history.
The method for warning management as recited in claim14,wherein the risk information and the personal information are assigned with respective weights in calculation of the risk level.
The method for warning management as recited in claim11,further comprising:

obtaining,from a navigating system,the near future position of the vehicle based on the current geographic position.
The method for warning management as recited in claim17,wherein the risk map is also used as a navigating map in the navigating system.
The method for warning management as recited in claim11,further comprising:

controlling or configuring other components of the vehicle based on the calculated risk level.
A computer readable medium with computer executable instructions stored thereon for performing the method for warning management as recited in any one of claims11-19.