CN111717221A - Automatic driving takeover risk assessment and man-machine friendly early warning method and early warning system - Google Patents

Automatic driving takeover risk assessment and man-machine friendly early warning method and early warning system Download PDF

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CN111717221A
CN111717221A CN202010478005.0A CN202010478005A CN111717221A CN 111717221 A CN111717221 A CN 111717221A CN 202010478005 A CN202010478005 A CN 202010478005A CN 111717221 A CN111717221 A CN 111717221A
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takeover
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CN111717221B (en
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孙棣华
赵敏
毛鹏
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Chongqing University
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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
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B60W60/005—Handover processes
    • B60W60/0059—Estimation of the risk associated with autonomous or manual driving, e.g. situation too complex, sensor failure or driver incapacity
    • 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
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W50/08—Interaction between the driver and the control system
    • B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0635—Risk analysis of enterprise or organisation activities
    • 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
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W50/08—Interaction between the driver and the control system
    • B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
    • B60W2050/143—Alarm means

Abstract

The invention discloses an automatic driving takeover risk assessment and man-machine friendly early warning method and an early warning system, wherein the early warning method comprises the steps of firstly calculating a takeover risk value during automatic driving takeover, and then sending takeover early warning of a corresponding mode to a driver according to a man-machine friendly takeover early warning algorithm so as to remind the driver to carry out takeover operation; the early warning system is based on an early warning method and comprises an automatic driving judgment module, a pipe connection demand module, a vehicle pipe connection risk value evaluation module and a warning module; the automobile is integrated with an early warning system. Under the condition of comprehensively considering multiple risk sources, the invention analyzes the risk of the vehicle connecting pipe caused by multiple physical objects in traffic, evaluates the risk at the moment of connecting pipe by combining the connecting pipe reaction characteristic of the driver of the vehicle, simultaneously considers the comfort level of the driver, establishes a man-machine friendly early warning method, can ensure the safety of automatic driving connecting pipe, and simultaneously improves the user experience of the driver, and the method can also provide technical support for an intelligent driving auxiliary system.

Description

Automatic driving takeover risk assessment and man-machine friendly early warning method and early warning system
Technical Field
The invention relates to the field of automatic driving, in particular to an automatic driving takeover risk assessment and man-machine friendly early warning method and an early warning system.
Background
The ability of an autonomous vehicle to improve safety, comfort and efficiency of driving has become one of the important trends in vehicle development. However, autodrive is not kicked on at once, and according to a classification standard established by the Society of Automotive Engineers (SAE) in the united states, the autodrive grade of a vehicle is classified into six grades: manual driving (L0); driving assistance (L1); partial autopilot (L2); conditional autonomous driving (L3); highly autonomous driving (L4); full autopilot (L5). The vehicles that are currently predominant in the market are L1 and L2. The L3 autonomous vehicle has become a new and important direction of development. And will be in the L3 automatic driving stage for a long time in the future due to technical and other limiting factors.
With L3 autonomous driving, the driver does not need to continuously supervise the environment and can do secondary tasks unrelated to driving, such as reading, making a phone call or using electronic equipment. However, the driver must be able to take over the vehicle when the vehicle autopilot system fails or the system reaches a limit. The driving load of a driver in automatic driving is greatly different from that of manual driving, and in an emergency, when the driver is required to take over the driving right of the vehicle, the cognitive load is increased sharply. The driver is difficult to deal with dangerous situations in extremely low to extremely high step load, great potential safety hazards exist, and traffic accidents are easy to happen. Therefore, the method can accurately evaluate the automatic driving takeover risk, ensure the takeover safety, provide basis for perfecting a takeover early warning mechanism, and is the key to prevent traffic accidents when the driver takes over the driving right. Meanwhile, research results show that when the system reminds a driver to take over the driving right of the vehicle, the urgent feeling and the annoyance degree of the driver are obviously different by respectively adopting different human-computer interaction modes such as auditory sense, visual sense, tactile sense and the like. Under the accurate risk that aassessment autopilot was taken over, the prerequisite of guaranteeing safety, choose for use the more comfortable human-computer interaction mode of driver, can improve driver's driving comfort.
Disclosure of Invention
In view of the above, in order to overcome the above problems, one of the objectives of the present invention is to provide an automatic driving takeover risk assessment and human-machine friendly early warning method, which combines the takeover reaction of the driver to accurately assess the automatic driving takeover risk and establish a human-machine friendly takeover early warning method considering the user experience of the driver on the basis; the second purpose is to provide an automatic driving takeover risk assessment and man-machine friendly early warning system based on the method.
The purpose of the invention is realized by the following technical scheme:
the invention has the beneficial effects that:
under the condition of comprehensively considering multiple risk sources, the invention analyzes the risk of the vehicle connecting pipe caused by multiple physical objects in traffic, evaluates the risk at the moment of connecting pipe by combining the connecting pipe reaction characteristic of the driver of the vehicle, simultaneously considers the comfort level of the driver, establishes a man-machine friendly early warning method, can ensure the safety of automatic driving connecting pipe, and simultaneously improves the user experience of the driver, and the method can also provide technical support for an intelligent driving auxiliary system.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objectives and other advantages of the invention may be realized and attained by the means of the instrumentalities and/or embodiments described below.
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In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail with reference to the accompanying drawings:
FIG. 1 shows a flow chart of the present invention;
fig. 2 shows a flow diagram of the man-machine friendly takeover early warning algorithm of the invention.
Detailed Description
The following is a detailed description of preferred embodiments of the invention. It should be understood that the preferred embodiments are illustrative of the invention only and are not limiting upon the scope of the invention.
Example 1
The embodiment provides a man-machine friendly early warning method for ensuring safety of automatic driving takeover, which includes the steps of firstly judging whether a vehicle is in an automatic driving state, specifically judging whether an automatic driving function is started through an automatic driving system, and if the automatic driving function is started, judging whether a driver needs to take over at the current moment, specifically: when the vehicle is in an automatic driving state, whether a signal requiring the driver to take over the driving right of the vehicle is received is judged, and the signal can be sent by automatic equipment failure or an automatic driving system. When the states of the automatic driving function and the driver take over are both satisfied (the automatic driving function is started and the driver takes over the automatic driving function), the automatic driving take over risk assessment and the man-machine friendly early warning are carried out, and the specific flow is shown in figure 1.
Firstly, acquiring the total takeover risk field intensity at the position of the vehicle according to the behavior field intensity caused by a static physical object and a moving physical object in a traffic road. The static physical object is an obstacle on the roadside, an obstacle prompt object set by people or a car which is stopped at the roadside and is to be repaired or waits for a red light.
Wherein, according to the state information of the static physical object in the traffic road and the related information of the vehicle, in order to represent the take-over risk caused by the static physical object, the position (x) of the static object in the vehicle is calculatedj,yj) The resulting potential energy field strength ES(acquisition method of behavior field intensity of static physical object):
Figure BDA0002516457090000031
dsj＝(xj-xs,yj-ys) Formula (2)
Wherein: k represents the field intensity coefficient;
Msa virtual mass representing a stationary physical object;
Rsrepresenting a road risk impact factor at which a stationary physical object is located;
dsjrepresenting the boundary from the stationary physical object s to (x)j,yj) (ii) a distance vector of (x)j,yj) Is the vehicle position.
The moving physical object comprises a moving object operated by a driver and a moving object operated by a driver, and the moving physical object is not drivenThe human-controlled moving objects are completely automatic driving automobiles and unmanned automobiles, and the position (x) of the unmanned moving object in the automobile is calculated according to the state information of the moving physical object in the traffic road and the relevant information of the automobile in order to represent the takeover risk caused by the unmanned moving objectj,yj) The generated kinetic energy field intensity Ed(acquisition mode of behavior field intensity of moving object without driver manipulation):
Figure BDA0002516457090000032
ddj＝(xj-xd,yj-yd) Formula (4)
Wherein: k3Representing kinetic energy field coefficients;
Mda virtual mass representing an unmanned moving object;
Rdrepresenting a road risk influence factor where the moving object operated by the driver is located;
ddjrepresenting said boundary d to (x) of the moving object without driver manipulationj,yj) A distance vector of (d);
vda velocity vector representing the unmanned moving object;
θdrepresents vdAnd ddjThe included angle of (A);
gradEd,djis EdThe gradient vector of (2).
According to the state information of the moving physical object controlled by the driver in the traffic road and the driver and the related information of the vehicle, in order to represent the takeover risk caused by the behavior characteristics of the driver, the position (x) of the driver at the vehicle is calculatedj,yj) Resulting behavioral field intensity Ex(there is the acquisition mode of the behavioral field intensity of the driver's controlled moving object):
Figure BDA0002516457090000033
wherein: dxA risk factor representative of a driver;
Mxa virtual mass representing a moving physical object manipulated by a driver;
Rxrepresenting a road risk influence factor where a moving physical object manipulated by a driver is located;
dxjrepresenting the boundary x to (x) of a moving physical object manipulated by a driverj,yj) The distance vector of (2).
According to the steps, the behavior field intensity caused by the static physical object and the moving physical object in the traffic channel is obtained through calculation, the total takeover risk field intensity at the position of the vehicle is obtained through the formulas (1), (3) and (5), and the total takeover risk field intensity is expressed as:
Et＝Es+Ed+Exformula (6)
Secondly, acquiring a vehicle takeover risk value according to the takeover risk total field intensity at the position of the vehicle, and specifically comprising the following steps:
step 1: based on the state information of the vehicle and the total takeover risk field strength (equation (6)) at the position of the vehicle, the field force applied to the vehicle is obtained, and the field force applied to the vehicle can be expressed as:
Fi＝Ei·Mj·Rj·(1+Dj) Formula (7)
Wherein: fiRepresenting the force applied by the vehicle in a takeover risk field formed by the ith static object, the moving physical object without the control of the driver or the moving physical object with the control of the driver at the takeover time;
Eirepresenting the field strength of the risk field formed by the single object;
Mja virtual mass representative of the host vehicle;
Rjrepresenting the position of the vehicle (x)j,yj) Road risk impact factor of (1);
Djrepresenting the risk factor of the driver of the vehicle.
Step 2: the method comprises the following steps of obtaining a risk value generated by a single traffic physical object based on a single risk field force borne by a vehicle, specifically:
Figure BDA0002516457090000041
Figure BDA0002516457090000042
Figure BDA0002516457090000043
Figure BDA0002516457090000044
Figure BDA0002516457090000045
wherein: RISKiAnd RISKiRespectively representing the take-over risk value and the change rate thereof brought by the field force of a single static object, a moving object or a driver to the vehicle;
RISKs、RISKdand RISKxRespectively representing the risk values respectively possessed by the vehicle at the takeover time in takeover risk fields formed by the static object, the non-driver operated moving physical object and the driver operated moving physical object.
And step 3: acquiring comprehensive RISKs RISK of a plurality of static objects, non-driver-controlled moving physical objects and driver-controlled moving physical objects which are received by the vehicle at the moment of taking over, specifically:
Figure BDA0002516457090000051
Figure BDA0002516457090000052
wherein: l represents the width of the lane;
direpresenting traffic physical object i to lane where the vehicle is locatedDistance of the center line;
mithe weight value of a single risk represents the filtering effect of the lane where a single traffic object is located on the risk;
and 4, step 4: and (3) taking the take-over reaction time of the driver (the driver has a reaction time after receiving the take-over early warning) into consideration, acquiring the risk TR of the driver at the moment when the driver takes over the driving right of the vehicle:
Figure BDA0002516457090000053
wherein: t is ttorRepresenting the predicted driver take over for the reaction time.
Thirdly, as shown in fig. 2, according to the host vehicle takeover risk value TR, it is determined that the risk of the host vehicle takeover is at the risk threshold value TR of the first scene and the second scene5And TR10The first scene is a taking-over scene that the time TTC of collision between the vehicle and an obstacle in front of the vehicle channel is 4-6 seconds and no vehicle exists around the vehicle, and the setting of the embodiment is 5S; the second scenario is a takeover scenario in which the time TTC of collision between the host vehicle and the obstacle in front of the host vehicle is 8 to 12 seconds, and no vehicle is around the host vehicle, and this embodiment is set to 10S.
Comparing the risk TR and TR of the driver at the time when the driver takes over the driving right of the vehicle obtained by the formula (15)5And TR10When TR>TR5And then, a first early warning mode is adopted to remind a driver of taking over the driving right of the vehicle in an emergency, and the self vehicle is driven at the speed of-2.5 to-4 m/s2Deceleration of (1) waiting for the driver to take over; when TR10<TR<TR5When the driver needs to take over the driving right of the vehicle, the driver is reminded to take over the driving right of the vehicle in an emergency by adopting a second early warning mode; when TR10>And during TR, a third early warning mode is adopted to remind the driver of taking over the driving right of the vehicle, and the comfort levels of the first early warning mode, the second early warning mode and the third early warning mode are gradually improved (based on man-machine friendliness, a proper taking over early warning mode is selected to remind the driver of the vehicle).
In this embodiment, the first early warning mode is a combined early warning mode of hearing with high urgency degree, vision and touch to remind the driver to take over the driving right of the vehicle in an emergency, and the self-vehicle is at-4 m/s2Deceleration ofWaiting for the driver to take over, the tactile signal is the driver seat vibration, the audible signal is the audio signal of high frequency and high peak value, that is, the automatic driving is about to fail, please take over urgently, and the visual signal is the same information displayed on the screen of the center console.
The second early warning mode is a combined early warning mode of vision and hearing with moderate urgency degree to remind the driver to take over the driving right of the vehicle in an emergency.
The third early warning mode is a combined early warning mode of vision and hearing with higher comfort level to remind a driver to take over the driving right of the vehicle, the hearing signals are audio signals with better comfort level, namely 'automatic driving is about to fail and please take over in time', and the visual signals are the same information displayed on a screen of a central console.
The risk TR of the driver at the time of taking over the driving right of the vehicle, calculated by the method described above, is 15, TR5Is 20, TR10And if the number is 10, a second early warning mode, namely a combined early warning mode of vision and hearing with moderate urgency is adopted to remind the driver of taking over the driving right of the vehicle in an emergency.
Example 2
The embodiment provides a man-machine friendly early warning system which comprises an automatic driving judgment module, a pipe connection demand module, a vehicle pipe connection risk value evaluation module and an alarm module; the automatic driving judging module is used for judging whether the vehicle is in an automatic driving state or not; the takeover demand module is used for judging whether the vehicle needs to be taken over by a driver; the vehicle takeover risk value evaluation module is used for selecting a proper takeover early warning mode by adopting the man-machine friendly early warning method in the embodiment 1 when the vehicle is in an automatic driving state and the need of taking over by a driver exists; the alarm module is used for carrying out alarm prompt on the driver by adopting the early warning mode judged by the vehicle takeover risk value evaluation module.
For example, the automatic driving judging module judges that the automatic driving function is started through the automatic driving system, transmits the signal to the takeover demand module, the takeover demand module judges that the driver needs to take over according to the fault of the automatic equipment or the signal sent by the automatic driving system, and then transmits the signal to the vehicle takeover risk value evaluation module,the vehicle takeover risk value evaluation module determines that the risk TR of the driver of the vehicle at the time of taking over the driving right of the vehicle is 10 by the method described in embodiment 1, and the risk of the vehicle takeover is at the risk threshold TR of the first scene and the second scene5、TR10Respectively 15 and 5, transmitting a signal adopting a second early warning mode to the warning module, and reminding a driver of taking over the driving right of the vehicle in an emergency by the warning module by adopting a visual and auditory combined early warning mode with moderate urgency.
The embodiment also provides the automobile with the automatic driving function, and the man-machine friendly early warning system is integrated.
Finally, the above embodiments are only intended to illustrate the technical solutions of the present invention and not to limit the present invention, and although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions, and all of them should be covered by the claims of the present invention.

Claims (8)

1. The automatic driving takeover risk assessment and man-machine friendly early warning method is characterized by comprising the following steps:
acquiring the total field intensity of the takeover risk at the position of the vehicle according to the field intensity of the behavior field caused by the static physical object and the moving physical object in the traffic road;
acquiring a vehicle connection pipe risk value according to the connection pipe risk total field intensity at the vehicle position;
and selecting a proper takeover early warning mode to remind the driver of the vehicle based on man-machine friendliness according to the vehicle takeover risk value.
2. The automated driving takeover risk assessment and human-machine-friendly early warning method according to claim 1, characterized in that: the acquisition mode of the behavior field intensity caused by the static object is as follows:
Figure FDA0002516457080000011
dsj＝(xj-xs,yj-ys)
wherein:
k represents the field intensity coefficient;
Msa virtual mass representing a stationary physical object;
Rsrepresenting a road risk impact factor at which a stationary physical object is located;
dsjrepresenting the boundary from the stationary physical object s to (x)j,yj) (ii) a distance vector of (x)j,yj) Is the vehicle position.
3. The automated driving takeover risk assessment and human-machine-friendly early warning method according to claim 2, characterized in that: the moving physical objects comprise moving objects without being controlled by a driver and moving objects controlled by the driver;
the behavior field intensity of the moving object controlled by the driver is obtained in the following mode:
Figure FDA0002516457080000012
ddj＝(xj-xd,yj-yd)
wherein:
K3representing kinetic energy field coefficients;
Mda virtual mass representing an unmanned moving object;
Rdrepresenting a road risk influence factor where the moving object operated by the driver is located;
ddjrepresenting said boundary d to (x) of the moving object without driver manipulationj,yj) A distance vector of (d);
vda velocity vector representing the unmanned moving object;
θdrepresents vdAnd ddjThe included angle of (A);
gradEd,djis EdIn the direction of gradient ofAn amount;
the method for acquiring the behavior field intensity of the moving object controlled by the driver comprises the following steps:
Figure FDA0002516457080000021
wherein:
Dxa risk factor representative of a driver;
Mxa virtual mass representing the driver-manipulated moving physical object;
Rxrepresenting a road risk influence factor where the moving physical object manipulated by the driver is located;
dxjrepresenting the boundaries x to (x) of the moving physical object manipulated by the driverj,yj) The distance vector of (2).
4. The automated driving takeover risk assessment and human-machine-friendly early warning method according to claim 3, characterized in that: the total field intensity of the joint pipe risk at the position of the vehicle is specifically as follows:
Et＝Es+Ed+Ex。
5. the human-friendly early warning method as claimed in claim 4, wherein: the method for acquiring the vehicle takeover risk value comprises the following steps:
acquiring the field force applied to the vehicle based on the state information of the vehicle and the total takeover risk field strength at the position of the vehicle, wherein the field force applied to the vehicle can be represented as:
Fi＝Ei·Mj·Rj·(1+Dj)
wherein: fiRepresenting the force applied by the vehicle in a takeover risk field formed by the ith static object, the moving physical object without the control of the driver or the moving physical object with the control of the driver at the takeover time;
Eirepresenting the field strength of the risk field formed by the single object;
Mja virtual mass representative of the host vehicle;
Rjrepresenting the position of the vehicle (x)j,yj) Road risk impact factor of (1);
Dja risk factor representative of the driver of the host vehicle;
acquiring a risk value generated by a single traffic physical object, specifically:
Figure FDA0002516457080000022
Figure FDA0002516457080000023
Figure FDA0002516457080000024
Figure FDA0002516457080000025
Figure FDA0002516457080000026
wherein: RISKiAnd RISKiRespectively representing the take-over risk value and the change rate thereof brought by the field force of a single static object, a moving object or a driver to the vehicle;
RISKs、RISKdand RISKxRespectively representing risk values respectively possessed by the vehicle at the takeover time in takeover risk fields formed by the static object, the moving physical object without the control of the driver and the moving physical object with the control of the driver;
acquiring comprehensive RISKs RISK of a plurality of static objects, non-driver-controlled moving physical objects and driver-controlled moving physical objects which are received by the vehicle at the moment of taking over, specifically:
Figure FDA0002516457080000031
Figure FDA0002516457080000032
wherein:
l represents the width of the lane;
direpresenting the distance from the traffic physical object i to the center line of the lane where the vehicle is located;
mithe weight value of a single risk represents the filtering effect of the lane where a single traffic object is located on the risk;
and (3) taking the take-over reaction time of the driver into consideration, and acquiring the risk TR of the driver at the moment of taking over the driving right of the vehicle:
Figure FDA0002516457080000033
wherein: t is ttorRepresenting the predicted driver take over for the reaction time.
6. The automated driving takeover risk assessment and human-friendly early warning method according to claim 5, characterized in that: the method for selecting the proper takeover early warning mode comprises the following steps:
when TR>TR5And then, a first early warning mode is adopted to remind a driver of taking over the driving right of the vehicle in an emergency, and the self vehicle is driven at the speed of-2.5 to-4 m/s2Deceleration of (1) waiting for the driver to take over;
when TR10<TR<TR5When the driver needs to take over the driving right of the vehicle, the driver is reminded to take over the driving right of the vehicle in an emergency by adopting a second early warning mode;
when TR10>During TR, reminding a driver to take over the driving right of the vehicle by adopting a third early warning mode;
wherein, TR5Is a take-over risk threshold, TR, of the vehicle in a first scene10A takeover risk threshold for the host vehicle in a second scene;
the comfort levels of the first early warning mode, the second early warning mode and the third early warning mode are gradually improved.
7. The automated driving takeover risk assessment and human-friendly early warning method according to claim 6, characterized in that: the first scene is a taking-over scene that the collision time TTC between the vehicle and an obstacle in front of the vehicle channel is 4-6 seconds and no vehicle is around; the second scene is a taking-over scene that the collision time TTC between the vehicle and the obstacle in front of the vehicle channel is 8-12 seconds and no vehicle is around.
8. Risk assessment and man-machine friendly early warning system are taken over in autopilot, its characterized in that: the system comprises an automatic driving judgment module, a pipe connection demand module, a vehicle pipe connection risk value evaluation module and an alarm module;
the automatic driving judging module is used for judging whether the vehicle is in an automatic driving state or not;
the takeover demand module is used for judging whether the vehicle needs to be taken over by a driver;
the vehicle takeover risk value evaluation module is used for selecting a proper takeover early warning mode by adopting the automatic driving takeover risk evaluation and man-machine friendly early warning method as claimed in any one of claims 1 to 7 when the vehicle is in an automatic driving state and the need of taking over by a driver exists;
the alarm module is used for carrying out alarm prompt on the driver by adopting the early warning mode judged by the vehicle takeover risk value evaluation module.
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