CN115716481A - Man-machine interaction control system of automatic driving vehicle - Google Patents
Man-machine interaction control system of automatic driving vehicle Download PDFInfo
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- CN115716481A CN115716481A CN202211629049.4A CN202211629049A CN115716481A CN 115716481 A CN115716481 A CN 115716481A CN 202211629049 A CN202211629049 A CN 202211629049A CN 115716481 A CN115716481 A CN 115716481A
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Abstract
The invention discloses a man-machine interaction control system of an automatic driving vehicle, which belongs to the technical field of automatic driving, can realize the corresponding tracking of fatigue driving behaviors of a driver through a fatigue driving prediction unit, gives different voice feedbacks to the driver through a vehicle-mounted system when the driver meets the fatigue driving behaviors in various tracking modes, carries out partial intervention on the driving behaviors of the driver through a system intervention unit, informs the driver whether to transfer driving right to the system through voice broadcast, switches to an automatic driving mode within 15-30S after the vehicle-mounted system informs the driver through a system takeover unit, and ensures that the automatic driving technology is fully utilized, improves the driving reliability of the automatic driving vehicle, helps the driver reduce violation and improves the driving safety in the automatic driving mode.
Description
Technical Field
The invention relates to the technical field of automatic driving, in particular to a man-machine interaction control system of an automatic driving vehicle.
Background
The L3 level automatic driving means that under a specific environment, the reactions of driving operation, surrounding environment monitoring and the like can be completed without the operation of a driver, the man-machine interaction means the information exchange process between a person and a computer for completing a determined task through a certain dialogue language and in a certain interaction mode, and the main aim of the automatic driving man-machine interaction function is to realize the mutual understanding between an automatic driving system and the driver so as to ensure the safe operation of the automatic driving vehicle.
The human-computer interaction system in the prior art cannot reasonably analyze the fatigue driving behavior of the driver, and the vehicle-mounted system can only judge whether the driver is fatigue driving according to the driving time of the driver, so that the automatic driving technology is not fully utilized, and the problem of low reliability of the vehicle-mounted system during alarming exists.
For the problems in the related art, no effective solution is available at present.
Disclosure of Invention
1. Technical problem to be solved
The invention aims to provide a human-computer interaction control system of an automatic driving vehicle, which can realize the corresponding tracking of the fatigue driving behavior of a driver through a fatigue driving prediction unit, give different voice feedback to the driver through a vehicle-mounted system when the driver meets the fatigue driving behavior in various tracking modes, perform partial intervention on the driving behavior of the driver through a system intervention unit, inform the driver whether to transfer the driving right to the system through voice broadcast, switch into an automatic driving mode within 15-30S after the vehicle-mounted system informs the driver through a system takeover unit, and ensure that the automatic driving technology is fully utilized, improve the running reliability of the automatic driving vehicle, help the driver to reduce the violation and improve the driving safety in the automatic driving mode.
2. Technical scheme
In order to solve the above problems, the present invention adopts the following technical solutions.
A man-machine interaction control system of an automatic driving vehicle comprises the automatic driving vehicle and a man-machine interaction control system, the human-computer interaction system comprises a vehicle-mounted system and a cloud server, the vehicle-mounted system comprises AI voice recognition, voice broadcasting and the like, the vehicle-mounted system is awakened through the AI voice recognition, or awakens the vehicle-mounted system by manually driving the keys in the vehicle, the cloud server comprises a human-computer interaction module, a driving early warning module, a driving data monitoring module, an environmental data acquisition module and a data storage module, the human-computer interaction module comprises a user login unit and a path analysis unit, the user login unit is used for awakening the vehicle-mounted system by a driver, more accurate analysis is carried out on the habit of the user with the login record in the cloud server, the path analysis unit is used for carrying out route planning after the driver sets the destination, the route planning comprises an optimal path, a fastest path and a most provincial path, the route planning is used for a driver to select a proper route according to the self condition, the driver fatigue driving behavior can be correspondingly tracked through the fatigue driving prediction unit, and gives different voice feedbacks to the driver through the vehicle-mounted system when the driver meets the fatigue driving behaviors in various tracking modes, the system intervention unit is used for carrying out partial intervention on the driving behavior of the driver and informing the driver whether to transfer the driving right to the system or not through voice broadcast, the system takes over the unit and switches to the automatic driving mode in 15-30S after the vehicle-mounted system informs the driver, in the automatic driving mode, the vehicle runs according to the preset route in the path analysis unit, the automatic driving technology can be fully utilized, and the running reliability of the automatic driving vehicle is improved, the driver is helped to reduce the violation of regulations and the driving safety is improved.
Furthermore, the driving early warning module comprises a fatigue driving prediction unit, a driver facial feature analysis unit, a driver somatosensory analysis unit, a system intervention unit and a system takeover unit, wherein the fatigue driving prediction unit is used for predicting and analyzing behaviors with driving risks in the manual driving process of a driver, transmitting the predicted and analyzed behaviors to the cloud server, and finally broadcasting the behaviors to the driver through the voice of the vehicle-mounted system.
Further, the facial feature analysis unit of driver includes three kinds of tracking modes of eye visual tracking, lip visual tracking and driver's posture tracking, the tired driving action of eye visual tracking includes that frequency of blinking increases, blink time is long, the sight is dull and the sight direction shifts, the tired driving action of lip visual tracking includes yawning, calling and eating, the tired driving action of driver's posture tracking includes that the frequency of nodding the head increases and the position of sitting that does not match with driving habit, and when the driver satisfied two kinds of tired driving actions in the tracking mode simultaneously, the on-vehicle system passes through voice broadcast, proposes not to drive fatigue.
Further, the driver somatosensory analysis unit is used for informing the driver to turn on a corresponding air conditioner through the vehicle-mounted system when the driver has sweating behaviors or trembling behaviors, or additionally inquiring whether a seat massage function needs to be turned on or not after the vehicle-mounted system suggests not to fatigue driving through voice broadcasting, so as to relieve and reduce the fatigue degree of the driver.
Further, the system intervention unit is used for partially intervening the driving behaviors of the driver when the driver simultaneously meets three to four fatigue driving behaviors in the tracking mode, and informing the driver whether to transfer the driving right to the system through voice broadcast, the system taking-over unit is used for switching the vehicle-mounted system into an automatic driving mode within 15-30S after informing the driver when the driver simultaneously meets the four fatigue driving behaviors in the tracking mode, and the vehicle runs according to a preset route in the path analysis unit in the automatic driving mode.
Further, driving data monitoring module includes GPS positioning unit, driving speed detecting element and in-car environment analysis unit, the GPS positioning unit reaches cloud ware on with the real-time position of vehicle, prevents that the driver loses the antithetical couplet or the rescue of being convenient for after taking place the dangerous condition, driving speed detecting element combines the speed limit highway section on the route planning to current speed of a motor vehicle to through on-vehicle system suggestion driver speed reduction driving, help driver reduces the security of violating the regulations and improving the driving, environment analysis unit analyzes vehicle surrounding information, and the personnel of being convenient for accomplish to keep away the barrier in advance for improve vehicle driving safety coefficient.
Further, the environmental data collection module includes thermal imaging collection unit, image acquisition unit and camera detecting element, thermal imaging collection unit is used for detecting the peripheral crowd of vehicle, prevents to injure the pedestrian by mistake at the in-process of traveling or backing a car, image acquisition unit, camera detecting element detects traffic lights and speed measuring probe on the route planning road to the place ahead situation of blocking up carries out the prejudgement, when above-mentioned incident takes place in the place ahead of the route, through the speed reduction driving of on-vehicle system suggestion driver, help the driver to reduce and violate regulations and improve the security of driving.
Furthermore, the data storage module comprises a data storage unit and a data transmission unit, the driver single planning route and driving behavior data are stored through the data storage unit, and the currently stored data are uploaded to the cloud server through the data transmission unit.
3. Advantageous effects
Compared with the prior art, the invention has the advantages that:
the scheme can realize the corresponding tracking of the fatigue driving behavior of the driver through the fatigue driving prediction unit, and different voice feedbacks are given to the driver through the vehicle-mounted system when the driver meets the fatigue driving behavior in various tracking modes, the driving behavior of the driver is partially interfered through the system interference unit, and the driver is informed whether to transfer the driving right to the system through voice broadcast, the vehicle-mounted system is switched into an automatic driving mode within 15-30S after being informed of the driver through the system takeover unit, and the vehicle runs according to the preset route in the path analysis unit in the automatic driving mode, so that the automatic driving technology can be fully utilized, the running reliability of the automatic driving vehicle is improved, and the reduction of violation of regulations and the improvement of the driving safety of the driver are facilitated.
Drawings
FIG. 1 is a system block diagram of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention; it is to be understood that the embodiments described are merely exemplary embodiments, rather than exemplary embodiments, and that all other embodiments may be devised by those skilled in the art without departing from the scope of the present invention.
In the description of the present invention, it should be noted that the terms "upper", "lower", "inner", "outer", "top/bottom", etc. indicate orientations or positional relationships based on orientations or positional relationships shown in the drawings, which are merely for convenience of description and simplification of description, but do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "disposed," "sleeved/connected," "connected," and the like are to be construed broadly, e.g., "connected," which may be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in a specific case to those of ordinary skill in the art.
Example 1:
referring to fig. 1, the human-computer interaction control system of the autonomous vehicle comprises the autonomous vehicle and a human-computer interaction control system, wherein the human-computer interaction system comprises a vehicle-mounted system and a cloud server, the vehicle-mounted system comprises AI voice recognition, voice broadcasting and the like, the vehicle-mounted system is awakened through the AI voice recognition or is awakened through a manual driving of an inner key of the vehicle, the cloud server comprises a human-computer interaction module, a driving early warning module, a driving data monitoring module, an environmental data acquisition module and a data storage module, the human-computer interaction module comprises a user login unit and a path analysis unit, the user login unit is used for awakening the vehicle-mounted system by a driver, the analysis on the user habits with login records in the cloud server is more accurate, the path analysis unit is used for planning a route after the driver sets a destination, the route planning comprises an optimal path, a fastest path and a most economical path, and the route planning is used for the driver to select an appropriate route according to the self condition.
The driving early warning module comprises a fatigue driving prediction unit, a driver facial feature analysis unit, a driver somatosensory analysis unit, a system intervention unit and a system taking-over unit, wherein the fatigue driving prediction unit is used for predicting and analyzing the behavior with driving risk in the manual driving process of a driver, transmitting the prediction analysis to the cloud server and finally broadcasting the behavior to the driver through the voice of the vehicle-mounted system.
The facial feature analysis unit of the driver comprises three tracking modes of eye vision tracking, lip vision tracking and body state tracking of the driver, fatigue driving behaviors of the eye vision tracking comprise increased blinking frequency, long blinking time, dull sight and visual direction deviation, fatigue driving behaviors of the lip vision tracking comprise yawning, calling and eating, fatigue driving behaviors of the body state tracking of the driver comprise increased nodding frequency and sitting postures unmatched with driving habits, and if the driver meets two fatigue driving behaviors in the tracking modes at the same time, the vehicle-mounted system reports through voice and suggests not to fatigue driving.
The driver somatosensory analysis unit is used for informing the driver to turn on a corresponding air conditioner through the vehicle-mounted system when the driver has sweating behaviors or trembling behaviors, or additionally inquiring whether a seat massage function needs to be turned on or not after the vehicle-mounted system suggests fatigue driving through voice broadcasting, so as to relieve and reduce the fatigue degree of the driver.
The system intervention unit is used for partially intervening the driving behaviors of the driver when the driver simultaneously meets three to four fatigue driving behaviors in the tracking mode, informing the driver whether to transfer the driving right to the system through voice broadcasting, and the system taking over unit is used for switching the vehicle system into an automatic driving mode within 15-30S after informing the driver when the driver simultaneously meets the four fatigue driving behaviors in the tracking mode, and the vehicle runs according to a preset route in the path analysis unit in the automatic driving mode.
The driving data monitoring module comprises a GPS positioning unit, a driving speed detection unit and an in-vehicle environment analysis unit, the GPS positioning unit uploads the position of a vehicle in real time to a cloud server, driver loss or rescue after dangerous conditions occur is prevented, the driving speed detection unit analyzes the speed limit road section on the current vehicle speed combined route planning, and prompts the driver to decelerate through an on-vehicle system, the driver is helped to reduce violation and improve driving safety, the environment analysis unit analyzes information around the vehicle, and the personnel can avoid obstacles in advance, so that the safety factor of vehicle driving is improved.
The environmental data collection module includes thermal imaging collection unit, image acquisition unit and camera detecting element, thermal imaging collection unit is used for detecting the peripheral crowd of vehicle, the prevention is in the in-process injury pedestrian by mistake of going or backing a car, image acquisition unit, camera detecting element detects traffic lights and speed measuring probe on the route planning road, and carry out the prejudgement to the place ahead situation of blocking up, when above-mentioned incident takes place in the place ahead of route, through the speed reduction driving of on-vehicle system suggestion driver, help the driver to reduce violating regulations and improve the security of driving.
The data storage module comprises a data storage unit and a data transmission unit, the driver single planning route and driving behavior data are stored through the data storage unit, and the currently stored data are uploaded to the cloud server through the data transmission unit.
According to the scheme, the fatigue driving behavior of the driver can be correspondingly tracked through the fatigue driving prediction unit, different voice feedbacks are given to the driver through the vehicle-mounted system when the driver meets the fatigue driving behavior in various tracking modes, the driving behavior of the driver is partially interfered through the system interference unit, the driver is informed whether to transfer the driving right to the system or not through voice broadcast, the vehicle-mounted system is switched to the automatic driving mode within 15-30S after being informed of the driver through the system take-over unit, and the vehicle runs according to the preset route in the path analysis unit in the automatic driving mode.
The foregoing is only a preferred embodiment of the present invention; the scope of the invention is not limited thereto. Any person skilled in the art should be able to cover the technical scope of the present invention by equivalent or modified solutions and modifications within the technical scope of the present invention.
Claims (8)
1. Human-computer interaction control system of automatic driving vehicle, including automatic driving vehicle and human-computer interaction control system, human-computer interaction system includes vehicle mounted system and cloud ware, vehicle mounted system includes AI speech recognition, pronunciation report etc. its characterized in that: the cloud server comprises a man-machine interaction module, a driving early warning module, a driving data monitoring module, an environmental data acquisition module and a data storage module, wherein the man-machine interaction module comprises a user login unit and a path analysis unit, the user login unit is used for awakening a vehicle-mounted system by a driver, the analysis on the user habit with login records in the cloud server is more accurate, the path analysis unit is used for planning a route after the driver sets a destination, the route planning comprises an optimal path, a fastest path and a most-economical path, and the route planning is used for the driver to select a proper route according to the self condition.
2. The human-computer interaction control system of an autonomous vehicle of claim 1, characterized in that: the driving early warning module comprises a fatigue driving prediction unit, a driver facial feature analysis unit, a driver somatosensory analysis unit, a system intervention unit and a system take-over unit, wherein the fatigue driving prediction unit is used for predicting and analyzing behaviors with driving risks in the manual driving process of a driver, transmitting the predicted and analyzed behaviors to a cloud server, and finally broadcasting the predicted and analyzed behaviors to the driver through a vehicle-mounted system voice.
3. The human-computer interaction control system of an autonomous vehicle of claim 2, characterized in that: the facial feature analysis unit of the driver comprises three tracking modes of eye vision tracking, lip vision tracking and driver posture tracking, the fatigue driving behaviors of the eye vision tracking comprise blinking frequency increase, blinking time length, dull sight and visual line direction deviation, the fatigue driving behaviors of the lip vision tracking comprise yawning, calling and eating, the fatigue driving behaviors of the driver posture tracking comprise increasing of nodding frequency and sitting postures unmatched with driving habits, and if the driver simultaneously meets the two fatigue driving behaviors in the tracking modes, the vehicle-mounted system can report through voice and suggest not to fatigue driving.
4. The human-computer interaction control system of an autonomous vehicle as recited in claim 3, wherein: the driver somatosensory analysis unit is used for informing the driver to turn on a corresponding air conditioner after the driver is informed by the vehicle-mounted system when the driver has a sweating behavior or a trembling behavior, or additionally inquiring whether a seat massage function needs to be turned on or not after the vehicle-mounted system suggests not to be fatigue-driven through voice broadcasting so as to relieve and reduce the fatigue of the driver.
5. The human-computer interaction control system of an autonomous vehicle of claim 3, characterized in that: the system intervention unit is used for partially intervening the driving behaviors of the driver when the driver simultaneously meets three to four fatigue driving behaviors in the tracking mode, and informing the driver whether to transfer the driving right to the system through voice broadcasting, the system taking-over unit is used for switching the vehicle-mounted system into an automatic driving mode within 15-30S after informing the driver when the driver simultaneously meets the four fatigue driving behaviors in the tracking mode, and the vehicle runs according to a preset route in the path analysis unit in the automatic driving mode.
6. The human-computer interaction control system of an autonomous vehicle of claim 1, characterized in that: the driving data monitoring module includes GPS positioning unit, driving speed detecting element and in-car environmental analysis unit, the GPS positioning unit uploads the position of vehicle in real time to the cloud ware, and the rescue of being convenient for after the dangerous condition takes place for the prevention driver loses the antithetical couplet, driving speed detecting element combines the speed limit highway section on the route planning to current speed of a motor vehicle to carry out the analysis to through on-vehicle system suggestion driver speed reduction, help driver reduces the security of violating the regulations and improving the driving, environmental analysis unit carries out the analysis to information around the vehicle, and the personnel of being convenient for accomplish to keep away the barrier in advance for improve vehicle driving's factor of safety.
7. The human-computer interaction control system of an autonomous vehicle of claim 1, characterized in that: the environment data acquisition module comprises a thermal imaging acquisition unit, an image acquisition unit and a camera detection unit, wherein the thermal imaging acquisition unit is used for detecting people around a vehicle to prevent the people from being accidentally injured by the vehicle in the driving or backing process, the image acquisition unit is used for detecting traffic lights and speed measuring probes on a route planning road and prejudging the congestion state in the front, and when the above events occur in the front of the route, a driver is prompted to decelerate through an on-board system to help the driver to reduce the traffic violation and improve the driving safety.
8. The human-computer interaction control system of an autonomous vehicle of claim 1, characterized in that: the data storage module comprises a data storage unit and a data transmission unit, the data storage unit is used for storing the single planned route and the driving behavior data of the driver, and the data transmission unit is used for uploading the currently stored data to the cloud server.
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