Methods, devices, electronic equipment and procedures for early warning of flying car crashes

Abstract

This invention discloses a method, device, electronic equipment, and program product for early warning of flying car crashes, including: acquiring the kinematic parameters and power system operating parameters of the target flying car to determine whether the target flying car is in an out-of-control crash state; when in an out-of-control crash state, predicting the target flying car's crash trajectory based on the kinematic parameters, power system operating parameters, and real-time environmental parameters, determining the target landing point coordinates and final crash speed, and determining the danger level based on the final crash speed and the total weight of the target flying car; sending voice warning information to the target landing point coordinates through a directional speaker, and projecting laser warning signs to the target landing point coordinates through a laser emitter; transmitting the target landing point coordinates and danger level to a ground communication base station, enabling the ground communication base station to provide regional crash warnings for the area where the target landing point coordinates are located. This invention reduces the risk of secondary injury from flying car crashes and can be applied to the field of flying car technology.

Description

Technical Field

[0001] This invention relates to the field of flying car technology, and in particular to a flying car crash warning method, device, electronic equipment and program product. Background Technology

[0002] With the rapid development of the low-altitude economy, flying cars, as a new type of transportation combining aviation and ground driving functions, are finding increasingly wide applications. However, during flight, flying cars are susceptible to accidents and crashes due to factors such as power system failures, extreme weather, and operational errors. This not only threatens the safety of passengers but also poses a risk of secondary injury to people and facilities on the ground.

[0003] Existing safety technologies for flying cars primarily focus on passive protection and single-dimensional early warning: At the passive protection level, measures such as reinforcing the fuselage structure and equipping it with parachutes or airbags reduce the risk of injury or death to occupants after a crash, but lack effective mechanisms for the safety of ground personnel. At the early warning level, some models' crash warning modules can only send location signals to air traffic control platforms or the manufacturer's backend, failing to directly reach ground personnel, resulting in a lack of timely danger alerts. While a few solutions can issue audible and visual warnings, their range is limited and their visibility is low due to factors such as fall altitude, ambient noise, and weather conditions, making effective alerts difficult. At the ground coordination level, there is a lack of real-time linkage between flying cars and ground public facilities, preventing ground personnel from knowing the fall trajectory and precise landing point in advance, hindering evasive decisions and resulting in weak secondary injury prevention capabilities.

[0004] The above problems urgently need to be addressed. Summary of the Invention

[0005] The purpose of this invention is to at least partially solve one of the technical problems existing in the prior art.

[0006] Therefore, one objective of this invention is to provide a flying car crash warning method that enables coordinated air and ground warnings when a flying car is at risk of crashing, and accurately alerts ground personnel to dangerous areas, thereby reducing the risk of secondary injury from flying car crashes.

[0007] Another objective of this invention is to provide a flying car crash warning device.

[0008] To achieve the above-mentioned technical objectives, the technical solutions adopted in the embodiments of the present invention include: On one hand, embodiments of the present invention provide a method for early warning of flying car crashes, comprising the following steps: Obtain the kinematic parameters and power system operating parameters of the target flying car, and determine whether the target flying car is in an uncontrolled crash state based on the kinematic parameters and the power system operating parameters; When the target flying car is in an out-of-control falling state, the falling trajectory of the target flying car is predicted based on the kinematic parameters, the power system operating parameters and real-time environmental parameters, and the target landing point coordinates and final falling speed are determined. Then, the danger level is determined based on the final falling speed and the total weight of the target flying car. A voice warning message is sent to the target landing point coordinates via a directional speaker, and a laser warning mark is projected to the target landing point coordinates via a laser emitter; The target landing point coordinates and the danger level are transmitted to a ground communication base station, enabling the ground communication base station to issue a regional fall warning for the area where the target landing point coordinates are located.

[0009] Furthermore, in one embodiment of the present invention, the kinematic parameters include position, velocity, acceleration, and attitude angle; the power system operating parameters include thrust value, motor status, and control signal communication status; and the step of determining whether the target flying car is in an uncontrolled crash state based on the kinematic parameters and the power system operating parameters specifically includes: Determine whether the target flying car is falling abnormally based on the kinematic parameters; Determine whether the target flying car has a power system malfunction based on the power system operating parameters; When the target flying car falls abnormally and its power system fails, it is determined that the target flying car is in an uncontrolled falling state.

[0010] Furthermore, in one embodiment of the present invention, the step of predicting the fall trajectory of the target flying car based on the kinematic parameters, the power system operating parameters, and real-time environmental parameters, and determining the target landing point coordinates and final fall velocity, specifically includes: Construct the state vector, observation vector, state transition matrix, and observation matrix of the target flying car; A dynamic model of the target flying car is constructed, the control input is determined based on the motion parameters of the power system, and the air resistance input is determined based on the real-time environmental parameters; The initial state estimate of the target flying car is determined based on the kinematic parameters; Based on the current state estimate of the target flying vehicle, the state vector, the observation vector, the state transition matrix, and the observation matrix, predict the optimal state estimate of the target flying vehicle at the next moment; Substituting the optimal state estimate, the control input, and the air resistance input into the dynamic model, the predicted state of the target flying car at the next moment is obtained; The fall trajectory is determined based on a predicted sequence of states at future moments; The target landing point coordinates are determined based on the intersection of the falling trajectory and the ground, and the final falling speed is determined based on the predicted state corresponding to the intersection.

[0011] Furthermore, in one embodiment of the present invention, determining the danger level based on the final fall velocity and the total weight of the target flying vehicle specifically includes: The kinetic energy of the fall is calculated based on the final fall velocity and the total weight of the target flying car. The danger level is determined based on the fall kinetic energy and a preset kinetic energy threshold.

[0012] Furthermore, in one embodiment of the present invention, the step of sending a voice warning message to the target landing point coordinates via a directional speaker and projecting a laser warning mark to the target landing point coordinates via a laser emitter specifically includes: The voice signal power is determined based on the current altitude of the target flying car; The directional loudspeaker installed on the target flying car sends a preset voice warning message to the target landing point coordinates according to the voice signal power and the preset frequency band; The radius of the warning area is determined based on the aforementioned hazard level; The laser warning sign is projected onto the target landing point coordinates by the laser emitter mounted on the target flying car, based on the radius of the warning area.

[0013] Furthermore, in one embodiment of the present invention, transmitting the target landing point coordinates and the danger level to a ground communication base station, so that the ground communication base station can provide a regional fall warning for the area where the target landing point coordinates are located, specifically includes: The target landing point coordinates and the hazard level are transmitted to the ground communication base station in the area where the target landing coordinates are located via V2X; The ground communication base station pushes fall warning information to road traffic warning terminals in the area where the target landing point coordinates are located, so that the road traffic warning terminals can issue warnings through sound and light or screens; The ground communication base station pushes fall warning information to vehicles and user terminals in the area where the target landing point coordinates are located.

[0014] Furthermore, in one embodiment of the present invention, the road traffic warning terminal includes intelligent streetlights, traffic lights, road warning screens, and roadside broadcasting terminals.

[0015] On the other hand, embodiments of the present invention provide a flying car crash warning device, comprising: The uncontrolled fall judgment module is used to acquire the kinematic parameters and power system operating parameters of the target flying car, and to determine whether the target flying car is in an uncontrolled fall state based on the kinematic parameters and power system operating parameters; The crash trajectory prediction module is used to predict the crash trajectory of the target flying car based on the kinematic parameters, the power system operating parameters, and real-time environmental parameters when the target flying car is in an out-of-control crash state, and to determine the target landing point coordinates and final crash speed, and then determine the danger level based on the final crash speed and the total weight of the target flying car. An airborne warning module is used to send voice warning information to the target landing point coordinates via a directional speaker and to project laser warning signs to the target landing point coordinates via a laser emitter. The ground-based early warning module is used to transmit the target landing point coordinates and the danger level to a ground communication base station, so that the ground communication base station can provide regional fall warnings for the area where the target landing point coordinates are located.

[0016] On the other hand, embodiments of the present invention provide an electronic device, including: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the above-described method for early warning of a flying car crash.

[0017] On the other hand, embodiments of the present invention also provide a computer-readable storage medium storing a processor-executable computer program that, when executed by a processor, implements the aforementioned method for early warning of a flying car crash.

[0018] On the other hand, embodiments of the present invention also provide a computer program product, including a computer program that, when executed by a processor, implements the above-described method for early warning of a flying car crash.

[0019] The advantages and beneficial effects of the present invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention: This invention acquires the kinematic parameters and power system operating parameters of a target flying car. Based on these parameters, it determines whether the flying car is in an uncontrolled fall. If so, it predicts the car's trajectory based on the kinematic parameters, power system operating parameters, and real-time environmental parameters, determining the target landing point coordinates and final fall velocity. Then, based on the final fall velocity and the flying car's total weight, it determines the danger level. A voice warning is sent to the target landing point coordinates via a directional speaker, and a laser warning marker is projected onto the coordinates via a laser emitter. The landing point coordinates and danger level are transmitted to a ground communication base station, enabling the base station to provide area-wide fall warnings for the area where the landing point is located. This invention enables coordinated air and ground-based warnings when a flying car is at risk of falling, accurately alerting ground personnel to dangerous areas and reducing the risk of secondary injuries from flying car crashes. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the embodiments of the present invention are described below. It should be understood that the drawings described below are only for the convenience of clearly describing some embodiments of the technical solutions of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 A flowchart illustrating the steps of a flying car crash warning method provided in an embodiment of the present invention; Figure 2 This is a structural block diagram of a flying car crash warning device provided in an embodiment of the present invention; Figure 3 This is a structural block diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of this invention; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this invention as detailed in the appended claims.

[0023] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein is for the purpose of describing embodiments of the invention only and is not intended to limit the invention.

[0024] The flying car crash warning method provided in this invention can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or vehicle terminal, but is not limited to these. The server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network. The software can be an application that implements the flying car crash warning method, but is not limited to the above forms.

[0025] This invention can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This invention can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This invention can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0026] It should be noted that in various specific embodiments of the present invention, when processing data related to user identity or characteristics, such as user information, user behavior data, user historical data, and user parking space location information, user permission or consent is obtained first. Furthermore, the collection, use, and processing of this data comply with relevant laws, regulations, and standards. In addition, when embodiments of the present invention require access to sensitive personal information of users, separate permission or consent from the user is obtained through pop-ups or redirection to a confirmation page. Only after obtaining the user's separate permission or consent is the necessary user-related data for the normal operation of the embodiments of the present invention acquired.

[0027] Reference Figure 1 This invention provides a method for early warning of flying car crashes, specifically including the following steps: S101. Obtain the kinematic parameters and power system operating parameters of the target flying car, and determine whether the target flying car is in an out-of-control crash state based on the kinematic parameters and power system operating parameters. S102. When the target flying car is in an out-of-control falling state, predict the falling trajectory of the target flying car based on kinematic parameters, power system operating parameters and real-time environmental parameters, determine the target landing point coordinates and final falling speed, and then determine the danger level based on the final falling speed and the total weight of the target flying car. S103. Send a voice warning message to the target landing point coordinates through a directional speaker, and project a laser warning sign to the target landing point coordinates through a laser emitter; S104. Transmit the target landing point coordinates and hazard level to the ground communication base station, so that the ground communication base station can issue a regional fall warning for the area where the target landing point coordinates are located.

[0028] The embodiments of the present invention can achieve coordinated early warning from the air and the ground when there is a risk of flying car crash, and accurately indicate dangerous areas to ground personnel, thereby reducing the risk of secondary injury from flying car crashes.

[0029] As a further optional implementation, the kinematic parameters include position, velocity, acceleration, and attitude angles, and the power system operating parameters include thrust value, motor status, and control signal communication status. Determining whether the target flying car is in an uncontrolled crash state based on the kinematic parameters and power system operating parameters specifically includes: S1011. Determine whether the target flying car is falling abnormally based on kinematic parameters; S1012. Determine whether the target flying car has a power system malfunction based on the power system operating parameters; S1013. When the target flying car falls abnormally and its power system fails, it is determined that the target flying car is in an uncontrolled falling state.

[0030] Specifically, the onboard warning device of the target flying car is equipped with a six-axis inertial sensor, a GPS positioning module, and a power system parameter acquisition interface. It is used to collect kinematic parameters such as acceleration, angular velocity, altitude, and geographical location of the flying car in real time, as well as power system operating parameters (such as motor speed, battery voltage, and propulsion system thrust). Then, based on the kinematic parameters and power system operating parameters, it determines whether the target flying car is in an out-of-control crash state.

[0031] First, determine whether the target flying car is experiencing an abnormal descent based on its kinematic parameters. Kinematic parameters directly reflect flight status; abnormalities in the following indicators suggest an abnormal descent of the target flying car: 1) The vertical velocity continuously exceeds 3 m / s downwards, and there is no active command to descend; 2) The pitch angle remains below -15° (the nose is diving downwards); 3) The absolute value of the roll angle is consistently >30° (severe fuselage tilt); 4) Irregular and sudden changes in heading angle (exceeding ±20° / s); 5) Vertical acceleration remains <-0.5g; 6) Irregular abrupt changes in lateral / longitudinal acceleration (exceeding ±0.3g / s).

[0032] Then, the operating parameters of the power system are used to determine whether the target flying car has a power system malfunction. Power system malfunction is the main cause of uncontrolled crashes. Abnormalities in the following indicators suggest a power system malfunction in the target flying car: 1) Actual thrust is less than 70% of the rated value; 2) The thrust difference of the multi-rotor system exceeds 15%; 3) The motor speed deviates from the set value by more than 10%; 4) The motor temperature exceeds the rated operating temperature; 5) The motor current changes by more than 20%; 6) The deviation between the control surface / rotor control command and the actual position exceeds 5°; 7) Communication between the flight control system and the power system is interrupted for more than 1 second.

[0033] Finally, based on the aforementioned judgment results, a decision is output. When the kinematic parameters meet the characteristics of runaway and the power system parameters have corresponding faults, the target flying car is determined to be in a runaway and crashing state.

[0034] As a further optional implementation, the fall trajectory of the target flying car is predicted based on kinematic parameters, power system operating parameters, and real-time environmental parameters, and the target impact point coordinates and final fall velocity are determined, specifically including: S1021. Construct the state vector, observation vector, state transition matrix, and observation matrix of the target flying car; S1022. Construct a dynamic model of the target flying car, determine the control input based on the motion parameters of the power system, and determine the air resistance input based on the real-time environmental parameters; S1023. Determine the initial state estimate of the target flying car based on kinematic parameters; S1024. Based on the current state estimate, state vector, observation vector, state transition matrix, and observation matrix of the target flying car, predict the optimal state estimate of the target flying car at the next moment. S1025. Substitute the optimal state estimate, control input, and air resistance input into the dynamic model to obtain the predicted state of the target flying car at the next moment. S1026. Determine the fall trajectory based on the predicted state sequence at future moments; S1027. Determine the target landing point coordinates based on the intersection of the fall trajectory and the ground, and determine the final fall speed based on the predicted state corresponding to the intersection.

[0035] Specifically, this embodiment of the invention, based on the Kalman filter algorithm and dynamic model, dynamically calculates the crash trajectory of the flying car and predicts its target landing point coordinates according to kinematic parameters, power system operating parameters, and real-time environmental parameters (such as wind speed and wind direction). The specific process is as follows: Step 1: Construct the state vector, observation vector, state transition matrix, and observation matrix. 1) State Vector

[0036] The state vector needs to fully describe the motion state of the flying car, and 6 core physical quantities with degrees of freedom are selected:

[0037] The position component includes (Three-dimensional position in geodetic coordinate system), velocity components include (Three-dimensional velocity in geodetic coordinates), attitude angular components include (Rolling angle) (Pitch angle) (Yaw angle), angular velocity components include (Roll velocity) (Pitch angular velocity) (Yaw rate).

[0038] 2) Observation Vector

[0039] The physical quantity selected must be directly measurable by the sensor and must have a mapping relationship with the state vector:

[0040] Among them, observation location Observation speed from GNSS / visual SLAM system Attitude observation from IMU / Doppler radar From AHRS (Attitude and Bearing Reference System).

[0041] 3) State Transition Matrix

[0042] Based on the derivation of the Newton-Euler equations of motion, describe the evolution of the state over time under the condition of no external force:

[0043] Among them, for the translational part (No external force), the corresponding matrix block is the identity matrix; for the rotating part, based on the attitude kinematics equations Jacobian matrix A function of attitude angle Discretization: The continuous system is converted into a discrete-time system using the Euler method or the Runge-Kutta method. ,in This is process noise.

[0044] 4) Observation Matrix

[0045] Establish a linear mapping relationship between the observation vector and the state vector:

[0046] The observation matrix is ​​a diagonal matrix structure, taking the value 1 when the observation directly corresponds to a state component, and 0 when there is no direct correspondence. Example: If the observation position is directly equal to the state position, then... Chinese correspondence The row and column are 1, and the remaining attitude angular velocity related terms are 0.

[0047] Step 2: Constructing the dynamic model and determining the input terms 1) Construction of dynamic model Based on Newton's second law and Euler's equations, establish the 6-DOF dynamic equations:

[0048] in, The total mass of the flying car The moment of inertia matrix (requires CAD modeling or experimental measurement); force components include (Control input force) (Air resistance) (Gravity); torque components include (Control input torque) (Aerodynamic torque).

[0049] 2) Determine the control input

[0050] The control input comes from the motion parameters of the power system:

[0051] Among them, the rotor thrust is (The rotational speed of each rotor is converted via motor control signals); the control surface deflection angle is... (For example, the deflection angle of flaps and ailerons is switched via servo control signals).

[0052] Transformation relationship: Establish a mapping model from control signals to actual forces / torques through dynamic system characteristic experiments. .

[0053] 3) Determine the air resistance input

[0054] Calculated based on real-time environmental parameters:

[0055] Among them, environmental parameters include (Air density, calculated from atmospheric pressure / temperature) (Relative airflow velocity, synthesized from state vector velocity and wind speed); aerodynamic parameters include (Reference area, taken as the maximum windward area of ​​the flying car) (Drag coefficient, obtained through wind tunnel experiments or CFD simulation); It is a direction vector (the unit direction vector relative to the airflow).

[0056] Step 3: Initial State Estimation 1) Data Collection Collect initial measurement data from multiple sensors: initial position Initial angular velocity Initial linear acceleration Initial attitude angle and initial airspeed .

[0057] 2) State fusion Multi-sensor data fusion is performed using extended Kalman filtering (EKF). Establish the state prediction equation: ; Calculate the observation residuals: ; Updated state estimate: ,in Kalman gain; Output initial state estimate .

[0058] Step 4: Optimal State Prediction. Unscented Kalman filtering (UKF) is used to handle nonlinear state transitions.

[0059] 1) Generate Sigma points Based on the current state estimate With covariance matrix Generate 2n+1 Sigma points:

[0060] Among them, scaling parameters , (Sigma point distribution parameters) (Secondary scaling parameter) is a parameter tuning variable.

[0061] 2) State prediction Substitute each Sigma point into the state transition equation:

[0062] Calculate the mean and covariance of the predicted state:

[0063]

[0064] Among them, the weighting coefficients include (Mean weight) (Covariance weights). For process noise (set based on sensor accuracy and system uncertainty).

[0065] 3) Observation Update Substitute the predicted Sigma point into the observation equation:

[0066] Calculate the mean and covariance of the predicted observations:

[0067]

[0068] in, For observation noise (based on sensor measurement error settings).

[0069] Calculate the Kalman gain and update the optimal state estimate:

[0070]

[0071]

[0072] Finally, output the optimal state estimate for the next time step. .

[0073] Step 5: Calculate the predicted state at the next time step Substitute the optimal state estimate, control input, and air resistance input into the dynamic model:

[0074] Solving the differential equation using numerical integration yields:

[0075] Step 6: Determine the fall trajectory The predicted state sequence for future time moments is generated using a recursive method. Trajectory generation stops when any of the following conditions are met: Location conditions: (The flying car arrives at the ground); Time constraints: (Reaching the maximum number of prediction steps); Speed ​​conditions: (Speed ​​reduced to below the safety threshold).

[0076] Step 7: Determine the landing point coordinates and final fall velocity 1) Calculation of landing point coordinates Find the first time the trajectory satisfies status Compared to the previous state The intersection points are accurately calculated using linear interpolation.

[0077]

[0078] The final landing point coordinates are .

[0079] 2) Calculation of final fall velocity The velocity at the moment of impact is also calculated using linear interpolation:

[0080] The final falling speed is .

[0081] As a further optional implementation, the hazard level is determined based on the final fall velocity and the total weight of the target flying vehicle, specifically including: S1028. Calculate the kinetic energy of the fall based on the final fall velocity and the total weight of the target flying car; S1029. Determine the hazard level based on the fall kinetic energy and the preset kinetic energy threshold.

[0082] Specifically, the kinetic energy of the fall is calculated based on the final fall velocity and the total weight of the target flying vehicle, and the hazard level is determined based on the kinetic energy and a preset kinetic energy threshold. For example: Level I (minor) corresponds to a kinetic energy of ≤10,000J; Level II (moderate) corresponds to 10,000J < kinetic energy ≤50,000J; Level III (significant) corresponds to 50,000J < kinetic energy ≤200,000J; Level IV (major) corresponds to 200,000J < kinetic energy ≤500,000J; and Level V (extremely serious) corresponds to a kinetic energy >500,000J.

[0083] As a further optional implementation, a voice warning message is sent to the target landing point coordinates via a directional speaker, and a laser warning mark is projected to the target landing point coordinates via a laser emitter, specifically including: S1031. Determine the voice signal power based on the target flying car's current altitude; S1032. A preset voice warning message is sent to the target landing point coordinates through a directional loudspeaker installed on the target flying car, based on the voice signal power and a preset frequency band. S1033. Determine the radius of the warning area based on the hazard level; S1034. A laser warning sign is projected onto the target landing point coordinates by a laser emitter installed on the target flying car, based on the radius of the warning area.

[0084] Specifically, once the target's landing point is determined, a high-decibel directional loudspeaker immediately activates, playing a voice warning "Flying car crash, danger avoidance" in a loop at a high frequency of 2000-3000Hz (this frequency band has strong penetration and high visibility in urban noise environments). The sound power can be dynamically adjusted according to the fall height. When the fall height is above 500 meters, the power is no less than 120 decibels, and when it is below 500 meters, the power is adjusted to 80-100 decibels to avoid noise pollution while ensuring the warning effect. A high-brightness laser emitter is activated simultaneously, determining the radius of the warning area according to the danger level, and emitting a red laser beam, which is focused and projected onto the predicted target landing point to form a ring laser warning circle. The laser power is ≥500mW, ensuring that it can be clearly identified by ground personnel in sunny, cloudy, and light rain / fog conditions.

[0085] As a further optional implementation, the target impact point coordinates and hazard level are transmitted to a ground communication base station, enabling the ground communication base station to issue a regional fall warning for the area where the target impact point coordinates are located. This specifically includes: S1041. Transmit the target landing point coordinates and hazard level to the ground communication base station in the area where the target landing point coordinates are located via V2X; S1042. Push fall warning information to the road traffic warning terminal in the area where the target landing point coordinates are located through the ground communication base station, so that the road traffic warning terminal can give warnings through sound and light or screen. S1043. Push fall warning information to vehicles and user terminals in the area where the target landing point coordinates are located through ground communication base stations.

[0086] As an optional implementation, the road traffic warning terminal includes smart streetlights, traffic lights, road warning screens, and roadside broadcast terminals.

[0087] Specifically, a V2X communication module is used to transmit the predicted target landing point coordinates and hazard level to a ground communication base station. The ground communication base station is distributed in urban roads, below low-altitude flight paths, and densely populated areas. It has the ability to receive and forward V2X communication signals and is used to distribute the received target landing point coordinates and hazard level to road traffic warning terminals, vehicles, and user terminals within the coverage area.

[0088] Road traffic warning terminals include public facilities such as smart streetlights, traffic lights, road warning screens, and roadside broadcast terminals, with built-in warning control modules. Upon receiving warning data, they activate corresponding warning modes based on the level of danger: In high-risk situations, smart streetlights flash high-frequency red warning lights (5 flashes per second) and simultaneously play voice warnings; traffic lights switch to a full red no-entry state, and road warning screens display a bold red warning: "Flying car crash ahead, avoid immediately"; in medium-risk situations, smart streetlights flash medium-frequency red warning lights (3 flashes per second), and road warning screens display "Flying car crash warning, be careful"; in low-risk situations, smart streetlights remain constantly lit with red warning lights, and road warning screens display "Proceed with caution".

[0089] The ground communication base station is connected to the operator platform. After receiving the early warning data, it sends an emergency warning text message to mobile phone users within a 500-meter radius of the crash area based on the landing point coordinates and the danger level. The text message contains the message "[Emergency Warning] There is a risk of flying car crash in your area. The landing point is XX. Do not approach and take evasive action immediately." At the same time, the city's emergency broadcasting system broadcasts voice warning information to the coverage area.

[0090] The method steps of the embodiments of the present invention have been described above. It can be understood that the embodiments of the present invention can achieve coordinated air and ground early warning when a flying car is at risk of crashing, and accurately alert ground personnel to dangerous areas, thereby reducing the risk of secondary injury from flying car crashes.

[0091] Compared with the prior art, the embodiments of the present invention have the following advantages: 1) High accuracy of landing point warning: The Kalman filter algorithm is used in combination with real-time environmental parameters to optimize trajectory prediction, and the landing point is accurately located. Combined with the red laser ring warning circle, ground personnel can clearly identify the boundary of the danger zone and avoid decision-making errors caused by the ambiguity of the warning range. 2) Strong environmental adaptability: High-frequency directional speakers have strong penetration power and can effectively overcome urban noise interference; high-power laser warnings are not affected by weather such as rain and fog, and can ensure warning effects in a variety of complex environments, thus solving the limitations of traditional sound and light warnings; 3) Good compatibility and scalability: Adopting the V2X vehicle-to-everything (V2X) standard communication protocol, it can seamlessly connect with existing intelligent transportation systems and ground public facilities without large-scale modifications, reducing system deployment costs and facilitating rapid promotion and application; 4) Significantly improved secondary injury prevention capabilities: Through precise early warning and coordinated action, ground personnel can be informed of dangers in advance and take evasive action, greatly reducing the probability of secondary injury to ground personnel and facilities after a flying car crash, and providing strong protection for the safe operation of flying cars.

[0092] Reference Figure 2This invention provides a flying car crash warning device, comprising: The out-of-control crash judgment module is used to acquire the kinematic parameters and power system operating parameters of the target flying car, and to determine whether the target flying car is in an out-of-control crash state based on the kinematic parameters and power system operating parameters. The crash trajectory prediction module is used to predict the crash trajectory of a target flying car when it is in an out-of-control crash state, based on kinematic parameters, power system operating parameters and real-time environmental parameters, and to determine the target landing point coordinates and final crash speed. Then, the danger level is determined based on the final crash speed and the total weight of the target flying car. The airborne warning module is used to send voice warning messages to the target landing point coordinates via a directional speaker and to project laser warning signs to the target landing point coordinates via a laser transmitter. The ground-based early warning module transmits the target's landing point coordinates and hazard level to the ground communication base station, enabling the ground communication base station to issue a regional fall warning for the area where the target's landing point coordinates are located.

[0093] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0094] Reference Figure 3 This invention provides an electronic device, comprising: At least one processor; At least one memory for storing at least one program; When the above-mentioned at least one program is executed by the above-mentioned at least one processor, the above-mentioned at least one processor implements the above-mentioned method for early warning of flying car crashes.

[0095] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0096] This invention also provides a computer-readable storage medium storing a processor-executable computer program that, when executed by a processor, implements the aforementioned method for early warning of a flying car crash.

[0097] This invention provides a computer-readable storage medium that can execute a flying car crash warning method provided in the method embodiments of this invention. It can execute any combination of the implementation steps of the method embodiments and has the corresponding functions and beneficial effects of the method.

[0098] This invention also provides a computer program product, including a computer program that, when executed by a processor, implements the aforementioned method for early warning of a flying car crash.

[0099] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0100] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0101] The embodiments described in this invention are for the purpose of more clearly illustrating the technical solutions of the embodiments of this invention, and do not constitute a limitation on the technical solutions provided by the embodiments of this invention. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this invention are also applicable to similar technical problems.

[0102] The terms "first," "second," "third," "fourth," etc. (if present) in the specification and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0103] In some alternative embodiments, the functions / operations mentioned in the block diagrams may not occur in the order shown in the operation diagrams. For example, depending on the functions / operations involved, two consecutively shown blocks may actually be executed substantially simultaneously, or the aforementioned blocks may sometimes be executed in reverse order. Furthermore, the embodiments presented and described in the flowcharts of this invention are provided by way of example to provide a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed and sub-operations described as part of a larger operation are executed independently.

[0104] Furthermore, although the invention has been described in the context of functional modules, it should be understood that, unless otherwise stated, one or more of the aforementioned functions and / or features may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the invention. Rather, given the properties, functions, and internal relationships of the various functional modules in the apparatus disclosed herein, the actual implementation of the module will be understood within the scope of conventional skill of an engineer. Therefore, those skilled in the art can implement the invention as set forth in the claims using ordinary techniques without excessive experimentation. It is also understood that the specific concepts disclosed are merely illustrative and not intended to limit the scope of the invention, which is determined by the full scope of the appended claims and their equivalents.

[0105] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0106] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0107] More specific examples (a non-exhaustive list) of computer-readable media include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the aforementioned program can be printed, because the aforementioned program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0108] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0109] In the foregoing description of this specification, references to terms such as "one embodiment," "another embodiment," or "some embodiments" indicate that a specific feature, structure, material, or characteristic described in connection with an embodiment or example is included in at least one embodiment or example of the present invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0110] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

[0111] The above is a detailed description of the preferred embodiments of the present invention. However, the present invention is not limited to the above embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention. All such equivalent modifications or substitutions are included within the scope defined by the claims of the present invention.

Claims

1. A method for early warning of flying car crashes, characterized in that, Includes the following steps: Obtain the kinematic parameters and power system operating parameters of the target flying car, and determine whether the target flying car is in an uncontrolled crash state based on the kinematic parameters and the power system operating parameters; When the target flying car is in an out-of-control falling state, the falling trajectory of the target flying car is predicted based on the kinematic parameters, the power system operating parameters and real-time environmental parameters, and the target landing point coordinates and final falling speed are determined. Then, the danger level is determined based on the final falling speed and the total weight of the target flying car. A voice warning message is sent to the target landing point coordinates via a directional speaker, and a laser warning mark is projected to the target landing point coordinates via a laser emitter; The target landing point coordinates and the danger level are transmitted to a ground communication base station, enabling the ground communication base station to issue a regional fall warning for the area where the target landing point coordinates are located.

2. The method for early warning of flying car crashes according to claim 1, characterized in that, The kinematic parameters include position, velocity, acceleration, and attitude angle; the power system operating parameters include thrust value, motor status, and control signal communication status; and the step of determining whether the target flying car is in an uncontrolled crash state based on the kinematic parameters and the power system operating parameters specifically includes: Determine whether the target flying car is falling abnormally based on the kinematic parameters; Determine whether the target flying car has a power system malfunction based on the power system operating parameters; When the target flying car falls abnormally and its power system fails, it is determined that the target flying car is in an uncontrolled falling state.

3. The method for early warning of flying car crashes according to claim 1, characterized in that, The step of predicting the fall trajectory of the target flying car based on the kinematic parameters, the power system operating parameters, and real-time environmental parameters, and determining the target landing point coordinates and final fall velocity, specifically includes: Construct the state vector, observation vector, state transition matrix, and observation matrix of the target flying car; A dynamic model of the target flying car is constructed, the control input is determined based on the motion parameters of the power system, and the air resistance input is determined based on the real-time environmental parameters; The initial state estimate of the target flying car is determined based on the kinematic parameters; Based on the current state estimate of the target flying vehicle, the state vector, the observation vector, the state transition matrix, and the observation matrix, predict the optimal state estimate of the target flying vehicle at the next moment; Substituting the optimal state estimate, the control input, and the air resistance input into the dynamic model, the predicted state of the target flying car at the next moment is obtained; The fall trajectory is determined based on a predicted sequence of states at future moments; The target landing point coordinates are determined based on the intersection of the falling trajectory and the ground, and the final falling speed is determined based on the predicted state corresponding to the intersection.

4. The method for early warning of flying car crashes according to claim 1, characterized in that, The determination of the danger level based on the final fall velocity and the total weight of the target flying car specifically includes: The kinetic energy of the fall is calculated based on the final fall velocity and the total weight of the target flying car. The danger level is determined based on the fall kinetic energy and a preset kinetic energy threshold.

5. The method for early warning of flying car crashes according to claim 1, characterized in that, The step of sending a voice warning message to the target landing point coordinates via a directional speaker and projecting a laser warning mark to the target landing point coordinates via a laser emitter specifically includes: The voice signal power is determined based on the current altitude of the target flying car; The directional loudspeaker installed on the target flying car sends a preset voice warning message to the target landing point coordinates according to the voice signal power and the preset frequency band; The radius of the warning area is determined based on the aforementioned hazard level; The laser warning sign is projected onto the target landing point coordinates by the laser emitter mounted on the target flying car, based on the radius of the warning area.

6. The method for early warning of flying car crashes according to claim 1, characterized in that, The step of transmitting the target impact point coordinates and the hazard level to a ground communication base station, enabling the ground communication base station to issue a regional fall warning for the area where the target impact point coordinates are located, specifically includes: The target landing point coordinates and the hazard level are transmitted to the ground communication base station in the area where the target landing coordinates are located via V2X; The ground communication base station pushes fall warning information to road traffic warning terminals in the area where the target landing point coordinates are located, so that the road traffic warning terminals can issue warnings through sound and light or screens; The ground communication base station pushes fall warning information to vehicles and user terminals in the area where the target landing point coordinates are located.

7. A method for early warning of flying car crashes according to claim 6, characterized in that, The road traffic warning terminal includes smart streetlights, traffic lights, road warning screens, and roadside broadcast terminals.

8. A flying car crash warning device, characterized in that, include: The uncontrolled fall judgment module is used to acquire the kinematic parameters and power system operating parameters of the target flying car, and to determine whether the target flying car is in an uncontrolled fall state based on the kinematic parameters and power system operating parameters; The crash trajectory prediction module is used to predict the crash trajectory of the target flying car based on the kinematic parameters, the power system operating parameters, and real-time environmental parameters when the target flying car is in an out-of-control crash state, and to determine the target landing point coordinates and final crash speed, and then determine the danger level based on the final crash speed and the total weight of the target flying car. An airborne warning module is used to send voice warning information to the target landing point coordinates via a directional speaker and to project laser warning signs to the target landing point coordinates via a laser emitter. The ground-based early warning module is used to transmit the target landing point coordinates and the danger level to a ground communication base station, so that the ground communication base station can provide regional fall warnings for the area where the target landing point coordinates are located.

9. An electronic device, characterized in that, include: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements a flying car crash warning method as described in any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements a flying car crash warning method as described in any one of claims 1 to 7.

Images