Vehicle prompting method, device and equipment based on congestion condition and medium

Abstract

The invention relates to the field of vehicle intelligent control, in particular to a vehicle prompting method, device and equipment based on congestion conditions and a medium. According to the method, the motion data of the traffic participants in the vehicle driving environment are captured in real time, the target congestion role of the vehicle is accurately determined, the limitation of single complex congestion scene recognition in the prior art is broken through, and multi-element congestion factors generated by low-speed driving of the expressway and parallel multi-lane can be handled in a targeted manner. And obtaining a safety prompt strategy based on the preset mapping relation and executing prompt operation, and dynamically adjusting a guide mode according to real-time congestion to realize real-time dynamic regulation and control. Meanwhile, by detecting the congestion change trend after prompting, prompting is stopped when an effective response condition is hit, excessive intervention is avoided, and a closed-loop cooperative guiding mechanism is formed. Therefore, the problem that real-time dynamic regulation and control and cooperative guidance cannot be carried out on complex congestion of the expressway in the prior art is effectively solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of intelligent control of vehicles, and in particular to a vehicle prompting method and device based on congestion conditions, equipment and a medium. BACKGROUND

[0002] With the acceleration of urbanization and the continuous growth of the number of motor vehicles, the problem of highway traffic congestion is becoming increasingly prominent, and the congestion caused by low-speed driving of vehicles in front and parallel driving of multiple lanes accounts for a large proportion. Such traffic conditions not only lead to a significant decrease in traffic efficiency, but also increase fuel consumption and exhaust emissions, and are prone to induce safety hazards such as rear-end collisions and scratches.

[0003] Currently, traffic management systems rely on fixed speed limit signs or simple variable information boards, which are difficult to dynamically adjust lane allocation and speed guidance in real time according to congestion conditions. In addition, although traditional navigation software can provide congestion warnings, it lacks the ability to coordinate and control the driving behavior of parallel vehicles, and cannot effectively alleviate the traffic bottleneck caused by uneven lane occupation or low-speed parallel driving. SUMMARY

[0004] Therefore, the embodiments of the present application provide a vehicle prompting method and device based on congestion conditions, equipment and a medium to solve the problem that the prior art cannot dynamically control and coordinate in real time the congestion caused by low-speed driving and parallel driving of multiple lanes on highways.

[0005] In a first aspect, the embodiments of the present application provide a vehicle prompting method based on congestion conditions, which comprises: When there is a congestion condition in the driving process of a vehicle, based on the motion data of traffic participants in the driving environment of the vehicle, a target congestion role to which the vehicle belongs is determined; Based on the mapping relationship between the preset congestion role and the preset prompting strategy, a safety prompting strategy corresponding to the target congestion role is obtained; According to the safety prompting strategy, a corresponding prompting operation is performed, and the change trend of the congestion condition after prompting is detected; If the change trend of the congestion condition hits the effective response condition of the safety prompting strategy, the prompting operation corresponding to the safety prompting strategy is stopped.

[0006] Further, the determination of the target congestion role to which the vehicle belongs based on the motion data of traffic participants in the driving environment of the vehicle comprises: From the motion data of traffic participants in the driving environment of the vehicle, the first motion data of a first traffic participant located in front of the vehicle, the second motion data of a second traffic participant located in the adjacent lane of the vehicle, and the number and third motion data of a third traffic participant located behind the vehicle are obtained; Acquire real-time motion data of the vehicle during its journey, as well as the first distance between the vehicle and the first traffic participant; If the first distance is greater than a preset distance, the difference between the real-time motion data and the second motion data is within a preset difference range, and the number of the third traffic participants is greater than a preset number, then the target congestion role to which the vehicle belongs is determined to be the first role, wherein the first role is used to characterize that the vehicle is at the forefront of the congestion scenario, or... If the first distance is less than or equal to a preset distance, the difference between the real-time motion data and the first motion data is within a preset difference range, and / or the difference between the real-time motion data and the third motion data is within a preset difference range, then the target congestion role to which the vehicle belongs is determined to be the second role, wherein the second role is used to characterize the vehicle being in a traffic queue in a congestion scenario.

[0007] Furthermore, if the target congestion role is the first role, the step of performing the corresponding prompting operation in the vehicle according to the safety prompting strategy includes: Send a first prompt message to the driver and detect whether the vehicle's driver assistance function is activated, wherein the first prompt message is used to prompt the driver to accelerate or change lanes; If the vehicle's driver assistance function is activated, the system detects the safe redundancy space around the vehicle. Based on the compatibility of the safe redundancy space with the driving environment, it actively controls the vehicle to accelerate or change lanes. After the vehicle completes the acceleration or lane change, a second prompt message is sent to the driver, wherein the second prompt message is used to indicate that the vehicle has completed the acceleration or lane change; or... If the vehicle's driver assistance function is not activated, the system detects whether the driver controls the vehicle to perform an acceleration or lane change. If the driver controls the vehicle to perform an acceleration or lane change, a third prompt message is sent to the driver after the vehicle completes the acceleration or lane change. Alternatively, if the driver does not control the vehicle to perform an acceleration or lane change, the system obtains the prompt level corresponding to the first prompt message and performs a prompt operation on the driver in a manner higher than the prompt level to prompt the driver to accelerate or change lanes.

[0008] Furthermore, the step of providing a prompt to the driver in a manner higher than the prompt level includes: Obtain multiple candidate prompting methods that are higher than the aforementioned prompting level; The current driving risk of the vehicle is obtained by using the vehicle's driving status and the driver's physiological characteristic data; The system selects a prompt method that matches the driving risk from multiple candidate prompt methods and performs the prompt operation on the driver according to the prompt method.

[0009] Furthermore, if the target congestion role is a second role, the step of performing the corresponding prompting operation in the vehicle according to the safety prompting strategy includes: Acquire a second distance between a third traffic participant located behind the vehicle and the vehicle, and third motion data of the third traffic participant; If the second distance is less than the safe distance and the third motion data is greater than the preset safe threshold, then a fifth prompt message is sent to the first traffic participant in front of the vehicle, and a sixth prompt message is sent to the third traffic participant behind the vehicle. The fifth prompt message is used to prompt the first traffic participant to accelerate or change lanes, and the sixth prompt message is used to prompt the third traffic participant to accelerate.

[0010] Furthermore, the method also includes: If the trend of congestion does not meet the effective response conditions of the safety prompt strategy, then obtain the change in motion data of at least one traffic participant in an adjacent lane and the idle time of the adjacent lane. Based on the change in motion data and the idle time, the traffic priority of the adjacent lanes is determined, and the adjacent lane with the highest traffic priority is selected as the target lane. Obtain candidate paths for the vehicle to travel from the current lane to the target lane, and the safety window time required for each candidate path; Acquire the driver's driving habit data and analyze the driving habit data to determine the driver's lane change reaction time; The lane change reaction time is matched with the safety window time, and supplementary prompt information is generated based on the matched candidate path.

[0011] Furthermore, the step of matching the lane change reaction time with the safety window time and generating supplementary prompt information based on the matched candidate path includes: By comparing the lane change reaction time with the safe window time of each candidate path, valid candidate paths whose safe window time is greater than the lane change reaction time are obtained. Calculate the passage risk value for each candidate valid path based on the turning angle and minimum safe distance of each valid candidate path; The candidate valid paths are sorted from smallest to largest according to the traffic risk value to obtain the target path; The supplementary prompt information is generated based on the target path. Secondly, embodiments of the present invention provide a vehicle alert device based on congestion conditions, characterized in that the device comprises: The analysis module is used to determine the target congestion role of a vehicle based on the motion data of traffic participants in the vehicle's driving environment when there is congestion during the vehicle's operation. The acquisition module is used to acquire the safety prompt policy corresponding to the target congestion role based on the mapping relationship between the preset congestion role and the preset prompt policy; The detection module is used to perform corresponding prompting operations according to the safety prompting strategy, and to detect the changing trend of congestion after the prompting. The execution module is used to stop executing the prompting operation corresponding to the safety prompting strategy if the trend of the congestion situation matches the effective response condition of the safety prompting strategy.

[0012] Thirdly, embodiments of the present invention provide a computer device, including: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the method described in the first aspect or any corresponding embodiment thereof.

[0013] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing computer instructions that cause a computer to perform the method described in the first aspect or any of its corresponding embodiments.

[0014] This application accurately identifies the target congestion role of vehicles by capturing real-time motion data of traffic participants in the vehicle driving environment. It overcomes the limitation of existing technologies in recognizing only a single type of complex congestion scenario and can specifically address the diverse congestion factors arising from low-speed driving and multi-lane parallel traffic on highways. Based on a preset mapping relationship, it obtains and executes safety prompt strategies, and can dynamically adjust guidance methods according to real-time congestion, achieving real-time dynamic control. Simultaneously, by detecting the congestion trend after prompting, it stops prompting when a valid response condition is met, avoiding excessive intervention and forming a closed-loop collaborative guidance mechanism. This effectively solves the problem that existing technologies cannot perform real-time dynamic control and collaborative guidance for complex congestion on highways. Attached Figure Description

[0015] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of a vehicle alert method based on congestion conditions according to some embodiments of the present invention; Figure 2 This is a schematic diagram of a system framework according to some embodiments of the present invention; Figure 3 This is a schematic diagram of yet another vehicle alert method based on congestion conditions according to some embodiments of the present invention; Figure 4 This is a schematic diagram of yet another vehicle alert method based on congestion conditions according to some embodiments of the present invention; Figure 5 This is a structural block diagram of a vehicle alert device based on congestion conditions according to an embodiment of the present invention; Figure 6 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] According to embodiments of the present invention, a vehicle alert method, apparatus, device, and medium based on congestion conditions are provided. It should be noted that the steps shown in the flowcharts in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowcharts, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0019] This embodiment provides a vehicle alert method based on congestion conditions. Figure 1 This is a flowchart of a vehicle alert method based on congestion conditions according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps: Step S101: When there is congestion during vehicle operation, determine the target congestion role of the vehicle based on the motion data of traffic participants in the vehicle's driving environment.

[0020] In this embodiment, the vehicle's real-time location and motion status are first acquired through the NSS module (which receives and processes satellite navigation signals, providing global positioning, navigation, and timing services) and the IMU module (which compensates for GPS signal loss and provides motion data when there is no satellite signal for a short period of time). Simultaneously, the radar sensor module (which uses lidar or millimeter-wave radar to detect traffic participants outside the vehicle; lidar is responsible for high-precision imaging at close range and provides distance and orientation of road targets, while millimeter-wave radar detects near and far targets and outputs accurate target speeds) and the camera sensor module (which uses front-view, surround-view, or side-view cameras to detect traffic participants outside the vehicle and provides information such as distance, orientation, and type of road targets) collaboratively collect motion data of surrounding traffic participants (including speed, distance, and orientation of vehicles in front, behind, and adjacent lanes). The vehicle-to-vehicle information interaction is achieved through the V2V communication module (a wireless communication technology that allows direct data exchange between vehicles, sharing information such as location, speed, and direction in real time to improve safety and optimize traffic flow).

[0021] Subsequently, the central domain controller module (which integrates and processes target information from radar and cameras, determines function triggering conditions, and issues alarm signals) performs fusion analysis on the above data. If the data shows that the vehicle is in a following state (small speed difference with the vehicle in front, close distance, and vehicles following behind), it is identified as a "slow-speed following vehicle in congestion". If the data shows that the vehicle is at the front of the congestion and is running parallel to vehicles in the adjacent lane at low speed with vehicles backing up, it is identified as a "slow-speed parallel vehicle in front of the congestion", thus completing the determination of the target congestion role of the vehicle.

[0022] Specifically, based on the motion data of traffic participants in the vehicle's driving environment, the target congestion role of the vehicle is determined, including the following steps A1-A4: Step A1: Obtain the first motion data of the first traffic participant located in front of the vehicle, the second motion data of the second traffic participant located in the adjacent lane of the vehicle, and the number and third motion data of the third traffic participant located behind the vehicle from the motion data of traffic participants in the driving environment where the vehicle is located.

[0023] Based on the motion data of traffic participants in the known driving environment of the vehicle, by filtering and classifying these data, the first motion data (including speed, acceleration, and direction of travel) of the first traffic participant directly in front of the vehicle (such as the vehicle in front) is extracted, the second motion data (including speed and changes in lateral distance from the vehicle) of the second traffic participant located in the adjacent lane to the left or right of the vehicle is extracted, and the number of third traffic participants (such as the vehicle behind) located directly behind and diagonally behind the vehicle is counted, providing key data for subsequent role determination.

[0024] Step A2: Obtain real-time motion data of the vehicle during its journey, as well as the first distance between the vehicle and the first traffic participant.

[0025] The vehicle acquires real-time motion data (such as real-time speed, acceleration, and steering angle) during its driving process using its own sensors (such as IMU modules and vehicle speed sensors). At the same time, it extracts the first distance between the vehicle and the first traffic participant in front (i.e., the longitudinal straight-line distance between the two vehicles) from existing traffic participant motion data or obtains it through the distance calculation module, forming the core parameters for determining the positional relationship between the vehicle and the vehicle in front.

[0026] Step A3: If the first distance is greater than the preset distance, the difference between the real-time motion data and the second motion data is within the preset difference range, and the number of third traffic participants is greater than the preset number, then the target congestion role to which the vehicle belongs is determined to be the first role, wherein the first role is used to characterize the vehicle being at the forefront in the congestion scenario.

[0027] The first distance is compared with the preset distance (such as 100 meters set according to road speed limit and congestion characteristics). If the first distance is greater than the preset distance, and the difference between the real-time vehicle motion data and the second motion data of the second traffic participant (such as the speed difference within ±5 km / h) is within the preset difference range, and the number of the third traffic participants behind is greater than the preset number (such as 3 or more vehicles), then the target congestion role to which the vehicle belongs is determined to be the first role, that is, the vehicle is at the forefront in the congestion scenario.

[0028] Step A4: If the first distance is less than or equal to the preset distance, the difference between the real-time motion data and the first motion data is within the preset difference range, and / or the difference between the real-time motion data and the third motion data is within the preset difference range, then the target congestion role to which the vehicle belongs is determined to be the second role, wherein the second role is used to characterize the vehicle being in the traffic queue in the congestion scenario.

[0029] If the first distance is less than or equal to the preset distance, and the difference between the vehicle's real-time motion data and the first motion data of the first traffic participant (e.g., the speed difference is within ±3 km / h) is within the preset difference range, and / or the difference between the vehicle's real-time motion data and the third motion data of the third traffic participant (e.g., the speed difference is within ±4 km / h) is within the preset difference range, then the target congestion role to which the vehicle belongs is determined to be the second role, that is, the vehicle is in the traffic queue in the congestion scenario.

[0030] Step S102: Based on the mapping relationship between preset congestion roles and preset prompting strategies, obtain the safety prompting strategy corresponding to the target congestion role.

[0031] In this embodiment, based on the preset mapping relationship between congestion roles such as "slow-moving vehicles in congestion" and "low-moving parallel vehicles ahead in congestion" and corresponding prompt strategies, when a vehicle is determined to be a slow-moving vehicle in congestion, the preset strategy is invoked: the status of the following vehicle is judged by the speed difference and relative distance. If the following vehicle is at a safe distance, the text prompt module is triggered to output the text prompt "vehicle approaching from behind". If the following vehicle approaches at high speed, the speaker prompt module is activated simultaneously to issue a voice prompt "vehicle approaching at high speed from behind" to the driver of this vehicle, and a deceleration signal is pushed to the following vehicle through the V2V communication module. When a vehicle is determined to be a low-moving parallel vehicle ahead in congestion, the preset strategy is invoked: the text prompt module is activated for the first time to execute the L1 level text prompt. If the vehicle is driving assistance activated, the acceleration or lane change module is linked to perform the operation. If not activated, the prompt is upgraded to L2 level voice prompt, L3 level voice prompt + steering wheel vibration according to the driver's reaction status, until the highest level prompt has no response. The case is recorded through the V2V communication module, thereby obtaining a safety prompt strategy that is accurately matched with the target congestion role.

[0032] Step S103: Perform the corresponding prompting operation according to the safety prompting strategy, and detect the changing trend of congestion after the prompting.

[0033] In this embodiment, according to the safety prompt strategy, prompts of the corresponding level (such as L1 level text prompts, L2 level voice prompts, or L3 level voice prompts + steering wheel vibration) are sent to the driver through a text prompt module, a speaker prompt module, etc. At the same time, the acceleration or lane change module is linked to perform operations when the assisted driving is activated. During this process, the surrounding traffic speed, vehicle distance changes, and congestion range are continuously monitored through radar, cameras, and V2V communication modules, and the congestion is analyzed in real time to see whether the congestion is relieved after the prompt (such as the traffic speed increases and the vehicle distance increases), thereby obtaining the trend of congestion changes.

[0034] In one embodiment of this application, if the target congestion role is the first role, the corresponding prompting operation is performed inside the vehicle according to the safety prompting strategy, including the following steps B1-B3: Step B1: Send a first prompt message to the driver and check whether the vehicle's driver assistance functions are activated. The first prompt message is used to prompt the driver to accelerate or change lanes.

[0035] First, the system sends an initial prompt to the driver via a text or speaker prompt module, guiding the driver to accelerate or change lanes in text or voice format. Simultaneously, the central domain controller module monitors the vehicle's driver assistance functions in real time, interacting with the vehicle control system to confirm whether these functions are enabled, providing a basis for subsequent actions based on their status.

[0036] Step B2: If the vehicle's driver assistance function is activated, the safe redundancy space around the vehicle is detected. Based on the adaptability of the safe redundancy space to the driving environment, the vehicle is actively controlled to accelerate or change lanes. After the vehicle completes the acceleration or lane change, a second prompt message is sent to the driver. The second prompt message is used to prompt the vehicle to complete the acceleration or lane change.

[0037] If the vehicle's driver assistance functions are detected as active, the radar and camera sensor modules will immediately activate to comprehensively detect the safety redundancy space around the vehicle, including distances to vehicles in front and behind, available space in adjacent lanes, and the speed and direction of surrounding vehicles. Next, the central domain controller module will analyze this detection data with the current driving environment (such as road congestion and traffic density) to calculate the compatibility between the safety redundancy space and the driving environment. When the compatibility reaches a preset threshold, the central domain controller module will send a command to the acceleration or lane change module to actively control the vehicle to perform acceleration or lane change operations. After the vehicle completes acceleration or lane change, the speaker notification module will send a second notification to the driver, informing the driver via voice that the vehicle has completed the corresponding operation.

[0038] Step B3: If the vehicle's driver assistance function is not activated, detect whether the driver controls the vehicle to perform acceleration or lane change actions; if the driver controls the vehicle to perform acceleration or lane change actions, send a third prompt message to the driver after the vehicle completes the acceleration or lane change; or, if the driver does not control the vehicle to perform acceleration or lane change actions, obtain the prompt level corresponding to the first prompt message, and perform a prompt operation on the driver according to a prompt method higher than the prompt level, so as to prompt the driver to accelerate or change lanes.

[0039] If the vehicle's driver assistance functions are detected as not activated, sensors will monitor the driver's actions in real time to determine whether the driver has controlled the vehicle to perform acceleration or lane change actions. If the driver has performed acceleration or lane change actions, the speaker notification module will send a third notification message to the driver after the vehicle has completed the operation, informing them that the operation has been completed.

[0040] If the driver fails to perform the relevant operation, the central domain controller module will obtain the prompt level (such as L1, L2, L3) corresponding to the first prompt information, and then perform the prompt operation on the driver through the corresponding prompt module according to the prompt method of higher level, such as upgrading from L1 level text prompt to L2 level voice prompt, or upgrading from L2 level to L3 level voice prompt plus steering wheel vibration. This prompts the driver to accelerate or change lanes.

[0041] In one embodiment of this application, prompting the driver according to a prompting method higher than the prompting level includes: obtaining multiple candidate prompting methods higher than the prompting level; using the vehicle's driving status and the driver's physiological characteristic data to obtain the current driving risk of the vehicle; obtaining a prompting method that matches the driving risk from the multiple candidate prompting methods, and performing a prompting operation on the driver according to the prompting method.

[0042] Based on the preset progressive rules for prompt levels, all candidate solutions with levels higher than the current prompt level are retrieved from the prompt method library. For example, when the current prompt level is L1 (verbal prompt), candidate prompt methods include L2 (voice prompt), L3 (voice prompt + steering wheel vibration), and extended methods such as "voice prompt + single-side seat vibration" and "voice prompt + red highlighted text on the HUD," ensuring that candidate methods cover multiple dimensions of stimulation, including auditory, visual, and tactile, to meet the prompt needs in different risk scenarios.

[0043] Real-time vehicle status is collected via radar and cameras, including current speed, distance to vehicles in front and behind, and approach speed of vehicles in adjacent lanes. Simultaneously, in-vehicle cameras (monitoring blink frequency and gaze direction) and heart rate sensors acquire driver physiological data, such as fatigue level (blink interval >3 seconds indicates mild fatigue) and focus level (gaze deviating from the road for >2 seconds indicates distraction). This data is input into a risk assessment model to calculate a driving risk value (e.g., 0-100 points, with 80 points or above indicating high risk). High risk is characterized by "severe driver fatigue + high-speed approach of a vehicle from behind," while low risk is characterized by "driver focus + stable status of surrounding vehicles."

[0044] Based on the matching rules between driving risk values ​​and candidate prompting methods (e.g., high risk corresponds to strong stimulus combination prompts, and medium risk corresponds to medium intensity prompts), a suitable solution is selected from the candidate methods. For example, for high risk, "voice reminder (high frequency and rapid) + continuous steering wheel vibration + bilateral seat vibration" is selected; for medium risk, "voice reminder + yellow flashing text on the HUD" is selected. After determining the prompting method, the central domain controller sends instructions to the corresponding prompting modules (speaker, steering wheel vibration module, HUD, etc.) to synchronously execute the prompting operation, ensuring that the driver can quickly perceive and respond.

[0045] In another embodiment of this application, if the target congestion role is the second role, the corresponding prompting operation is performed in the vehicle according to the safety prompting strategy, including: obtaining the second distance between the third traffic participant located behind the vehicle and the vehicle, and the third motion data of the third traffic participant; if the second distance is less than the safe distance and the third motion data is greater than the preset safety threshold, then a fifth prompting message is sent to the first traffic participant located in front of the vehicle, and a sixth prompting message is sent to the third traffic participant located behind the vehicle, wherein the fifth prompting message is used to prompt the first traffic participant to accelerate or change lanes, and the sixth prompting message is used to prompt the third traffic participant to accelerate.

[0046] Specifically, the radar sensor module (such as millimeter-wave radar) at the rear of the vehicle continuously detects the position and movement of third road users (i.e., the following vehicle), calculates and obtains the longitudinal distance (i.e., the second distance) between the two vehicles in real time, and outputs the real-time speed, acceleration, and other third motion data of the following vehicle through the radar module. If the following vehicle is in the radar detection blind spot, the vehicle can also receive the position and motion information actively sent by the following vehicle through the V2V communication module to ensure the accuracy and real-time nature of the second distance and third motion data, providing data support for subsequent risk assessment.

[0047] If the second distance is less than the safe distance and the third motion data is greater than the preset safe threshold, a fifth prompt message is sent to the first traffic participant in front of the vehicle, and a sixth prompt message is sent to the third traffic participant behind the vehicle. The fifth prompt message is used to prompt the first traffic participant to accelerate or change lanes, and the sixth prompt message is used to prompt the third traffic participant to accelerate: When the system detects that the second distance between the following vehicle and the current vehicle (e.g., 20 meters) is less than the preset safe distance (e.g., 50 meters), and the third motion data of the following vehicle (e.g., real-time speed of 80 km / h exceeds the preset safe threshold of 50 km / h in the congested scenario of this road segment, or acceleration of 2 m / s²) is greater than the preset safe threshold of 50 km / h in the congested scenario of this road segment, the system will send a fifth prompt message to the first traffic participant in front of the vehicle and a sixth prompt message to the third traffic participant behind the vehicle. 2 Exceeding the preset threshold by 1m / s 2 When a vehicle is detected as having a rear-end collision risk, the central domain controller module sends a fifth alert message (such as "A vehicle is approaching at high speed from behind; it is recommended to accelerate or change lanes to the right to avoid it") to the first traffic participant (i.e., the vehicle in front) via the V2V communication module. At the same time, it sends a sixth alert message (such as "The distance to the vehicle in front is too close; please immediately reduce your speed to 30 kilometers per hour") to the third traffic participant (i.e., the vehicle behind). This two-way alert reduces the risk of collision. Both the fifth and sixth alert messages are transmitted wirelessly and are converted into voice announcements by the speaker module of the receiving vehicle, ensuring that both drivers are aware of the alert and can take appropriate measures.

[0048] Step S104: If the trend of congestion changes meets the effective response condition of the safety prompt strategy, then stop executing the prompt operation corresponding to the safety prompt strategy.

[0049] In this embodiment, when the radar, camera, and V2V communication module detect that the congestion situation improves to a preset standard after the prompting operation is performed—for example, after a vehicle accelerates, the speed of traffic in the current lane increases to a preset threshold (e.g., from 15 km / h to 25 km / h) and remains there for more than 10 seconds without decreasing; or after a vehicle changes lanes, the parallel congestion in adjacent lanes is relieved, the average distance between vehicles behind increases by more than 20%, and the congestion area does not continue to expand—at this time, the central domain controller module determines that the prompting operation has taken effect, and then sends a termination command to the text prompting module, speaker prompting module, and steering wheel vibration module to stop the current text display, voice broadcast, and vibration reminder, while recording the effective duration and effect data of this prompt for subsequent optimization of the response conditions of the safety prompting strategy.

[0050] As an example, such as Figure 2 As shown, when a vehicle encounters congestion, GNSS+IMU collects positioning data, and radar+camera acquires movement data of traffic participants. This data is then exchanged with the cloud / other vehicle information via the V2V communication module. The central domain controller determines the vehicle's target congestion role based on this information. Then, according to the preset congestion role and prompting strategy mapping, a safety prompting strategy is matched and executed through the central control text and speaker prompting modules, or by linking the vehicle's acceleration / lane change module to intervene. At the same time, the congestion trend is detected. If a valid response condition is met, the controller instructs the relevant modules to stop the prompting operation, thereby realizing intelligent prompting and dynamic control in congestion scenarios.

[0051] This application accurately identifies the target congestion role of vehicles by capturing real-time motion data of traffic participants in the vehicle driving environment. It overcomes the limitation of existing technologies in recognizing only a single type of complex congestion scenario and can specifically address the diverse congestion factors arising from low-speed driving and multi-lane parallel traffic on highways. Based on a preset mapping relationship, it obtains and executes safety prompt strategies, and can dynamically adjust guidance methods according to real-time congestion, achieving real-time dynamic control. Simultaneously, by detecting the congestion trend after prompting, it stops prompting when a valid response condition is met, avoiding excessive intervention and forming a closed-loop collaborative guidance mechanism. This effectively solves the problem that existing technologies cannot perform real-time dynamic control and collaborative guidance for complex congestion on highways.

[0052] Figure 3 This is a flowchart of a vehicle alert method based on congestion conditions according to an embodiment of the present invention, such as... Figure 3 As shown, the process includes the following steps: Step S201: If the trend of congestion does not meet the effective response conditions of the safety prompt strategy, then obtain the change in motion data of at least one traffic participant in an adjacent lane and the idle time of the adjacent lane.

[0053] In this embodiment, firstly, when the detected trend of congestion does not meet the effective response conditions of the safety warning strategy (e.g., the vehicle does not accelerate or change lanes after the original warning, the speed of surrounding traffic does not increase significantly, and the congestion area does not shrink), a data collection mechanism is immediately triggered. At this time, the vehicle's radar sensor module and camera sensor module focus on adjacent lanes (including left and right lanes) and collect motion data of all traffic participants in the lane in real time, including the real-time speed, acceleration, direction of travel, and relative distance to surrounding vehicles. By continuously tracking and recording this data for 5-10 seconds, the changes in motion data are calculated, specifically the speed fluctuation amplitude (e.g., speed standard deviation), acceleration change rate (e.g., frequency of rapid acceleration or deceleration), and overall traffic flow efficiency (e.g., the number of vehicles passing a fixed point per unit time). These data changes can intuitively reflect the traffic stability of adjacent lanes; for example, the smaller the speed fluctuation amplitude and the lower the acceleration change rate, the smoother the traffic flow in that lane.

[0054] Then, while collecting changes in motion data, the idle time of adjacent lanes is simultaneously calculated. The calculation of idle time is based on "space sufficient to safely accommodate the vehicle," that is, using cameras and radar to identify continuous car-free areas in adjacent lanes that can accommodate the vehicle (considering vehicle length and front and rear safety distances), and recording the duration of this area from its appearance to the present. For example, if a certain section in an adjacent lane has maintained a car-free distance of at least 50 meters for the past 8 seconds (meeting the vehicle's length plus a 20-meter safety distance in front and behind), then the idle time of that section is 8 seconds.

[0055] In addition, data exchange with vehicles in adjacent lanes will be conducted via a V2V communication module to verify the accuracy of idle time data collected by sensors and avoid misjudgments caused by sensor blind spots. Finally, the changes in motion data and idle time of adjacent lanes will be compiled into structured data as the basis for subsequent determination of lane priority.

[0056] Step S202: Based on the change in motion data and idle time, determine the traffic priority of adjacent lanes, and select the adjacent lane with the highest traffic priority as the target lane.

[0057] In this embodiment, firstly, quantitative scoring standards are set for motion data changes and idle time, converting the two into comparable values. For motion data changes, a "stability scoring" mechanism is adopted: if the speed fluctuation range of adjacent lanes is within ±3 km / h, the acceleration change rate is less than 0.5 m / s², and the traffic flow propulsion efficiency is more than 10% higher than that of the current lane, the stability score is 80-100 points; if the speed fluctuation range is ±3-5 km / h, the acceleration change rate is 0.5-1 m / s², and the traffic flow propulsion efficiency is the same as that of the current lane, the score is 50-79 points; if the speed fluctuation range exceeds ±5 km / h and there are frequent sudden accelerations or decelerations, the score is below 50 points. For idle time, a "continuous scoring" mechanism is adopted: idle time exceeding 10 seconds and space sufficient for the vehicle to safely change lanes is scored as 80-100 points; idle time between 5-10 seconds is scored as 50-79 points; and idle time less than 5 seconds is scored as less than 50 points.

[0058] Then, based on the urgency of the current congestion scenario, weights are assigned to the stability score and the persistence score (for example, in severe congestion, idle time has a higher weight, accounting for 60%; in light congestion, motion data stability has a higher weight, accounting for 60%), and a weighted average score is calculated for each adjacent lane. The adjacent lane with the highest overall score is determined as the lane with the highest traffic priority, i.e., the target lane.

[0059] For example, the stability score of the left lane is 90 points and the continuity score is 85 points, while the stability score of the right lane is 70 points and the continuity score is 60 points. In a severe congestion scenario (with a continuity weight of 60%), the overall score of the left lane is 90×40%+85×60%=87 points, and the score of the right lane is 70×40%+60×60%=64 points. Therefore, the left lane is identified as the target lane.

[0060] Step S203: Obtain candidate paths for the vehicle to travel from the current lane to the target lane, and the safe window time required for each candidate path.

[0061] In this embodiment, firstly, based on the location of the target lane (left or right), the real-time location of the current vehicle (including the coordinates of the vehicle's center point and the driving direction angle), and the distribution of traffic participants in the target lane, at least three candidate paths are generated through a path planning algorithm. The differences between these paths are mainly reflected in the steering angle (such as a small-angle gentle steering, a medium-angle conventional steering) and the steering timing (such as an immediate steering, a steering delayed by 1-2 seconds).

[0062] For example, if the target lane is on the right, and the vehicle in front of the vehicle on the right is 80 meters away from the vehicle and the vehicle behind the vehicle is 60 meters away from the vehicle, candidate paths such as "turn immediately with a 5° steering angle and cross the lane line within 2 seconds" and "turn with an 8° steering angle and delay for 1 second and cross the lane line within 1.5 seconds" are generated to ensure that the path covers the needs of different driving habits and road conditions.

[0063] Then, for each candidate path, the required safe window time is calculated through simulation. The calculation of the safe window time needs to comprehensively consider the real-time speeds of vehicles in front and behind in the target lane, their relative distances to the vehicle, and the vehicle's steering performance (such as minimum turning radius and steering response delay). Specifically, the simulation will check whether the distance between the vehicle and the vehicle in front in the target lane is always greater than a safe distance (e.g., at least 30 meters) and whether the distance between the vehicle and the vehicle behind is always greater than a safe distance (e.g., at least 20 meters) when the vehicle is traveling along the candidate path, and record the time period from the start of turning to fully entering the target lane without conflicting with surrounding vehicles.

[0064] For example, simulation results for a candidate path show that the positional changes of vehicles in front and behind in the target lane will not overlap with the steering trajectory of this vehicle within the next 3-7 seconds, so the safe window time for this path is 3-7 seconds; the safe window time for another path may be 4-9 seconds. The difference in the safe window time of different paths reflects the urgency and safety of the steering operation.

[0065] Step S204: Obtain the driver's driving habit data and analyze the driving habit data to determine the driver's lane change reaction time.

[0066] In this embodiment, firstly, the central domain controller module accesses a locally stored driver driving habit database. This database contains records of over 100 lane-change operations performed by the driver in the past three months. Each record details the lane-change scenario (e.g., congestion, smooth traffic), the prompting method (e.g., voice, vibration), the time interval from receiving the lane-change prompt to starting to turn the steering wheel, the vehicle speed during the lane change, and the steering angle. For example, the records may display data such as "In congested scenarios, the average response time of drivers to 'voice + vibration' prompts is 1.8 seconds" and "After receiving a lane-change prompt, drivers typically delay turning for 0.5 seconds before starting to steer," ensuring the comprehensiveness and scenario-specificity of the data.

[0067] Then, these driving habit data will be analyzed from multiple dimensions to filter out records that are highly matched with the current congestion scenario (such as only retaining lane change records when the target lane is left or right under congestion conditions), and the driver's lane change reaction time will be calculated using statistical methods.

[0068] The calculation of lane change reaction time is based on the "time difference between receiving the prompt and starting to turn the steering wheel," and the average value is taken after removing outliers (such as excessive delays caused by sudden situations). For example, 20 valid records were selected, with time differences of 1.6 seconds, 1.9 seconds, 1.7 seconds, etc. The calculated average value is 1.8 seconds, and the standard deviation is 0.2 seconds. Therefore, the driver's lane change reaction time is determined to be 1.8 seconds, which reflects the typical response speed of the driver in similar scenarios.

[0069] Step S205: Match the lane change reaction time with the safety window time, and generate supplementary prompt information based on the matched candidate path.

[0070] In this embodiment, the lane change reaction time is matched with the safety window time, and supplementary prompt information is generated based on the matched candidate paths. This includes: comparing the lane change reaction time with the safety window time of each candidate path to obtain valid candidate paths whose safety window time is greater than the lane change reaction time; calculating the traffic risk value of each valid candidate path based on the turning angle and minimum safe distance of each valid candidate path; sorting the valid candidate paths in ascending order of traffic risk value to obtain the target path; and generating supplementary prompt information based on the target path.

[0071] Specifically, the lane change reaction time is compared with the safe window time of each candidate path to obtain valid candidate paths with a safe window time greater than the lane change reaction time. The driver's lane change reaction time (e.g., determined to be 2 seconds after analysis) is compared with the safe window time of each candidate path (e.g., 3-7 seconds, 4-9 seconds, etc.) one by one. Paths with a safe window time start earlier than the lane change reaction time and end later than the sum of the lane change reaction time and the time required for the lane change operation are selected to ensure that the driver has sufficient time to complete the lane change preparation and operation. For example, paths with a safe window time of only 1-3 seconds are eliminated, and paths with a safe window time of ≥4 seconds are retained as valid candidate paths.

[0072] Based on the turning angle and minimum safe distance of each valid candidate path, the traffic risk value of each candidate valid path is calculated: For each valid candidate path, its turning angle (e.g., 5°, 8°, etc.) and minimum safe distance (i.e., the closest distance to surrounding vehicles during the path execution, such as 25 meters, 30 meters, etc.) are extracted first, and then the traffic risk value is calculated through a risk assessment algorithm. The larger the turning angle (e.g., 8° is riskier than 5°) and the smaller the minimum safe distance (e.g., 25 meters is riskier than 30 meters), the higher the risk value, and vice versa. For example, a path with a turning angle of 5° and a minimum safe distance of 30 meters may have a risk value of 20, while another path with a turning angle of 8° and a minimum safe distance of 25 meters may have a risk value of 40. This is used to quantify the safety level of different paths.

[0073] Candidate valid routes are sorted from lowest to highest traffic risk value to obtain the target route. Supplementary prompts are generated based on the target route: all valid candidate routes are sorted from lowest to highest traffic risk value, and the route with the lowest risk value is selected as the target route to ensure optimal safety for lane-changing operations. For example, a route with a risk value of 20 is ranked higher than a route with a risk value of 40, and the former is determined as the target route. Subsequently, supplementary prompts are generated based on the target route's turning direction (left or right), turning angle, safe window time (e.g., 4-8 seconds), and required speed (e.g., 20 km / h). The content might be, "It is recommended to change lanes to the right with a 5° turning angle in 3 seconds, maintain a speed of 20 km / h during the lane change, and ensure sufficient distance between vehicles in front and behind in the target lane (minimum safe distance 30 meters)." This information is simultaneously pushed through voice, HUD display, and other means to guide the driver in accurately executing the lane-changing operation.

[0074] As a complete example, such as Figure 4 As shown: Step 1: After the vehicle starts, it automatically activates GNSS (satellite positioning) + IMU (inertial navigation) to collect its own positioning data, and at the same time, it turns on radar + camera to continuously detect surrounding traffic participants (the position / speed of vehicles in front and behind); all data is uploaded to the cloud through the V2V communication module and interacts with surrounding vehicles in real time to ensure that vehicle-to-vehicle and vehicle-to-environment information is synchronized.

[0075] Step 2: Analyze V2V interaction data and perception data to determine whether the current vehicle is "the vehicle at the front of the congestion" (e.g., at the front of the congestion queue, with vehicles behind it backed up and speeds <15 km / h): If the judgment is "No" (the vehicle is a "follower vehicle" in the congestion and does not affect the passage behind) → proceed to the "follower vehicle branch process".

[0076] If the determination is "yes" (the vehicle is in a congested area ahead and needs to be actively diverted) → proceed to the "Vehicle Branching Process Ahead".

[0077] Branch 1: Follow-the-car process (the vehicle is in a congested follow-the-car state).

[0078] Step 3: Calculate the real-time distance to the vehicle behind (e.g., measure the longitudinal distance between the two vehicles using radar) and compare it with the preset "safe distance threshold" (e.g., a safe distance ≥ 30 meters in congested scenarios).

[0079] If "Yes" (follower vehicle distance ≥ 30 meters, no risk of rear-end collision): execute the text prompt (the central control screen displays "Vehicles approaching from behind, safe distance") → process ends.

[0080] If "No" (the following distance is less than 30 meters and the following vehicle's speed is 10 kilometers per hour greater than the in front vehicle, indicating a risk of rear-end collision): trigger a voice prompt (the speaker plays "The following vehicle is approaching at high speed, please slow down!") → proceed to step 4.

[0081] Step 4: After the voice prompt, the camera and sensors monitor the driver's actions (e.g., whether the brake is applied, hazard lights are activated, or the accelerator is operated): If "yes" (the driver actively brakes to slow down, or the following vehicle reports "slowed down" via V2V, and the distance between vehicles is restored to a safe level): the preceding vehicle manually slows down, or the following vehicle completes the slowdown → process ends.

[0082] If "No" (driver does not operate, distance continues to decrease): Repeat voice prompt (looping "Vehicles approaching from behind, please slow down!") → until driver responds or other termination conditions are triggered.

[0083] Branch 2: Vehicle flow ahead (vehicles are in a state of congestion ahead).

[0084] Step 3: After determining that there is “congested traffic ahead”, first execute the L1 level prompt (e.g., the central control screen displays “You are a congested traffic ahead, it is recommended to speed up / change lanes to clear the congestion”) → complete the “execute prompt action” step.

[0085] Step 4: Check if the vehicle has driver assistance features enabled (e.g., adaptive cruise control, lane change assist): If “Yes” (vehicle assisted driving is activated and lane change / acceleration conditions are met): Automatic lane change / acceleration is triggered (the system automatically plans a safe lane change route, or slightly increases the vehicle speed to 20 km / h) → process ends.

[0086] If "No" (the vehicle is manually driven and the driver assistance functions are not enabled) → proceed to step 5.

[0087] Step 5: Monitor whether the driver performs a "lane change / acceleration operation" (e.g., using turn signals, pressing the accelerator, or using paddle shifters) using a camera and sensors: If “Yes” (the driver actively changes lanes to an empty lane or accelerates to 20 km / h): Manually execute lane change / acceleration → process ends.

[0088] If "No" (driver not operating, congestion continues to worsen): Trigger prompt upgrade (e.g., voice + steering wheel vibration, playing "Please change lanes / accelerate immediately, vehicles behind are backed up!") → Proceed to step 6.

[0089] Step 6: After the upgrade prompt, the system checks whether the current prompt level has reached the "maximum level" (e.g., "voice + vibration + seat massage reminder" has been triggered): If “No” (maximum level not reached): Continue to upgrade prompt (e.g., add “HUD red warning”) → Return to step 5 and re-monitor driver response.

[0090] If "Yes" (maximum level reached, driver still not responding): Feedback to V2V system to record event (upload "Vehicle ahead of congestion not responding, manual intervention required" to the cloud) → process ends.

[0091] This embodiment also provides a vehicle alert device based on congestion conditions. This device is used to implement the above embodiments and preferred embodiments, and details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0092] This embodiment provides a vehicle alert device based on traffic congestion conditions, such as... Figure 5 As shown, it includes: Analysis module 501 is used to determine the target congestion role of a vehicle based on the motion data of traffic participants in the vehicle's driving environment when there is congestion during vehicle operation. The acquisition module 502 is used to acquire the safety prompt policy corresponding to the target congestion role based on the mapping relationship between the preset congestion role and the preset prompt policy. The detection module 503 is used to perform corresponding prompting operations according to the safety prompting strategy, and to detect the changing trend of congestion after the prompting. Execution module 504 is used to stop executing the prompting operation corresponding to the safety prompting policy if the changing trend of the congestion situation meets the valid response condition of the safety prompting policy.

[0093] In this embodiment, the analysis module 501 is used to obtain, from the motion data of traffic participants in the driving environment where the vehicle is located, the first motion data of the first traffic participant in front of the vehicle, the second motion data of the second traffic participant in the adjacent lane of the vehicle, and the number and third motion data of the third traffic participant behind the vehicle; obtain the real-time motion data of the vehicle during driving, and the first distance between the vehicle and the first traffic participant; if the first distance is greater than a preset distance, the difference between the real-time motion data and the second motion data is within a preset difference range, and the number of the third traffic participants is greater than a preset number, then the target congestion role to which the vehicle belongs is determined to be the first role, wherein the first role is used to characterize that the vehicle is at the front end in the congestion scenario; or, if the first distance is less than or equal to the preset distance, the difference between the real-time motion data and the first motion data is within a preset difference range, and / or the difference between the real-time motion data and the third motion data is within a preset difference range, then the target congestion role to which the vehicle belongs is determined to be the second role, wherein the second role is used to characterize that the vehicle is in the traffic queue in the congestion scenario.

[0094] In this embodiment, if the target congestion role is the first role, the detection module 503 is used to send a first prompt message to the driver and detect whether the vehicle's driver assistance function is activated. The first prompt message is used to prompt the driver to accelerate or change lanes. If the vehicle's driver assistance function is activated, the module detects the safety redundancy space around the vehicle, and based on the adaptability of the safety redundancy space to the driving environment, actively controls the vehicle to accelerate or change lanes. After the vehicle completes the acceleration or lane change, the module sends a second prompt message to the driver. The second prompt message is used to prompt the vehicle to complete the acceleration or lane change. Alternatively, if the vehicle's driver assistance function is not activated, the module detects whether the driver controls the vehicle to perform an acceleration or lane change. If the driver controls the vehicle to perform an acceleration or lane change, the module sends a third prompt message to the driver after the vehicle completes the acceleration or lane change. Alternatively, if the driver does not control the vehicle to perform an acceleration or lane change, the module obtains the prompt level corresponding to the first prompt message and performs a prompt operation on the driver according to a prompt method higher than the prompt level to prompt the driver to accelerate or change lanes.

[0095] In this embodiment of the application, the detection module 503 is used to obtain multiple candidate prompting methods that are higher than the prompting level; to obtain the current driving risk of the vehicle using the vehicle's driving status and the driver's physiological characteristic data; to obtain the prompting method that matches the driving risk from the multiple candidate prompting methods, and to perform prompting operations on the driver according to the prompting method.

[0096] In this embodiment of the application, if the target congestion role is the second role, the detection module 503 is used to obtain the second distance between the third traffic participant located behind the vehicle and the vehicle, and the third motion data of the third traffic participant; if the second distance is less than the safe distance and the third motion data is greater than the preset safe threshold, then a fifth prompt message is sent to the first traffic participant located in front of the vehicle, and a sixth prompt message is sent to the third traffic participant located behind the vehicle, wherein the fifth prompt message is used to prompt the first traffic participant to accelerate or change lanes, and the sixth prompt message is used to prompt the third traffic participant to accelerate.

[0097] In this embodiment, the device further includes: a calculation module, configured to: if the trend of congestion does not meet the effective response conditions of the safety prompt strategy, acquire the change in motion data of at least one traffic participant in an adjacent lane and the idle time of the adjacent lane; determine the traffic priority of the adjacent lane based on the change in motion data and the idle time, and take the adjacent lane with the highest traffic priority as the target lane; acquire candidate paths for the vehicle to travel from the current lane to the target lane, and the safety window time required for each candidate path; acquire the driver's driving habit data, and analyze the driving habit data to determine the driver's lane change reaction time; match the lane change reaction time with the safety window time, and generate supplementary prompt information based on the matched candidate paths.

[0098] In this embodiment, the calculation module is used to compare the lane change reaction time with the safe window time of each candidate path to obtain an effective candidate path whose safe window time is greater than the lane change reaction time; calculate the traffic risk value of each effective candidate path based on the turning angle and minimum safe distance of each effective candidate path; sort the effective candidate paths in ascending order of traffic risk value to obtain the target path; and generate supplementary prompt information based on the target path.

[0099] Please see Figure 6 , Figure 6 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 6As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system).

[0100] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0101] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0102] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device as shown by a landing page for an app. Furthermore, the memory 20 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 alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, which can be connected to the computer device 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.

[0103] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0104] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0105] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0106] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A vehicle alert method based on congestion conditions, characterized in that, The method includes: When there is congestion during vehicle operation, the target congestion role of the vehicle is determined based on the motion data of traffic participants in the vehicle's driving environment. Based on the mapping relationship between preset congestion roles and preset prompting strategies, obtain the safety prompting strategy corresponding to the target congestion role; Perform the corresponding prompting operation according to the aforementioned safety prompting strategy, and detect the changing trend of congestion after the prompting; If the trend of congestion changes matches the effective response condition of the safety alert strategy, then the alert operation corresponding to the safety alert strategy will be stopped.

2. The method according to claim 1, characterized in that, The determination of the target congestion role of the vehicle based on the movement data of traffic participants in the vehicle's driving environment includes: From the motion data of traffic participants in the driving environment where the vehicle is located, obtain the first motion data of the first traffic participant in front of the vehicle, the second motion data of the second traffic participant in the adjacent lane of the vehicle, and the number, third motion data, and third motion of the third traffic participant behind the vehicle. Acquire real-time motion data of the vehicle during its journey, as well as the first distance between the vehicle and the first traffic participant; If the first distance is greater than a preset distance, the difference between the real-time motion data and the second motion data is within a preset difference range, and the number of the third traffic participants is greater than a preset number, then the target congestion role to which the vehicle belongs is determined to be the first role, wherein the first role is used to characterize that the vehicle is at the forefront of the congestion scenario, or... If the first distance is less than or equal to a preset distance, the difference between the real-time motion data and the first motion data is within a preset difference range, and / or the difference between the real-time motion data and the third motion data is within a preset difference range, then the target congestion role to which the vehicle belongs is determined to be the second role, wherein the second role is used to characterize the vehicle being in a traffic queue in a congestion scenario.

3. The method according to claim 2, characterized in that, If the target congestion role is the first role, the corresponding prompting operation performed in the vehicle according to the safety prompting strategy includes: Send a first prompt message to the driver and detect whether the vehicle's driver assistance function is activated, wherein the first prompt message is used to prompt the driver to accelerate or change lanes; If the vehicle's driver assistance function is activated, the system detects the safe redundancy space around the vehicle. Based on the compatibility of the safe redundancy space with the driving environment, it actively controls the vehicle to accelerate or change lanes. After the vehicle completes the acceleration or lane change, a second prompt message is sent to the driver, wherein the second prompt message is used to indicate that the vehicle has completed the acceleration or lane change; or... If the vehicle's driver assistance function is not activated, the system detects whether the driver controls the vehicle to perform an acceleration or lane change. If the driver controls the vehicle to perform an acceleration or lane change, a third prompt message is sent to the driver after the vehicle completes the acceleration or lane change. Alternatively, if the driver does not control the vehicle to perform an acceleration or lane change, the system obtains the prompt level corresponding to the first prompt message and performs a prompt operation on the driver in a manner higher than the prompt level to prompt the driver to accelerate or change lanes.

4. The method according to claim 3, characterized in that, The step of providing a prompt to the driver in a manner higher than the prompt level includes: Obtain multiple candidate prompting methods that are higher than the aforementioned prompting level; The current driving risk of the vehicle is obtained by using the vehicle's driving status and the driver's physiological characteristic data; The system selects a prompt method that matches the driving risk from multiple candidate prompt methods and performs the prompt operation on the driver according to the prompt method.

5. The method according to claim 2, characterized in that, If the target congestion role is the second role, the step of performing the corresponding prompting operation in the vehicle according to the safety prompting strategy includes: Acquire a second distance between a third traffic participant located behind the vehicle and the vehicle, and third motion data of the third traffic participant; If the second distance is less than the safe distance and the third motion data is greater than the preset safe threshold, then a fifth prompt message is sent to the first traffic participant in front of the vehicle, and a sixth prompt message is sent to the third traffic participant behind the vehicle. The fifth prompt message is used to prompt the first traffic participant to accelerate or change lanes, and the sixth prompt message is used to prompt the third traffic participant to accelerate.

6. The method according to claim 1, characterized in that, The method further includes: If the trend of congestion does not meet the effective response conditions of the safety prompt strategy, then obtain the change in motion data of at least one traffic participant in an adjacent lane and the idle time of the adjacent lane. Based on the change in motion data and the idle time, the traffic priority of the adjacent lanes is determined, and the adjacent lane with the highest traffic priority is selected as the target lane. Obtain candidate paths for the vehicle to travel from the current lane to the target lane, and the safety window time required for each candidate path; Acquire driver's driving habit data and analyze the driving habit data to determine the driver's lane change reaction time; The lane change reaction time is matched with the safety window time, and supplementary prompt information is generated based on the matched candidate path.

7. The method according to claim 6, characterized in that, The step of matching the lane change reaction time with the safety window time and generating supplementary prompt information based on the matched candidate path includes: By comparing the lane change reaction time with the safe window time of each candidate path, valid candidate paths whose safe window time is greater than the lane change reaction time are obtained. Calculate the passage risk value for each candidate valid path based on the turning angle and minimum safe distance of each valid candidate path; The candidate valid paths are sorted from smallest to largest according to the traffic risk value to obtain the target path; The supplementary prompt information is generated based on the target path.

8. A vehicle alert device based on traffic congestion, characterized in that, The device includes: The analysis module is used to determine the target congestion role of a vehicle based on the motion data of traffic participants in the vehicle's driving environment when there is congestion during the vehicle's operation. The acquisition module is used to acquire the safety prompt policy corresponding to the target congestion role based on the mapping relationship between the preset congestion role and the preset prompt policy; The detection module is used to perform corresponding prompting operations according to the safety prompting strategy, and to detect the changing trend of congestion after the prompting. The execution module is used to stop executing the prompting operation corresponding to the safety prompting strategy if the trend of the congestion situation matches the effective response condition of the safety prompting strategy.

9. A computer device, characterized in that, include: A memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, the processor executing the computer instructions to perform the method of any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the method of any one of claims 1 to 7.

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