Expressway overtaking safety taillight indication method and system

Abstract

The invention discloses an expressway overtaking safety taillight indication method and system, and relates to the technical field of intelligent network connection automobile active safety, and the method comprises the steps: monitoring and obtaining the current vehicle operation parameters of a current vehicle and a preset surrounding vehicle in a vehicle approaching range; identifying and obtaining a target vehicle located in front of the current vehicle or on an adjacent lane; the real-time driving track of the target vehicle, the real-time dynamic state of the current vehicle, the relative speed of the two vehicles and the vehicle distance information of the two vehicles are obtained, and a corresponding overtaking risk assessment value is obtained based on a preset risk assessment model; when the overtaking risk assessment value is not greater than a first preset assessment threshold value, issuing overtaking permission prompt information; and when the overtaking risk assessment value is greater than a second preset assessment threshold value, issuing rear vehicle risk prompt information. The overtaking safety is evaluated in real time through multi-source data fusion, data feedback based on real-time perception is provided for the vehicle, and the traffic accident rate is reduced.

Description

Technical Field

[0001] This application relates to the field of active safety technology for intelligent connected vehicles, specifically to a method and system for indicating safe taillights when overtaking on highways. Background Technology

[0002] Overtaking maneuvers on highways are inherently risky, requiring drivers to possess keen situational awareness and rapid decision-making abilities. Although various driver assistance systems have been developed to mitigate these risks, existing technologies still have significant limitations in handling the dynamic and multi-factor scenarios involved in overtaking.

[0003] Traditional taillight indicator systems primarily convey the driver's lane-changing intentions; their function is relatively static and cannot provide real-time feedback on surrounding traffic conditions or the safety of the current overtaking maneuver. While blind spot monitoring systems can detect obstacles or oncoming vehicles in adjacent lanes, their perception range is limited, and they lack the comprehensive assessment capabilities for dynamic conditions such as longitudinal speed differences and acceleration trends in high-speed scenarios. Lane departure warning systems, although helpful in maintaining lane position, are not designed to support overtaking decisions. Adaptive cruise control systems focus on longitudinal distance control and do not intelligently analyze the timing and safety of lane changes and overtaking.

[0004] Therefore, existing systems are mostly single-point functions, lacking overall perception and decision support for overtaking behavior. They have not achieved deep integration with other vehicle systems (such as on-board sensors, V2V communication, etc.) and cannot provide data-driven, real-time safety guidance to drivers or surrounding vehicles, making it difficult to meet the higher requirements for safe overtaking in increasingly complex traffic environments.

[0005] To meet practical needs, a highway overtaking safety taillight indicator technology is proposed. Summary of the Invention

[0006] To address the shortcomings of existing technologies, the purpose of this application is to provide a method and system for indicating safe overtaking taillights on highways. This system uses multi-source data fusion to assess overtaking safety in real time, provides vehicles with data feedback based on real-time perception, and reduces the incidence of traffic accidents.

[0007] To achieve the above objectives, the technical solution adopted in this application is as follows: In a first aspect, this application provides a method for indicating a safe taillight for overtaking on a highway, the method comprising the following steps: Monitor the current vehicle and surrounding vehicles within a preset vehicle proximity range to obtain the corresponding current vehicle operating parameters; Based on the current vehicle's and the surrounding vehicles' current operating parameters, a target vehicle located in the lane in front of or adjacent to the current vehicle is identified. Based on the current operating parameters of the current vehicle and the target vehicle, the real-time driving trajectory of the target vehicle, the real-time self-vehicle dynamics of the current vehicle, the relative speed between the two vehicles, and the distance between the two vehicles are obtained, and the corresponding overtaking risk assessment value is obtained based on the preset risk assessment model. When the overtaking risk assessment value is not greater than the first preset assessment value threshold, an overtaking permission prompt message is issued; When the overtaking risk assessment value exceeds a second preset assessment threshold, a risk warning message for following vehicles is issued; wherein... The vehicle's current operating parameters include the vehicle's current speed, current acceleration, lane keeping status information, or lane departure status information.

[0008] Based on the above technical solution, the step of issuing an overtaking permission prompt when the overtaking risk assessment value is not greater than the first preset assessment value threshold includes the following steps: When the overtaking risk assessment value is not greater than the first preset assessment value threshold, the taillights of the current vehicle are controlled to illuminate a green warning light to indicate that the conditions for safe overtaking are met.

[0009] Based on the above technical solution, the step of issuing a following vehicle risk warning when the overtaking risk assessment value is greater than the second preset assessment value threshold includes the following steps: When the overtaking risk assessment value is greater than the second preset assessment value threshold, the taillights of the current vehicle are controlled to illuminate as a red warning light.

[0010] Based on the above technical solution, after controlling the taillights of the current vehicle to illuminate a red warning light when the overtaking risk assessment value is greater than the second preset assessment value threshold, the method further includes the following steps: Electronic risk warnings are sent to vehicles behind via V2V communication technology.

[0011] Based on the above technical solution, when the overtaking risk assessment value is greater than the second preset assessment value threshold, the method further includes the following steps: Control the steering wheel of the current vehicle to vibrate as a warning; Control the audio-visual playback system of the current vehicle to provide auditory cues.

[0012] Secondly, this application provides a highway overtaking safety taillight indicator system, the system comprising: The environmental perception module is used to monitor the current vehicle and surrounding vehicles within a preset range to obtain the corresponding current vehicle operating parameters. The environmental perception module is also used to identify a target vehicle located in the lane in front of or adjacent to the current vehicle based on the current vehicle's and the surrounding vehicles' current operating parameters. The data processing module is used to obtain the real-time driving trajectory of the target vehicle, the real-time self-vehicle dynamics of the current vehicle, the relative speed between the two vehicles, and the distance between the two vehicles based on the current operating parameters of the current vehicle and the target vehicle, and to obtain the corresponding overtaking risk assessment value based on the preset risk assessment model. An instruction and communication module is used to issue an overtaking permission prompt when the overtaking risk assessment value is not greater than a first preset assessment value threshold. The instruction and communication module is also used to issue a following vehicle risk warning when the overtaking risk assessment value is greater than a second preset assessment value threshold; wherein... The vehicle's current operating parameters include the vehicle's current speed, current acceleration, lane keeping status information, or lane departure status information.

[0013] Based on the above technical solution, the indication and communication module includes an adaptive taillight indication submodule, which is used to control the taillights of the current vehicle to light up a green indicator light when the overtaking risk assessment value is not greater than a first preset assessment value threshold, so as to indicate that the conditions for safe overtaking are met.

[0014] Based on the above technical solution, the adaptive taillight indicator submodule is also used to control the taillights of the current vehicle to illuminate a red warning light when the overtaking risk assessment value is greater than the second preset assessment value threshold.

[0015] Based on the above technical solution, the indication and communication module also includes a V2V communication submodule, which is used to send electronic risk warnings to vehicles behind via V2V communication technology.

[0016] Based on the above technical solution, the system further includes: The driver feedback module is used to control the steering wheel of the current vehicle to vibrate and control the audio-visual system of the current vehicle to provide auditory prompts when the overtaking risk assessment value is greater than the second preset assessment value threshold.

[0017] Compared with the prior art, the advantages of this application are: This application uses multi-source data fusion to assess overtaking safety in real time, providing vehicles with data feedback based on real-time perception, thereby reducing the incidence of traffic accidents; Enhancing driver situational awareness can provide drivers with clear and reliable judgment based on the dynamic information of target vehicles ahead, thereby preventing accidents caused by misjudgment; By continuously monitoring the status of the lane ahead using a rear-mounted camera and related sensors, a vehicle-to-vehicle collaborative early warning mechanism is established to detect the presence of vehicles in real time, thereby supporting risk assessment of overtaking intentions of vehicles behind. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating the steps of the highway overtaking safety taillight indication method according to an embodiment of this application; Figure 2 This is a structural block diagram of a highway overtaking safety taillight indicator system according to an embodiment of this application; Figure 3 This is a schematic diagram illustrating the principle structure of the highway overtaking safety taillight indication method according to an embodiment of this application. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] The embodiments of this application will be further described in detail below with reference to the accompanying drawings.

[0022] This application provides a method and system for indicating safe overtaking taillights on highways. By fusing multi-source data, it assesses overtaking safety in real time, provides vehicles with data feedback based on real-time perception, and reduces the incidence of traffic accidents.

[0023] To achieve the aforementioned technical effects, the overall concept of this application is as follows: A method for indicating safe overtaking taillights on highways, the method comprising the following steps: S1. Monitor the current vehicle and surrounding vehicles within the preset vehicle proximity range to obtain the corresponding current vehicle operating parameters; S2. Based on the current operating parameters of the current vehicle and surrounding vehicles, identify the target vehicle located in the lane in front of or adjacent to the current vehicle. S3. Based on the current operating parameters of the current vehicle and the target vehicle, obtain the real-time driving trajectory of the target vehicle, the real-time self-vehicle dynamics of the current vehicle, the relative speed between the two vehicles and the distance between the two vehicles, and obtain the corresponding overtaking risk assessment value based on the preset risk assessment model. S4. When the overtaking risk assessment value is not greater than the first preset assessment value threshold, an overtaking permission prompt message is issued; S5. When the overtaking risk assessment value exceeds the second preset assessment threshold, a risk warning message for following vehicles is issued; whereby... The vehicle's current operating parameters include the vehicle's current speed, vehicle's current acceleration, lane keeping status information, or lane departure status information.

[0024] The embodiments of this application will be further described in detail below with reference to the accompanying drawings.

[0025] Firstly, see [the following] Figure 1 As shown in the figure, this application provides a method for indicating a safe overtaking taillight on a highway, which includes the following steps: S1. Monitor the current vehicle and surrounding vehicles within the preset vehicle proximity range to obtain the corresponding current vehicle operating parameters; S2. Based on the current operating parameters of the current vehicle and surrounding vehicles, identify the target vehicle located in the lane in front of or adjacent to the current vehicle. S3. Based on the current operating parameters of the current vehicle and the target vehicle, obtain the real-time driving trajectory of the target vehicle, the real-time self-vehicle dynamics of the current vehicle, the relative speed between the two vehicles and the distance between the two vehicles, and obtain the corresponding overtaking risk assessment value based on the preset risk assessment model. S4. When the overtaking risk assessment value is not greater than the first preset assessment value threshold, an overtaking permission prompt message is issued; S5. When the overtaking risk assessment value exceeds the second preset assessment threshold, a risk warning message for following vehicles is issued; whereby... The vehicle's current operating parameters include the vehicle's current speed, current acceleration, lane keeping status information, or lane departure status information.

[0026] In this embodiment of the application, overtaking safety is evaluated in real time by fusing multi-source data, and data feedback based on real-time perception is provided to the vehicle to reduce the traffic accident rate; Enhancing driver situational awareness can provide drivers with clear and reliable judgment based on the dynamic information of target vehicles ahead, thereby preventing accidents caused by misjudgment; By continuously monitoring the status of the lane ahead using a rear-mounted camera and related sensors, a vehicle-to-vehicle collaborative early warning mechanism is established to detect the presence of vehicles in real time, thereby supporting risk assessment of overtaking intentions of vehicles behind.

[0027] Furthermore, the step of issuing an overtaking permission prompt when the overtaking risk assessment value is not greater than a first preset assessment value threshold includes the following steps: When the overtaking risk assessment value is not greater than the first preset assessment value threshold, the taillights of the current vehicle are controlled to illuminate a green warning light to indicate that the conditions for safe overtaking are met.

[0028] Furthermore, the step of issuing a following vehicle risk warning when the overtaking risk assessment value is greater than the second preset assessment value threshold includes the following steps: When the overtaking risk assessment value is greater than the second preset assessment value threshold, the taillights of the current vehicle are controlled to illuminate as a red warning light.

[0029] Furthermore, after controlling the taillights of the current vehicle to illuminate a red warning light when the overtaking risk assessment value is greater than the second preset assessment value threshold, the method further includes the following steps: Electronic risk warnings are sent to vehicles behind via V2V communication technology.

[0030] Furthermore, when the overtaking risk assessment value is greater than the second preset assessment value threshold, the method further includes the following steps: Control the steering wheel of the current vehicle to vibrate as a warning; Control the audio-visual playback system of the current vehicle to provide auditory cues.

[0031] This application provides a highway overtaking safety taillight indicator technology that integrates Advanced Driving Assistance System (ADAS) sensors, an onboard computing platform, and vehicle-to-vehicle (V2V) communication technology. Through real-time perception and intelligent analysis of the vehicle's surrounding environment, dynamic operating conditions, and the behavior of following vehicles, it achieves accurate assessment of overtaking safety. The system collects data from sensors including radar, lidar, and ultrasonic sensors, and combines this data with operating parameters (such as speed, acceleration, and lane position) provided by the vehicle's electronic control unit (ECU). A built-in decision-making algorithm dynamically calculates whether safe overtaking conditions are met, and provides visual feedback through adaptive taillight indicators—for example, green light indicates safety, and red light indicates risk.

[0032] Furthermore, the system can transmit relevant warning information to following vehicles in real time via V2V communication, guiding them to make more reasonable driving decisions. The system is also equipped with haptic (such as steering wheel vibration) and audio feedback mechanisms within the vehicle to improve the driver's perception and reaction efficiency.

[0033] Specifically, the technical solutions of this application embodiment can achieve the following technical effects: Enhanced Context Awareness: Through multimodal sensor fusion and AI algorithms, the system can comprehensively grasp the dynamics of vehicles in front and behind and the environmental conditions, significantly improving the accuracy of overtaking decisions.

[0034] Collaborative traffic optimization: Risk information is shared with surrounding vehicles through V2V communication (communication latency ≤100ms), achieving a leap from "single-vehicle intelligence" to "group collaboration".

[0035] Proactive risk intervention: Unlike traditional reactive safety systems, this system can predict risks and issue warnings before overtaking behavior is initiated, thus achieving proactive safety protection.

[0036] System self-evolution capability: AI modules based on reinforcement learning can continuously adapt to new environments, optimize algorithms, and improve long-term operating efficiency.

[0037] Furthermore, the key technical points of the technical solutions provided in the embodiments of this application are as follows: (1) Target detection accuracy and short-term trajectory prediction stability in high-speed scenarios: The algorithm model requires sufficient training samples, including various vehicle behavior patterns and environmental variables under high-speed conditions. The model needs high-frequency input and must maintain low-latency output.

[0038] (2) Design of multivariate risk models: By fusing multi-dimensional parameters such as predicted trajectory, relative speed, vehicle distance, and acceleration, a unified "risk score" is output. This score can be dynamically adjusted in special scenarios (multi-vehicle lane merging, construction sections, short sight distance sections, etc.) to improve the robustness of the scoring model. Given the dynamic and complex nature of high-speed traffic environments, the system needs to possess adaptive adjustment capabilities. Through continuous collection of operational data and iterative training with samples, the trajectory prediction and risk scoring models are dynamically optimized, thereby improving assessment accuracy and reducing false trigger rates.

[0039] In summary, the embodiments of this application provide an overtaking safety enhancement scheme for future intelligent transportation scenarios, which has proactive decision-making capabilities and multi-source fusion perception capabilities. It effectively makes up for the deficiencies of existing technologies in highway overtaking safety and improves the level of inter-vehicle collaboration and driver safety perception.

[0040] Based on the technical solution of this application embodiment, the specific workflow is as follows: First, environmental awareness initialization: After the system starts up, the ADAS module is activated, and sensors such as radar, lidar, and cameras begin to collect information about surrounding vehicles and road environment simultaneously, forming a multimodal raw dataset.

[0041] Second, vehicle status data reading: The ECU synchronously reads the current vehicle operating parameters, such as current speed, acceleration, lane keeping / departure status, etc.

[0042] Thirdly, target recognition and trajectory prediction: The AI ​​processing unit integrates environmental perception data, executes target detection algorithms, and identifies target vehicles in front and adjacent lanes.

[0043] Fourth point, overtaking risk assessment: The system inputs information such as the target vehicle's trajectory, the vehicle's dynamics, relative speed, and distance to the risk scoring model (such as a combination of rule-based model and neural network) for scoring, and the scoring result is a risk value between 0 and 1.

[0044] Fifthly, the instruction feedback mechanism is triggered: If the risk score is ≤0.3, the taillights will illuminate a green warning light, indicating that the conditions for safe overtaking are met. If the score is greater than 0.7, the taillights will illuminate as a red warning light, and an electronic risk warning will be sent to the following vehicle via V2V.

[0045] Sixth point, driver feedback and intervention: If a risk is detected, the system simultaneously triggers tactile (steering wheel vibration) and auditory cues to help the driver maintain attention and avoid the risk.

[0046] Seventh point, system updates and learning: The system refreshes the above process every second, continuously updating decisions. Data collected during operation is synchronously used for subsequent model iteration training (reinforcement learning / adaptive calibration mechanism).

[0047] It should be noted that, from a technical feasibility perspective, the technical solutions in this application utilize radar, lidar, ultrasonic sensors, cameras, ECUs, AI inference modules, and other hardware platforms that are already maturely applied in the current automotive electronics field. Their core software algorithms (such as object detection, trajectory prediction, and decision-making models) have been extensively validated in intelligent driving systems and possess a high degree of engineering feasibility. From the perspective of deployment feasibility, the system can be used for pre-installation integration in the development of new models, as well as for aftermarket retrofitting on vehicles already on the road, and has good compatibility and scalability. From an economic and feasibility perspective, the system has significant effects in reducing traffic accident risks, reducing vehicle maintenance costs, and enhancing user safety. It has clear market and social value and is suitable for large-scale promotion and application.

[0048] Secondly, see Figures 2-3 As shown in the figure, this application provides a highway overtaking safety taillight indicator system, which includes: The environmental perception module is used to monitor the current vehicle and surrounding vehicles within a preset range to obtain the corresponding current vehicle operating parameters. The environmental perception module is also used to identify a target vehicle located in the lane in front of or adjacent to the current vehicle based on the current vehicle's and the surrounding vehicles' current operating parameters. The data processing module is used to obtain the real-time driving trajectory of the target vehicle, the real-time self-vehicle dynamics of the current vehicle, the relative speed between the two vehicles, and the distance between the two vehicles based on the current operating parameters of the current vehicle and the target vehicle, and to obtain the corresponding overtaking risk assessment value based on the preset risk assessment model. An instruction and communication module is used to issue an overtaking permission prompt when the overtaking risk assessment value is not greater than a first preset assessment value threshold. The instruction and communication module is also used to issue a following vehicle risk warning when the overtaking risk assessment value is greater than a second preset assessment value threshold; wherein... The vehicle's current operating parameters include the vehicle's current speed, current acceleration, lane keeping status information, or lane departure status information.

[0049] In this embodiment of the application, overtaking safety is evaluated in real time by fusing multi-source data, and data feedback based on real-time perception is provided to the vehicle to reduce the traffic accident rate; Enhancing driver situational awareness can provide drivers with clear and reliable judgment based on the dynamic information of target vehicles ahead, thereby preventing accidents caused by misjudgment; By continuously monitoring the status of the lane ahead using a rear-mounted camera and related sensors, a vehicle-to-vehicle collaborative early warning mechanism is established to detect the presence of vehicles in real time, thereby supporting risk assessment of overtaking intentions of vehicles behind.

[0050] Furthermore, the indication and communication module includes an adaptive taillight indication submodule, which is used to control the taillights of the current vehicle to illuminate a green indicator light when the overtaking risk assessment value is not greater than a first preset assessment value threshold, so as to indicate that the conditions for safe overtaking are met.

[0051] Furthermore, the adaptive taillight indicator submodule is also used to control the taillights of the current vehicle to illuminate a red warning light when the overtaking risk assessment value is greater than a second preset assessment value threshold.

[0052] Furthermore, the indication and communication module also includes a V2V communication submodule, which is used to send electronic risk warnings to vehicles behind via V2V communication technology.

[0053] Furthermore, the system also includes: The driver feedback module is used to control the steering wheel of the current vehicle to vibrate and control the audio-visual system of the current vehicle to provide auditory prompts when the overtaking risk assessment value is greater than the second preset assessment value threshold.

[0054] It should be noted that the embodiments of this application provide an intelligent taillight indication system for improving overtaking safety on highways. The system integrates advanced driver assistance system (ADAS) sensors, on-board processing unit and vehicle-to-vehicle (V2V) communication module, which can perform real-time perception and dynamic analysis of traffic environment, determine the feasibility of overtaking behavior and provide proactive feedback.

[0055] This system detects the presence and dynamic status of target vehicles ahead using radar, lidar, or ultrasonic sensors, and acquires operating parameters from the vehicle's electronic control unit (ECU) and ADAS module, including but not limited to current vehicle speed, acceleration, lane position, and lane departure status. The system fuses and processes this multi-source data, and assesses whether safe overtaking conditions are met based on a preset algorithm.

[0056] Based on the assessment results, the system drives the taillight adaptive indicator to provide color-coded feedback: green indicates safe overtaking conditions, while red indicates potential risk. Simultaneously, when an unsafe condition is detected, the system sends electronic warning information to following vehicles via the V2V communication module, enabling risk sharing and coordinated response between vehicles.

[0057] To further enhance drivers' ability to perceive potential risks, the system also features an in-vehicle multimodal alarm mechanism. This mechanism uses tactile feedback (such as steering wheel vibration) and audio signals to alert drivers to their current status, thereby improving their awareness and ability to respond to overtaking safety in complex traffic environments.

[0058] This application provides an active safety solution based on real-time data analysis, which significantly improves overtaking safety in high-speed driving environments and has good system integration and practical deployability, making it suitable for both pre-installed and aftermarket applications in intelligent connected vehicles.

[0059] This application provides a highway overtaking safety taillight indicator technology that integrates Advanced Driving Assistance System (ADAS) sensors, an onboard computing platform, and vehicle-to-vehicle (V2V) communication technology. Through real-time perception and intelligent analysis of the vehicle's surrounding environment, dynamic operating conditions, and the behavior of following vehicles, it achieves accurate assessment of overtaking safety. The system collects data from sensors including radar, lidar, and ultrasonic sensors, and combines this data with operating parameters (such as speed, acceleration, and lane position) provided by the vehicle's electronic control unit (ECU). A built-in decision-making algorithm dynamically calculates whether safe overtaking conditions are met, and provides visual feedback through adaptive taillight indicators—for example, green light indicates safety, and red light indicates risk.

[0060] Furthermore, the system can transmit relevant warning information to following vehicles in real time via V2V communication, guiding them to make more reasonable driving decisions. The system is also equipped with haptic (such as steering wheel vibration) and audio feedback mechanisms within the vehicle to improve the driver's perception and reaction efficiency.

[0061] Specifically, the technical solution of this application proposes an intelligent taillight indicator system, which aims to improve overtaking safety under highway conditions. This system comprehensively utilizes Advanced Driver Assistance System (ADAS) sensors, Electronic Control Unit (ECU), Artificial Intelligence (AI) based processing module, and Vehicle-to-Vehicle (V2V) communication technology to construct a closed-loop environmental perception-intelligent decision-making-active prompting system architecture, as detailed below: 1. Environmental Awareness Module (ADAS): It integrates radar (detection range ≥100m), lidar, ultrasonic sensors and cameras (120° field of view) to collect real-time spatial information about the vehicle's surroundings, including key data such as the position, speed, acceleration and direction of vehicles in front and adjacent lanes, to ensure a comprehensive understanding of the current traffic situation.

[0062] 2. Data Processing Module (ECU + AI Unit): As the central information processing hub, the ECU integrates data from various sensors and performs preliminary processing in conjunction with the vehicle's own dynamic parameters (vehicle speed, acceleration, lane departure, etc.) before transmitting the data to the AI ​​processing unit. The AI ​​module, by fusing the perception data, executes intelligent algorithms including target detection, trajectory prediction (based on an LSTM model), and risk assessment to determine whether the current conditions are suitable for safe overtaking.

[0063] 3. Indication and Communication Module: Adaptive taillight indicator submodule: Based on the judgment results of the AI ​​module, the taillight indicator displays real-time signals at the rear of the vehicle through color-coded lights: green (risk score ≤ 0.3) indicates that it is safe to overtake, and red (score > 0.7 and V2V triggered) indicates that it is unsafe.

[0064] V2V communication submodule: When an unsafe situation is detected, it automatically broadcasts electronic warnings to surrounding vehicles via DSRC or 5G protocol to achieve information sharing and traffic coordination.

[0065] 4. Driver Feedback Module: Inside the vehicle, the system provides immediate warnings or guidance to the driver through steering wheel vibration (haptic feedback), instrument panel or HUD displays, and sound prompts (auditory feedback), thereby improving the driver's risk perception and reaction speed.

[0066] 5. System stability and maintainability: The system is equipped with a dedicated power supply unit to ensure that critical modules can operate stably even under voltage fluctuations; it also supports OTA software upgrades and has adaptive learning capabilities, continuously optimizing judgment strategies as data accumulates.

[0067] Specifically, the technical solutions of this application embodiment can achieve the following technical effects: Enhanced Context Awareness: Through multimodal sensor fusion and AI algorithms, the system can comprehensively grasp the dynamics of vehicles in front and behind and the environmental conditions, significantly improving the accuracy of overtaking decisions.

[0068] Collaborative traffic optimization: Risk information is shared with surrounding vehicles through V2V communication (communication latency ≤100ms), achieving a leap from "single-vehicle intelligence" to "group collaboration".

[0069] Proactive risk intervention: Unlike traditional reactive safety systems, this system can predict risks and issue warnings before overtaking behavior is initiated, thus achieving proactive safety protection.

[0070] System self-evolution capability: AI modules based on reinforcement learning can continuously adapt to new environments, optimize algorithms, and improve long-term operating efficiency.

[0071] Furthermore, the key technical points of the technical solutions provided in the embodiments of this application are as follows: (1) Target detection accuracy and short-term trajectory prediction stability in high-speed scenarios: The algorithm model requires sufficient training samples, including various vehicle behavior patterns and environmental variables under high-speed conditions. The model needs high-frequency input and must maintain low-latency output.

[0072] (2) Design of multivariate risk models: By fusing multi-dimensional parameters such as predicted trajectory, relative speed, vehicle distance, and acceleration, a unified "risk score" is output. This score can be dynamically adjusted in special scenarios (multi-vehicle lane merging, construction sections, short sight distance sections, etc.) to improve the robustness of the scoring model. Given the dynamic and complex nature of high-speed traffic environments, the system needs to possess adaptive adjustment capabilities. Through continuous collection of operational data and iterative training with samples, the trajectory prediction and risk scoring models are dynamically optimized, thereby improving assessment accuracy and reducing false trigger rates.

[0073] In summary, the embodiments of this application provide an overtaking safety enhancement scheme for future intelligent transportation scenarios, which has proactive decision-making capabilities and multi-source fusion perception capabilities. It effectively makes up for the deficiencies of existing technologies in highway overtaking safety and improves the level of inter-vehicle collaboration and driver safety perception.

[0074] Based on the technical solution of this application embodiment, the specific workflow is as follows: First, environmental awareness initialization: After the system starts up, the ADAS module is activated, and sensors such as radar, lidar, and cameras begin to collect information about surrounding vehicles and road environment simultaneously, forming a multimodal raw dataset.

[0075] Second, vehicle status data reading: The ECU synchronously reads the current vehicle operating parameters, such as current speed, acceleration, lane keeping / departure status, etc.

[0076] Thirdly, target recognition and trajectory prediction: The AI ​​processing unit integrates environmental perception data, executes target detection algorithms, and identifies target vehicles in front and adjacent lanes.

[0077] Fourth point, overtaking risk assessment: The system inputs information such as the target vehicle's trajectory, the vehicle's dynamics, relative speed, and distance to the risk scoring model (such as a combination of rule-based model and neural network) for scoring, and the scoring result is a risk value between 0 and 1.

[0078] Fifthly, the instruction feedback mechanism is triggered: If the risk score is ≤0.3, the taillights will illuminate a green warning light, indicating that the conditions for safe overtaking are met. If the score is greater than 0.7, the taillights will illuminate as a red warning light, and an electronic risk warning will be sent to the following vehicle via V2V.

[0079] Sixth point, driver feedback and intervention: If a risk is detected, the system simultaneously triggers tactile (steering wheel vibration) and auditory cues to help the driver maintain attention and avoid the risk.

[0080] Seventh point, system updates and learning: The system refreshes the above process every second, continuously updating decisions. Data collected during operation is synchronously used for subsequent model iteration training (reinforcement learning / adaptive calibration mechanism).

[0081] It should be noted that, from a technical feasibility perspective, the technical solutions in this application utilize radar, lidar, ultrasonic sensors, cameras, ECUs, AI inference modules, and other hardware platforms that are already maturely applied in the current automotive electronics field. Their core software algorithms (such as object detection, trajectory prediction, and decision-making models) have been extensively validated in intelligent driving systems and possess a high degree of engineering feasibility. From the perspective of deployment feasibility, the system can be used for pre-installation integration in the development of new models, as well as for aftermarket retrofitting on vehicles already on the road, and has good compatibility and scalability. From an economic and feasibility perspective, the system has significant effects in reducing traffic accident risks, reducing vehicle maintenance costs, and enhancing user safety. It has clear market and social value and is suitable for large-scale promotion and application.

[0082] In summary, the highway overtaking safety taillight indicator system provided in this application embodiment has the same technical principle as the highway overtaking safety taillight indicator method provided in the first aspect in terms of technical problems, technical solutions and technical effects, so it will not be described in detail here.

[0083] In the description of this application, it should be noted that the terms "upper," "lower," etc., indicating the orientation or positional relationship are based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. Unless otherwise expressly specified and limited, the terms "installed," "connected," and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication between two elements. For those skilled in the art, the specific meaning of the above terms in this application can be understood according to the specific circumstances.

[0084] It should be noted that in this application, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0085] The above description is merely a specific embodiment of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for indicating safety taillights for overtaking on highways, characterized in that, The method includes the following steps: Monitor the current vehicle and surrounding vehicles within a preset vehicle proximity range to obtain the corresponding current vehicle operating parameters; Based on the current vehicle's and the surrounding vehicles' current operating parameters, a target vehicle located in the lane in front of or adjacent to the current vehicle is identified. Based on the current operating parameters of the current vehicle and the target vehicle, the real-time driving trajectory of the target vehicle, the real-time self-vehicle dynamics of the current vehicle, the relative speed between the two vehicles, and the distance between the two vehicles are obtained, and the corresponding overtaking risk assessment value is obtained based on the preset risk assessment model. When the overtaking risk assessment value is not greater than the first preset assessment value threshold, an overtaking permission prompt message is issued; When the overtaking risk assessment value exceeds a second preset assessment threshold, a risk warning message for following vehicles is issued; wherein... The vehicle's current operating parameters include the vehicle's current speed, current acceleration, lane keeping status information, or lane departure status information.

2. The highway overtaking safety taillight indication method as described in claim 1, characterized in that, When the overtaking risk assessment value is not greater than the first preset assessment value threshold, the overtaking permission prompt information is issued, including the following steps: When the overtaking risk assessment value is not greater than the first preset assessment value threshold, the taillights of the current vehicle are controlled to illuminate a green warning light to indicate that the conditions for safe overtaking are met.

3. The highway overtaking safety taillight indication method as described in claim 1, characterized in that, When the overtaking risk assessment value is greater than the second preset assessment value threshold, a risk warning message for following vehicles is issued, including the following steps: When the overtaking risk assessment value is greater than the second preset assessment value threshold, the taillights of the current vehicle are controlled to illuminate as a red warning light.

4. The highway overtaking safety taillight indication method as described in claim 3, characterized in that, After controlling the taillights of the current vehicle to illuminate a red warning light when the overtaking risk assessment value is greater than the second preset assessment value threshold, the method further includes the following steps: Electronic risk warnings are sent to vehicles behind via V2V communication technology.

5. The highway overtaking safety taillight indication method as described in claim 1, characterized in that, When the overtaking risk assessment value is greater than the second preset assessment value threshold, the method further includes the following steps: Control the steering wheel of the current vehicle to vibrate as a warning; Control the audio-visual playback system of the current vehicle to provide auditory cues.

6. A highway overtaking safety taillight indicator system, characterized in that, The system includes: The environmental perception module is used to monitor the current vehicle and surrounding vehicles within a preset range to obtain the corresponding current vehicle operating parameters. The environmental perception module is also used to identify a target vehicle located in the lane in front of or adjacent to the current vehicle based on the current vehicle's and the surrounding vehicles' current operating parameters. The data processing module is used to obtain the real-time driving trajectory of the target vehicle, the real-time self-vehicle dynamics of the current vehicle, the relative speed between the two vehicles, and the distance between the two vehicles based on the current operating parameters of the current vehicle and the target vehicle, and to obtain the corresponding overtaking risk assessment value based on the preset risk assessment model. An instruction and communication module is used to issue an overtaking permission prompt when the overtaking risk assessment value is not greater than a first preset assessment value threshold. The instruction and communication module is also used to issue a following vehicle risk warning when the overtaking risk assessment value is greater than a second preset assessment value threshold; wherein... The vehicle's current operating parameters include the vehicle's current speed, current acceleration, lane keeping status information, or lane departure status information.

7. The highway overtaking safety taillight indicator system as described in claim 6, characterized in that: The indication and communication module includes an adaptive taillight indication submodule, which is used to control the taillights of the current vehicle to light up a green indicator light when the overtaking risk assessment value is not greater than a first preset assessment value threshold, so as to indicate that the conditions for safe overtaking are met.

8. The highway overtaking safety taillight indicator system as described in claim 7, characterized in that: The adaptive taillight indicator submodule is also used to control the taillights of the current vehicle to illuminate a red warning light when the overtaking risk assessment value is greater than a second preset assessment value threshold.

9. The highway overtaking safety taillight indicator system as described in claim 7, characterized in that: The instruction and communication module also includes a V2V communication submodule, which is used to send electronic risk warnings to vehicles behind via V2V communication technology.

10. The highway overtaking safety taillight indicator system as described in claim 6, characterized in that, The system also includes: The driver feedback module is used to control the steering wheel of the current vehicle to vibrate and control the audio-visual system of the current vehicle to provide auditory prompts when the overtaking risk assessment value is greater than the second preset assessment value threshold.

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