Driver danger early warning and automatic driving assistance system based on multi-environment perception

Abstract

The invention belongs to the technical field of intelligent traffic, and discloses a driver danger early warning and automatic driving assistance system based on multi-environment perception, which comprises an environment perception unit used for acquiring environment illumination intensity, a vehicle automation state and a driver behavior; and the strategy generation unit is used for comparing the data acquired by the environment sensing unit with a preset threshold value, and generating an early warning strategy based on a comparison result. According to the technical scheme, the obstacle avoidance capability of a driver in day and night switching and automatic / manual modes can be improved.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent transportation technology, and in particular relates to a driver danger warning and automated driving assistance system based on multi-environment perception. Background Art

[0002] Drivers are required to continuously monitor the road environment during automated driving (e.g., SAE Level 2). However, at night or in low-light conditions, their hazard perception ability is significantly reduced, leading to delayed takeover or obstacle avoidance errors, such as increased lateral control deviation and prolonged braking reaction time during nighttime driving. Furthermore, existing driver monitoring systems are mostly based on a single condition, targeting only automated modes or only considering daytime scenarios. They lack dynamic adaptability to complex environments such as day-night switching and switching between automated and manual driving modes, and are unable to effectively optimize driving safety. Automated driving also weakens the driver's perception-action coupling, such as reduced lane keeping ability after takeover. At the same time, nighttime driving further exacerbates hazard response lags. Therefore, there is an urgent need for a comprehensive warning system that can combine lighting conditions, automated modes, and driver behavior in real time to improve driving safety in complex scenarios. Summary of the Invention

[0003] The purpose of the present invention is to provide a driver hazard warning and automated driving assistance system based on multi-environment perception to solve the problems existing in the above-mentioned prior art.

[0004] To achieve the above objectives, the present invention provides a driver hazard warning and automated driving assistance system based on multi-environment perception, comprising:

[0005] Environmental perception unit, used to obtain ambient light intensity, vehicle automation status and driver behavior;

[0006] The strategy generating unit is used to compare the data acquired by the environment sensing unit with a preset threshold value and generate an early warning strategy based on the comparison result.

[0007] Optionally, the environment perception unit specifically includes:

[0008] Light perception module, used to detect ambient light intensity in real time and distinguish between daytime and nighttime modes;

[0009] Automation status detection module, used to obtain the vehicle's current automation driving level;

[0010] The driver behavior monitoring module is used to collect the driver's gaze direction, hand movements and takeover response time.

[0011] Optionally, the policy generation unit specifically includes:

[0012] Mode-differentiated threshold management module, used to manage preset thresholds and monitoring frequencies according to different modes;

[0013] Takeover assistance module, used to automatically initiate emergency obstacle avoidance control when a delay in driver reaction is detected in automated driving mode.

[0014] Optionally, the mode differentiation threshold management module specifically includes:

[0015] Threshold reduction module, used to lower the trigger threshold of danger detection in night mode and trigger early warning;

[0016] The monitoring frequency management module is used to increase the monitoring frequency of driver distraction in automated driving mode.

[0017] Optionally, the driver hazard warning and automated driving assistance system further includes a human-computer interaction unit, which is used to optimize the prompt interface.

[0018] Optionally, the human-computer interaction unit specifically includes:

[0019] Night mode optimization module, used to use high-contrast warning icons and sound prompts in night mode to reduce visual interference;

[0020] The automation mode optimization module is used to enhance the driver's awareness of taking over through dual feedback of steering wheel vibration and voice prompts in automated driving mode.

[0021] The technical effects of the present invention are:

[0022] The present invention provides a dynamically adjusted driver hazard warning and assistance system that optimizes hazard warning strategies and enhances the driver's obstacle avoidance capabilities during day / night switching and in automated / manual modes through real-time perception of ambient lighting conditions, vehicle automation status, and driver behavior characteristics. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0024] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of this application. The exemplary embodiments and descriptions of this application are intended to explain this application and do not constitute an improper limitation on this application. In the accompanying drawings:

[0025] Figure 1 Schematic diagram of the system structure in an embodiment of the present invention;

[0026] Figure 2 This is a comparison diagram of the warning interface in day and night modes in an embodiment of the present invention;

[0027] Figure 3 This is a flowchart of the takeover prompt in the automated driving mode in an embodiment of the present invention. DETAILED DESCRIPTION

[0028] Various exemplary embodiments of the present invention will now be described in detail. This detailed description should not be considered as limiting the present invention, but rather as a more detailed description of certain aspects, features, and embodiments of the present invention.

[0029] It should be understood that the terms described herein are intended only to describe particular embodiments and are not intended to limit the present invention. In addition, for numerical ranges herein, it should be understood that each intermediate value between the upper and lower limits of the range is also specifically disclosed. Each smaller range between any intermediate value within a stated value or stated range and any other stated value or intermediate value within the stated range is also encompassed by the present invention. The upper and lower limits of these smaller ranges may be independently included or excluded within the scope.

[0030] It will be apparent to those skilled in the art that various modifications and variations may be made to the specific embodiments of the present invention without departing from the scope or spirit of the invention. Other embodiments will be apparent to those skilled in the art from the present invention. The present description and examples are intended to be illustrative only.

[0031] The words “include,” “including,” “have,” “contain,” etc. used in this article are open-ended terms, meaning including but not limited to.

[0032] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0033] like Figure 1 - Figure 3 As shown, this embodiment provides a driver hazard warning and automated driving assistance system based on multi-environment perception, including: an environmental perception unit, used to obtain ambient light intensity, vehicle automation status and driver behavior; a strategy generation unit, used to compare the data obtained by the environmental perception unit with a preset threshold, and generate a warning strategy based on the comparison result.

[0034] This embodiment provides a dynamically adjusted driver hazard warning and assistance system that optimizes hazard warning strategies by real-time sensing of ambient lighting conditions, vehicle automation status, and driver behavior characteristics, thereby enhancing the driver's obstacle avoidance capabilities during day / night switching and in automated / manual modes.

[0035] The specific components of this embodiment include:

[0036] Multimodal environmental perception module, including light sensor, automatic status detection module and driver behavior monitoring module;

[0037] Light sensor: Detects ambient light intensity in real time and distinguishes between day and night modes.

[0038] Automation status detection module: obtains the vehicle's current automation level (such as SAE Level 2 or manual driving).

[0039] Driver behavior monitoring module: collects the driver's gaze direction, hand movements and takeover response time through the vehicle's on-board camera or steering wheel sensor.

[0040] Dynamic early warning strategy generation module:

[0041] Differentiated thresholds for day and night modes: In night mode, the trigger threshold for hazard detection is lowered (e.g., the safe distance to the vehicle ahead is shortened) and early warnings are triggered. In automated driving mode, the frequency of driver distraction monitoring is increased.

[0042] Takeover assistance logic: When the system detects that the driver's response is delayed in automated mode (such as braking time exceeding a preset value), it automatically initiates emergency obstacle avoidance control (such as active braking or lane keeping assist).

[0043] Human-computer interaction optimization module:

[0044] Adaptive interface design: In night mode, high-contrast warning icons (such as flashing red) and audio prompts are used to reduce visual distractions. In automated mode, dual feedback, including steering wheel vibration and audio prompts, reinforces driver awareness.

[0045] In summary, this embodiment achieves the following effects:

[0046] Multi-dimensional fusion of environment, automation and behavior: For the first time, it combines lighting conditions, automation level and real-time driver behavior data to dynamically adjust warning strategies.

[0047] Differentiated thresholds for day and night: Optimizes the danger assessment algorithm for low-visibility environments at night to compensate for driver perception delays.

[0048] Enhanced takeover mechanism in automated mode: Through multimodal interaction design (vibration + voice), the driver's transition time from automated to manual control is shortened.

[0049] Figure 1 This is a system architecture diagram of this embodiment, showing the linkage relationship between environment perception, strategy generation and human-computer interaction modules. Figure 2 Comparison of warning interfaces in day and night modes (regular icons during the day and highlighted warnings at night). Figure 3 This is a flowchart for takeover prompts in automated driving mode, including feedback and emergency control logic after the system detects danger.

[0050] The specific implementation process of this embodiment includes:

[0051] Hardware deployment: A light sensor is installed on the vehicle's front windshield, a data processing unit is integrated into the center console, and a tactile feedback device is embedded in the steering wheel.

[0052] Software Logic: In night mode, if the driver is detected not paying attention to the road during automated driving (via eye tracking), a secondary alert (voice and vibration) is immediately triggered. If the vehicle approaches a potential hazard (such as a pedestrian crossing the road) and the driver does not respond, the system automatically applies the brakes and records the event data for algorithm optimization.

[0053] Test verification: Reproduce day and night scenarios and automated / manual modes in a driving simulator to verify the system's improvement effect on braking reaction time and lane departure rate.

[0054] In summary, this embodiment discloses a driver hazard warning and automated driving assistance system based on multi-environmental perception. By integrating ambient lighting, automation level, and driver behavior data, it dynamically optimizes warning strategies. In night mode, it lowers the hazard determination threshold and enhances visual cues. In automated mode, it shortens takeover delays through multimodal interaction. This system can significantly improve driving safety in complex scenarios and is suitable for the optimized design of intelligent vehicles and advanced driver assistance systems (ADAS).

[0055] The above description is merely a preferred embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A driver hazard warning and automated driving assistance system based on multi-environment perception, characterized in that: include: Environmental perception unit, used to obtain ambient light intensity, vehicle automation status and driver behavior; The strategy generating unit is used to compare the data acquired by the environment sensing unit with a preset threshold value and generate an early warning strategy based on the comparison result.

2. The driver hazard warning and automated driving assistance system based on multi-environment perception according to claim 1, characterized in that: The environment perception unit specifically includes: Light perception module, used to detect ambient light intensity in real time and distinguish between daytime and nighttime modes; Automation status detection module, used to obtain the vehicle's current automation driving level; The driver behavior monitoring module is used to collect the driver's gaze direction, hand movements and takeover response time.

3. The driver hazard warning and automated driving assistance system based on multi-environment perception according to claim 1, characterized in that: The strategy generation unit specifically includes: Mode-differentiated threshold management module, used to manage preset thresholds and monitoring frequencies according to different modes; Takeover assistance module, used to automatically initiate emergency obstacle avoidance control when a delay in driver reaction is detected in automated driving mode.

4. The driver hazard warning and automated driving assistance system based on multi-environment perception according to claim 3 is characterized in that: The mode differentiation threshold management module specifically includes: Threshold reduction module, used to lower the trigger threshold of danger detection in night mode and trigger early warning; The monitoring frequency management module is used to increase the monitoring frequency of driver distraction in automated driving mode.

5. The driver hazard warning and automated driving assistance system based on multi-environment perception according to claim 1, characterized in that: The driver hazard warning and automated driving assistance system also includes a human-computer interaction unit, which is used to optimize the prompt interface.

6. The driver hazard warning and automated driving assistance system based on multi-environment perception according to claim 5 is characterized in that: The human-computer interaction unit specifically includes: Night mode optimization module, used to use high-contrast warning icons and sound prompts in night mode to reduce visual interference; The automation mode optimization module is used to enhance the driver's awareness of taking over through dual feedback of steering wheel vibration and voice prompts in automated driving mode.

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