Intelligent double-layer bus second-layer passenger safety monitoring method and system

Abstract

The invention provides an intelligent double-deck bus second-deck passenger safety monitoring method and system. The method comprises the steps of collecting passenger data and vehicle dynamic data; the collected data are processed, and passenger behaviors and vehicle abnormal postures are recognized; outputting a passenger behavior recognition result and a vehicle abnormal posture evaluation result; presetting a passenger behavior safety threshold value and a vehicle abnormal posture threshold value, and dividing risk levels; determining a corresponding risk level according to the output result; and implementing a corresponding emergency response instruction according to the risk level. The system gives out early warning prompts to passengers in various modes, corresponding protection measures are taken to keep the vehicle stable, and the safety of the passengers and the driving safety of the vehicle are effectively protected.

Description

Technical Field

[0001] The present invention relates to the technical field of public transportation vehicle safety, and in particular to a safety monitoring method and system for passengers on the second floor of an intelligent double-decker bus. Background Art

[0002] With the acceleration of urbanization, double-decker buses, as large-capacity public transportation, play an important role in alleviating urban traffic pressure. However, due to their higher position, passengers on the second floor face higher safety risks in emergency situations (such as sudden braking, rollover, etc.). Existing safety systems focus more on the overall stability of the vehicle and the protection of passengers on the first floor, and the special monitoring and emergency response mechanism for passengers on the second floor is still imperfect. Summary of the invention

[0003] Based on the above problems, the present invention aims to provide an intelligent double-decker bus second-floor passenger safety monitoring method and system to solve the problem of imperfect special monitoring and emergency response mechanism for double-decker buses on second-floor passengers.

[0004] The technical solution adopted by the present invention is: a method for monitoring the safety of passengers on the second floor of an intelligent double-decker bus, comprising: S1. Collect passenger data and vehicle driving data; S2, processing the data collected in S1 to determine the passenger behavior and abnormal vehicle posture; S3, outputting passenger behavior recognition results and vehicle abnormal posture assessment results; S4. Preset passenger behavior safety thresholds and vehicle abnormal posture thresholds and divide risk levels; S5. Determine the corresponding preset risk level according to the output passenger behavior recognition result and vehicle driving status assessment result; S6. Implement corresponding emergency response instructions according to the risk level.

[0005] Furthermore, the passenger data in S1 includes sitting, standing, running, pushing, falling, walking and passenger distribution; the vehicle driving data includes current vehicle speed, vehicle speed, throttle position, brake status, sudden acceleration, sudden braking, turning speed and vehicle roll inclination.

[0006] Furthermore, in S1, the passenger data and vehicle dynamic data are collected by high-definition cameras, infrared thermal imaging sensors, pressure distribution sensors, acceleration sensors and on-board terminals installed on the bus; The high-definition cameras are installed at the head and tail of the second floor of the bus to collect video images inside the car; Infrared thermal imaging sensors are installed at the head, middle and tail of the second floor of the bus to monitor the body temperature of passengers and detect abnormal temperatures or heat sources in the car; Pressure distribution sensors are installed under the seats of the second-floor bus to monitor seat occupancy; The acceleration sensor is installed at the head of the second floor of the bus to monitor the vehicle's driving status, including sudden acceleration, sudden braking and vehicle roll inclination; The vehicle terminal is installed in the cab to collect real-time vehicle condition information, including current vehicle speed, vehicle speed, throttle position and brake status.

[0007] Furthermore, the data processing step in S2 includes: S01. Use image recognition technology to identify passenger behavior from video images captured by high-definition cameras; S02. Using image recognition technology to identify the emergency exit status of the vehicle using the video image collected by the high-definition camera; S03. Calculate the abnormal posture of the vehicle through sensor data and vehicle terminal data.

[0008] Furthermore, the passenger behavior safety threshold is divided into the following levels: 1. Normal behavior: If a passenger is detected sitting quietly in a seat or standing and holding the armrest for 1 consecutive minute, it is considered normal behavior and belongs to the low risk level; 2. Running behavior: If more than 3 passengers are detected running in the carriage within 5 consecutive seconds, it is considered abnormal behavior and belongs to the medium risk level; 3. Pushing behavior: If two or more pushing actions are detected within 10 seconds, and each pushing involves more than two passengers, it is considered abnormal behavior and belongs to the medium risk level; 4. Falling behavior: If a passenger falls and fails to stand up within 5 seconds, it is considered a high-risk level; 5. Seat occupancy rate: If the seat occupancy rate of a single floor exceeds 80%, and the seat occupancy rate on one side of the carriage differs by more than 20% from the seat occupancy rate on the other side of the carriage, it is considered that the passenger distribution is uneven and belongs to the medium risk level; 6. Standing passenger density: If there are more than 4 people per square meter in the standing passenger area and this lasts for more than 10 minutes, the standing passenger density is considered too high and is considered a medium risk level. The vehicle abnormal posture threshold is divided into the following levels: 1. When 0<roll angle ≤4°, 0<pitch angle ≤6°, 0<lateral acceleration ≤0.25m / s² and 0<vertical acceleration ≤0.15m / s², it is a low risk level; 2. When 4°<roll angle ≤6°, 6°<pitch angle ≤8°, 0.25 m / s²<lateral acceleration ≤0.35 m / s² and 0.15 m / s²<vertical acceleration ≤0.2 m / s², it is considered medium risk level; 3. When the roll angle is greater than 6°, the pitch angle is greater than 8°, the lateral acceleration is greater than 0.35 m / s², and the vertical acceleration is greater than 0.24 m / s², it is considered a high risk level; 4. Emergency exits are blocked by luggage or passengers, which is a medium risk level; 5. The emergency exit is opened while the vehicle is moving, which is a high-risk level.

[0009] An intelligent double-decker bus second-floor passenger safety monitoring system, characterized in that the system comprises a data acquisition module, an intelligent analysis module and a response module; The data acquisition module acquires passenger data and vehicle dynamic data; The intelligent analysis module processes the data in the data acquisition module, identifies the passenger behavior and vehicle status, and classifies the passenger behavior and vehicle status into risk levels; The response module automatically executes preset emergency measures according to the risk level of passenger behavior and vehicle status.

[0010] Furthermore, the emergency response module includes automatic voice prompts, emergency lighting and instructions, automatic seat belt tightening devices and emergency exit control devices.

[0011] Furthermore, the risk level is divided into low risk level, medium risk level and high risk level. Furthermore, when the emergency response strategy is at a low risk level, the system reminds passengers to pay attention to safety through voice prompts or display screen information; when the risk level is medium, the system activates the automatic seat belt tightening device, and enhances the passengers' safety awareness through voice and light prompts; when the risk level is high, the system immediately triggers emergency braking, turns on emergency lighting and evacuation indication systems, and issues clear evacuation instructions through the in-vehicle broadcast and display screen.

[0012] Furthermore, the system also includes an information reporting and remote intervention module, which uploads emergency data to a cloud server and a remote monitoring center. The remote monitoring center displays the vehicle status and passenger safety in real time through the received data; the remote monitoring center can send remote door locking and emergency braking instructions, and dispatch rescue forces to the scene for rescue and disposal.

[0013] Beneficial effects of the present invention: The present invention collects passenger behavior data and vehicle driving data, identifies passenger behavior and vehicle status, divides passenger behavior and vehicle status into risk levels, and automatically executes preset emergency measures according to the risk level. It issues early warning prompts to passengers in various ways, reminds passengers to pay attention to safety and take corresponding protective measures, adjusts the vehicle speed to keep the vehicle stable, and activates the seat belt pre-tensioning device to ensure that the passengers are fixed, effectively protecting the safety of passengers and vehicle driving safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 Installation layout of high-definition cameras and infrared thermal imaging sensors.

[0016] There are 1 high-definition camera and 2 infrared thermal imaging sensors. DETAILED DESCRIPTION

[0017] An intelligent double-decker bus second-floor passenger safety monitoring method, comprising: S1. Collect passenger data and vehicle driving data; S2, processing the data collected in S1 to determine the passenger behavior and abnormal vehicle posture; S3, outputting passenger behavior recognition results and vehicle abnormal posture assessment results; S4. Preset passenger behavior safety thresholds and vehicle abnormal posture thresholds and divide risk levels; S5. Determine the corresponding preset risk level according to the output passenger behavior recognition result and vehicle driving status assessment result; S6. Implement corresponding emergency response instructions according to the risk level.

[0018] The passenger data in S1 include sitting, standing, running, pushing, falling, walking and passenger distribution; the vehicle driving data includes current vehicle speed, vehicle speed, throttle position, brake status, sudden acceleration, sudden braking, turning speed and vehicle roll inclination.

[0019] In the S1, the passenger data and vehicle dynamic data are collected by high-definition cameras, infrared thermal imaging sensors, pressure distribution sensors, acceleration sensors and vehicle terminals installed on the bus; The high-definition cameras are installed at the head and tail of the second floor of the bus to collect video images inside the car; Infrared thermal imaging sensors are installed at the head and tail of the second floor of the bus to monitor the body temperature of passengers and detect abnormal temperatures or heat sources in the car; Pressure distribution sensors are installed under the seats of the second-floor bus to monitor seat occupancy; The acceleration sensor is installed at the head of the second floor of the bus to monitor the vehicle's driving status, including sudden acceleration, sudden braking and vehicle roll inclination; The vehicle terminal is installed in the cab to collect real-time vehicle condition information, including current vehicle speed, vehicle speed, throttle position and brake status.

[0020] The data processing step in S2 includes: S01. Use image recognition technology to identify passenger behavior from video images captured by high-definition cameras; S02. Using image recognition technology to identify the emergency exit status of the vehicle using the video image collected by the high-definition camera; S03. Calculate the abnormal posture of the vehicle through sensor data and vehicle terminal data.

[0021] The passenger behavior safety thresholds are divided into the following levels: 1. Normal behavior: If a passenger is detected sitting quietly in a seat or standing and holding the armrest for 1 consecutive minute, it is considered normal behavior and belongs to the low risk level; 2. Running behavior: If more than 3 passengers are detected running in the carriage within 5 consecutive seconds, it is considered abnormal behavior and belongs to the medium risk level; 3. Pushing behavior: If two or more pushing actions are detected within 10 seconds, and each pushing involves more than two passengers, it is considered abnormal behavior and belongs to the medium risk level; 4. Falling behavior: If a passenger falls and fails to stand up within 5 seconds, it is considered a high-risk level; 5. Seat occupancy rate: If the seat occupancy rate of a single floor exceeds 80%, and the seat occupancy rate on one side of the carriage differs by more than 20% from the seat occupancy rate on the other side of the carriage, it is considered that the passenger distribution is uneven and belongs to the medium risk level; 6. Standing passenger density: If there are more than 4 people per square meter in the standing passenger area and this lasts for more than 10 minutes, the standing passenger density is considered too high and is considered a medium risk level. The vehicle abnormal posture threshold is divided into the following levels: 1. When 0<roll angle ≤4°, 0<pitch angle ≤6°, 0<lateral acceleration ≤0.25m / s² and 0<vertical acceleration ≤0.15m / s², it is a low risk level; 2. When 4°<roll angle ≤6°, 6°<pitch angle ≤8°, 0.25 m / s²<lateral acceleration ≤0.35 m / s² and 0.15 m / s²<vertical acceleration ≤0.2 m / s², it is considered medium risk level; 3. When the roll angle is greater than 6°, the pitch angle is greater than 8°, the lateral acceleration is greater than 0.35 m / s², and the vertical acceleration is greater than 0.24 m / s², it is considered a high risk level; 4. Emergency exits are blocked by luggage or passengers, which is a medium risk level; 5. The emergency exit is opened while the vehicle is moving, which is a high-risk level.

[0022] An intelligent double-decker bus second-floor passenger safety monitoring system, characterized in that the system comprises a data acquisition module, an intelligent analysis module and a response module; The data acquisition module acquires passenger data and vehicle dynamic data; The intelligent analysis module processes the data in the data acquisition module, identifies the passenger behavior and vehicle status, and classifies the passenger behavior and vehicle status into risk levels; The response module automatically executes preset emergency measures according to the risk level of passenger behavior and vehicle status.

[0023] The emergency response module includes automatic voice prompts, emergency lighting and instructions, automatic seat belt tightening devices and emergency exit control devices.

[0024] The risk levels are divided into low risk level, medium risk level and high risk level. When the emergency response strategy is at a low risk level, the system reminds passengers to pay attention to safety through voice prompts or display information; when the risk level is medium, the system activates the automatic seat belt tightening device, and enhances passengers' safety awareness through voice and light prompts; when the risk level is high, the system immediately triggers emergency braking, turns on emergency lighting and evacuation indication systems, and issues clear evacuation instructions through the in-vehicle broadcast and display.

[0025] The system also includes an information reporting and remote intervention module, which uploads emergency data to a cloud server and a remote monitoring center. The remote monitoring center displays the vehicle status and passenger safety in real time through the received data; the remote monitoring center can send remote door locks, initiate emergency braking commands, and dispatch rescue forces to the scene for rescue and disposal.

[0026] The system control process is as follows: 1. System startup and initialization Power supply check: When the system starts, the stability of the power supply is checked first to ensure that all devices can be powered normally.

[0027] Hardware self-check: Afterwards, the system performs a self-check on each hardware device, including the camera, sensor, communication module, display, speaker, etc., to ensure that they are in normal working condition without any fault or damage.

[0028] Software loading: After the hardware self-test passes, the system loads the necessary software programs and algorithms, including security monitoring algorithms, emergency response plans, etc., to prepare for subsequent monitoring and emergency response.

[0029] Parameter configuration: According to actual needs, the system configures corresponding safety thresholds, warning levels, emergency response priorities and other parameters, so that in subsequent data analysis and risk assessment, the risk level can be accurately judged and corresponding emergency measures can be taken.

[0030] 2. Passenger Safety Monitoring and Data Collection Video surveillance: The system captures real-time video images inside the carriage through a high-definition camera installed in the second-floor carriage.

[0031] Using image recognition technology, video images are analyzed to identify passengers' behaviors, such as standing, falling, crowding, etc., as well as to monitor whether the emergency exit area is illegally opened or blocked.

[0032] Sensor monitoring: The system monitors seat occupancy through pressure sensors and identifies empty, full or overloaded states so that passenger distribution can be adjusted in a timely manner.

[0033] Infrared sensors can be used to monitor passengers' body temperature and detect abnormal temperatures or heat sources within the vehicle cabin.

[0034] The acceleration sensor monitors the vehicle's driving status, including sudden acceleration, sudden braking, and roll, so as to issue timely warnings when abnormal conditions occur in the vehicle.

[0035] Data integration: The system integrates video surveillance data and sensor data to form a comprehensive second-level passenger safety status report, providing a basis for subsequent data analysis and risk assessment.

[0036] 3. Data Analysis and Risk Assessment Real-time analysis: The system processes and analyzes the collected data in real time.

[0037] Behavior recognition: Through image recognition technology, the system can identify abnormal behaviors of passengers, such as falling, crowding, etc., and monitor abnormal conditions in emergency exit areas.

[0038] State assessment: The system combines sensor data to assess the vehicle's driving state and determine whether there are abnormal conditions such as sudden acceleration, sudden braking, and roll.

[0039] Risk assessment: According to the preset risk level assessment rules, the current risk level is judged and potential safety hazards are predicted. If the risk level reaches the preset threshold, the system will trigger the emergency response mechanism.

[0040] Risk level assessment rules: 1. Abnormality of passenger behavior: Analyze passengers’ behaviors, such as running, pushing, falling, etc., through video surveillance and image recognition technology, and divide them into different risk levels according to the degree of abnormality of the behavior.

[0041] 2. Passenger distribution unevenness: Use pressure sensors to monitor the distribution of passengers in seats and carriages to determine whether there is local overload or extremely uneven passenger distribution, and divide the risk level according to the unevenness.

[0042] 3. Abnormality of vehicle posture: The vehicle's roll, pitch and other posture changes are monitored through posture monitoring sensors (such as accelerometers and gyroscopes). The severity and duration of the posture changes are used to assess whether the vehicle is in an abnormal state and to classify the vehicle into corresponding risk levels.

[0043] 4. Emergency exit status: Monitor the status of emergency exits through video surveillance and sensors, including whether they are blocked or illegally opened, and assess the risk level based on the availability and safety of the emergency exits.

[0044] Passenger behavior abnormality threshold (1) Running behavior: If more than three passengers are detected running in the car within five consecutive seconds, it is considered abnormal behavior and is classified as a medium-risk level.

[0045] (2) Pushing behavior: If two or more pushing actions are detected within 10 seconds, and each pushing action involves more than two passengers, it is considered abnormal behavior and is classified as medium risk. If the pushing behavior continues to intensify, such as involving more people or more intense actions, it is classified as high risk.

[0046] (3) Falling behavior: If a passenger is detected falling and unable to stand up within 5 seconds, it is considered a high-risk level.

[0047] Passenger distribution unevenness threshold (1) Seat occupancy rate: If the seat occupancy rate of a single floor exceeds 80%, and the seat occupancy rate of a certain area (such as one side of the carriage) differs from that of other areas by more than 20%, it is considered that the passenger distribution is uneven and the risk level is medium.

[0048] (2) Standing passenger density: If the number of standing passengers exceeds 4 per square meter and lasts for more than 10 minutes, it is considered that the standing passenger density is too high and is classified as medium risk.

[0049] Vehicle posture abnormality threshold According to the roll angle value, pitch angle value, lateral acceleration value, and vertical acceleration value collected by the acceleration sensor, a table of corresponding vehicle body condition risk levels is summarized, as shown in Table 1.

[0050] Table 1 Vehicle body condition risk level Emergency exit status threshold Blockage detection: If the emergency exit is detected to be blocked or cannot be used normally (such as blocked by luggage, passengers, etc.), it is a high risk level.

[0051] Illegal opening: If the emergency exit is opened in a non-emergency situation, it is classified as a medium risk level.

[0052] Emergency Response Strategy: 1. At a low risk level, the system only reminds passengers to pay attention to safety through voice prompts or display information.

[0053] 2. At the medium risk level, the system activates the automatic seat belt tightening device and enhances the passengers' safety awareness through voice and light prompts.

[0054] 3. When the risk level is high, the system immediately triggers the emergency brake, turns on the emergency lighting and evacuation indication system, and issues clear evacuation instructions through the in-vehicle broadcast and display screen.

[0055] IV. Emergency Response and Early Warning Warning Tips: The system sends warning alerts to passengers through in-car broadcasts, display screens, mobile phone apps, etc., reminding them to pay attention to safety and take appropriate protective measures.

[0056] The content of the early warning prompts includes abnormal vehicle driving status, abnormal passenger behavior, the location of emergency exits and evacuation instructions, etc.

[0057] Emergency measures: Based on the risk assessment results, the system automatically adjusts the vehicle speed to maintain vehicle stability and activates the seat belt pretensioner to ensure that passengers are secured. At the same time, the system activates the emergency lighting and evacuation indicator system to provide guidance for passenger evacuation. If necessary, the system will also send an emergency signal to the driver's console and remote monitoring center to request support.

[0058] V. Information reporting and remote intervention Data upload: The system uploads emergency data to the cloud server and remote monitoring center for real-time monitoring and analysis.

[0059] Remote monitoring: The remote monitoring center uses the received data to display the vehicle status and passenger safety in real time, and predict and intervene in potential risks.

[0060] Remote intervention: The remote monitoring center can send instructions to the vehicle, such as remotely locking the doors, activating emergency brakes, etc. to control the development of the situation.

[0061] Rescue dispatch: The monitoring center can dispatch rescue forces to the scene for rescue and disposal.

[0062] 6. Post-event processing and records Data recording: The system saves data of the entire emergency response process including video recordings, sensor data, emergency response instructions, etc. for subsequent analysis and evaluation.

[0063] Data Analysis: Conduct in-depth analysis of recorded data to evaluate the effectiveness of emergency response and optimize system parameters and plans to improve system reliability and efficiency.

[0064] Report generation: Generate emergency response reports based on the results of data analysis for reference by management and relevant departments to improve and optimize system performance.

[0065] System recovery: After confirming that the emergency situation has been resolved, the system returns to normal monitoring status and continues to conduct safety monitoring of the second-floor passengers and prepare for emergency response.

[0066] The above-mentioned embodiment only expresses one implementation mode of the present invention, and its description is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that for ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be based on the attached claims.

Claims

1. A method for monitoring the safety of passengers on the second floor of an intelligent double-decker bus, characterized in that: include S1. Collect passenger data and vehicle driving data; S2, processing the data collected in S1 to determine the passenger behavior and abnormal vehicle posture; S3, outputting passenger behavior recognition results and vehicle abnormal posture assessment results; S4. Preset passenger behavior safety thresholds and vehicle abnormal posture thresholds and divide risk levels; S5. Determine the corresponding preset risk level according to the output passenger behavior recognition result and vehicle driving status assessment result; S6. Implement corresponding emergency response instructions according to the risk level.

2. According to claim 1, a method for monitoring the safety of passengers on the second floor of an intelligent double-decker bus is characterized in that: The passenger data in S1 include sitting, standing, running, pushing, falling, walking and passenger distribution; the vehicle driving data includes current vehicle speed, vehicle speed, throttle position, brake status, sudden acceleration, sudden braking, turning speed and vehicle roll inclination.

3. The method for monitoring the safety of passengers on the second floor of an intelligent double-decker bus according to claim 1 is characterized in that: In the S1, the passenger data and vehicle dynamic data are collected by high-definition cameras, infrared thermal imaging sensors, pressure distribution sensors, acceleration sensors and vehicle terminals installed on the bus; The high-definition cameras are installed at the head and tail of the second floor of the bus to collect video images inside the car; Infrared thermal imaging sensors are installed at the head, middle and tail of the second floor of the bus to monitor the body temperature of passengers and detect abnormal temperatures or heat sources in the car; Pressure distribution sensors are installed under the seats of the second-floor buses to monitor seat occupancy; The acceleration sensor is installed at the head of the second floor of the bus to monitor the vehicle's driving status, including sudden acceleration, sudden braking and vehicle roll inclination; The vehicle terminal is installed in the cab to collect real-time vehicle condition information, including current vehicle speed, vehicle speed, throttle position and brake status.

4. The method for monitoring the safety of passengers on the second floor of an intelligent double-decker bus according to claim 1, characterized in that: The data processing step in S2 includes: S01. Use image recognition technology to identify passenger behavior from video images captured by high-definition cameras; S02. Using image recognition technology to identify the emergency exit status of the vehicle using the video image collected by the high-definition camera; S03. Calculate the abnormal posture of the vehicle through sensor data and vehicle terminal data.

5. The method for monitoring the safety of passengers on the second floor of an intelligent double-decker bus according to claim 1 is characterized in that: The passenger behavior safety thresholds are divided into the following levels:

1. Normal behavior: If a passenger is detected sitting quietly in a seat or standing and holding the armrest for 1 consecutive minute, it is considered normal behavior and belongs to the low risk level; 2. Running behavior: If more than 3 passengers are detected running in the carriage within 5 consecutive seconds, it is considered abnormal behavior and belongs to the medium risk level; 3. Pushing behavior: If two or more pushing actions are detected within 10 seconds, and each pushing involves more than two passengers, it is considered abnormal behavior and belongs to the medium risk level; 4. Falling behavior: If a passenger falls and fails to stand up within 5 seconds, it is considered a high-risk level; 5. Seat occupancy rate: If the seat occupancy rate of a single floor exceeds 80%, and the seat occupancy rate on one side of the carriage differs by more than 20% from the seat occupancy rate on the other side of the carriage, it is considered that the passenger distribution is uneven and belongs to the medium risk level; 6. Standing passenger density: If there are more than 4 people per square meter in the standing passenger area and this lasts for more than 10 minutes, the standing passenger density is considered too high and is classified as medium risk. The vehicle abnormal posture threshold is divided into the following levels:

1. When 0<roll angle ≤4°, 0<pitch angle ≤6°, 0<lateral acceleration ≤0.25m / s² and 0<vertical acceleration ≤0.15m / s², it is a low risk level; 2. When 4°<roll angle ≤6°, 6°<pitch angle ≤8°, 0.25 m / s²<lateral acceleration ≤0.35 m / s² and 0.15 m / s²<vertical acceleration ≤0.2 m / s², it is considered medium risk level; 3. When the roll angle is greater than 6°, the pitch angle is greater than 8°, the lateral acceleration is greater than 0.35 m / s², and the vertical acceleration is greater than 0.24 m / s², it is considered a high risk level; 4. Emergency exits are blocked by luggage or passengers, which is a medium risk level; 5. The emergency exit is opened while the vehicle is moving, which is a high-risk level.

6. An intelligent double-decker bus second-floor passenger safety monitoring system, characterized in that: The system includes a data acquisition module, an intelligent analysis module and a response module; The data acquisition module collects passenger data and vehicle dynamic data; The intelligent analysis module processes the data in the data acquisition module, identifies the passenger behavior and vehicle status, and classifies the passenger behavior and vehicle status into risk levels; The response module automatically executes preset emergency measures according to the risk level of passenger behavior and vehicle status.

7. The intelligent double-decker bus second-floor passenger safety monitoring system according to claim 6 is characterized in that: The emergency response module includes automatic voice prompts, emergency lighting and instructions, automatic seat belt tightening devices and emergency exit control devices.

8. The intelligent double-decker bus second-floor passenger safety monitoring system according to claim 6 is characterized in that: The risk levels are divided into low risk level, medium risk level and high risk level.

9. The intelligent double-decker bus second-floor passenger safety monitoring system according to claim 6 is characterized in that: When the emergency response strategy is at a low risk level, the system reminds passengers to pay attention to safety through voice prompts or display information; when the risk level is medium, the system activates the automatic seat belt tightening device and enhances the safety awareness of passengers through voice and light prompts; At high risk levels, the system immediately triggers emergency braking, turns on emergency lighting and evacuation indication systems, and issues clear evacuation instructions through the in-vehicle broadcast and display screen.

10. The intelligent double-decker bus second-floor passenger safety monitoring system according to claim 6, characterized in that: The system also includes an information reporting and remote intervention module, which uploads emergency data to a cloud server and a remote monitoring center. The remote monitoring center displays the vehicle status and passenger safety in real time through the received data; the remote monitoring center can send remote door locks, initiate emergency braking commands, and dispatch rescue forces to the scene for rescue and disposal.

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