An industrial control network security early warning system

Abstract

The present invention discloses an industrial control network security early warning system, which relates to the technical field of industrial control, and comprises a pedestrian monitoring module, a danger level analysis module and an early warning control module, and is characterized in that: the pedestrian monitoring module is electrically connected to the danger level analysis module, the danger level analysis module is electrically connected to the early warning control module, the pedestrian monitoring module is used to monitor the real-time position of pedestrians when they are walking, the danger level analysis module is used to analyze and calculate the danger level of the current food delivery vehicle, the early warning control module is used to control the warning distance of the food delivery vehicle's driving speed, the pedestrian monitoring module comprises a high-definition camera unit, a facial recognition module, a timing unit, a pedestrian tracking module and a map coordinate module, the high-definition camera unit is used to photograph pedestrians, and the timing unit is used to provide a basis for analyzing the position behavior of pedestrians at different times. The present invention has the characteristic of real-time prediction.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial control security, and in particular to an industrial control network security early warning system. Background Art

[0002] An unmanned food delivery vehicle is an electric vehicle that can drive autonomously and deliver food automatically. It is usually equipped with sensors and cameras, and can achieve autonomous navigation and food delivery functions through an artificial intelligence industrial control network. This type of vehicle can autonomously drive to the destination and complete the food delivery task based on preset path planning and map information without human intervention.

[0003] When a delivery truck is transporting food, if the speed is set too fast on a road where pedestrians and vehicles are mixed, the speed will be adjusted to cope with the changing behavior of pedestrians on the road. The food will be bumped and vibrated during transportation. If the amplitude of the change is too large, the food will be squeezed or broken during transportation, thus affecting the taste and quality of the food. If the speed is set too slow, the delivery efficiency will be delayed. Therefore, it is necessary to design an industrial control network security early warning system with real-time prediction. Summary of the invention

[0004] The purpose of the present invention is to provide an industrial control network security early warning system to solve the problems raised in the above background technology.

[0005] In order to solve the above-mentioned technical problems, the present invention provides the following technical solutions: an industrial control network security early warning system, comprising a pedestrian monitoring module, a danger level analysis module and an early warning control module, characterized in that: the pedestrian monitoring module is electrically connected to the danger level analysis module, the danger level analysis module is electrically connected to the early warning control module, the pedestrian monitoring module is used to monitor the real-time position of pedestrians when they are walking, the danger level analysis module is used to analyze and calculate the danger level of the current food delivery vehicle, and the early warning control module is used to control the warning distance of the food delivery vehicle's driving speed.

[0006] According to the above technical solution, the pedestrian monitoring module includes a high-definition camera unit, a facial recognition module, a timing unit, a pedestrian tracking module, a distance judgment module and a map coordinate module. The high-definition camera unit is used to photograph pedestrians, the timing unit is used to provide a basis for analyzing the location behavior of pedestrians at different times, the pedestrian tracking module is used to track the information of pedestrians in the picture according to the characteristics of pedestrians, the map coordinate module is used to generate a coordinate system with the takeaway car as the origin and calibrate the coordinate position of the pedestrian, the facial recognition module is used to identify the facial features of pedestrians, and the distance judgment module is used to judge the distance between the pedestrian and the takeaway car;

[0007] The danger level analysis module includes a gravity sensing unit, a perception calculation module, an inertia calculation module and a danger level calculation module. The gravity sensing unit is used to detect the weight of food borne by the carrying surface of the takeaway vehicle. The perception calculation module is electrically connected to the high-definition camera unit. The perception calculation module is used to evaluate the perception of pedestrians to the takeaway vehicle when walking. The danger level calculation module is electrically connected to the gravity sensing unit and the perception calculation module. The danger level calculation module is used to analyze and calculate the danger level of the takeaway vehicle. The inertia calculation module is used to calculate the inertia of the takeaway vehicle according to the real-time weight of the food.

[0008] The early warning control module includes a speed control module, a speed sensing module and an early warning module. The speed control module is electrically connected to the danger level calculation module. The speed control module is used to calculate the maximum driving speed of the delivery vehicle according to the danger level of the food loaded on the delivery vehicle. The speed sensing module is used to monitor the driving speed of the delivery vehicle in real time. The early warning module is electrically connected to the speed control module and the speed sensing module. The early warning module is used to analyze and determine whether the current position relationship between the delivery vehicle and the pedestrian has reached the warning distance and give a warning to the pedestrian.

[0009] According to the above technical solution, the operation method of the system includes:

[0010] S1: The merchant puts the prepared food on the takeaway truck, which delivers it to the reserved location and drives on the road;

[0011] S2: The pedestrian monitoring module starts running, monitors the walking process of pedestrians on the road, weighs the weight of food to obtain its inertia, and transmits the monitoring data to the danger level analysis module in real time, and controls the takeaway car to adjust the speed when it reaches the warning distance while driving;

[0012] S3: Monitor pedestrian facial information. The danger level analysis module evaluates the pedestrian's perception during walking based on the monitoring data and sets the critical distance for rapid movement.

[0013] S4: Evaluate and calculate the safety value Q of the delivery vehicle. When there are multiple pedestrians ahead, the pedestrian with the largest safety value Q is always used for early warning and control. After the early warning control module obtains the danger level of the delivery vehicle, it calculates the optimal driving speed.

[0014] According to the above technical solution, S2 includes the following steps:

[0015] S21: The gravity sensing unit detects the gravity value of the carrying position of the takeaway vehicle in real time, and transmits an electrical signal to the inertia calculation module and the danger degree calculation module of the takeaway vehicle when the gravity value changes;

[0016] S22: The high-definition camera unit and the timing unit are both started after receiving the electrical signal, the high-definition camera unit takes a high-definition picture of pedestrians walking in the direction of the takeaway vehicle, and the timing unit starts timing;

[0017] S23: The pedestrian tracking module automatically focuses on the pedestrian according to the pedestrian's characteristics, and the map coordinate module marks the position of the pedestrian in the road coordinate system;

[0018] S24: Establish a plane rectangular coordinate system with the center point of the takeaway car as the origin (0, 0), a line perpendicular to the edge of the road as the X-axis, and the road extension direction as the Y-axis;

[0019] S25: The high-definition camera unit continuously captures images of pedestrians walking, and the map coordinate module continuously obtains the vertical position of the pedestrian's body, obtains the vertical position coordinates (x, y) of the pedestrian's body, calculates the distance between the pedestrian's position and the food delivery vehicle, and calculates the braking distance of the food delivery vehicle when it brakes suddenly.

[0020] According to the above technical solution, S25 includes the following steps:

[0021] S25-1: When a pedestrian enters the detection range of the takeaway vehicle, the timing unit will detect the pedestrian at interval t 0 Timing is performed to record the real-time position of pedestrians in the coordinate system at different times;

[0022] S25-2: The perception calculation module obtains the real-time position (x 1 ,y 1 )、(x 2 ,y 2 )…(x n ,y n ), where n is the number of measurements, and by the formula Calculate the distance l between the pedestrian position and the takeaway car in each time period 1 , l 2 ...l n , until the vertical coordinate position of the delivery vehicle exceeds the pedestrian, then stop monitoring the pedestrian.

[0023] According to the above technical solution, in S25, the calculation formula for the braking distance of the food delivery vehicle during emergency braking is:

[0024] The weight of food is measured in real time. 1 The weight of the takeaway truck when empty is G 0 , the real-time speed of the takeaway car during measurement is V n The maximum braking force of the takeaway car when braking suddenly is F, then the emergency braking time Emergency braking distance In addition, when braking suddenly, take into account tn Relative speed of pedestrians over time Assuming that the pedestrian continues to walk in the original state when the car brakes suddenly, the relative position of the pedestrian changes The warning distance is S n +S l , when the warning distance is reached, it means that if the pedestrian is currently walking towards the vehicle's route, the vehicle will collide even if it brakes suddenly. At this time, the real-time speed of the takeaway car needs to be reduced to V n .

[0025] According to the above technical solution, S3 includes the following steps: when no pedestrian is detected, the takeaway car uses the maximum speed V m When the distance to any pedestrian reaches the critical distance S for fast movement, k Reduce to medium speed V n When driving, the facial recognition module identifies the facial information of each pedestrian in front, models the pedestrian's head, and calculates the proportion of the face to the entire head contour. The pedestrian's perception of the food delivery vehicle is proportional to the recognized facial ratio. When a larger facial ratio is recognized, it means that the pedestrian has a greater probability of sensing the presence of the food delivery vehicle, and a greater probability of making a walking route that does not conflict with the food delivery vehicle's route, and is more likely to drive at the maximum speed. At this time, the critical distance for rapid movement S k The smaller the setting, the more specific:

[0026] Where S k2 is the maximum critical distance of rapid movement, S k1 is the minimum critical distance of rapid movement, W is the proportion of the currently recognized pedestrian face to the entire head contour, and W 0 is the average proportion of the face to the entire head contour when the pedestrian is facing the delivery car. When there are multiple pedestrians in front, S is calculated for each pedestrian separately. k , and take the maximum value.

[0027] According to the above technical solution, in S4, the speed of the takeaway car is reduced to the medium speed Vz ， Finally, the speed of the takeaway car is adjusted according to the safety value Q of the takeaway car. The calculation formula of the safety value Q of the takeaway car is:

[0028]

[0029] Among them, a i is the weight coefficient of the lateral position of pedestrians and vehicles. All weight coefficients are combined into a sequence {a 1 , a 2 , …a i}, each term of the series increases successively, that is, x i The weight value is higher than xi-1 The larger the calculated Q is, the larger the average lateral distance between pedestrians and delivery vehicles is within a period of time, which shows that the safety value is greater. Conversely, the smaller the safety value is, the optimal driving speed V is g =μQV z , μ is a constant.

[0030] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention calculates the inertia of the delivery vehicle based on the current food weight, calculates the braking distance, and obtains the minimum warning distance from pedestrians, and adjusts the warning distance in real time according to the food weight. Secondly, the pedestrian's face is recognized, and the proportion of facial recognition is calculated, thereby calculating the probability of pedestrians perceiving the delivery vehicle. The greater the perception probability, the faster the vehicle travels, thereby making advance judgments and responses to potential accidents. At the same time, the safety level is calculated based on the lateral distance between the pedestrian and the delivery vehicle. The safer the vehicle, the greater the driving speed. Therefore, the delivery vehicle is guaranteed to travel as fast as possible under the premise of safety, and the problem of fluctuating speed due to temporary decisions can be avoided. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0032] Figure 1 It is a schematic diagram of the overall module structure of the present invention. DETAILED DESCRIPTION

[0033] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0034] See also Figure 1 The present invention provides a technical solution: an industrial control network security early warning system, including a pedestrian monitoring module, a danger level analysis module and an early warning control module, characterized in that: the pedestrian monitoring module is electrically connected to the danger level analysis module, the danger level analysis module is electrically connected to the early warning control module, the pedestrian monitoring module is used to monitor the real-time position of pedestrians when they are walking, the danger level analysis module is used to analyze and calculate the danger level of the current takeaway car, and the early warning control module is used to control the warning distance of the takeaway car's driving speed;

[0035] The pedestrian monitoring module includes a high-definition camera unit, a facial recognition module, a timing unit, a pedestrian tracking module, a distance judgment module and a map coordinate module. The high-definition camera unit is used to shoot pedestrians. The timing unit is used to provide a basis for analyzing the location and behavior of pedestrians at different times. The pedestrian tracking module is used to track the information of pedestrians in the picture according to the characteristics of pedestrians. The map coordinate module is used to generate a coordinate system with the takeaway car as the origin and calibrate the coordinate position of the pedestrian. The facial recognition module is used to identify the facial features of pedestrians. The distance judgment module is used to judge the distance between pedestrians and the takeaway car.

[0036] The danger level analysis module includes a gravity sensing unit, a perception calculation module, an inertia calculation module and a danger level calculation module. The gravity sensing unit is used to detect the weight of food borne by the carrying surface of the takeaway vehicle. The perception calculation module is electrically connected to the high-definition camera unit. The perception calculation module is used to evaluate the perception of pedestrians to the takeaway vehicle when walking. The danger level calculation module is electrically connected to the gravity sensing unit and the perception calculation module. The danger level calculation module is used to analyze and calculate the danger level of the takeaway vehicle. The inertia calculation module is used to calculate the inertia of the takeaway vehicle according to the real-time weight of the food.

[0037] The early warning control module includes a speed control module, a speed sensing module and an early warning module. The speed control module is electrically connected to the danger level calculation module. The speed control module is used to analyze and calculate the maximum driving speed of the takeaway vehicle according to the danger level of the food loaded on the takeaway vehicle. The speed sensing module is used to monitor the driving speed of the takeaway vehicle in real time. The early warning module is electrically connected to the speed control module and the speed sensing module. The early warning module is used to analyze and determine whether the current position relationship between the takeaway vehicle and the pedestrian has reached the warning distance and give an early warning to the pedestrian.

[0038] The system's method of operation includes:

[0039] S1: The merchant puts the prepared food on the takeaway truck, which delivers it to the reserved location and drives on the road;

[0040] S2: The pedestrian monitoring module starts running, monitors the walking process of pedestrians on the road, weighs the weight of food to obtain its inertia, and transmits the monitoring data to the danger level analysis module in real time, and controls the takeaway car to adjust the speed when it reaches the warning distance while driving;

[0041] S3: Monitor pedestrian facial information. The danger level analysis module evaluates the pedestrian's perception during walking based on the monitoring data and sets the critical distance for rapid movement.

[0042] S4: Evaluate and calculate the safety value Q of the food delivery vehicle. When there are multiple pedestrians ahead, the pedestrian with the largest safety value Q is always used for early warning and control. After the early warning control module obtains the danger level of the food delivery vehicle, it calculates the optimal driving speed.

[0043] S2 includes the following steps:

[0044] S21: The gravity sensing unit detects the gravity value of the carrying position of the takeaway vehicle in real time, and transmits an electrical signal to the inertia calculation module and the danger degree calculation module of the takeaway vehicle when the gravity value changes;

[0045] S22: The high-definition camera unit and the timing unit are both started after receiving the electrical signal, the high-definition camera unit takes a high-definition picture of pedestrians walking in the direction of the takeaway vehicle, and the timing unit starts timing;

[0046] S23: The pedestrian tracking module automatically focuses on the pedestrian according to the pedestrian's characteristics, and the map coordinate module marks the position of the pedestrian in the road coordinate system;

[0047] S24: Establish a plane rectangular coordinate system with the center point of the takeaway car as the origin (0, 0), a line perpendicular to the edge of the road as the X-axis, and the road extension direction as the Y-axis;

[0048] S25: The high-definition camera unit continuously captures the images of the pedestrian walking, and the map coordinate module continuously obtains the vertical position of the pedestrian's body, obtains the vertical position coordinates (x, y) of the pedestrian's body, calculates the distance between the pedestrian's position and the food delivery vehicle, and calculates the braking distance of the food delivery vehicle when it brakes suddenly;

[0049] S25 includes the following steps:

[0050] S25-1: When a pedestrian enters the detection range of the takeaway vehicle, the timing unit will detect the pedestrian at interval t 0 Timing is performed to record the real-time position of pedestrians in the coordinate system at different times;

[0051] S25-2: The perception calculation module obtains the real-time position (x 1 ,y 1 )、(x 2 ,y 2 )…(x n ,y n ), where n is the number of measurements, and by the formula Calculate the distance l between the pedestrian position and the takeaway car in each time period 1 , l 2 ...l n , until the vertical coordinate position of the takeaway car exceeds the pedestrian, then stop monitoring the pedestrian;

[0052] In S25, the calculation formula for the braking distance of the food delivery vehicle during emergency braking is:

[0053] The weight of food is measured in real time. 1 The weight of the takeaway truck when empty is G 0 , the real-time speed of the takeaway car during measurement is V n The maximum braking force of the takeaway car when braking suddenly is F, then the emergency braking time Emergency braking distance In addition, when braking suddenly, take into account t n Relative speed of pedestrians over time Assuming that the pedestrian continues to walk in the original state when the car brakes suddenly, the relative position of the pedestrian changes The warning distance is S n +S l , when the warning distance is reached, it means that if the pedestrian is currently walking towards the vehicle's route, the vehicle will collide even if it brakes suddenly. At this time, the real-time speed of the takeaway car needs to be reduced to V n ;

[0054] S3 includes the following steps: when no pedestrian is detected, the delivery vehicle uses the maximum speed V m When the distance to any pedestrian reaches the critical distance S for fast movement, k Reduce to medium speed V z When driving, the facial recognition module identifies the facial information of each pedestrian in front, models the pedestrian's head, and calculates the proportion of the face to the entire head contour. The pedestrian's perception of the food delivery vehicle is proportional to the recognized facial ratio. When a larger facial ratio is recognized, it means that the pedestrian has a greater probability of sensing the presence of the food delivery vehicle, and a greater probability of making a walking route that does not conflict with the food delivery vehicle's route, and is more likely to drive at the maximum speed. At this time, the critical distance for rapid movement S k The smaller the setting, the more specific:

[0055] Where S k2 is the maximum critical distance of rapid movement, S k1 is the minimum critical distance of rapid movement, W is the proportion of the currently recognized pedestrian face to the entire head contour, and W 0 is the average proportion of the face to the entire head contour when the pedestrian is facing the delivery car. When there are multiple pedestrians in front, S is calculated for each pedestrian separately. k , and take the maximum value;

[0056] In S4, the speed of the takeaway car is reduced to a medium speed V z Finally, the speed of the takeaway car is adjusted according to the safety value Q of the takeaway car. The calculation formula of the safety value Q of the takeaway car is:

[0057]

[0058] Among them, a i is the weight coefficient of the lateral position of pedestrians and vehicles. All weight coefficients are combined into a sequence {a 1 , a 2 , …a i}, each term of the series increases successively, that is, x i The weight value is higher than x i-1 The larger the calculated Q is, the larger the average lateral distance between pedestrians and delivery vehicles is within a period of time, which shows that the safety value is greater. Conversely, the smaller the safety value is, the optimal driving speed V is g =μQV z , μ is a constant.

[0059] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0060] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An industrial control network security early warning system, characterized by: It includes a pedestrian monitoring module, a danger level analysis module and an early warning control module, and is characterized in that: the pedestrian monitoring module is electrically connected to the danger level analysis module, the danger level analysis module is electrically connected to the early warning control module, the pedestrian monitoring module is used to monitor the real-time position of pedestrians when they are walking, the danger level analysis module is used to analyze and calculate the danger level of the current takeaway car, and the early warning control module is used to control the warning distance of the takeaway car's driving speed; The pedestrian monitoring module includes a high-definition camera unit, a facial recognition module, a timing unit, a pedestrian tracking module, a distance judgment module and a map coordinate module. The high-definition camera unit is used to photograph pedestrians. The timing unit is used to provide a basis for analyzing the location and behavior of pedestrians at different times. The pedestrian tracking module is used to track the information of pedestrians in the picture according to the characteristics of pedestrians. The map coordinate module is used to generate a coordinate system with the takeaway car as the origin and calibrate the coordinate position of the pedestrian. The facial recognition module is used to identify the facial features of pedestrians. The distance judgment module is used to judge the distance between the pedestrian and the takeaway car. The danger level analysis module includes a gravity sensing unit, a perception calculation module, an inertia calculation module and a danger level calculation module. The gravity sensing unit is used to detect the weight of food borne by the carrying surface of the takeaway vehicle. The perception calculation module is electrically connected to the high-definition camera unit. The perception calculation module is used to evaluate the perception of pedestrians to the takeaway vehicle when walking. The danger level calculation module is electrically connected to the gravity sensing unit and the perception calculation module. The danger level calculation module is used to analyze and calculate the danger level of the takeaway vehicle. The inertia calculation module is used to calculate the inertia of the takeaway vehicle according to the real-time weight of the food. The early warning control module includes a speed control module, a speed sensing module and an early warning module. The speed control module is electrically connected to the danger level calculation module. The speed control module is used to analyze and calculate the maximum driving speed of the takeaway vehicle according to the danger level of the food loaded on the takeaway vehicle. The speed sensing module is used to monitor the driving speed of the takeaway vehicle in real time. The early warning module is electrically connected to the speed control module and the speed sensing module. The early warning module is used to analyze and determine whether the current position relationship between the takeaway vehicle and the pedestrian reaches the warning distance and give an early warning to the pedestrian. The system's method of operation includes: S1: The merchant puts the prepared food on the takeaway truck, which delivers it to the reserved location and drives on the road; S2: The pedestrian monitoring module starts running, monitors the walking process of pedestrians on the road, weighs the weight of food to obtain its inertia, and transmits the monitoring data to the danger level analysis module in real time, and controls the takeaway car to adjust the speed when it reaches the warning distance while driving; S3: Monitor pedestrian facial information. The danger level analysis module evaluates the pedestrian's perception during walking based on the monitoring data and sets the critical distance for rapid movement. S4: Evaluate and calculate the safety value Q of the food delivery vehicle. When there are multiple pedestrians ahead, the pedestrian with the largest safety value Q is always used for early warning and control. After the early warning control module obtains the danger level of the food delivery vehicle, it calculates the optimal driving speed. The S2 comprises the following steps: S21: The gravity sensing unit detects the gravity value of the carrying position of the takeaway vehicle in real time, and transmits an electrical signal to the inertia calculation module and the danger degree calculation module of the takeaway vehicle when the gravity value changes; S22: The high-definition camera unit and the timing unit are both started after receiving the electrical signal, the high-definition camera unit takes a high-definition picture of pedestrians walking in the direction of the takeaway vehicle, and the timing unit starts timing; S23: The pedestrian tracking module automatically focuses on the pedestrian according to the pedestrian's characteristics, and the map coordinate module marks the position of the pedestrian in the road coordinate system; S24: Establish a plane rectangular coordinate system with the center point of the takeaway car as the origin (0,00, the line perpendicular to the edge of the road as the X-axis, and the road extension direction as the Y-axis; S25: The high-definition camera unit continuously captures the images of the pedestrian walking, and the map coordinate module continuously obtains the vertical position of the pedestrian's body, obtains the vertical position coordinates (x, y) of the pedestrian's body, calculates the distance between the pedestrian's position and the food delivery vehicle, and calculates the braking distance of the food delivery vehicle when it brakes suddenly; The S25 comprises the following steps: S25-1: When a pedestrian enters the detection range of the food delivery vehicle, the timing unit counts at interval t0 and records the real-time position of the pedestrian in the coordinate system at different times; S25-2: The perception calculation module obtains the real-time position (x1, y1), (x2, y2)…(x1, y1) of the vertical line of the pedestrian's body relative to the takeaway car transmitted by the high-definition camera unit. n ,y n ), where n is the number of measurements, and the formula Calculate the distances l1, l2,...l between the pedestrian and the delivery vehicle in each time period. n , until the vertical coordinate position of the takeaway car exceeds the pedestrian, then stop monitoring the pedestrian; In S25, the calculation formula for the braking distance of the food delivery vehicle during emergency braking is: The weight of the food weighed in real time is G1, the weight of the takeaway car when empty is G0, and the real-time speed of the takeaway car during measurement is V n The maximum braking force of the takeaway car when braking suddenly is F, then the emergency braking time Emergency braking distance In addition, when braking suddenly, take into account t n Relative speed of pedestrians over time Assuming that the pedestrian continues to walk in the original state when the car brakes suddenly, the relative position of the pedestrian changes The warning distance is S n +S l , when the warning distance is reached, it means that if the pedestrian is currently walking towards the vehicle's route, the vehicle will collide even if it brakes suddenly. At this time, the real-time speed of the takeaway car needs to be reduced to V n ; S3 includes the following steps: when no pedestrian is detected, the takeaway car uses the maximum speed V m When the distance to any pedestrian reaches the critical distance S for fast movement, k Reduce to medium speed V z When driving, the facial recognition module recognizes the facial information of each pedestrian in front, models the pedestrian's head, and calculates the proportion of the face to the entire head contour. The pedestrian's perception of the takeaway car is proportional to the recognized facial ratio. When a larger facial ratio is recognized, the critical distance S is moved quickly. k The smaller the setting, the more specific: Where S k2 is the maximum critical distance of rapid movement, S k1 is the minimum critical distance for rapid movement, W is the proportion of the currently recognized pedestrian’s face to the entire head contour, W0 is the average proportion of the pedestrian’s face to the entire head contour when the pedestrian faces the delivery car head-on, and S is calculated for each pedestrian when there are multiple pedestrians in front. k , and take the maximum value; In S4, the speed of the takeaway vehicle is reduced to a medium speed V z Finally, the speed of the takeaway car is adjusted according to the safety value Q of the takeaway car. The calculation formula of the safety value Q of the takeaway car is: Among them, a i is the weight coefficient of the lateral position of pedestrians and vehicles. All weight coefficients are combined into a sequence {a1, a2, …a i }, each term of the series increases successively, that is, x i The weight value is higher than x i-1 The larger the calculated Q is, the greater the average lateral distance between pedestrians and delivery vehicles in a period of time, which shows that the safety value is greater and the optimal driving speed V g =μQV z , μ is a constant.

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