A collision avoidance assistance system for intelligent connected vehicles merging into the target lane

Abstract

The present invention discloses a collision avoidance assistance system for intelligent connected vehicles merging into a target lane, comprising: a vehicle network information receiving module for acquiring road condition information and status information of vehicles in the target lane; an on-board status sensing module for acquiring the status information of the vehicle; a merging process estimation module for fitting the merging trajectory of the vehicle; a forward safety distance calculation module for calculating the longitudinal safety distance between the vehicle and the preceding vehicle in the target lane; a rearward first safety distance calculation module for calculating the first longitudinal safety distance between the vehicle and the following vehicle in the target lane; a rearward second safety distance calculation module for calculating the second longitudinal safety distance between the vehicle and the following vehicle in the target lane; an anti-collision decision module for determining whether merging is safe and issuing a decision signal; and a danger warning module for issuing a danger warning. The present invention can help drivers safely complete merging operations, thereby improving vehicle driving safety and traffic efficiency.

Description

Technical Field

[0001] The present invention belongs to the field of safe assisted driving and relates to active automobile safety technology. Specifically, it relates to a collision avoidance assistance system for an intelligent connected vehicle merging into a target lane, which is used to help the driver safely complete the merging operation and improve the driving safety and traffic efficiency of the vehicle. Background Art

[0002] The merging process refers to the process by which vehicles on auxiliary roads or non-standard routes merge onto main roads or roads with high traffic volume. This maneuver requires high-level driving skills. However, some drivers lack driving experience and have difficulty judging the appropriate merging timing. This can manifest in two situations: missing the appropriate merging opportunity, resulting in reduced traffic efficiency; and merging at the wrong time, leading to traffic disruption and even collisions. Therefore, using a collision avoidance assistance system to help drivers complete merging maneuvers can effectively improve traffic efficiency, reduce the possibility of collisions, and improve drivers' driving skills to a certain extent.

[0003] With the development of communication technology, intelligent connected vehicles (ICVs) have become a hot topic in the automotive industry. Through IoV technology, ICVs enable comprehensive information exchange between vehicles, between people, between roads, and between vehicles and cloud platforms. This enhances vehicle intelligence and improves driving safety, comfort, efficiency, and convenience.

[0004] Currently, existing collision avoidance assistance systems for merging into a target lane have the following problems: 1) They fail to consider the vehicle's trajectory during the merging process, resulting in a significant discrepancy between the calculated results and the actual situation; 2) They fail to consider the impact of road traffic conditions, weather conditions, driver characteristics, and road surface adhesion on the merging process, making it impossible to guarantee merging safety under some extreme conditions; 3) The warning method is single, making it impossible for the driver to intuitively understand the degree of danger of the merging behavior. Summary of the Invention

[0005] In response to the above-mentioned problems, the present invention provides a collision avoidance assistance system for an intelligent connected vehicle merging into a target lane, which is used to help the driver safely complete the merging operation and improve the driving safety and traffic efficiency of the vehicle.

[0006] In order to achieve the above object, the specific technical solutions of the present invention are as follows:

[0007] A collision avoidance assistance system for intelligent connected vehicles merging into a target lane includes a vehicle network information receiving module, a vehicle status perception module, a merging process estimation module, a forward safety distance calculation module, a rearward first safety distance calculation module, a rearward second safety distance calculation module, an anti-collision decision module, and a danger warning module;

[0008] The vehicle network information receiving module includes a vehicle-to-road communication submodule and a vehicle-to-vehicle communication submodule. The vehicle-to-road communication submodule collects road condition information, which includes: the up and down slope angles α of the current road, the visibility D of the current road, the traffic flow ρ of the current road section, and the limit traffic flow ρ0 of the current road section; the vehicle-to-vehicle communication submodule obtains the status information of the vehicle in front of the target lane and the status information of the vehicle behind the target lane. The status information of the vehicle in front of the target lane includes: the driving speed v of the vehicle in front of the target lane f and the vehicle type of the vehicle in front of the target lane, the state information of the vehicle behind the target lane includes: the speed v of the vehicle behind the target lane r , the vehicle type of the vehicle behind the target lane and the maximum braking deceleration a of the vehicle behind the target lane r ;

[0009] The preceding vehicle in the target lane is the vehicle that is in front of the vehicle and closest to the vehicle in the target lane; the following vehicle in the target lane is the vehicle that is behind the vehicle and closest to the vehicle in the target lane; the vehicle is the vehicle that is about to merge into the target lane;

[0010] The vehicle state perception module includes a vehicle-mounted sensor, a vehicle-mounted camera, a vehicle-mounted human-computer interaction screen and a vehicle-mounted radar. The vehicle-mounted sensor collects the vehicle's driving speed v and the road adhesion coefficient μ of the current road. The vehicle-mounted camera collects the distance L between the vehicle and the center line of the target lane and the angle θ between the vehicle body and the center line of the target lane. The vehicle-mounted human-computer interaction screen collects the driver's conservatism Y. The vehicle-mounted radar collects the longitudinal distance s between the vehicle and the vehicle in front of the target lane. f and the longitudinal distance s between the vehicle and the vehicle behind it in the target lane r , the longitudinal direction is a direction parallel to the lane line;

[0011] The merging process estimation module fits the driving trajectory of the vehicle merging into the target lane based on the relevant information collected by the vehicle state perception module, and calculates the estimated merging time t and the estimated merging longitudinal displacement x;

[0012] The forward safety distance calculation module calculates the longitudinal safety distance between the vehicle and the preceding vehicle in the target lane based on the relevant information obtained by the vehicle network information receiving module, the vehicle state perception module and the merging process estimation module.

[0013] The rear first safety distance calculation module calculates the first longitudinal safety distance between the vehicle and the vehicle behind in the target lane based on the relevant information obtained by the vehicle network information receiving module, the vehicle state perception module and the merging process estimation module.

[0014] The rear second safety distance calculation module calculates the second longitudinal safety distance between the vehicle and the vehicle behind in the target lane based on the relevant information obtained by the vehicle network information receiving module, the vehicle state perception module and the merging process estimation module.

[0015] The anti-collision decision module calculates the safety correction coefficient K based on the relevant information collected by the Internet of Vehicles information receiving module and the vehicle status perception module, and uses the safety correction coefficient K to adjust the longitudinal safety distance between the vehicle and the vehicle in front of the target lane. The first longitudinal safety distance between the vehicle and the vehicle behind in the target lane The second longitudinal safety distance between the vehicle and the vehicle behind it in the target lane Perform corrections, and determine a decision signal to be sent to a danger warning module based on the correction result and the distance information measured by the vehicle-mounted radar, the decision signal including a bidirectional safety signal, a rearward first-level warning signal, a rearward second-level warning signal, a forward warning signal, and a bidirectional warning signal;

[0016] The danger warning module includes a safety indicator light, a buzzer and an on-board human-computer interaction screen. It receives the decision signal sent by the anti-collision decision module, selects the warning method corresponding to the decision signal, and issues a danger warning.

[0017] Furthermore, the merging process estimation module estimates the process of the vehicle merging into the target lane based on the distance L between the vehicle and the centerline of the target lane, the angle θ between the vehicle body and the centerline of the target lane, and the vehicle's speed v, and calculates the estimated merging time t and the estimated merging longitudinal displacement x. The specific calculation method is as follows:

[0018] (1) When θ>θ0, a circular curve is used to fit the vehicle's merging trajectory. The formula for estimating the merging time t is:

[0019]

[0020] Where θ0 is the merging angle threshold, which is set by the manufacturer based on the vehicle's steering performance; t is the estimated merging time, which approximates the time it takes for the vehicle to merge into the target lane; v0 is the merging speed threshold, which is set by the manufacturer based on the vehicle's power performance; L is the distance between the vehicle and the centerline of the target lane, θ is the angle between the vehicle and the centerline of the target lane, and v is the vehicle's speed.

[0021] The calculation formula for estimating the incoming longitudinal displacement x is:

[0022]

[0023] Where x is the estimated merging longitudinal displacement, which is used to approximate the longitudinal displacement of the vehicle when merging into the target lane; L is the distance between the vehicle and the centerline of the target lane; θ is the angle between the vehicle body and the centerline of the target lane;

[0024] (2) When θ≤θ0, a straight line is used to fit the vehicle’s merging trajectory. The formula for estimating the merging time t is:

[0025]

[0026] Where θ0 is the merging angle threshold, which is set by the manufacturer based on the vehicle's steering performance; t is the estimated merging time, which approximates the time it takes for the vehicle to merge into the target lane; v0 is the merging speed threshold, which is set by the manufacturer based on the vehicle's power performance; L is the distance between the vehicle and the centerline of the target lane, θ is the angle between the vehicle and the centerline of the target lane, and v is the vehicle's speed.

[0027] The calculation formula for estimating the incoming longitudinal displacement x is:

[0028]

[0029] Where x is the estimated merging longitudinal displacement, which approximates the longitudinal displacement that the vehicle will travel when merging into the target lane; θ0 is the merging angle threshold, which is set by the manufacturer based on the vehicle's steering performance; and L is the distance between the vehicle and the centerline of the target lane.

[0030] Furthermore, the forward safety distance calculation module calculates the vehicle speed v, the estimated merging time t, the estimated merging longitudinal displacement x, the vehicle speed v of the vehicle in front of the target lane, and the vehicle speed v of the vehicle in front of the target lane. f and the vehicle type of the vehicle in front of the target lane, calculate the longitudinal safety distance between the vehicle and the vehicle in front of the target lane The specific calculation method is as follows:

[0031] When v>v f When the longitudinal safety distance between the vehicle and the vehicle in front of the target lane is The calculation formula is:

[0032]

[0033] When v≤vf, the longitudinal safety distance between the vehicle and the vehicle in front of the target lane The calculation formula is:

[0034]

[0035] in, is the longitudinal safety distance between the vehicle and the preceding vehicle in the target lane, x is the estimated merging longitudinal displacement, t is the estimated merging time, and v f is the speed of the vehicle ahead in the target lane, v is the speed of the vehicle, μ is the road adhesion coefficient of the current road, g is the acceleration of gravity, and α is the uphill and downhill slope angles of the current road; a1 is the maximum braking deceleration of the vehicle on a level and good road surface, and its specific value is set by the manufacturer according to the braking performance of the vehicle; d f is the minimum longitudinal safety distance between the host vehicle and the vehicle ahead in the target lane, which is determined by the vehicle type of the vehicle ahead in the target lane. The vehicle type is classified according to the maximum allowable gross mass of the vehicle, including light vehicles, medium vehicles, and heavy vehicles. The light vehicle is a vehicle with a maximum allowable gross mass less than or equal to 3000kg, the medium vehicle is a vehicle with a maximum allowable gross mass greater than 3000kg and less than or equal to 12000kg, and the heavy vehicle is a vehicle with a maximum allowable gross mass greater than 12000kg. The minimum longitudinal safety distance d between the host vehicle and the vehicle ahead in the target lane is determined by the vehicle type of the vehicle ahead in the target lane. f The value of is:

[0036] When the vehicle type of the preceding vehicle in the target lane is the light vehicle, d f 2m;

[0037] When the vehicle type of the preceding vehicle in the target lane is the medium-sized vehicle, d f 3m;

[0038] When the vehicle type of the preceding vehicle in the target lane is the heavy vehicle, d f is 4m.

[0039] Furthermore, the rear first safety distance calculation module calculates the following parameters based on the up and down slope angles α of the current road, the road adhesion coefficient μ of the current road, the vehicle's driving speed v, the estimated merging time t, the estimated merging longitudinal displacement x, the vehicle's driving speed v in the target lane, and the vehicle's r and the vehicle type of the vehicle behind the target lane, calculate the first longitudinal safety distance between the vehicle and the vehicle behind the target lane The specific calculation method is as follows:

[0040] When v<v r The first longitudinal safety distance between the vehicle and the vehicle behind in the target lane is The calculation formula is:

[0041]

[0042] When v≥v r The first longitudinal safety distance between the vehicle and the vehicle behind in the target lane is The calculation formula is:

[0043]

[0044] in, is the first longitudinal safety distance between the vehicle and the vehicle behind it in the target lane, x is the estimated merging longitudinal displacement, t is the estimated merging time, and v r is the speed of the vehicle behind the target lane, v is the speed of the vehicle, μ is the road adhesion coefficient of the current road, g is the acceleration due to gravity, and α is the up and down slope angle of the current road; a2 is the reference acceleration when the vehicle accelerates, and its specific value is set by the manufacturer according to the vehicle's power performance; d r is the minimum longitudinal safety distance between the host vehicle and the vehicle behind in the target lane, which is determined by the vehicle type behind the target lane. The vehicle type is classified according to the maximum allowable gross vehicle mass, including light vehicles, medium vehicles, and heavy vehicles. The light vehicle is a vehicle with a maximum allowable gross vehicle mass less than or equal to 3000kg, the medium vehicle is a vehicle with a maximum allowable gross vehicle mass greater than 3000kg and less than or equal to 12000kg, and the heavy vehicle is a vehicle with a maximum allowable gross vehicle mass greater than 12000kg. The minimum longitudinal safety distance d between the host vehicle and the vehicle behind in the target lane is determined by the vehicle type behind the target lane. r The value of is:

[0045] When the vehicle type of the vehicle behind the target lane is the light vehicle, d r 2m;

[0046] When the vehicle type behind the target lane is the medium-sized vehicle, d r 3m;

[0047] When the vehicle type of the vehicle behind the target lane is the heavy vehicle, d r is 4m.

[0048] Furthermore, the rear second safety distance calculation module calculates the following safety distance based on the up and down slope angles α of the current road, the road adhesion coefficient μ of the current road, the vehicle's driving speed v, the estimated merging time t, the estimated merging longitudinal displacement x, the vehicle's driving speed v in the target lane, and the vehicle's driving speed v in the target lane. r , the vehicle type of the vehicle behind the target lane and the maximum braking deceleration a of the vehicle behind the target lane r , calculate the second longitudinal safety distance between the vehicle and the vehicle behind in the target lane The specific calculation method is as follows:

[0049] When v<v r The second longitudinal safety distance between the vehicle and the vehicle behind in the target lane is The calculation formula is:

[0050]

[0051] When v≥v rThe second longitudinal safety distance between the vehicle and the vehicle behind in the target lane is The calculation formula is:

[0052]

[0053] in, is the second longitudinal safety distance between the vehicle and the vehicle behind it in the target lane, x is the estimated merging longitudinal displacement, t is the estimated merging time, and v r is the speed of the vehicle behind the target lane, v is the speed of the vehicle, μ is the road adhesion coefficient of the current road, g is the acceleration of gravity, α is the up and down slope angle of the current road, and a r is the maximum braking deceleration of the vehicle behind in the target lane; t r is the braking reaction time of the vehicle behind the target lane, which consists of the driver's reaction time and the braking coordination time, t r Take 1.5s; d r is the minimum longitudinal safety distance between the host vehicle and the vehicle behind in the target lane, which is determined by the vehicle type behind the target lane. The vehicle type is classified according to the maximum allowable gross vehicle mass, including light vehicles, medium vehicles, and heavy vehicles. The light vehicle is a vehicle with a maximum allowable gross vehicle mass less than or equal to 3000kg, the medium vehicle is a vehicle with a maximum allowable gross vehicle mass greater than 3000kg and less than or equal to 12000kg, and the heavy vehicle is a vehicle with a maximum allowable gross vehicle mass greater than 12000kg. The minimum longitudinal safety distance d between the host vehicle and the vehicle behind in the target lane is determined by the vehicle type behind the target lane. r The value of is:

[0054] When the vehicle type of the vehicle behind the target lane is the light vehicle, d r 2m;

[0055] When the vehicle type behind the target lane is the medium-sized vehicle, d r 3m;

[0056] When the vehicle type of the vehicle behind the target lane is the heavy vehicle, d r is 4m.

[0057] Furthermore, the collision avoidance decision module calculates the safety correction factor K based on the traffic flow ρ of the current road section, the limit traffic flow ρ0 of the current road section, the visibility D of the current road, the driver's conservatism Y and the road adhesion coefficient μ of the current road. The calculation formula is:

[0058]

[0059] Among them, K is the safety correction factor, 1≤K<2; ω1, ω2, ω3, ω4 are weight factors, which are trained through neural networks to obtain appropriate values, and ω1+ω2+ω3+ω4=1; ρ is the traffic flow of the current section, ρ0 is the maximum traffic flow of the current section, D is the visibility of the current road, D0 is the dangerous threshold of visibility, and D0 is taken as 500m; Y is the driver's conservatism, 0≤Y≤100, and its specific value is manually set by the driver on the on-board human-computer interaction screen, with a default value of 50; μ is the road adhesion coefficient of the current road, μ0 is the dangerous threshold of the road adhesion coefficient, and μ0 is taken as 0.3;

[0060] The anti-collision decision module sends a decision signal to the danger warning module, and the decision signal is determined by:

[0061] when and and When the hazard warning module is activated, a two-way safety signal is sent to the hazard warning module;

[0062] when and When the hazard warning module is triggered, a first-level warning signal is sent to the hazard warning module;

[0063] when and When the hazard warning module is triggered, a backward secondary warning signal is sent;

[0064] when and When the hazard warning module is detected, a forward warning signal is sent to the hazard warning module;

[0065] when and When a warning signal is sent to the danger warning module;

[0066] Among them, s f is the longitudinal distance between the vehicle and the preceding vehicle in the target lane, s r is the longitudinal distance between the vehicle and the vehicle behind it in the target lane, is the longitudinal safety distance between the vehicle and the preceding vehicle in the target lane, is the first longitudinal safety distance between the vehicle and the vehicle behind it in the target lane, is the second longitudinal safety distance between the vehicle and the vehicle behind in the target lane, and K is the safety correction factor.

[0067] Furthermore, the danger warning module receives the decision signal sent by the collision avoidance decision module and issues a warning according to the decision signal. The specific method of the warning is:

[0068] When the received decision signal is a two-way safety signal, the incoming safety indicator light displays green, the buzzer does not sound an alarm, and the on-board human-computer interaction screen does not display an arrow pattern;

[0069] When the received decision signal is a rear-level first-level warning signal, the incoming safety indicator light turns yellow, the buzzer sounds an alarm at a frequency of f0, and the on-board human-computer interaction screen displays a flashing arrow pattern, the arrow pointing to the rear, the arrow flashing frequency is f0, and the arrow transparency is p0;

[0070] When the received decision signal is a rear-level secondary warning signal, the incoming safety indicator light turns red, the buzzer sounds an alarm at a frequency of 2f0, and the on-board human-computer interaction screen displays a flashing arrow pattern, the arrow pointing to the rear, the arrow flashing frequency is 2f0, and the transparency of the arrow is 0.5p0;

[0071] When the received decision signal is a forward warning signal, the incoming safety indicator light turns red, the buzzer sounds an alarm at a frequency of 2f0, and the on-board human-computer interaction screen displays a flashing arrow pattern, the arrow points forward, the arrow flashes at a frequency of 2f0, and the transparency of the arrow is 0.5p0;

[0072] When the received decision signal is a bidirectional warning signal, the incoming safety indicator light turns red, the buzzer sounds an alarm at a frequency of 3f0, and the on-board human-computer interaction screen displays a flashing double-arrow pattern, with the double arrows pointing forward and backward, the flashing frequency of the double arrows is 3f0, and the transparency of the double arrows is 0.3p0;

[0073] Among them, f0 is the alarm standard frequency, p0 is the pattern standard transparency;

[0074] The control method of the alarm standard frequency f0 adopts fuzzy control, and the specific method is as follows:

[0075] The input of the fuzzy control method is the forward distance relative deviation e1 and the backward distance relative deviation e2, and the output is the alarm standard frequency f0, where the calculation formulas of e1 and e2 are:

[0076]

[0077]

[0078] Among them, e1 is the relative deviation of the forward distance, e2 is the relative deviation of the backward distance, K is the safety correction factor, is the longitudinal safety distance between the vehicle and the preceding vehicle in the target lane, s f is the longitudinal distance between the vehicle and the preceding vehicle in the target lane, is the first longitudinal safety distance between the vehicle and the vehicle behind in the target lane, s r is the longitudinal distance between the vehicle and the vehicle behind it in the target lane;

[0079] The fuzzy subset of the input of the fuzzy control method is defined as e1 = {NB, NM, NS, ZE, PS, PM, PB}, that is, {negative large, negative medium, negative small, zero, positive small, positive medium, positive large}, e2 = {NB, NM, NS, ZE, PS, PM, PB}, that is, {negative large, negative medium, negative small, zero, positive small, positive medium, positive large}, and the fuzzy subset of the output is defined as f0 = {ZE, PO, PS, PM, PB}, that is, {zero, positive, positive small, positive medium, positive large}.

[0080] The above fuzzy control rules are:

[0081]

[0082] The calculation formula of the pattern standard transparency p0 is as follows:

[0083]

[0084] Among them, β1 and β2 are weight factors, which are trained by neural network to obtain appropriate values, and β1+β2=1; p0 is the standard transparency of the pattern, K is the safety correction factor, is the longitudinal safety distance between the vehicle and the preceding vehicle in the target lane, s f is the longitudinal distance between the vehicle and the preceding vehicle in the target lane, is the first longitudinal safety distance between the vehicle and the vehicle behind in the target lane, s r It is the longitudinal distance between the vehicle and the vehicle behind it in the target lane.

[0085] Compared with the prior art, the present invention has the following beneficial effects:

[0086] 1. The present invention uses vehicle networking technology to collect road condition information and the status information of vehicles in the target lane, ensuring the accuracy and real-time nature of the information, making the calculation and decision-making of the collision avoidance assistance system more precise.

[0087] 2. The present invention takes into account the impact of road traffic conditions, atmospheric visibility, driver characteristics and road adhesion on the merging process, making the decision of the collision avoidance assistance system more in line with the actual situation and improving the safety of the vehicle merging into the target lane.

[0088] 3. The present invention uses different warning methods to remind drivers according to different dangerous situations, intuitively showing the driver the degree of danger of merging behavior, helping the driver to safely complete the merging operation at the appropriate time, not only minimizing the risk of collision but also improving traffic efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0089] The present invention will be further described below with reference to the accompanying drawings:

[0090] Figure 1 This is a schematic diagram of the proposed collision avoidance assistance system composition and workflow;

[0091] Figure 2 This is a schematic diagram of the vehicle merging into the target lane along a circular curve trajectory;

[0092] Figure 3 This is a schematic diagram of the vehicle merging into the target lane along a straight driving trajectory. DETAILED DESCRIPTION

[0093] The present invention will be further explained below with reference to the accompanying drawings.

[0094] like Figure 1 As shown, the entire system includes a vehicle network information receiving module, a vehicle status perception module, an inflow process estimation module, a forward safety distance calculation module, a rearward first safety distance calculation module, a rearward second safety distance calculation module, an anti-collision decision module and a danger warning module.

[0095] For the vehicle network information receiving module, the vehicle network information receiving module includes a vehicle-to-road communication submodule and a vehicle-to-vehicle communication submodule. The vehicle-to-road communication submodule collects road condition information, and the road condition information includes: the up and down slope angles α of the current road, the visibility D of the current road, the traffic flow ρ of the current section, and the limit traffic flow ρ0 of the current section; the vehicle-to-vehicle communication submodule obtains the status information of the vehicle in front of the target lane and the status information of the vehicle behind the target lane. The status information of the vehicle in front of the target lane includes: the driving speed v of the vehicle in front of the target lane f and the vehicle type of the vehicle in front of the target lane, the state information of the vehicle behind the target lane includes: the speed v of the vehicle behind the target lane r , the vehicle type of the vehicle behind the target lane and the maximum braking deceleration a of the vehicle behind the target lane r ; Among them, the front vehicle in the target lane is a vehicle that is in the target lane, located in front of the vehicle and closest to the vehicle; the rear vehicle in the target lane is a vehicle that is in the target lane, located behind the vehicle and closest to the vehicle; the vehicle is the vehicle that is preparing to merge into the target lane.

[0096] As for the vehicle state perception module, the vehicle state perception module includes vehicle-mounted sensors, vehicle-mounted cameras, vehicle-mounted human-computer interaction screens and vehicle-mounted radars. The vehicle-mounted sensors collect the vehicle's driving speed v and the road adhesion coefficient μ of the current road. The vehicle-mounted cameras collect the distance L between the vehicle and the center line of the target lane and the angle θ between the vehicle body and the center line of the target lane. The vehicle-mounted human-computer interaction screen collects the driver's conservatism Y. The vehicle-mounted radar collects the longitudinal distance s between the vehicle and the vehicle in front of the target lane. f and the longitudinal distance s between the vehicle and the vehicle behind it in the target lane r , the longitudinal direction is a direction parallel to the lane line.

[0097] The merging process prediction module fits the vehicle's trajectory into the target lane based on the relevant information collected by the vehicle state perception module, and calculates the estimated merging time t and the estimated merging longitudinal displacement x. The specific calculation method is as follows:

[0098] (1) Figure 2 As shown in Figure 2, when θ>θ0, a circular curve is used to fit the vehicle's merging trajectory, and the calculation formula for the estimated merging time t is:

[0099]

[0100] Where θ0 is the merging angle threshold, which is set by the manufacturer based on the vehicle's steering performance; t is the estimated merging time, which approximates the time it takes for the vehicle to merge into the target lane; v0 is the merging speed threshold, which is set by the manufacturer based on the vehicle's power performance; L is the distance between the vehicle and the centerline of the target lane, θ is the angle between the vehicle and the centerline of the target lane, and v is the vehicle's speed.

[0101] The calculation formula for estimating the incoming longitudinal displacement x is:

[0102]

[0103] Where x is the estimated merging longitudinal displacement, which is used to approximate the longitudinal displacement of the vehicle when merging into the target lane; L is the distance between the vehicle and the centerline of the target lane; θ is the angle between the vehicle body and the centerline of the target lane;

[0104] (2) Figure 3 As shown in , when θ≤θ0, a straight line is used to fit the vehicle’s merging trajectory, and the calculation formula for the estimated merging time t is:

[0105]

[0106] Where θ0 is the merging angle threshold, which is set by the manufacturer based on the vehicle's steering performance; t is the estimated merging time, which approximates the time it takes for the vehicle to merge into the target lane; v0 is the merging speed threshold, which is set by the manufacturer based on the vehicle's power performance; L is the distance between the vehicle and the centerline of the target lane, θ is the angle between the vehicle and the centerline of the target lane, and v is the vehicle's speed.

[0107] The calculation formula for estimating the incoming longitudinal displacement x is:

[0108]

[0109] Where x is the estimated merging longitudinal displacement, which approximates the longitudinal displacement that the vehicle will travel when merging into the target lane; θ0 is the merging angle threshold, which is set by the manufacturer based on the vehicle's steering performance; and L is the distance between the vehicle and the centerline of the target lane.

[0110] The forward safety distance calculation module calculates the longitudinal safety distance between the vehicle and the preceding vehicle in the target lane based on the relevant information obtained by the vehicle network information receiving module, the vehicle state perception module and the merging process estimation module. The specific calculation method is as follows:

[0111] When v>v f When the longitudinal safety distance between the vehicle and the vehicle in front of the target lane is The calculation formula is:

[0112]

[0113] When v≤v f When the longitudinal safety distance between the vehicle and the vehicle in front of the target lane is The calculation formula is:

[0114]

[0115] in, is the longitudinal safety distance between the vehicle and the preceding vehicle in the target lane, x is the estimated merging longitudinal displacement, t is the estimated merging time, and v f is the speed of the vehicle ahead in the target lane, v is the speed of the vehicle, μ is the road adhesion coefficient of the current road, g is the acceleration of gravity, and α is the uphill and downhill slope angles of the current road; a1 is the maximum braking deceleration of the vehicle on a level and good road surface, and its specific value is set by the manufacturer according to the braking performance of the vehicle; d fis the minimum longitudinal safety distance between the host vehicle and the vehicle ahead in the target lane, which is determined by the vehicle type of the vehicle ahead in the target lane. The vehicle type is classified according to the maximum allowable gross mass of the vehicle, including light vehicles, medium vehicles, and heavy vehicles. The light vehicle is a vehicle with a maximum allowable gross mass less than or equal to 3000kg, the medium vehicle is a vehicle with a maximum allowable gross mass greater than 3000kg and less than or equal to 12000kg, and the heavy vehicle is a vehicle with a maximum allowable gross mass greater than 12000kg. The minimum longitudinal safety distance d between the host vehicle and the vehicle ahead in the target lane is determined by the vehicle type of the vehicle ahead in the target lane. f The value of is:

[0116] When the vehicle type of the preceding vehicle in the target lane is the light vehicle, d f 2m;

[0117] When the vehicle type of the preceding vehicle in the target lane is the medium-sized vehicle, d f 3m;

[0118] When the vehicle type of the preceding vehicle in the target lane is the heavy vehicle, d f is 4m.

[0119] The first safety distance calculation module calculates the first longitudinal safety distance between the vehicle and the vehicle behind it in the target lane based on the relevant information obtained by the vehicle network information receiving module, the vehicle state perception module and the merging process estimation module. The specific calculation method is as follows:

[0120] When v<v r The first longitudinal safety distance between the vehicle and the vehicle behind in the target lane is The calculation formula is:

[0121]

[0122] When v≥v r The first longitudinal safety distance between the vehicle and the vehicle behind in the target lane is The calculation formula is:

[0123]

[0124] in, is the first longitudinal safety distance between the vehicle and the vehicle behind it in the target lane, x is the estimated merging longitudinal displacement, t is the estimated merging time, and v r is the speed of the vehicle behind the target lane, v is the speed of the vehicle, μ is the road adhesion coefficient of the current road, g is the acceleration due to gravity, and α is the up and down slope angle of the current road; a2 is the reference acceleration when the vehicle accelerates, and its specific value is set by the manufacturer according to the vehicle's power performance; d ris the minimum longitudinal safety distance between the host vehicle and the vehicle behind in the target lane, which is determined by the vehicle type behind the target lane. The vehicle type is classified according to the maximum allowable gross vehicle mass, including light vehicles, medium vehicles, and heavy vehicles. The light vehicle is a vehicle with a maximum allowable gross vehicle mass less than or equal to 3000kg, the medium vehicle is a vehicle with a maximum allowable gross vehicle mass greater than 3000kg and less than or equal to 12000kg, and the heavy vehicle is a vehicle with a maximum allowable gross vehicle mass greater than 12000kg. The minimum longitudinal safety distance d between the host vehicle and the vehicle behind in the target lane is determined by the vehicle type behind the target lane. r The value of is:

[0125] When the vehicle type of the vehicle behind the target lane is the light vehicle, d r 2m;

[0126] When the vehicle type behind the target lane is the medium-sized vehicle, d r 3m;

[0127] When the vehicle type of the vehicle behind the target lane is the heavy vehicle, d r is 4m.

[0128] The second safety distance calculation module calculates the second longitudinal safety distance between the vehicle and the vehicle behind it in the target lane based on the relevant information obtained by the vehicle network information receiving module, the vehicle state perception module and the merging process estimation module. The specific calculation method is as follows:

[0129] When v<v r The second longitudinal safety distance between the vehicle and the vehicle behind in the target lane is The calculation formula is:

[0130]

[0131] When v≥v r The second longitudinal safety distance between the vehicle and the vehicle behind in the target lane is The calculation formula is:

[0132]

[0133] in, is the second longitudinal safety distance between the vehicle and the vehicle behind it in the target lane, x is the estimated merging longitudinal displacement, t is the estimated merging time, and v r is the speed of the vehicle behind the target lane, v is the speed of the vehicle, μ is the road adhesion coefficient of the current road, g is the acceleration of gravity, α is the up and down slope angle of the current road, and a r is the maximum braking deceleration of the vehicle behind in the target lane; t ris the braking reaction time of the vehicle behind the target lane, which consists of the driver's reaction time and the braking coordination time, t r Take 1.5s; d r is the minimum longitudinal safety distance between the host vehicle and the vehicle behind in the target lane, which is determined by the vehicle type behind the target lane. The vehicle type is classified according to the maximum allowable gross vehicle mass, including light vehicles, medium vehicles, and heavy vehicles. The light vehicle is a vehicle with a maximum allowable gross vehicle mass less than or equal to 3000kg, the medium vehicle is a vehicle with a maximum allowable gross vehicle mass greater than 3000kg and less than or equal to 12000kg, and the heavy vehicle is a vehicle with a maximum allowable gross vehicle mass greater than 12000kg. The minimum longitudinal safety distance d between the host vehicle and the vehicle behind in the target lane is determined by the vehicle type behind the target lane. r The value of is:

[0134] When the vehicle type of the vehicle behind the target lane is the light vehicle, d r 2m;

[0135] When the vehicle type behind the target lane is the medium-sized vehicle, d r 3m;

[0136] When the vehicle type of the vehicle behind the target lane is the heavy vehicle, d r is 4m.

[0137] For the collision avoidance decision module, the collision avoidance decision module calculates the safety correction coefficient K based on the relevant information collected by the Internet of Vehicles information receiving module and the vehicle status perception module. The calculation formula is:

[0138]

[0139] Among them, K is the safety correction factor, 1≤K<2; ω1, ω2, ω3, ω4 are weight factors, which are trained through neural networks to obtain appropriate values, and ω1+ω2+ω3+ω4=1; ρ is the traffic flow of the current section, ρ0 is the maximum traffic flow of the current section, D is the visibility of the current road, D0 is the dangerous threshold of visibility, and D0 is taken as 500m; Y is the driver's conservatism, 0≤Y≤100, and its specific value is manually set by the driver on the on-board human-computer interaction screen, with a default value of 50; μ is the road adhesion coefficient of the current road, μ0 is the dangerous threshold of the road adhesion coefficient, and μ0 is taken as 0.3;

[0140] The anti-collision decision module uses the safety correction factor K to calculate the longitudinal safety distance between the vehicle and the vehicle in front of the target lane. The first longitudinal safety distance between the vehicle and the vehicle behind in the target lane The second longitudinal safety distance between the vehicle and the vehicle behind it in the target lane Correction is performed, and a decision signal to be sent to the danger warning module is determined based on the correction result and the distance information measured by the vehicle-mounted radar. The decision signal includes a bidirectional safety signal, a rearward first-level warning signal, a rearward second-level warning signal, a forward warning signal, and a bidirectional warning signal. The method for determining the decision signal is:

[0141] when and and When the hazard warning module is activated, a two-way safety signal is sent to the hazard warning module;

[0142] when and When the hazard warning module is triggered, a first-level warning signal is sent to the hazard warning module;

[0143] when and When the hazard warning module is triggered, a backward secondary warning signal is sent;

[0144] when and When the hazard warning module is detected, a forward warning signal is sent to the hazard warning module;

[0145] when and When a warning signal is sent to the danger warning module;

[0146] Among them, s f is the longitudinal distance between the vehicle and the preceding vehicle in the target lane, s r is the longitudinal distance between the vehicle and the vehicle behind it in the target lane, is the longitudinal safety distance between the vehicle and the preceding vehicle in the target lane, is the first longitudinal safety distance between the vehicle and the vehicle behind it in the target lane, is the second longitudinal safety distance between the vehicle and the vehicle behind in the target lane, and K is the safety correction factor.

[0147] The hazard warning module includes a safety indicator light, a buzzer, and an onboard human-computer interaction screen. It receives the decision signal sent by the collision avoidance decision module, selects the warning method corresponding to the decision signal, and issues a hazard warning. The specific warning method is as follows:

[0148] When the received decision signal is a two-way safety signal, the incoming safety indicator light displays green, the buzzer does not sound an alarm, and the on-board human-computer interaction screen does not display an arrow pattern;

[0149] When the received decision signal is a rear-level first-level warning signal, the incoming safety indicator light turns yellow, the buzzer sounds an alarm at a frequency of f0, and the on-board human-computer interaction screen displays a flashing arrow pattern, the arrow pointing to the rear, the arrow flashing frequency is f0, and the arrow transparency is p0;

[0150] When the received decision signal is a rear-level secondary warning signal, the incoming safety indicator light turns red, the buzzer sounds an alarm at a frequency of 2f0, and the on-board human-computer interaction screen displays a flashing arrow pattern, the arrow pointing to the rear, the arrow flashing frequency is 2f0, and the transparency of the arrow is 0.5p0;

[0151] When the received decision signal is a forward warning signal, the incoming safety indicator light turns red, the buzzer sounds an alarm at a frequency of 2f0, and the on-board human-computer interaction screen displays a flashing arrow pattern, the arrow points forward, the arrow flashes at a frequency of 2f0, and the transparency of the arrow is 0.5p0;

[0152] When the received decision signal is a bidirectional warning signal, the incoming safety indicator light turns red, the buzzer sounds an alarm at a frequency of 3f0, and the on-board human-computer interaction screen displays a flashing double-arrow pattern, with the double arrows pointing forward and backward, the flashing frequency of the double arrows is 3f0, and the transparency of the double arrows is 0.3p0;

[0153] Among them, f0 is the alarm standard frequency, p0 is the pattern standard transparency;

[0154] The control method of the alarm standard frequency f0 adopts fuzzy control, and the specific method is as follows:

[0155] The input of the fuzzy control method is the forward distance relative deviation e1 and the backward distance relative deviation e2, and the output is the alarm standard frequency f0, where the calculation formulas of e1 and e2 are:

[0156]

[0157]

[0158] Among them, e1 is the relative deviation of the forward distance, e2 is the relative deviation of the backward distance, K is the safety correction factor, is the longitudinal safety distance between the vehicle and the preceding vehicle in the target lane, s f is the longitudinal distance between the vehicle and the preceding vehicle in the target lane, is the first longitudinal safety distance between the vehicle and the vehicle behind in the target lane, s r is the longitudinal distance between the vehicle and the vehicle behind it in the target lane;

[0159] The fuzzy subset of the input of the fuzzy control method is defined as e1 = {NB, NM, NS, ZE, PS, PM, PB}, that is, {negative large, negative medium, negative small, zero, positive small, positive medium, positive large}, e2 = {NB, NM, NS, ZE, PS, PM, PB}, that is, {negative large, negative medium, negative small, zero, positive small, positive medium, positive large}, and the fuzzy subset of the output is defined as f0 = {ZE, PO, PS, PM, PB}, that is, {zero, positive, positive small, positive medium, positive large}.

[0160] The above fuzzy control rules are:

[0161]

[0162] The calculation formula of the pattern standard transparency p0 is as follows:

[0163]

[0164] Among them, β1 and β2 are weight factors, which are trained by neural network to obtain appropriate values, and β1+β2=1; p0 is the standard transparency of the pattern, K is the safety correction factor, is the longitudinal safety distance between the vehicle and the preceding vehicle in the target lane, s f is the longitudinal distance between the vehicle and the preceding vehicle in the target lane, is the first longitudinal safety distance between the vehicle and the vehicle behind in the target lane, s r It is the longitudinal distance between the vehicle and the vehicle behind it in the target lane.

Claims

1. A collision avoidance assistance system for an intelligent connected vehicle merging into a target lane, characterized in that: It includes a vehicle network information receiving module, a vehicle status perception module, an inflow process estimation module, a forward safety distance calculation module, a rearward first safety distance calculation module, a rearward second safety distance calculation module, an anti-collision decision module, and a danger warning module; The vehicle network information receiving module includes a vehicle-to-road communication submodule and a vehicle-to-vehicle communication submodule. The vehicle-to-road communication submodule collects road condition information, which includes: the up and down slope angles α of the current road, the visibility D of the current road, the traffic flow ρ of the current road section, and the limit traffic flow ρ0 of the current road section; the vehicle-to-vehicle communication submodule obtains the status information of the vehicle in front of the target lane and the status information of the vehicle behind the target lane. The status information of the vehicle in front of the target lane includes: the driving speed v of the vehicle in front of the target lane f and the vehicle type of the vehicle in front of the target lane, the state information of the vehicle behind the target lane includes: the speed v of the vehicle behind the target lane r , the vehicle type of the vehicle behind the target lane and the maximum braking deceleration a of the vehicle behind the target lane r ; The preceding vehicle in the target lane is the vehicle that is in front of the vehicle and closest to the vehicle in the target lane; the following vehicle in the target lane is the vehicle that is behind the vehicle and closest to the vehicle in the target lane; the vehicle is the vehicle that is about to merge into the target lane; The vehicle state perception module includes a vehicle-mounted sensor, a vehicle-mounted camera, a vehicle-mounted human-computer interaction screen and a vehicle-mounted radar. The vehicle-mounted sensor collects the vehicle's driving speed v and the road adhesion coefficient μ of the current road. The vehicle-mounted camera collects the distance L between the vehicle and the center line of the target lane and the angle θ between the vehicle body and the center line of the target lane. The vehicle-mounted human-computer interaction screen collects the driver's conservatism Y. The vehicle-mounted radar collects the longitudinal distance s between the vehicle and the vehicle in front of the target lane. f and the longitudinal distance s between the vehicle and the vehicle behind it in the target lane r , the longitudinal direction is a direction parallel to the lane line; The merging process estimation module fits the driving trajectory of the vehicle merging into the target lane based on the relevant information collected by the vehicle state perception module, and calculates the estimated merging time t and the estimated merging longitudinal displacement x; The forward safety distance calculation module calculates the longitudinal safety distance between the vehicle and the preceding vehicle in the target lane based on the relevant information obtained by the vehicle network information receiving module, the vehicle state perception module and the merging process estimation module. The rear first safety distance calculation module calculates the first longitudinal safety distance between the vehicle and the vehicle behind in the target lane based on the relevant information obtained by the vehicle network information receiving module, the vehicle state perception module and the merging process estimation module. The specific calculation method is as follows: When v<v r The first longitudinal safety distance between the vehicle and the vehicle behind in the target lane is The calculation formula is: When v≥v r The first longitudinal safety distance between the vehicle and the vehicle behind in the target lane is The calculation formula is: Among them, α is the up and down slope angle of the current road, μ is the road adhesion coefficient of the front road, v is the driving speed of the vehicle, t is the estimated merging time, x is the estimated merging longitudinal displacement, v r is the speed of the vehicle behind in the target lane, a2 is the reference acceleration when the vehicle accelerates; d r The minimum longitudinal safety distance between the vehicle and the vehicle behind it in the target lane, which is determined by the type of vehicle behind it in the target lane. The rear second safety distance calculation module calculates the second longitudinal safety distance between the vehicle and the vehicle behind in the target lane based on the relevant information obtained by the vehicle network information receiving module, the vehicle state perception module and the merging process estimation module. The specific calculation method is as follows: When v<v r The second longitudinal safety distance between the vehicle and the vehicle behind in the target lane is The calculation formula is: When v≥v r The second longitudinal safety distance between the vehicle and the vehicle behind in the target lane is The calculation formula is: Among them, a r is the maximum braking deceleration of the vehicle behind in the target lane, t r is the braking reaction time of the vehicle behind in the target lane, which is composed of the driver's reaction time and the braking coordination time, and g is the acceleration due to gravity; The anti-collision decision module calculates the safety correction coefficient K based on the relevant information collected by the Internet of Vehicles information receiving module and the vehicle status perception module, and uses the safety correction coefficient K to adjust the longitudinal safety distance between the vehicle and the vehicle in front of the target lane. The first longitudinal safety distance between the vehicle and the vehicle behind in the target lane The second longitudinal safety distance between the vehicle and the vehicle behind it in the target lane Perform corrections, and determine a decision signal to be sent to a danger warning module based on the correction result and the distance information measured by the vehicle-mounted radar, the decision signal including a bidirectional safety signal, a rearward first-level warning signal, a rearward second-level warning signal, a forward warning signal, and a bidirectional warning signal; The danger warning module includes a safety indicator light, a buzzer and an on-board human-computer interaction screen. It receives the decision signal sent by the anti-collision decision module, selects the warning method corresponding to the decision signal, and issues a danger warning.

2. The collision avoidance assistance system for an intelligent connected vehicle merging into a target lane according to claim 1, characterized in that: The merging process estimation module estimates the process of the vehicle merging into the target lane based on the distance L between the vehicle and the centerline of the target lane, the angle θ between the vehicle body and the centerline of the target lane, and the vehicle's speed v. It calculates the estimated merging time t and the estimated merging longitudinal displacement x. The specific calculation method is as follows: (1) When θ>θ0, a circular curve is used to fit the vehicle's merging trajectory. The formula for estimating the merging time t is: Where θ0 is the merging angle threshold, which is set by the manufacturer based on the vehicle's steering performance; t is the estimated merging time, which represents the time it takes for the vehicle to merge into the target lane; v0 is the merging speed threshold, which is set by the manufacturer based on the vehicle's dynamic performance. The calculation formula for estimating the incoming longitudinal displacement x is: Where x is the estimated merging longitudinal displacement, which is used to represent the longitudinal displacement that the vehicle will pass through when merging into the target lane; (2) When θ≤θ0, a straight line is used to fit the vehicle’s merging trajectory. The formula for estimating the merging time t is: The calculation formula for estimating the incoming longitudinal displacement x is:

3. The collision avoidance assistance system for an intelligent connected vehicle merging into a target lane according to claim 1, characterized in that: The forward safety distance calculation module calculates the vehicle's speed v according to the current road's up and down slope angle α, the current road's road adhesion coefficient μ, the vehicle's speed v, the estimated merging time t, the estimated merging longitudinal displacement x, the vehicle's speed v in the target lane, and the vehicle's speed v in the target lane. f and the vehicle type of the vehicle in front of the target lane, calculate the longitudinal safety distance between the vehicle and the vehicle in front of the target lane The specific calculation method is as follows: When v>v f When the longitudinal safety distance between the vehicle and the vehicle in front of the target lane is The calculation formula is: When v≤v f When the longitudinal safety distance between the vehicle and the vehicle in front of the target lane is The calculation formula is: Where g is the acceleration due to gravity; a1 is the maximum braking deceleration of the vehicle on a level and good road surface, and its specific value is set by the manufacturer according to the braking performance of the vehicle; d f is the minimum longitudinal safety distance between the host vehicle and the vehicle ahead in the target lane, which is determined by the vehicle type of the vehicle ahead in the target lane. The vehicle type is classified according to the maximum allowable gross vehicle mass, including light vehicles, medium vehicles, and heavy vehicles. The light vehicle is a vehicle with a maximum allowable gross vehicle mass less than or equal to 3000kg, the medium vehicle is a vehicle with a maximum allowable gross vehicle mass greater than 3000kg and less than or equal to 12000kg, and the heavy vehicle is a vehicle with a maximum allowable gross vehicle mass greater than 12000kg. The minimum longitudinal safety distance d between the host vehicle and the vehicle ahead in the target lane is determined by the vehicle type of the vehicle ahead in the target lane. f The value of is: When the vehicle type of the preceding vehicle in the target lane is the light vehicle, d f 2m; When the vehicle type of the preceding vehicle in the target lane is the medium-sized vehicle, d f 3m; When the vehicle type of the preceding vehicle in the target lane is the heavy vehicle, d f is 4m.

4. The collision avoidance assistance system for an intelligent connected vehicle merging into a target lane according to claim 1, characterized in that: The vehicle type is classified according to the maximum allowable gross mass of the vehicle into light vehicles, medium vehicles, and heavy vehicles. The light vehicles are vehicles with a maximum allowable gross mass less than or equal to 3000 kg, the medium vehicles are vehicles with a maximum allowable gross mass greater than 3000 kg and less than or equal to 12000 kg, and the heavy vehicles are vehicles with a maximum allowable gross mass greater than 12000 kg. The minimum longitudinal safety distance d between the vehicle and the vehicle behind it in the target lane is d. r The value of is: When the vehicle type of the vehicle behind the target lane is the light vehicle, d r 2m; When the vehicle type behind the target lane is the medium-sized vehicle, d r 3m; When the vehicle type of the vehicle behind the target lane is the heavy vehicle, d r is 4m.

5. The collision avoidance assistance system for an intelligent connected vehicle merging into a target lane according to claim 1, characterized in that: The t r Take it as 1.5s.

6. The collision avoidance assistance system for an intelligent connected vehicle merging into a target lane according to claim 1, characterized in that: The collision avoidance decision module calculates the safety correction factor K based on the traffic flow ρ of the current road section, the limit traffic flow ρ0 of the current road section, the visibility D of the current road, the driver's conservatism Y and the road adhesion coefficient μ of the current road. The calculation formula is: Where K is the safety correction factor, 1≤K<2; ω1, ω2, ω3, and ω4 are weight factors, which are obtained through neural network training, and ω1+ω2+ω3+ω4=1; D0 is the dangerous threshold of visibility, D0 is taken as 500m; Y is the driver's conservatism, 0≤Y≤100, and its specific value is manually set by the driver on the on-board human-computer interaction screen, with a default value of 50; μ0 is the dangerous threshold of the road adhesion coefficient, μ0 is taken as 0.3; The anti-collision decision module sends a decision signal to the danger warning module, and the decision signal is determined by: when and and When the hazard warning module is activated, a two-way safety signal is sent to the hazard warning module; when and When the hazard warning module is triggered, a first-level warning signal is sent to the hazard warning module; when and When the hazard warning module is triggered, a backward secondary warning signal is sent; when and When the hazard warning module is detected, a forward warning signal is sent to the hazard warning module; when and When a warning signal is generated, a bidirectional warning signal is sent to the danger warning module.

7. The collision avoidance assistance system for an intelligent connected vehicle merging into a target lane according to claim 1, characterized in that: The danger warning module receives the decision signal sent by the collision avoidance decision module and issues a warning according to the decision signal. The specific method of the warning is as follows: When the received decision signal is a two-way safety signal, the incoming safety indicator light displays green, the buzzer does not sound an alarm, and the on-board human-computer interaction screen does not display an arrow pattern; When the received decision signal is a rear-level first-level warning signal, the incoming safety indicator light turns yellow, the buzzer sounds an alarm at a frequency of f0, and the on-board human-computer interaction screen displays a flashing arrow pattern, the arrow pointing to the rear, the arrow flashing frequency is f0, and the arrow transparency is p0; When the received decision signal is a rear-level secondary warning signal, the incoming safety indicator light turns red, the buzzer sounds an alarm at a frequency of 2f0, and the on-board human-computer interaction screen displays a flashing arrow pattern, the arrow pointing to the rear, the arrow flashing frequency is 2f0, and the transparency of the arrow is 0.5p0; When the received decision signal is a forward warning signal, the incoming safety indicator light turns red, the buzzer sounds an alarm at a frequency of 2f0, and the on-board human-computer interaction screen displays a flashing arrow pattern, the arrow points forward, the arrow flashes at a frequency of 2f0, and the transparency of the arrow is 0.5p0; When the received decision signal is a bidirectional warning signal, the incoming safety indicator light turns red, the buzzer sounds an alarm at a frequency of 3f0, and the on-board human-computer interaction screen displays a flashing double-arrow pattern, with the double arrows pointing forward and backward, the flashing frequency of the double arrows is 3f0, and the transparency of the double arrows is 0.3p0; Among them, f0 is the alarm standard frequency, p0 is the pattern standard transparency; The control method of the alarm standard frequency f0 adopts fuzzy control, and the specific method is as follows: The input of the fuzzy control method is the forward distance relative deviation e1 and the backward distance relative deviation e2, and the output is the alarm standard frequency f0, where the calculation formulas of e1 and e2 are: The fuzzy subset of the input of the fuzzy control method is defined as e1 = {NB, NM, NS, ZE, PS, PM, PB}, that is, {negative large, negative medium, negative small, zero, positive small, positive medium, positive large}, e2 = {NB, NM, NS, ZE, PS, PM, PB}, that is, {negative large, negative medium, negative small, zero, positive small, positive medium, positive large}, and the fuzzy subset of the output is defined as f0 = {ZE, PO, PS, PM, PB}, that is, {zero, positive, positive small, positive medium, positive large}. The calculation formula of the pattern standard transparency p0 is as follows: Among them, β1 and β2 are weight factors, and the values ​​are obtained through training of the neural network, and β1+β2=1.

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