A warning method for urban and suburban intersections without traffic lights

Abstract

The application discloses a warning method for a city suburb signal-free intersection, which comprises the following steps: firstly, measuring the initial speed of a motor vehicle and a non-motor vehicle; dataizing the unquantifiable factors of people, vehicles, roads and environment, and establishing a vehicle speed influencing factor model; calculating the motor vehicle speed V j1 ; correcting the motor vehicle speed; calculating the conflict area according to the intersection, and calculating the conflict probability according to the corrected motor vehicle speed and the non-motor vehicle speed; determining the warning mode through the conflict result; determining the warning result again after the single warning is finished; establishing a motor vehicle waiting threshold model; and warning the motor vehicle again when the waiting time of the non-motor vehicle exceeds the set threshold value. The application reduces the accident rate of the city suburb signal-free intersection, and guarantees the safety of road driving in the city suburb area.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of traffic warning, in particular to a warning method for a signal-free intersection in urban and suburban areas. BACKGROUND

[0002] With the acceleration of road construction, urban trunk roads are often connected with suburban and rural areas. Many intersections are formed between rural roads and urban trunk roads, and this phenomenon is particularly common in village roads. Almost every rural road along the trunk road forms an intersection with the main road. In addition, these roads lack the necessary road traffic safety facilities, and the phenomenon of non-motor vehicles and passing vehicles competing for roads is serious, which leads to frequent accidents between motor vehicles and non-motor vehicles. Moreover, due to the high speed of motor vehicles, the lack of protective equipment for non-motor vehicle personnel, and other reasons, such traffic accidents often cause serious casualties and pose a great threat to the lives and property of the general public. Therefore, warning devices need to be installed at intersections between urban and suburban roads and rural roads without traffic signals to reduce traffic accidents.

[0003] In existing warning devices, simple warning devices for motor vehicles and non-motor vehicles often have inaccurate information acquisition, overly conservative warning parameter settings, and other reasons that lead to high warning failure rates, greatly reducing road traffic efficiency. The invention patent with the publication number CN104900076A discloses a vehicle safety warning system for a main road and a secondary road intersection without traffic lights. The above scheme monitors and warns the vehicles driving on the main road that forms the intersection through the main road monitoring and warning device. The main road monitoring and warning device communicates with the secondary road warning linkage device to control the secondary road warning linkage device to output secondary road warning information. The secondary road warning linkage device outputs corresponding secondary road warning information according to the different states of the main road vehicles, thereby avoiding visual fatigue, improving the alertness of drivers and pedestrians, and effectively monitoring and warning the traffic state of the intersection. However, the following problems still exist: 1. The conflict prediction model of the scheme has a single scene and cannot adapt to most scenes. For example, the scheme uses a main speed radar and a secondary speed radar to set the speed at a distance of 20 meters from the intersection. However, due to the distance between the speed measurement position and the intersection, as well as factors such as specific road conditions, weather, and driving habits of drivers, the speed will fluctuate to a certain extent, leading to deviations in the predicted collision between main road vehicles and non-motor vehicles on the branch road, thereby reducing traffic efficiency and even causing traffic accidents; 2. The scheme does not provide a specific mathematical model for calculating conflicts and establish a corresponding conflict area to calculate the probability of conflict, and the judgment logic is too simple to deal with actual complex road conditions.

[0004] How to warn vehicles at the intersection without traffic lights in the urban suburbs is a technical problem to be solved urgently. SUMMARY

[0005] The present application provides a warning method for the intersection without traffic lights in the urban suburbs, detects vehicle information by a speed measuring device, obtains the speed of motor vehicles and non-motor vehicles in the road, analyzes and corrects the obtained speed, establishes a coordinate system for the live road, analyzes the conflict probability of vehicles using the obtained data, and finally warns according to the result.

[0006] TECHNICAL SOLUTION The warning method for the intersection without traffic lights in the urban suburbs comprises the following steps:

[0007] Step (1), measures the initial speed of motor vehicles and non-motor vehicles, and records the initial speed of motor vehicles as V j1 (km / h) and the initial speed of non-motor vehicles as V F (km / h).

[0008] Step (1) comprises the following process:

[0009] The speed of motor vehicles and non-motor vehicles is measured by a speed measuring device, the initial speed of motor vehicles is recorded as V j1 (km / h), and the initial speed of non-motor vehicles is recorded as V F (km / h).

[0010] Step (2), dataizes the unquantifiable factors of people, vehicles, roads and environment, and establishes a vehicle speed influencing factor model to correct the motor vehicle speed V j1 obtained in step (1), and records the speed of motor vehicles after correction by the vehicle speed influencing factor model as V j2 .

[0011] Step (2) comprises the following process:

[0012] (2.1), corrects the speed of motor vehicles, dataizes the unquantifiable factors of people and road environment, and realizes the calculation of the speed of motor vehicles in the conflict area through the result of the vehicle speed influencing factor model, and records the final speed as V j2 . After the initial measurement of the speed of motor vehicles V j1 (km / h) is completed, the initial measurement of the speed of motor vehicles V j1(km / h) to modify the vehicle speed influence factor model, first, the main factors of people X1, vehicles X2, roads X3 and environment X4 are established, the factors of people are: age c 11 , gender c 12 , driving age c 13 ; the factors of vehicles are: vehicle age c 21 , illegal driving c 22 ; the factors of roads are: road surface condition c 31 , marking clarity c 32 ; the factors of environment are: sight obstruction c 31 , weather c 32 , time c 33 . The coefficient intervals a ji of different factors are obtained, and the vehicle speed influence factor model is:

[0013]

[0014] a ji represents the coefficient interval of different factors, c 11 represents the influence degree of each vehicle speed influence factor, V j2 represents the speed of the motor vehicle after modification.

[0015] Step (3), calculate the conflict area according to the intersection, and calculate the probability of conflict according to the modified speed V j2 (km / h) of the motor vehicle and the speed V F (km / h) of the non-motor vehicle.

[0016] Step (3) includes the following processes:

[0017] Step (3.1), calculate the area of the conflict area by using the conflict area calculation model, when calculating, the largest road edge line is used as the conflict area edge line by using the assumed trajectory, and the trajectory of the non-motor vehicle is assumed, the non-motor vehicle travels according to the assumed trajectory, the trajectory is determined by the connecting line of the road marking nodes, and the area of the conflict area is obtained by combining the map and the conflict area calculation model.

[0018] Step (3.2), after calculating the area of the conflict area, the modified speed V j2 (km / h) of the motor vehicle and the speed V F of the non-motor vehicle are used to calculate the probability of conflict.The probability of a conflict is determined by the speed (km / h), conflict area, and vehicle area. A NOT-AND gate calculation method is used to calculate the conflict probability. The process is as follows: A coordinate system is established at the intersection, and driving areas are created for moving vehicles. To facilitate calculation, the conflict area is gridded, and the driving area is determined to be a square region. For vehicles traveling straight, the area is denoted as a rectangle perpendicular to the X-axis. For turning vehicles, a linear function is used for trajectory prediction. Considering that the actual impact range of a vehicle accident is not the area occupied by the vehicle, the impact range of the vehicle is expanded, using a circular area as the final impact range of the vehicle.

[0019] The process is implemented based on the conflict zone calculation model, the collision range model of non-motorized vehicles, the collision range model of motorized vehicles, the movement trajectory model of motorized and non-motorized vehicles, and the conflict probability determination model.

[0020] When using the conflict region calculation model, all conflict regions are defined as square regions, and the conflict region calculation model is as follows:

[0021] S 冲 ={(X,Y)|X L <X<X R And Y B <Y<Y T}

[0022] Among them, S 冲 (m 2 X represents the area of ​​the conflict zone. L X represents the left boundary line of the conflict region with respect to the coordinate system. R This represents the right boundary line of the conflict region with respect to the coordinate system, Y. B Y represents the lower boundary line of the conflict region with respect to the coordinate system, and Y represents the upper boundary line of the conflict region with respect to the coordinate system.

[0023] For the collision range models of non-motorized vehicles and motorized vehicles, the collision ranges of both are summarized as circles moving along a certain speed and trajectory:

[0024] S 机 ={(X,Y)|(XX)} VS +V j2X t) 2 +(YY VS +V j2Y t) 2 =3.5 2}

[0025] Where S 机 (m 2 X represents the collision range of a motor vehicle. VS The x-coordinate, Y-coordinate, represents the initial position of the vehicle in the coordinate system.VS the longitudinal coordinate of the initial position of the motor vehicle establishing the coordinate system, V j2X (km / h) the speed of the motor vehicle in the direction of the X axis, V j2Y (km / h) the speed of the motor vehicle in the direction of the Y axis, t (h) the time since the motor vehicle entered the initial position.

[0026] S 非 = {(X, Y) | (X - X FS + V FX t) 2 (Y - Y FS + V FY t) 2 = 3.5 2}

[0027] where S 非 (m 2 ) represents the collision range of the non-motor vehicle, X FS represents the longitudinal coordinate of the initial position of the non-motor vehicle establishing the coordinate system, Y FS represents the longitudinal coordinate of the initial position of the non-motor vehicle establishing the coordinate system, V FX (km / h) represents the speed of the non-motor vehicle in the direction of the X axis, V FY (km / h) represents the speed of the non-motor vehicle in the direction of the Y axis, t (h) represents the time since the non-motor vehicle entered the initial position.

[0028] To calculate the vehicle speed in the direction of the Y axis and the X axis in the collision range of the non-motor vehicle and the collision range of the motor vehicle, the motor vehicle and non-motor vehicle movement trajectory models need to be calculated, and the motor vehicle and non-motor vehicle movement trajectory models are set as functions:

[0029] y = f(x)

[0030] where y represents the longitudinal coordinate of the coordinate system established by the movement trajectory model, x represents the longitudinal coordinate of the coordinate system established by the movement trajectory model, and f(x) represents the function of the movement trajectory model.

[0031] Further, the speed V NM of the motor vehicle or non-motor vehicle in the X axis and Y axis is obtained:

[0032]

[0033] where V NM represents the speed of the motor vehicle or non-motor vehicle in the X axis and Y axis, represents the function of the speed of the motor vehicle or non-motor vehicle in the X axis and Y axis with respect to the motor vehicle and non-motor vehicle movement trajectory model.

[0034] Finally, the conflict area S 冲The collision range of a motor vehicle, S 机 The collision range S of non-motorized vehicles 非 After the analysis of the three was completed, S... 机 S represents the movement of a certain area by a motor vehicle along a certain trajectory. 非 This refers to the movement of non-motorized vehicles within a defined area following a specific trajectory. In the actual judgment process, it is determined based on the area within the conflict zone S. 冲 In the middle, will S appear at the same time? 非 The collision range of non-motorized vehicles and S 机 The overlapping areas of the collision ranges of the motor vehicles are considered. If an overlapping area exists, the current workflow determines that a vehicle collision will occur—represented as P=1 in the model; if no overlapping area exists, it is determined that no vehicle collision will occur—represented as P=0 in the model. This determination process is compiled into a model, which this invention defines as a collision probability determination model, as follows:

[0035]

[0036] Taking a conflict type involving a non-motorized vehicle approaching from the right and a motorized vehicle traveling in a straight lane as an example, the feasibility of this invention is verified. The left-hand lane marking of the motorized vehicle's straight lane is used as the Y-axis, with the direction of the road markings as the positive direction; the stop line of the motorized vehicle lane is used as the X-axis, with the right side of the vehicle's travel direction as the positive direction of the X-axis; the intersection of the X-axis of the stop line of the motorized vehicle lane and the Y-axis of the left-hand lane marking of the motorized vehicle's straight lane is used as the origin. The resulting conflict area calculation model is as follows:

[0037] S 冲 ={(X,Y)|1<X<2 and 5<Y<7}

[0038] Among them, S 冲 (m 2 ) represents the area of ​​the conflict zone, and X and Y represent the boundary lines of the conflict zone established by modeling in a two-dimensional coordinate system.

[0039] Step (3.3), after establishing the conflict zone calculation model, establish a collision range model for motor vehicles and non-motor vehicles appearing in the conflict zone. First, establish a collision range model for the moving motor vehicles.

[0040] The collision range of a moving motor vehicle is represented as a circle moving at a certain speed and trajectory; for the collision range of a non-motorized vehicle, a function is used as the center of the circle, and a trajectory formula for the circular region is established.

[0041] S 机 ={(X,Y)|(X-2)} 2 +(Y+35-V j2 t) 2= 3.5 2}

[0042] S 非 = {(X, Y) | (X - X 非 ) 2 + (Y + aX 非 + b) 2 = 0.75 2}

[0043] S 机 (m 2 ) represents the collision range of the motor vehicle, S 非 (m 2 ) represents the collision range of the non-motor vehicle.

[0044] After the collision ranges of the motor vehicle and the non-motor vehicle are obtained, the driving trajectories of the motor vehicle and the non-motor vehicle are determined, the driving trajectory of the motor vehicle is straight driving; and the driving trajectory of the non-motor vehicle is a linear function, which is expressed as:

[0045] y = kx + b

[0046] wherein x represents the X coordinate value of the coordinate system established by the non-motor vehicle during driving, y represents the y coordinate value of the coordinate system established by the non-motor vehicle during driving, and k and b represent the parameters of the moving trajectory equation.

[0047] When the driving trajectory of the non-motor vehicle is calculated, the coordinates of the initial position point of the motor vehicle are obtained when the trajectory is a linear function at the time of passing through the intersection, which is denoted as X0, Y0. Since only the speed of the non-motor vehicle is measured, the ratio relationship of the trigonometric functions under the same proportion is established to reflect the coordinates of the non-motor vehicle, and the ratio method is used to obtain the x-axis coordinate changing with time:

[0048]

[0049] wherein x represents the X-axis coordinate value of the collision region center point of the non-motor vehicle relative to the coordinate system; V 非 represents the speed of the non-motor vehicle, t represents the time calculated from the initial point, and b and k represent the moving trajectory parameters of the non-motor vehicle.

[0050] y is obtained as the y-axis coordinate value of the collision region center point of the non-motor vehicle relative to the coordinate system:

[0051]

[0052] wherein y represents the Y-axis coordinate value of the collision region center point of the non-motor vehicle relative to the coordinate system; V 非where v represents the speed of the non-motor vehicle, t represents the time since the initial point, and b and k represent the parameters of the non-motor vehicle trajectory.

[0053] Step (3.4) establishes the conflict probability determination model according to the conflict area S 冲 , the collision range S 机 of the motor vehicle, and the collision range S 非 of the non-motor vehicle, and the specific process is as follows:

[0054]

[0055] Step (4) determines the warning result according to the calculation result of the conflict probability determination model.

[0056] Step (4) includes the following processes:

[0057] Step (4.1), when the result of the conflict probability determination model is 0, no warning is given to the motor vehicle and the non-motor vehicle on the road. When the conflict probability occurs, the vehicle speed of the motor vehicle and the non-motor vehicle is recorded. The non-motor vehicle is given priority in warning and signal control. At the same time, the vehicle information of the motor vehicle in the lane is detected. After the signal control of the non-motor vehicle, the video information is rechecked, and if the motor vehicle flow exceeds the preset threshold, the lane where the motor vehicle is located is given signal control. In the specific warning of the non-motor vehicle, considering that different intersections have different signal light periods T 周 , the following non-motor vehicle waiting period model is used:

[0058]

[0059] where M represents the number of lanes, N represents the road capacity, t tong represents the non-motor vehicle passing time.

[0060] Step (4.2), when the warning device of the non-motor vehicle is working, the duration of the non-motor vehicle warning is defined by the vehicle passing time at the intersection. After the end of a warning period, the speed measuring device of the motor vehicle determines whether there are still motor vehicles on the road, and when motor vehicles appear again, the intersection of the non-motor vehicle and the motor vehicle is given periodic signal light warning.

[0061] Step (5), after a single warning ends, the vehicle information of the motor vehicle and the non-motor vehicle on the road is determined again, and a non-motor vehicle waiting threshold model is established:

[0062] Step (5) includes the following processes:

[0063] After completing a single warning work, the presence information of the motor vehicle on the road is collected by the motor vehicle speed measuring device, and the number of motor vehicle vehicles in the road at this time is recorded as g, and the non-motor vehicle continues to cycle warning. During the cycle warning process, the warning time of the non-motor vehicle is set to a threshold, a maximum time limit value is set, and the actual intersection parameters (intersection length L lu ), the number of road motor vehicles g, the safety distance L an and the motor vehicle speed v jj The non-motor vehicle waiting threshold model is established, and the non-motor vehicle waiting threshold model is as follows: first, set the safety vehicle distance L an , the number of vehicles g, the vehicle speed v jj , L lu represents the length of the intersection, T yue represents the waiting threshold of the non-motor vehicle

[0064]

[0065] When the waiting time of the non-motor vehicle exceeds the set threshold, the waiting time of the non-motor vehicle waiting threshold model is warned, and the warning time is calculated according to the waiting threshold model.

[0066] Working principle: the vehicle speed of the vehicle driving in the intersection without signal light in the city suburb is collected first, and the speed is corrected based on the factors of people, vehicles, roads and environment, and then the accuracy of vehicle speed prediction is improved; according to the road information, the motor vehicle and the non-motor vehicle speed, the conflict area is established, and the conflict area and the conflict probability are calculated according to the different situations of the conflict between the vehicles driving in different lanes and the non-motor vehicles, so that the warning module is in different working state, and then the driver is warned. Compared with the existing warning technology, the present application reduces the accident rate of this type of intersection and ensures the safety of driving in the suburb.

[0067] Advantages: compared with the prior art, the present application has the following advantages:

[0068] (1) The vehicle speed collected by the present application is substituted into the vehicle speed influencing factor model analyzed by the factors of people, vehicles, roads and environment, and the secondary corrected vehicle speed is obtained, which improves the accuracy of vehicle speed prediction, avoids the false judgment of the warning system due to the wrong estimation of the vehicle speed through the intersection, and avoids the system without warning or warning in the case where warning is not needed, improves the traffic efficiency and reduces the probability of traffic accidents.

[0069] (2) The present application establishes a conflict area calculation model and a conflict probability determination model for different situations of conflicts between motor vehicles and non-motor vehicles driving in different lanes, and then determines whether a conflict occurs and the probability of the conflict, and different warning measures are taken for different conflict results, which can accurately determine in complex road conditions and improve the accuracy and reliability of the determination probability. BRIEF DESCRIPTION OF DRAWINGS

[0070] Figure 1 The warning method flow chart of the present application for urban and suburban signal-free intersections;

[0071] Figure 2 The warning method work flow chart of the present application;

[0072] Figure 3 The conflict type chart for the first type of non-motor vehicle right-side oncoming vehicle and the motor vehicle driving in a straight lane;

[0073] Figure 4 The conflict type chart for the second type of non-motor vehicle right-side oncoming vehicle and the motor vehicle driving in a straight lane or a left-turn lane;

[0074] Figure 5 The conflict type chart for the third type of non-motor vehicle left-side oncoming vehicle and the motor vehicle driving in a straight lane;

[0075] Figure 6 The conflict type chart for the fourth type of non-motor vehicle left-side oncoming vehicle and the motor vehicle driving in a straight lane or a left-turn lane;

[0076] Figure 7 The non-motor vehicle warning device schematic diagram;

[0077] Figure 8 The implementation case schematic diagram of the present application. DETAILED DESCRIPTION

[0078] As shown in Figures 1 to 8 , the warning method of the present application for urban and suburban signal-free intersections includes the following steps:

[0079] (1) Measure the initial speed of the motor vehicle and the non-motor vehicle, and record the initial speed of the motor vehicle as V j1 (km / h); and record the initial speed of the non-motor vehicle as V F (km / h).

[0080] Step (1.1), use a speed measuring device to measure the initial speed of the motor vehicle, and record the initial speed of the motor vehicle as V j1 (km / h); and record the measured speed of the non-motor vehicle as V F (km / h).

[0081] Step (1.2), considering the distance setting of the speed measuring device, assuming the speed V as the maximum limit speed of the road c (70-80 km / h according to the Road Speed Limit Regulations and Over-speed Punishment Standards, urban suburban road speed limit) ; because the speed near the intersection is calculated as 70 km / h. The following calculation formula is used to calculate the braking distance:

[0082] D = V C × t f + 0.5(t f × a)

[0083] where t f is the braking time, which is 1.7 seconds using existing data, and a is the braking acceleration, which is 6.25 (m / s). The calculated braking distance is 42 m. Therefore, the speed measuring device is placed 42 m away from the intersection.

[0084] (2) Data of human, vehicle, road, and environmental factors are quantified, and a vehicle speed influencing factor model is established to correct the vehicle speed V j1 obtained in step (1). The corrected speed is denoted as V j2 ; the vehicle speed influencing factor model is:

[0085]

[0086] a ji represents the coefficient interval of different factors, c 11 represents the influence degree of each vehicle speed influencing factor, and V j2 represents the vehicle speed after correction by the vehicle speed influencing factor model.

[0087] Step (2.1), vehicle speed correction, related factors are established through analysis, and a vehicle speed influencing factor model is established. The human behavior factors and road environment factors that cannot be quantified are quantified, and the vehicle speed in the conflict area is calculated through the results of the vehicle speed influencing factor model. The final speed is denoted as V j2 . After the initial vehicle speed V j1 (km / h) is measured, the initial vehicle speed V j1 (km / h) is corrected by the vehicle speed influencing factor model. First, the human X1, vehicle X2, road X3, and environment X4 are established as the main level, and the second level factors are obtained: the human factors are age c 11 , gender c 12 , and driving experience c 13 ; the vehicle factors are vehicle age c 21 , and violation c 22 ; the road factors are road surface condition c 31 , and marking clarity c 32; environmental factors have line of sight c 31 , weather c 32 , time c 33 . For the above factors, the coefficient interval a ji , the final correction speed is calculated, which is:

[0088] V j2 =∑V j1 a ij c ij

[0089] a ji indicates the coefficient interval of different factors, c 11 indicates the influence degree of each vehicle speed influencing factor, V j2 indicates the speed of the motor vehicle after passing through the vehicle speed influencing factor model correction.

[0090] For human factors: age c 11 , gender c 12 , driving age c 13 , age c 11 influences the driver's psychology and operation, age is classified, and the age factor is converted into brake reaction time; The gender factor is also converted into brake reaction; The driving age c 13 is converted into the maintenance of vehicle speed.

[0091] For convenience of quantification and calculation, numerical analysis is carried out on human factors, and all factors are unitized, and the value range of the factor is recorded as (0, 2), which reflects the linear influence on vehicle factors.

[0092] Vehicle factors: vehicle age c 21 , violation c 22 , for vehicle age, analyze its brake time as an index, and violation is an important factor to judge whether to brake. Among the influencing factors of the vehicle, the mileage of the vehicle is an important factor affecting the braking and starting performance of the vehicle. Violation is the basis for whether the vehicle will continue to maintain the current vehicle speed at the intersection.

[0093] Road factors: road surface condition c 31 , marking clarity c 32 , road surface condition is used to convert vehicle trajectory and speed to determine the final trajectory and speed. The clarity of the marking is represented as the limit of the final braking distance.

[0094] Environmental factors have line of sight c 31 , weather c 32 , time c 33The degree of obstruction to visibility is a fixed value, but it changes depending on the intersection. Weather is a crucial factor; rainy or overcast days will have a certain impact on vehicle driving, with different effects on drivers depending on whether it is during the morning or evening rush hour.

[0095] Among human factors, considering that a single factor cannot directly determine the degree of influence on vehicle speed, the human factors are decomposed downwards. The factors influencing age, gender, and driving experience are decomposed into: Age: Stable driving age (age range 20-55 years), relatively stable driving age (age range 18-20, 55 years); Gender: Male, Female; Driving experience: Initial driving age (1-2 years), Mid-term driving experience (3-5 years), Late-term driving experience (5 years). These characteristics are then categorized, corresponding to 12 specific scenarios. An interval classification method is used to categorize the situations. P1 represents the stable driving behavior at an intersection under this scenario, taken as (0.9-1.0); P2 represents the non-stable driving behavior at an intersection under this scenario. For non-stable analysis, this invention does not consider braking behavior under abnormal conditions, so it is taken as (1.0-2.0).

[0096] The above methods were used to conduct factor analysis on vehicle, road, and environmental factors. For vehicle age c... 21 Violation C 22 Vehicles are categorized into high-performance vehicles (0-4 years old) and low-performance vehicles (5 years old). Traffic violations are assessed based on recent red-light running and speeding offenses, categorizing vehicles as prone to violations or not. Road surface conditions are also considered. 31 Marking clarity c 32 Road conditions are categorized by bumpiness level as smooth, moderately bumpy, and very bumpy. Road markings are categorized by clarity as clear and blurry. Environmental factors include obstruction of vision. 31 Weather c 32 Time c 33 Visibility obstruction is categorized into three types: unobstructed, moderately obstructed, and completely obstructed. Weather conditions are categorized into normal weather, rainy / snowy weather, and low visibility weather. Time is categorized into normal time and peak time.

[0097] Step (3): Calculate the conflict zone based on the intersection and the corrected speed V of the motor vehicles. j2 (km / h) and non-motorized vehicle speed V F (km / h) Calculate the probability of a collision.

[0098] The process of step (3) is as follows:

[0099] Step (3.1), in the conflict area, the conflict type is divided according to the direction of non-motorized vehicle collision: 1. Non-motorized vehicles approaching from the right, such as...Figure 3 、 4 as shown in Fig. 2, 2, non-motor vehicle left side of the car as shown in Figure 5 、 6 at the same time according to the lane of the vehicle driving is divided into: 1-1 non-motor vehicle right side of the car, motor vehicle driving in straight lane as shown in Figure 3 , 1-2 non-motor vehicle right side of the car, motor vehicle driving in straight left lane as shown in Figure 4 . 2-1 non-motor vehicle left side of the car, motor vehicle driving in straight lane as shown in Figure 5 , 2-2 non-motor vehicle left side of the car, motor vehicle driving in straight left lane as shown in Figure 6 .

[0100] In the establishment of conflict area, the conflict area is calculated by vehicle and road information, a certain intersection in Huai'an City Qingjiangpu District is used as an example, according to the actual measurement, the main road is a one-way double lane with a separation belt, the lane width is 3.5m, the rural branch road is a two-way four lane, the lane width is 3.0m, and the non-motor vehicle lane is not divided. According to the behavior selection mode of vehicles on the main road and the branch road at the intersection, the selection of motor vehicles is taken as the classification basis.

[0101] Step (3.2), the conflict area calculation model, through the conflict area as shown in Figures 3-6 , all the conflict areas are defined as square areas, and the conflict area calculation model is as follows:

[0102] S 冲 = {(X, Y) | X L <X<X R and Y B <Y<Y T}

[0103] Where S 冲 (m 2 ) represents the area of the conflict area, X L represents the left boundary line of the conflict area about the coordinate system, X R represents the right boundary line of the conflict area about the coordinate system, Y B represents the lower boundary line of the conflict area about the coordinate system, and Y represents the upper boundary line of the conflict area about the coordinate system.

[0104] For the first case, 1-1 non-motor vehicle right side of the car, motor vehicle driving in straight lane, when the non-motor vehicle right side of the car, there is Figure 3The conflict area is calculated. For the calculation of the conflict area, the maximum road edge is assumed as the conflict area edge for the assumed trajectory, and the straight line is assumed for the trajectory of the non-motor vehicle, so the trajectory is determined by the connection of the road marking nodes, and finally the area of the conflict area is calculated by combining the map and the actual measurement.

[0105] For the second case, the non-motor vehicle comes from the right side, and the motor vehicle travels in the straight lane, when the non-motor vehicle comes from the right side, there is a conflict area as shown in Figure 4 The conflict area is calculated by the above-mentioned conflict area calculation method.

[0106] For the third case, the non-motor vehicle comes from the left side, and the motor vehicle travels in the straight lane, when the non-motor vehicle comes from the left side, there is a conflict area as shown in Figure 5 The conflict area is calculated by the above-mentioned conflict area calculation method.

[0107] For the fourth case, the non-motor vehicle comes from the left side, and the motor vehicle travels in the straight lane, when the non-motor vehicle comes from the left side, there is a conflict area as shown in Figure 6

[0108] Step (3.3), after calculating the conflict area, the probability of conflict is determined by the final speed, the conflict area, and the two-dimensional area of the vehicle. The common vehicle type is used for the non-motor vehicle, with the length of 100 cm, 67 cm, and 50 cm, and the area of 0.67 m 2 , 0.67*1=0.67(m 2 ). The motor vehicle is divided into cars, 7-seater cars, small trucks, and semi-trailer vehicles, with the area of 10 m 2 , 15 m 2 , 18 m 2 , and 30 m 2 .

[0109] Step (3.4), the non-gate is used for the calculation of the conflict probability, and the coordinate system is established in the example intersection. The driving area of the vehicle is established, and the conflict area is square. The straight vehicle is recorded as a rectangular area perpendicular to the X axis, and the trajectory prediction function is used for the turning vehicle. Considering that the actual influence range of the vehicle accident is not the occupied area, the influence range of the vehicle is idealized and enlarged, and finally a circular area is used as the final influence range of the vehicle.

[0110] ​For the first non-motor vehicle right side to come, the motor vehicle driving in the straight lane driving conflict type as an example, the motor vehicle straight lane left side marking as Y axis, with the road marking direction as the Y axis positive direction; with the motor vehicle lane stop line as the X axis, with the right side of the vehicle driving direction as the positive direction of the X axis; the intersection of the two lines as the origin. Thus the conflict area calculation model is obtained:

[0111] S 冲 = {(X, Y) | 1 < X < 2 and 5 < Y < 7}

[0112] Wherein, S 冲 (m 2 ) represents the area of the conflict area, X, Y represents the conflict area boundary line (m) established in the manner of two-dimensional coordinate system modeling.

[0113] After establishing the conflict area, the motor vehicle and non-motor vehicle in the conflict area are collided to establish the model of the collision range. First, the motor vehicle driving collision range model is established.

[0114] The collision range of the motor vehicle driving is represented as a circle moving according to the set speed and trajectory, and the collision range of the non-motor vehicle is represented as a function coordinate point as the center of the circle, and the trajectory formula of the circular area is established.

[0115] S 机 = {(X, Y) | (X-2) 2 +(Y+35-V j2 t) 2 = 3.5 2}

[0116] S 非 = {(X, Y) | (X-X 非 ) 2 +(Y+aX 非 +b) 2 = 0.75 2}

[0117] S 机 (m 2 ) represents the collision range of the motor vehicle, S 非 (unit: m 2 ) represents the collision range of the motor vehicle.

[0118] After obtaining the collision range of the motor vehicle and the non-motor vehicle, the motion trajectory of the motor vehicle and the non-motor vehicle is determined. The driving trajectory of the motor vehicle is straight line driving; and the driving trajectory of the non-motor vehicle is a linear function, represented as y=kx+b.

[0119] In the process of obtaining the trajectory of the non-motor vehicle, the trajectory is obtained as a function of the coordinate system when the non-motor vehicle starts to pass through the intersection, denoted as X0, Y0, which is the initial position point coordinate of the motor vehicle. Since only the speed of the non-motor vehicle is known, the ratio of the trigonometric function is established to reflect the coordinates of the non-motor vehicle. The x-axis coordinate changing with time is obtained by using the ratio method for the trajectory of the non-motor vehicle:

[0120]

[0121] wherein x represents the x-axis coordinate value of the collision area center point of the non-motor vehicle relative to the coordinate system;

[0122] Similarly, the y-axis coordinate value of the collision area center point of the non-motor vehicle relative to the coordinate system is obtained:

[0123]

[0124] After modeling the conflict area S 冲 , the collision range S 机 of the motor vehicle, and the collision range S 非 of the non-motor vehicle, wherein S 机 represents the area movement of the motor vehicle according to the movement trajectory, and S 非 represents the area movement of the non-motor vehicle according to the movement trajectory. In the determination process, it is determined whether the collision range S 冲 of the non-motor vehicle and the collision range S 非 of the motor vehicle will overlap at the same time in the conflict area S 机 . If there is an overlap, it is determined that there is a driving conflict of the vehicles in this workflow, and if there is no overlap, it is determined that there is no driving conflict of the vehicles. The above determination process is defined as a conflict probability determination model, as follows:

[0125]

[0126] In step (4), the vehicle speed of the motor vehicle and the non-motor vehicle is reviewed. When the conflict probability occurs, the non-motor vehicle is preferentially warned and signal light controlled. When the vehicle information is reviewed and it is found that the number of motor vehicles in the current traffic flow is too large, the non-motor vehicle is signal controlled, and the video information is reviewed again. If the number of motor vehicles in the traffic flow is too large, the lane where the motor vehicle is located is signal controlled. Considering that different intersections have different signal light periods, the following is used:

[0127]

[0128] wherein M represents the number of lanes, N represents the road capacity, and t tong represents the vehicle passing time.

[0129] When different conflict results occur, different warning methods are adopted. First, after the conflict occurs, the non-motor vehicle is given priority for warning, and the specific warning device is as shown in the figure Figure 8 When the warning device of the non-motor vehicle is working, the time length of the non-motor vehicle warning is defined by the vehicle passing time at the intersection. After one warning period ends, the information collection device of the motor vehicle is revisited again, and the intersection of the non-motor vehicle and the motor vehicle is periodically given a signal light warning when the vehicle appears again.

[0130] The urban and suburban intersection warning system in the application is composed of an intelligent language warning component, an intelligent voice warning control module, an intelligent LED warning component, an LED display screen control module, a red and blue flashing light warning component, a red and blue flashing light control module, a video monitoring component, a video monitoring control module, a fastening device, and a solar cell panel.

[0131] The application adopts a combination of voice reminders and light flashing reminders to adopt different reminding methods for warning under different conditions. For example, in the first condition, the non-motor vehicle comes from the right side, and the motor vehicle only travels in the straight lane. When the non-motor vehicle comes from the right side, there is a conflict area as shown in the figure Figure 2 At this time, the warning device gives a voice alarm to the non-motor vehicle and reminds the non-motor vehicle to pay attention to the vehicle in the straight lane. At the same time, the warning device gives a warning light to remind the driver to be careful when driving. When the light alarm is adopted, the non-motor vehicle owner can pay attention to the reminder of the warning device in a noisy environment, so as to avoid the occurrence of an accident caused by a reminder dead angle of a single warning.

[0132] In a special condition, a threshold time for the non-motor vehicle to pass is set to avoid the situation that the non-motor vehicle waits for a long time when the motor vehicle passes all the time in the first condition during the rush hour. The threshold time is set for the non-motor vehicle to pass the road. When the waiting time of the non-motor vehicle reaches the threshold, the warning system turns on the red light flashing prohibition sign for the motor vehicle. The non-motor vehicle has the characteristics of small size and strong mobility, so the waiting time of the motor vehicle is reduced.

[0133] In step (5), after the single warning work is completed, the existence information of the motor vehicle on the road is collected through the motor vehicle speed measurement device, and the number of motor vehicles on the road at this time is recorded as g. At the same time, the non-motor vehicle continues to be given a cyclic warning. In the cyclic warning process, the warning time of the non-motor vehicle is set to a threshold, a maximum time limit value is set, and a non-motor vehicle waiting threshold model is established according to the actual intersection parameters (intersection length L lu ), the number of road motor vehicles g, the safety distance L an , and the motor vehicle speed v jj . The non-motor vehicle waiting threshold model is as follows:

[0134]

[0135] safe vehicle distance L an Take 15m, vehicle number g, vehicle speed v jj , L lu Indicates the length of the intersection, T yue Indicates the waiting threshold.

[0136] When the waiting time of the non-motor vehicle exceeds the set threshold, the non-motor vehicle is warned, and the warning time is calculated according to the above formula.

[0137] The present application predicts and analyzes the situation at the intersection in the embodiment.

[0138] The implementation case is as follows: in the road as Figure 8 , a 45-year-old male driver with 5 years of driving experience and 4 years of vehicle driving, no recent red light running and speeding behavior, clear road markings, good road conditions, non-exceptional weather, and non-peak driving time, with slight visual obstruction. And drive at a speed of 50km / h in the initial measurement, there is a motor vehicle in the branch road driving to the intersection at a speed of 30km / h. And according to the actual detection situation feedback, the motor vehicle is located on the straight road and is a non-motor vehicle on the right side, which belongs to the first type of conflict. The specific situation under this kind of situation is established as Figure 8 .

[0139] The speed of the motor vehicle is measured, and the initial measurement speed is recorded as V j1 (km / h), and the motor vehicle speed is set to 50km / h in this embodiment. Then record the initial position of the motor vehicle, the initial position of the motor vehicle coincides with the position of the speed measuring device, so the initial position of the motor vehicle is 42m away.

[0140] Secondly, the correction factor of the vehicle speed is determined, and the corresponding factors of the person X1, the vehicle X2, the road X3, and the environment X4 are set as 45-year-old male driver, 5 years of driving experience, 4 years of vehicle driving, no recent red light running and speeding behavior, clear road markings, good road conditions, non-exceptional weather, and non-peak driving time, with slight visual obstruction.

[0141] Step (1), speed acquisition: drive at a speed of 50km / h in the initial measurement, there is a motor vehicle in the branch road driving to the intersection at a speed of 30km / h, measure the speed of the non-motor vehicle, and record the measured speed as V F , the non-motor vehicle does not consider the correction and change factors of the speed and directly uses the measured speed V F , and finally uses the non-motor vehicle speed of 30km / h.

[0142] Step (2), speed correction: the establishment of vehicle speed influence factor model to achieve the final speed acquisition, the coefficient interval a of different factors ji , the final correction speed calculation formula is:

[0143]

[0144] The final corrected data of the specific vehicle is 53 km / h.

[0145] Step (3), establish conflict area model: take the first non-motor vehicle left side to come, motor vehicle driving in straight left lane conflict type as an example, the left side of the motor vehicle straight lane marking as Y axis, with the road marking direction as the positive direction; With the vehicle stop line as the X axis, with the right side of the vehicle driving direction as the positive direction of the X axis; The intersection of the two lines as the origin. Thus, the conflict area in this case is represented as:

[0146] S 冲 = {(X, Y) | 1 < X < 2 and 5 < Y < 7}.

[0147] The moving motor vehicle is represented as a circle according to the set speed and trajectory,

[0148] S 机 = {(X, Y) | (X-2) 2 +(Y+35-V j2 t) 2 = 3.5 2}

[0149] The moving trajectory of the non-motor vehicle adopts a function as the center of the circle, and the trajectory formula of the circular area is established

[0150] S 非 = {(X, Y) | (X-X 非 ) 2 +(Y+aX 非 +b) 2 = 0.75 2}

[0151] The moving trajectory of the non-motor vehicle is a linear function y=kx+b, according to the coordinate system, when it starts to pass through the intersection, the trajectory is a linear function, which is denoted as X0, Y0. Since only the speed of the non-motor vehicle is considered, the ratio relationship of the trigonometric function is established to reflect the coordinates of the non-motor vehicle. First, the is the hypotenuse of the triangle formed by the intersection with the x-axis and the y-axis, and the ratio method is used to obtain the x-axis coordinate changing with time:

[0152]

[0153] Similarly, the coordinates of the y-axis are obtained as:

[0154]

[0155] After all the coordinates are arranged, the formula is obtained as:

[0156]

[0157] The vehicle speed 53km / h and the non-motor vehicle speed 30km / h are brought into the above formula. It is calculated that the driver is a 45-year-old male with a driving age of 5 years, the vehicle has been driven for 4 years, no red light running and speeding behaviors have occurred recently, the road marking is clear, the road surface condition is good, the environment is non-abnormal weather, the driving time is non-peak period, and there is slight visual obstruction. When driving at a speed of 50km / h for the first time, a motor vehicle enters the intersection at a speed of 30km / h in the branch road, and the non-motor vehicle and the motor vehicle will collide, so a warning is given, and the warning period is calculated.

[0158] Step (4), the warning period is calculated: since the non-motor vehicle is warned, the speed is 30km / h and the model is used Finally, the time length is 36.66 seconds.

[0159] Step (5), the existence of vehicles on the motor vehicle lane is detected, and in this embodiment, no motor vehicle continues to travel in the lane, so the work flow is ended.

[0160] In the embodiment of the present application, the final result is calculated according to the specific embodiment: the driver is a 45-year-old male with a driving age of 5 years, the vehicle has been driven for 4 years, no red light running and speeding behaviors have occurred recently, the road marking is generally clear, the road surface condition is good, the environment is non-abnormal weather, the driving time is non-peak period, and there is slight visual obstruction. When driving at a speed of 50km / h for the first time, a motor vehicle enters the intersection at a speed of 30km / h in the branch road, and the non-motor vehicle and the motor vehicle will collide, and the non-motor vehicle is warned, the warning time is 36.66 seconds, and since no motor vehicle is found after the warning time is ended, the warning work is ended.

Claims

1. A warning method for traffic lightless intersections in suburban areas, characterized in that: Includes the following steps: (1) Measure the initial speeds of the motor vehicle and the non-motor vehicle; denot the initial speed of the motor vehicle as V. j1 The initial speed of a non-motorized vehicle is denoted as V. F ; (2) Data on people, vehicles, roads, and the environment are digitized to establish a model of factors affecting vehicle speed. This model is used to analyze the vehicle speed V obtained in step (1). j1 The corrected velocity is denoted as V. j2 The model for factors affecting vehicle speed is as follows: a ij c represents the coefficient range of different factors. ij V represents the degree of influence of each factor affecting vehicle speed. j2 This indicates the speed of the motor vehicle after correction by the vehicle speed influencing factor model; (3) Calculate the conflict zone based on the intersection and the corrected speed V of the motor vehicles. j2 Speed ​​V of non-motorized vehicles F The probability of a conflict is calculated as follows: (3.1) The area of ​​the conflict area is obtained by using the conflict area calculation model. The assumed trajectory is taken as the boundary of the conflict area with the largest road edge. At the same time, the driving trajectory of non-motorized vehicles is assumed. The trajectory is determined by connecting the road marking nodes. The area of ​​the conflict area is obtained by combining the map and the conflict area calculation model. (3.2) Speed ​​V after correction by motor vehicle j2 Speed ​​V of non-motorized vehicles F The probability of a conflict is determined by the conflict zone area and vehicle area. The process is as follows: A coordinate system is established at the intersection. For vehicles going straight, the area of ​​the rectangle perpendicular to the X-axis is recorded. For turning vehicles, a linear function is used for trajectory prediction. A conflict zone calculation model is employed. S 冲 = {(X,Y)|X L <X<X R and Y B <Y<Y T} S 冲 X represents the area of ​​the conflict zone. L X represents the left boundary line of the conflict zone. R Y represents the right boundary line of the conflict zone. B Y represents the lower boundary line of the conflict zone. T Indicates the upper boundary line of the conflict zone; The collision range S of the motor vehicle is determined. 机 : S 机 ={(X,Y)|(X-X VS +V j2X t) 2 +(Y-Y VS +V j2Y t) 2 =3.5 2 } S 机 X indicates the collision range of a motor vehicle. VS The x-coordinate, Y-coordinate, represents the initial position of the vehicle coordinate system. VS V represents the ordinate of the initial position for establishing the vehicle coordinate system. j2X V represents the velocity of a motor vehicle about the X-axis. j2Y The velocity of the vehicle is expressed about the Y-axis, and t represents the time since the vehicle entered its initial position. S 非 ={(X,Y)|(X-X FS +V FX t 非 ) 2 +(Y-Y FS +V FY t 非 ) 2 =3.5 2 } S 非 Indicates the collision range of non-motorized vehicles, X FS The x-coordinate, Y-coordinate, represents the initial position of the non-motorized vehicle coordinate system. FS V represents the x and y coordinates of the initial position for establishing the non-motorized vehicle coordinate system. FX V represents the speed of the non-motorized vehicle along the X-axis. FY The velocity t represents the speed of the non-motorized vehicle in the Y-axis direction. 非 This indicates the time elapsed since the non-motorized vehicle entered the initial position; The velocity V of the motor vehicle or non-motor vehicle on the X and Y axes is obtained. NM : Among them, V NM Represents the speed of a motor vehicle or non-motor vehicle along the X and Y axes. Functions representing the speeds of motor vehicles or non-motor vehicles on the X and Y axes with respect to the trajectory model of the motor vehicle or non-motor vehicle; (3.3) Establish the collision range of the motor vehicle: S 机 ={(X,Y)|(X-2) 2 +(Y+35-V j2 t) 2 =3.5 2 } Establish the collision range for non-motorized vehicles: S 非 ={(X,Y)|(X-X 非 ) 2 +(Y+aX 非 +b) 2 =0.75 2 } S 机 S indicates the collision range of a motor vehicle. 非 Indicates the collision range of the non-motorized vehicle; 'a' represents the parameter of the trajectory equation; X 非 b represents the x-coordinate of the motor vehicle's location; b represents the trajectory parameters of the non-motorized vehicle. The trajectory of the motor vehicle is a straight line, while the trajectory of the non-motorized vehicle is a linear function: y = kx + b. Let X0 be the initial X-coordinate of the motor vehicle's position and Y0 be the initial Y-coordinate of the motor vehicle's position. We then obtain: Where x represents the x-axis coordinate of the center point of the collision area of ​​the non-motorized vehicle; V 非 represents the speed of the non-motorized vehicle, t represents the time calculated from the initial point, and b and k represent the trajectory parameters of the non-motorized vehicle. Where y represents the Y-axis coordinate of the center point of the collision area of ​​the non-motorized vehicle; V 非 represents the speed of the non-motorized vehicle, t represents the time calculated from the initial point, and b and k represent the trajectory parameters of the non-motorized vehicle. (3.4) The conflict probability determination model is derived as follows: Where P=1 indicates that a vehicle driving conflict occurs, and P=0 indicates that no vehicle driving conflict occurs; (4) Determine the warning result based on the calculation results of the conflict probability determination model; (4.1) If the traffic flow exceeds a preset threshold, signal control is applied to the lane where the vehicles are located to obtain the traffic light cycle T. 周 : Where M represents the number of lanes, N represents the road capacity, and t tong Indicates the time taken for non-motorized vehicles to pass; (4.2) When motor vehicles reappear on the main road, periodic traffic light warnings shall be issued at the intersection of non-motorized vehicles and motorized vehicles; (5) After a single warning, the warning results for motor vehicles and non-motor vehicles are reassessed, and a waiting threshold model for non-motor vehicles is established: Among them, L an Represents the safe distance between vehicles, g represents the number of vehicles, and v jj L represents vehicle speed. lu T represents the length of the intersection. yue The waiting threshold for non-motorized vehicles; When the waiting time of non-motorized vehicles exceeds the set threshold, a warning will be issued to the non-motorized vehicles.

2. The warning method for traffic lightless intersections in suburban areas according to claim 1, characterized in that: In step (1), the initial speeds of motor vehicles and non-motor vehicles are measured by the speed measuring device.

3. The warning method for traffic lightless intersections in suburban areas according to claim 1, characterized in that: In step (2), the human factor includes age c 11 Gender c 12 Driving experience (c) 13 Vehicle factors include: vehicle age (c) 21 Violation C 22 Road factors include road surface conditions (c) 31 Marking clarity c 32 Environmental factors include obstructed views. 31 Weather c 32 Time c 33 .

4. The warning method for traffic lightless intersections in suburban areas according to claim 1, characterized in that: In step (3.1), the types of conflicts that occur in the conflict area are divided into non-motorized vehicles coming from the right and traveling in the straight lane or the straight-to-left-turn lane; And non-motorized vehicles coming from the left and traveling in the straight lane or the straight-to-left-turn lane.

5. The warning method for traffic lightless intersections in suburban areas according to claim 1, characterized in that: In step (3.2), the conflict area is defined as a square area.

6. The warning method for traffic lightless intersections in suburban areas according to claim 1, characterized in that: In step (3.2), the area of ​​influence of the vehicle is defined as a circular region.

7. The warning method for traffic lightless intersections in suburban areas according to claim 1, characterized in that: In step (3.2), the trajectory models of motor vehicles and non-motor vehicles are defined as functions: y = f(x) Where y represents the ordinate of the trajectory model of motor vehicles and non-motor vehicles, x represents the ordinate of the trajectory model of motor vehicles and non-motor vehicles, and f(x) represents the function of the trajectory model of motor vehicles and non-motor vehicles.

8. The warning method for traffic lightless intersections in suburban areas according to claim 1, characterized in that: In step (3.3), the ratio of trigonometric functions under the same scale is established to obtain the coordinates of the non-motorized vehicle.

9. The warning method for traffic lightless intersections in suburban areas according to claim 1, characterized in that: In step (5), the non-motorized vehicle passage time is calculated and a threshold is set for the warning time of non-motorized vehicles in the cyclical warning of non-motorized vehicles; a non-motorized vehicle waiting threshold model is established based on the speed of motor vehicles, actual intersection parameters, number of following vehicles, and safe distance factors.

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