CN106896393B - Vehicle cooperative type object positioning optimization method and vehicle cooperative positioning device - Google Patents

Abstract

The present invention discloses a vehicle cooperative object positioning optimization method and a vehicle cooperative positioning device, the method comprising: receiving an information packet from a vehicle, the information packet comprising a vehicle original coordinate and at least one object original coordinate provided by a neighboring vehicle, and the accuracy of their respective positioning; performing time delay compensation on the vehicle original coordinate and the object original coordinate to obtain a vehicle coordinate and an object coordinate after compensation by the neighboring vehicle respectively; executing an optimization program to optimize the coordinates of the vehicle and the object respectively to obtain the vehicle optimized coordinate and the object optimized coordinate respectively; thereby, the vehicle optimized coordinate and the object optimized coordinate have higher accuracy than the coordinate information measured by a GPS receiver, so that the vehicle can more accurately judge the distribution of surrounding objects and improve driving safety.

Description

Vehicle cooperative object localization optimization method and vehicle cooperative localization device

technical field

The present invention is an object positioning method, in particular to a cooperative object positioning (Cooperativepositioning) optimization method.

Background technique

The related technology of disposing sensors in vehicles to detect the surrounding environment has been developed for a long time. Provide a variety of environmental information. However, for the vehicle itself, the environmental information obtained by the environmental information sensor is still limited by many factors. For example, please refer to Figure 9. The first vehicle 101 can know the environmental information in this direction, for example, it can see that there are objects 200 (such as pedestrians, vehicles, animals) rushing out of the intersection, but for the second vehicle 102 in the lateral lane, due to limited A blind spot may be generated at its location due to the surrounding buildings, and even if the second vehicle 102 has a sensor, it is still unable to detect the sudden situation of the object 200 and collide with it. Therefore, if the environmental information is only provided by the sensors of the vehicle itself, there are still blind spots in practical applications.

To this end, a vehicle cooperative positioning method has been developed. The concept of cooperative is to share the respective sensing devices (such as road side sensing units (RSU)) with neighboring vehicles or surrounding sensing devices. , so that the vehicle can receive information from other vehicles to expand its sensing range. Following the example in FIG. 9 , if the second vehicle 102 can receive the information provided by the first vehicle, it can know its right There will be objects suddenly appearing at the intersection, and there will be enough time for emergency response.

However, the current cooperative positioning technology faces the technical disadvantage of poor accuracy. Please refer to the example shown in FIG. 10 . The first vehicle 101 represents the own vehicle, and the second vehicle 102 to the fourth vehicle 104 represent other nearby vehicles. For the second vehicle 102, it is equipped with a commercial GPS and a camera. Generally, the positioning error of commercial GPS is about 5-15 meters, and the positioning error of the camera is about 5 meters. Therefore, the second vehicle 102 uses The own position measured by the own GPS has a GPS error range A1, and when the second vehicle 102 uses the camera to sense the position of the third vehicle 103, the position of the third vehicle 103 measured by the camera has a camera error range A2 Therefore, if the second vehicle 102 transmits and shares the position information of the third vehicle sensed by the second vehicle 102 to the first vehicle 101, the position information of the third vehicle 103 received by the first vehicle 101 has accumulated errors. problem, as shown in GPS and camera cumulative error range A3.

Furthermore, if the first vehicle 101 transmits and shares the position information of the third vehicle 103 to the fourth vehicle 104 twice, the position error of the first vehicle 101 itself will be further added, resulting in the fourth vehicle 101 . The position information received by the vehicle 104 produces a greater amount of accumulated error. Therefore, when the information is transmitted and shared for many times, the positioning accuracy of the object will be significantly reduced, and it will even have no reference value.

SUMMARY OF THE INVENTION

In view of the problem of poor position information accuracy in the existing cooperative positioning technology, the main purpose of the present invention is to provide a vehicle cooperative object positioning optimization method, so as to increase the sense range of the vehicle and improve the accuracy of the position information. Improve vehicle driving safety.

In order to achieve the aforementioned object, the method of the present invention is implemented by using a co-location device arranged inside the vehicle, and the method includes:

An information packet is received by the vehicle, the information packet includes the original coordinates of the vehicle and the original coordinates of at least one object provided by a neighboring vehicle, and the original coordinates of the vehicle and the original coordinates of the object have respective positioning accuracy;

Perform time delay compensation on the original coordinates of the vehicle and the original coordinates of the object, so as to obtain a vehicle coordinate and an object coordinate after the compensation of the adjacent vehicle;

Execute an optimizer that includes:

Compare the positioning accuracy, compare the vehicle coordinates of the vehicle with the vehicle coordinates of the adjacent car, and determine which has higher positioning accuracy;

An optimization operation is first performed on vehicle coordinates with higher accuracy, and then an optimization operation is performed on vehicle coordinates with lower positioning accuracy, wherein the optimization operation executes:

a) Calculate a plurality of reference positions according to the vehicle coordinates of the own vehicle and the vehicle coordinates of the adjacent vehicle; and

b) According to the weight value of each reference position, calculate the optimized coordinates of a vehicle and the optimized coordinates of a neighboring vehicle respectively;

Optimizing the object coordinates is to compare the difference between the original vehicle coordinates of the adjacent car and the optimized coordinates of the adjacent car, and compensate the object coordinates provided by the adjacent car according to the difference to obtain the optimized coordinates of an object; and compare the own vehicle. The difference between the original vehicle coordinates of the vehicle and the vehicle-optimized coordinates of the vehicle, and the object coordinates provided by the vehicle are compensated according to the difference to obtain an object-optimized coordinate.

By means of the positioning optimization method of the present invention, the optimized vehicle coordinates and object coordinates of the own vehicle and adjacent vehicles can be obtained, and the optimized coordinates can be closer to the actual location, which is helpful for accurately judging objects in the surrounding environment during driving. , vehicle distribution status, improve the safety of vehicle driving.

Description of drawings

FIG. 1 is a block diagram of the structure of the co-location device of the present invention.

Fig. 2 is a flow chart of the vehicle cooperative object localization optimization method of the present invention.

FIG. 3 is a schematic diagram of the BSM information packet format of the present invention.

FIG. 4 is a schematic diagram of the present invention performing time delay compensation on the home position of the vehicle.

FIG. 5 is a flow chart of the optimization procedure executed by the location optimization module of the present invention.

FIG. 6A is a schematic diagram of obtaining the first reference position H1 according to the present invention.

FIG. 6B is a schematic diagram of obtaining the first reference position H2 according to the present invention.

FIG. 6C is a schematic diagram of obtaining the first reference position H3 according to the present invention.

FIG. 6D is a schematic diagram of obtaining the first reference position H4 according to the present invention.

FIG. 7 is a schematic diagram of calculating vehicle optimal coordinates by using multiple reference positions in the present invention.

FIG. 8 is a schematic diagram of information sharing among multiple vehicles in the present invention.

FIG. 9 is a schematic diagram of a vehicle passing through an intersection.

FIG. 10 is a schematic diagram of error accumulation of protocol positioning.

Among them, reference numerals:

10 Vehicle co-location device

11 Wireless transmission interface

12 Delay correction module

13 Position Optimization Module

14 Positioning comparison module

15 Body Sensor

21 Part 1

22 Part II

101 First vehicle

102 Second vehicle

103 Third vehicle

104 Fourth vehicle

200 objects

A1 GPS error range

A2 Camera Error Range

A3 GPS and camera cumulative error range

H This car

R Neighboring car

H1～H4 The first reference position to the fourth reference position

R1 reference position

M1～M4 The first coverage area to the fourth coverage area

Detailed ways

Please refer to FIG. 1 , the present invention utilizes a body sensor 15 equipped on each vehicle, including a GPS receiver and other various sensors, such as radar, cameras and other equipment to obtain the coordinates of the vehicle and environmental information around the vehicle , and transmits and shares the coordinates and environment information of the vehicle to the surrounding vehicles through wireless communication technology. Therefore, for any vehicle, it is a two-way wireless communication for receiving and transmitting with surrounding vehicles.

In the present invention, a vehicle co-location device 10 is provided inside the vehicle, and the vehicle co-location device 10 includes a wireless transmission interface 11 , a delay correction module 12 , a position optimization module 13 and a positioning comparison module 14 . The vehicle cooperative positioning device 10 executes a vehicle cooperative object positioning optimization method, which is shown in FIG. 2 and includes the following steps:

S10: Receive an information packet, the information packet includes the original coordinates of a vehicle and the original coordinates of at least one object of the adjacent vehicle, and the respective positioning accuracy of the original coordinates of the vehicle and the original coordinates of the object;

S20: Perform time delay compensation on the original coordinates of the vehicle and the original coordinates of the object, so as to obtain the coordinates of a vehicle and the coordinates of an object after compensation of the adjacent vehicle;

S30: Execute an optimization program;

S40: Coordinate alignment fusion.

In step S10: the wireless transmission interface 11 is responsible for bidirectional data transmission between the vehicle and the adjacent vehicle. In this embodiment, a short-range wireless communication interface (DSRC) is used to periodically send and receive information packets between vehicles. The information packet format is a basic safety message (Basic Safety Message, BSM) packet. Please refer to Figure 3. The information format of the information packet generally includes a msgID field, a first part 21 (Part I) and a second part 22 (Part 2). II), in which the first part 21 is defined as the necessary information, including the basic security information content, which is a part that each information packet must contain, but the second part 22 is an optional part, which can be selected by the user according to the application requirements. The required information is included in the second part 22, which is within the scope of self-definition.

In the first part 21 of the BSM information packet, there must be latitude and longitude information of the vehicle, that is, the original coordinates of the vehicle, indicating the position of the vehicle measured by the GPS receiver in the vehicle.

In the second part 22 of the BSM information packet, the present invention adds two types of information, the first type of information is the sensor type (eg RTK, GPS) that outputs the original coordinates of the vehicle and the positioning accuracy of the sensor. The second type of information includes the original coordinates of the object, the type of the sensor that generated the original coordinates of the object, or further includes the accuracy of the sensor. The original coordinates of the object refer to the use of other sensors of the vehicle ( Such as radar, lidar, camera, etc.) to sense the information of other objects other than the vehicle, which may be vehicles, pedestrians, moving objects or fixed objects. Each vehicle can send its own vehicle's original coordinates and object's original coordinates to the outside for the use of neighboring vehicles; and its own vehicle can also receive the vehicle's original coordinates and object's original coordinates provided by neighboring vehicles.

In step S20: the delay correction module 12 receives the BSM information packet transmitted by the adjacent vehicle through the wireless transmission interface 11, and obtains the original vehicle coordinates and the original coordinates of the object of the adjacent vehicle. In addition, the position optimization module 13 further receives the host vehicle. Various sensing results provided by the sensor, such as vehicle coordinates (GPS), object coordinates. The delay correction module 12 performs time delay compensation on the original coordinates of the vehicle and the original coordinates of the object provided by the adjacent vehicle. Please refer to FIG. 4 , a first vehicle 101 represents the own vehicle, and a second vehicle 102 near it represents the adjacent vehicle , when the first vehicle 101 receives the information packet sent by the second vehicle 102, the first vehicle 101 can calculate the A time delay amount n between the packet sending time and the packet receiving time. Because the second vehicle 102 continues to drive from the original position P _A to the position P _B after sending the packet, the original coordinates of the second vehicle 102 received by the first vehicle 101 only represent the original position P _A , and the delay correction module 12. Calculate a compensation distance moved by the second vehicle 102 according to the time delay amount n, add the compensation distance to obtain the real-time position P _B , and the calculation formula can be expressed as follows:

P _B =P _A +V×n, where V represents the vehicle speed of the second vehicle 102 .

When the delay correction module 12 calculates the real-time position P _B of the second vehicle 102 , the compensation distance can be added to the original coordinates of the object provided by the second vehicle 102 according to the compensation distance of the two positions PA and _{P B .} After the original coordinates of the vehicle and the original coordinates of the object have undergone time compensation, a vehicle coordinate and an object coordinate are obtained respectively, and are provided to the position optimization module 13 for subsequent processing.

In step S30: the position optimization module 13 receives the time-compensated vehicle coordinates and object coordinates of the adjacent vehicle, and receives the vehicle coordinates of the vehicle and the object coordinates measured by the sensor of the vehicle, and executes an optimization program As shown in Figure 5, the optimization program includes the following processes S31 to S33:

S31: Comparing the positioning accuracy is to compare the vehicle coordinates of the own vehicle and the vehicle coordinates of the adjacent vehicle, and determine which has higher accuracy. For example, if the vehicle coordinates of the own vehicle are obtained by a real-time kinematic measurement (RTK) device, and the vehicle coordinates of the neighboring vehicle are received by a general GPS receiver, it can be judged that the coordinates provided by RTK are highly accurate. Another example is that both the own vehicle and the adjacent vehicle use the same level of GPS receiver to provide coordinates, then you can judge which has higher accuracy according to the degree of trust in the two GPS signals, for example, according to the GGA information contained in the GPS signal to judge the two Which GPS signal is more reliable.

S32: Vehicle positioning optimization. After judging which vehicle coordinates of the vehicle and the adjacent vehicle have higher accuracy, the optimization operation will be performed first for the vehicle with higher accuracy, followed by the optimization operation for the vehicle with lower accuracy. Whether it is to optimize the location information of the own vehicle or the adjacent vehicle, the method is as follows:

a) Calculate multiple reference positions according to the vehicle coordinates of the vehicle and adjacent vehicles;

b) According to the weight value of each reference position, calculate the optimized coordinates of one vehicle and the optimized coordinates of a neighboring vehicle respectively.

In this embodiment, it is assumed that both the own vehicle and the adjacent vehicle are equipped with GPS receivers and other sensors, and the vehicle optimal coordinates are calculated according to the four reference positions, and when the vehicle coordinates of the own vehicle H and the adjacent vehicle are determined After the coordinates are obtained, it is known that the vehicle coordinates of the own vehicle H have high accuracy, so the vehicle coordinates of the own vehicle are prioritized to be optimized with the own vehicle H as the center, and the steps are described in detail below. First, please refer to FIG. 6A , the own vehicle and the adjacent vehicle are represented by H and R respectively, and the two vehicles can know their own vehicle coordinates according to their own GPS receivers, wherein the own vehicle H is based on the vehicle obtained by the GPS receiver. The coordinates are used as the first reference position H1. The difference between the first reference position H1 and the actual position of the vehicle H is due to the error of the GPS receiver. The vehicle coordinates sensed by the GPS receiver of the adjacent vehicle R are used as a reference position. R1.

Please refer to FIG. 6B , because the sensor of the adjacent vehicle R can sense the existence of the own vehicle H, it can know the relative distance D1 and the relative angle θ1 between the adjacent vehicle R and the own vehicle H, that is, the current vehicle H can be known. Relative coordinates of car H. The adjacent vehicle R takes its own reference position R1 as a reference, and converts the relative coordinates of the vehicle H into a latitude and longitude coordinate according to the distance D1 and the angle θ1, and the latitude and longitude coordinates serve as the second reference position H2. The information packet sent by the neighboring vehicle R includes the latitude and longitude coordinates of the second reference position H2.

Referring to FIG. 6C , since the sensor of the own vehicle H can sense the existence of the adjacent vehicle R, it can know the relative distance D2 and the relative angle θ2 between the own vehicle H and the adjacent vehicle R. After obtaining the relative distance D2 and relative angle θ2 between the host vehicle H and the neighboring vehicle R, the latitude and longitude coordinates of the host vehicle H are reversely derived using the reference position R1 of the neighboring vehicle R as a reference to obtain a third reference position H3.

Referring to FIG. 6D , information packets are transmitted between the neighboring vehicle R and the own vehicle H by wireless signals. Therefore, the relative distance D3 between the two vehicles can be estimated according to the strength attenuation between the wireless signal transmission and reception. For example, the power of the wireless signal transmitted by the neighboring car R is preset to -10dBi, while the power of the wireless signal received by the own car H has become -30dBi, which means that the distance between the two cars reduces the wireless signal by 20dBi, because the attenuation amplitude is different from The distance is proportional to the distance and an attenuation relation table can be established in advance, so the relative distance D3 between the two vehicles can be obtained by inferring or looking up the table according to the attenuation of 20dBi. On the other hand, because the vehicle coordinates measured by the GPS receiver of the own vehicle H and the adjacent vehicle R are known, that is, the first reference position H1 and the reference position R1 are both known, and the straight extension between the two positions can be used. The line infers the direction of the host vehicle H relative to the adjacent vehicle R. Therefore, a fourth reference position H4 is calculated according to the relative distance D3 and the direction based on the reference position R1 of the adjacent vehicle R as a reference.

Please refer to FIG. 7 , after obtaining the first reference position H1 to the fourth reference position H4, taking each reference position H1 to H4 as the center of the circle is equivalent to determining the first coverage range M1 to the fourth coverage range M4, each coverage range The size of the reference position is determined by the accuracy of the source sensor of its reference position. Assuming that the GPS receiver of the vehicle H has the best accuracy, the coverage of the first reference position H1 is the smallest, and the one with the higher accuracy , the reference position will also have a higher weight value ω, where the GPS receiver will provide its own accuracy. If other sensors cannot provide their own accuracy, the weight value can be determined according to the inferred position of the sensor and its distance. The farther the distance, the lower the weight. In the present invention, a vehicle optimization coordinate H(x, y) is calculated in the intersection area (as indicated by the oblique line area) of the first coverage range M1 to the fourth coverage range M4.

In step b), according to the weight value ω of each reference position, a vehicle optimized coordinate H(x, y) is calculated, and the calculation method can be expressed as follows:

其中，

in,

In the above formula, m represents the number of reference positions, so m=4 in this embodiment; (x _i , y _i ) represent the coordinates of the first to fourth reference positions H1 to H4 respectively; one of the weight values ω _i This calculation method can use the Adaboost algorithm or other algorithms.

In addition to the Adaboost algorithm, here is a way to calculate the weight value. First, assuming that the error values of the first reference position H1 to the fourth reference position H4 are 3, 6, 4, and 5 meters respectively, an inverse error algorithm can be used to calculate four different weight values. The calculation method is as follows:

Calculate the total error amount, ∑ _i ε _i =3+4+5+6=18

Calculate the difference between the total error and each error value respectively,

Calculate the total amount of variance,

The four weight values are:

其中(x_i,y_i)分别表示四个参考位置的坐标；H(x,y)代表车辆优化坐标。Vehicle-optimized coordinates of host vehicle H

Among them, (x _i , y _i ) respectively represent the coordinates of the four reference positions; H(x, y) represent the vehicle optimization coordinates.

After the optimization of the vehicle coordinates of the own vehicle H is completed, the next step is to optimize the vehicle coordinates of the adjacent vehicle R with the adjacent vehicle R as the center. The role, in other words, regards the adjacent car data as the own car data in the above calculation, and regards the own car data as the adjacent car data in the above calculation. Therefore, the optimal coordinates R(x, y) of the adjacent vehicle representing the adjacent vehicle can also be obtained.

S33 : object positioning optimization, that is, optimizing the object coordinates measured by the sensors of the adjacent vehicle R and the own vehicle H. In the part of the own vehicle H, since the optimized vehicle coordinates H(x, y) of the own vehicle H are known, the original vehicle coordinates of the own vehicle H can be compared according to the object coordinates measured by the own vehicle H sensor. and the difference between the vehicle's optimized coordinates H(x, y), when calculating the object's optimized coordinates of the object measured by the vehicle's H sensor, the difference between the vehicle's H sensor and the vehicle's H sensor is measured according to the difference. Then, the optimized coordinates of an object are obtained, and the optimized operation of the coordinates of the object measured by the vehicle H is completed. In the same way, in the part of the adjacent car R, because the optimized vehicle coordinates of the adjacent car R have been known, according to the object coordinates measured by the sensor of the adjacent car R, the original vehicle coordinates of the adjacent car R and its vehicle can be compared. The difference between the optimized coordinates, when recalculating the object optimized coordinates of the object measured by the R sensor of the adjacent car, the difference amount measured by the R sensor of the adjacent car is compensated according to the difference, and Get the optimized coordinates of an object.

In step S40, the present invention can use the positioning comparison module 14 to fuse multiple coordinates from different neighboring cars R. For example, referring to FIG. 8 , for the first vehicle 101 , any of the other vehicles 102 to 104 will sense surrounding objects and share them with the first vehicle 101 , and the first vehicle 101 will receive multiple The coordinates of the same object (for example, the second vehicle 102 ) are temporarily stored in a buffer. Therefore, the positioning comparison module 14 in the first vehicle 101 will extract the coordinates of the similar objects from the buffer and add them to the buffer. It is merged into a single position data, and the coordinates of different objects are added separately. One of the fusion methods is to calculate an average value of multiple coordinates through the K-Means clustering algorithm, calculate a representative vehicle coordinate by averaging the vehicle optimized coordinates of the same vehicle, and calculate a vehicle representative coordinate by averaging the optimized coordinates of the same object. Objects represent coordinates.

To sum up, the vehicle cooperative object localization optimization method of the present invention has the following advantages:

1. By exchanging the sensed data between the vehicle and neighboring vehicles, the sensing range of each vehicle can be expanded and more environmental data can be obtained.

2. The coordinate data of the vehicle and surrounding objects are re-corrected through the co-location device. Compared with the coordinate data measured by the GPS receiver alone, the present invention can obtain more accurate coordinates, whether it is applied to an automatic driving system, or It is used to warn the driver of the current situation of the surrounding environment in advance, which can improve driving safety.

3. Using the collaborative positioning method of the present invention, when the vehicle completes the optimization operation, the optimized vehicle positioning data, adjacent vehicle positioning data and one or more object positioning data can be obtained. These three pieces of data will be displayed as BSM information. The format of the packet is transmitted to the surrounding adjacent vehicles. At this time, when the adjacent vehicle receives the BSM information packet, it can also perform the optimization calculation of the present invention independently. Therefore, the surrounding vehicles can perform distributed calculation. The positioning data between the two will gradually improve the accuracy.

Claims (10)

1. A vehicle cooperative object positioning optimization method is characterized by being executed by a cooperative positioning device arranged in the vehicle, and the method comprises the following steps:

receiving an information packet by a vehicle, wherein the information packet comprises a vehicle original coordinate provided by an adjacent vehicle and at least one object original coordinate, and the vehicle original coordinate and the object original coordinate respectively have respective positioning accuracy;

time delay compensation is carried out on the original coordinates of the vehicle and the original coordinates of the object, so that a vehicle coordinate and an object coordinate after adjacent vehicle compensation are obtained respectively;

executing an optimization program, comprising:

comparing the positioning accuracy, comparing the vehicle coordinate of the vehicle with the vehicle coordinate of the adjacent vehicle, and judging which vehicle has higher positioning accuracy;

preferentially performing an optimization operation on the vehicle coordinates with higher positioning accuracy, and then performing the optimization operation on the vehicle coordinates with lower positioning accuracy, wherein the optimization operation performs:

a) calculating a plurality of reference positions according to the vehicle coordinates of the vehicle and the vehicle coordinates of the adjacent vehicle; and

b) respectively calculating a vehicle optimization coordinate and an adjacent vehicle optimization coordinate according to the weight value of each reference position;

optimizing the object coordinate, namely comparing the difference between the original vehicle coordinate of the adjacent vehicle and the optimized coordinate of the adjacent vehicle, and compensating the object coordinate provided by the adjacent vehicle according to the difference to obtain an object optimized coordinate; and comparing the difference between the original vehicle coordinates of the vehicle and the vehicle optimized coordinates of the vehicle, and compensating the object coordinates provided by the vehicle according to the difference to obtain the object optimized coordinates.

2. The vehicle-collaborative object location optimization method of claim 1, further comprising, after performing the optimization procedure:

and a coordinate comparison and fusion step, namely comparing the vehicle optimized coordinates of a plurality of adjacent vehicles and the optimized coordinates of a plurality of objects obtained after the optimization programs of different adjacent vehicles are executed, averaging the vehicle optimized coordinates of the same vehicle to calculate a vehicle representative coordinate, and averaging the object optimized coordinates of the same object to calculate an object representative coordinate.

3. The vehicle cooperative type object positioning optimization method according to claim 1 or 2, wherein the vehicle coordinates of the own vehicle and the vehicle original coordinates of the neighboring vehicle are output by GPS receivers provided in the own vehicle and the neighboring vehicle, respectively.

4. The vehicle-collaborative object location optimization method according to claim 3, wherein the step of comparing the vehicle coordinates of the host vehicle with the vehicle coordinates of the neighboring vehicle to determine which has higher location accuracy is to compare the location accuracies of the GPS receivers of the host vehicle and the neighboring vehicle.

5. The method as claimed in claim 4, wherein in the step of performing time delay compensation, a compensation distance moved by the neighboring vehicle within the time delay is calculated according to a time delay between a sending time and a receiving time of the information packet, and the vehicle coordinates are obtained by adding the compensation distance to the original vehicle coordinates of the neighboring vehicle.

6. The method as claimed in claim 5, wherein the neighboring vehicle uses the original coordinates of the vehicle outputted from its GPS receiver as a reference position, and the reference positions comprise:

a first reference position, which is the vehicle coordinate output by the vehicle with its own GPS receiver;

a second reference position, which is obtained by the adjacent vehicle sensing a relative coordinate of the vehicle by a sensor of the adjacent vehicle, then using the reference position as a reference point, and obtaining the longitude and latitude of the vehicle by back calculation of the relative coordinate;

a third reference position, which is obtained by using a sensor of the vehicle to sense the relative distance and angle of the adjacent vehicle, then using the reference position as a reference point, and obtaining the longitude and latitude of the vehicle by back calculation of the relative distance and angle;

and a fourth reference position, which is used for estimating the relative distance between the vehicle and the adjacent vehicle according to the attenuation degree of the information packet after the information packet is sent from the adjacent vehicle to the vehicle and received, acquiring the direction of the vehicle relative to the adjacent vehicle according to a straight extension line of the first reference position and the reference position, and obtaining the longitude and latitude of the vehicle according to the relative distance and the direction of the vehicle by back calculation to obtain the fourth reference position.

7. The vehicle cooperative object localization optimization method of claim 6, wherein the vehicle optimization coordinates are calculated by:

wherein,

m represents the number of reference positions, (x)_i,y_i) Coordinates of the first to fourth reference positions are represented, respectively, and the weight value of each reference position is ω_i。

8. The method as claimed in claim 7, wherein the information packet is a basic security information packet.

9. The method as claimed in claim 7, wherein the weight value of each reference position is determined according to the accuracy of the sensor used to generate each reference position.

10. A vehicle co-location apparatus, comprising:

the wireless transmission interface is used for providing data bidirectional transmission between the vehicle and the adjacent vehicle, and receives an information packet which comprises a vehicle original coordinate and at least one object original coordinate of the adjacent vehicle and the respective positioning accuracy of the vehicle original coordinate and the object original coordinate;

a delay correction module, which receives the information packet sent by the adjacent vehicle through the wireless transmission interface, and performs time delay compensation on the original coordinates of the vehicle and the original coordinates of the object to obtain a vehicle coordinate and an object coordinate after the time delay compensation;

a position optimization module, which receives the vehicle coordinates and the object coordinates of the neighboring vehicle provided by the delay correction module, and receives the vehicle coordinates of the host vehicle and the object coordinates measured by the sensor of the host vehicle, wherein the position optimization module executes an optimization program, and the optimization program comprises:

comparing the vehicle coordinates of the vehicle with those of the adjacent vehicles to judge which one has higher positioning accuracy;

preferentially performing an optimization operation on the vehicle coordinates with higher positioning accuracy, and then performing the optimization operation on the vehicle coordinates with lower positioning accuracy, wherein the optimization operation performs:

a) calculating a plurality of reference positions according to the vehicle coordinates of the vehicle and the vehicle coordinates of the adjacent vehicle; and

b) respectively calculating a vehicle optimization coordinate and an adjacent vehicle optimization coordinate according to the weight value of each reference position;

optimizing the object coordinate, namely comparing the difference between the original vehicle coordinate of the adjacent vehicle and the optimized coordinate of the adjacent vehicle, and compensating the object coordinate provided by the adjacent vehicle according to the difference to obtain an object optimized coordinate; and comparing the difference between the original vehicle coordinates of the vehicle and the vehicle optimized coordinates of the vehicle, and compensating the object coordinates provided by the vehicle according to the difference to obtain the object optimized coordinates.

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