VEHICLE RECOGNITION DEVICE AND METHOD

Abstract

Vehicle identification device (10) attached to a vehicle (1) which has: - a detection unit (21) designed to detect the speed of a first other vehicle, and - a communication unit (23) designed to receive information indicating the speed of a second other vehicle from the second other vehicle, comprising the vehicle detection device (10): - a computing unit (141, S102) designed to calculate a display value indicating a probability that the first other vehicle and the second other vehicle are the same vehicle, the display value being defined as a function of the speed of the first other vehicle as detected by the detection unit (21) and the speed of the second other vehicle as indicated by the information received from the communication unit (23); and - a determination unit (142, S103) designed to determine whether or not the first other vehicle and the second other vehicle are the same vehicle, based on the display value calculated by the computation unit (141, S102), wherein - the computing unit (141, S102) is designed to calculate the display value based on a change over time in the speed of the first other vehicle and a change over time in the speed of the second other vehicle, - the computing unit (141, S102) is designed to calculate the display value by correlating the change over time in the speed of the first other vehicle with the change over time in the speed of the second other vehicle during a computing period in which the display value is calculated, - the computing unit (141, S102) is designed to calculate the display value based on characteristics of either the change over time of the speed of the first other vehicle or the change over time of the speed of the second other vehicle, and - the computing unit (141, S102) is designed to set a weighting factor for a characteristic section of the computing period in which an acceleration of the first other vehicle or an acceleration of the second other vehicle is greater than or equal to a second predetermined threshold, greater than a weighting factor for the remaining part of the computing period in which the acceleration is below the second predetermined threshold.

Description

BACKGROUND (Technical Field)

[0001] The present invention relates to methods for detecting the driving state of a vehicle other than a subject vehicle. (State of the art)

[0002] Methods are known for acquiring position information from a vehicle other than the subject vehicle via vehicle-to-vehicle communication and for using the other vehicle's position information to determine its relative position to the subject vehicle. According to an example in JP 2007-280 060 A, the degree of agreement between a radar vector describing the magnitude and direction of the other vehicle detected by the radar and a GPS vector describing the magnitude and direction of the other vehicle determined based on the other vehicle's position information received via vehicle-to-vehicle communication is evaluated. If the degree of agreement is greater than or equal to a threshold, the vehicle with the radar vector is determined to be a vehicle with which the subject vehicle is communicating.

[0003] However, GPS location information can be highly inaccurate, leading to significant errors in the magnitude and direction of movement determined based on this location data. Consequently, for example, in situations where several vehicles, distinct from the subject vehicle, are traveling close together in the same direction, it is difficult to establish connections between the multiple other vehicles detected by the detector (such as radar or similar) mounted on the subject vehicle and the multiple other vehicles with which the subject vehicle communicates via vehicle-to-vehicle communication.

[0004] WO 2013 / 014 755 A1 further discloses a vehicle specification system comprising a communication device for receiving information about another vehicle, a detection device for detecting the other vehicle and a vehicle specification device for specifying the other vehicle, and WO 2012 / 059 973 A1 discloses a vehicle detection device for detecting driving information from another vehicle.

[0005] The purpose of the present disclosure is to provide a vehicle detection device and a vehicle detection method for accurately determining a link between a vehicle detected by a detector mounted in the subject vehicle and a vehicle with which the subject vehicle communicates via vehicle-to-vehicle communication.

[0006] The problem is solved by the subject matter of the independent claims. Advantageous further developments are specified in the dependent claims.

[0007] According to the invention, even in situations where several vehicles, different from the subject vehicle, are driving close together in the same direction, it is possible to determine more accurately whether or not the detection vehicle and the communication vehicle are the same vehicle, compared to the case where the determination is based solely on GPS location information.

[0008] Depending on specific implementation requirements of the methods according to the invention, the methods according to the invention can be realized using hardware or software. The implementation can be carried out using a digital storage medium, in particular a disk, DVD, flash memory, or CD, with electronically readable control signals stored thereon, in conjunction with a programmable computer system, such that the methods according to the invention are executed. The present invention is therefore usually a machine-readable medium with program code that serves to execute the methods according to the invention when the computer program product is running on a computer or processor. More precisely, the methods according to the invention are therefore a computer program with program code for executing at least one of the methods according to the invention when the computer program is running on a computer or processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The attached drawings show: Fig. 1A a schematic block diagram of a vehicle recognition device according to a first embodiment of the present invention; Fig. 1B a schematic block diagram of one in the Fig. 1A shown recognition unit; Fig. 2. An example of a positional relationship between the subject vehicle and other vehicles; Fig. 3. An example to determine that a communications vehicle and a data collection vehicle are the same vehicle; Fig. 4 a flowchart of a recognition process according to the first embodiment; Fig. 5. An example of a change over time in vehicle speed for both a communication vehicle and a detection vehicle; Fig. 6. An example of how to calculate a speed ratio; Fig. 7. An example of how to calculate a variance; Fig. 8 a flowchart of a conformity calculation process according to the first embodiment; Fig. 9 a flowchart of a calculation period determination process according to the first embodiment; Fig. 10 a flowchart of a recognition process according to a second embodiment; Fig. 11 a flowchart of a recognition process according to a third embodiment; Fig. 12 an example of a time interval characterized by a change in speed; Fig. 13 a flowchart of a recognition process according to a fourth embodiment; Fig. 14 an example of calculating a variance according to the fourth embodiment; Fig. 15 a flowchart of a variance calculation process according to the fourth embodiment; Fig. 16 an example of restricting candidates based on position information; Fig. 17 a flowchart of a recognition process according to a fifth embodiment; and Fig. 18 a flowchart of a position information determination process according to a fifth embodiment. DESCRIPTION OF THE SPECIFIC VERSIONS

[0010] The present invention is described in more detail below with reference to the accompanying drawings. Identical elements are consistently identified by the same reference numerals. (1. First embodiment)(1-1. Configuration)

[0011] One in the Fig. The vehicle detection device 10 shown in Figure 1 is mounted in a vehicle (as a subject vehicle) 1, which has a peripheral monitoring sensor 21 (as a detection unit), a status detection sensor 22, a wireless communication unit 23 (as a communication unit), and a vehicle control unit 24. In the present embodiment, it can be assumed that vehicles 2, which are distinct from the subject vehicle 1 and are located around the subject vehicle 1, each have a configuration identical to that of the subject vehicle 1.

[0012] The peripheral monitoring sensor 21 detects the speed, position, and other parameters of an object located around the subject vehicle 1 relative to the subject vehicle 1. In the present embodiment, a millimeter-wave radar is used as the peripheral monitoring sensor 21 to detect the vehicle 2, which is located in front of the subject vehicle 1 (see Fig. 2) Alternatively or in addition to millimeter wave radar, another device that works similarly to it, such as a laser radar or a camera, can be used.

[0013] The state detection sensor 22 detects speed, absolute position, acceleration, braking, steering angle, and the like of the subject vehicle 1. In the present embodiment, a speed sensor, a GPS receiver, an accelerator pedal sensor, a brake pedal sensor, and a steering angle sensor can be used together as the state detection sensor 22.

[0014] The wireless communication unit 23 sends information indicating a vehicle number (chassis number), speed, absolute position, acceleration, braking, steering angle and the like of the subject vehicle 1 to the other vehicle 2, which is present around the subject vehicle 1 (in the present embodiment within a detection range with the subject vehicle 1 in the middle).

[0015] The wireless communication unit 23 receives information from the other vehicle 2, which is present around the subject vehicle 1, indicating a vehicle number (chassis number), speed, absolute position, acceleration, braking, steering angle and the like of the other vehicle 2, for example via vehicle-to-vehicle communication, vehicle-to-road communication, mobile communication, communication via visible light and the like.

[0016] The vehicle detection device 10 comprises a monitoring information storage unit 11, a detection information storage unit 12, a communication information storage unit 13, and a detection unit 14. The monitoring information storage unit 11 stores information received from the peripheral monitoring sensor 21 and manages the information in chronological order. More precisely, the monitoring information storage unit 11 detects, from the peripheral monitoring sensor 21, each predetermined time interval, object numbers (identifying information assigned to the respective detected objects), information indicating the relative speed and relative position of each detected object, and information indicating the presence of a lost object.The monitoring information storage unit 11 stores, for each object number, the information (indicating the relative speed and relative position of the other vehicle 2) acquired in the last T cycles, including the (T-1)th previous cycle, the (T-2)th previous cycle, ..., the current cycle, where T is a positive integer. As described below, the value T is not a fixed value, but a value that is variably set depending on the detection status of the objects. More precisely, as long as each of the detected objects (the other vehicles 2) is continuously detected by the peripheral monitoring sensor 21, the associated information is stored at each predetermined time interval. As soon as at least one object is lost, the stored information is deleted.

[0017] The acquisition information storage unit 12 stores information received from the status sensor 22 and manages the information in chronological order. More precisely, the communication information storage unit 13 acquires information from the status sensor 22 at each predetermined time interval, indicating the speed, absolute position, acceleration, braking, steering angle, and the like of the subject vehicle 1. The acquisition information storage unit 12 stores the information (indicating the speed and absolute position of the subject vehicle 1) acquired in the last T cycles, as described above.

[0018] The communication information storage unit 13 stores information received from the wireless communication unit 23 and manages the information in chronological order. More precisely, the communication information storage unit 13 receives information from the wireless communication unit 23 at each predetermined time interval, indicating the vehicle identification number, speed, absolute position, acceleration, braking, steering angle, and similar data of each other vehicle 2. The communication information storage unit 13 stores, for each vehicle identification number, the information (indicating the speed and absolute position of the other vehicle 2) that was received in the last T cycles, as described above.

[0019] The detection unit 14 determines whether or not the other vehicle 2, which has a speed and the like detected by the peripheral monitoring sensor 21 (hereinafter referred to as a detection vehicle or detected vehicle), is the same vehicle as the other vehicle 2, which is the source of the information received by the wireless communication unit 23 (hereinafter referred to as a communication vehicle or communicating vehicle).

[0020] The recognition unit 14 indicates, as in Fig. Figure 1B shows a computing unit 141 designed to calculate a display value, which is described below, and a determination unit 142 designed to determine whether or not the detection vehicle (as a first other vehicle) and the communication vehicle (as a second other vehicle) are the same vehicle, based on the display value calculated by the computing unit 141.

[0021] More precisely, the recognition unit 14 calculates, as in Fig. Figure 3 shows that for each pair of communication vehicle and detection vehicle currently being detected, a display value is generated indicating the probability that the communication vehicle and detection vehicle of the pair are the same vehicle (or a degree of similarity between the communication vehicle and the detection vehicle). The detection unit 14 determines the pairs of communication vehicles and detection vehicles that are recognized as the same vehicle based on the calculated display values. For each pair of possible communication vehicle and detection vehicle pairs (imax × jmax), it is determined whether the communication vehicle and detection vehicle of the pair are the same vehicle, where imax represents a maximum number of vehicles (i.e., 1 ≤ number of vehicles i ≤ imax) and jmax represents a maximum number of objects (i.e., 1 ≤ number of objects j ≤ jmax).

[0022] For example, if, as in Fig. As shown in Figure 2, if two other vehicles 2 are driving in front of the subject vehicle 1 and within a detectable area of ​​the peripheral monitoring sensor 21, the number of detection vehicles jmax is two. If only these two other vehicles 2 are driving within the detection area with the subject vehicle 1 in the middle, the number of communication vehicles imax is also two. This scenario results in four pairs of communication vehicles and detection vehicles for which the vehicle identity must be determined. In practice, the vehicle identity does not need to be determined for all four of these pairs of communication vehicles and detection vehicles.Once a specific pair of communication vehicle and detection vehicle that can be identified as the same vehicle is determined during the vehicle identity determination for the respective pending pairs, as described below, vehicle identification can be skipped for the remaining pairs of communication vehicles and detection vehicles.

[0023] The vehicle control unit 24 executes a vehicle control process to implement a CACC (Cooperative Adaptive Cruise Control) function, i.e., a function for acquiring information indicating acceleration, braking, steering angle, and the like of the other vehicle 2 (also referred to as the vehicle ahead) traveling in the lane of and in front of subject vehicle 1, and for using the acquired information to automatically accelerate or decelerate subject vehicle 1. Alternatively, such a vehicle control process for implementing the CACC function can be replaced by another vehicle control process.

[0024] The recognition unit 14 and the vehicle control unit 24 are embodied by their respective microcomputers, which include a CPU (processor), ROM (read-only memory), RAM (read / write memory), and the like. That is, each microcomputer can function as either the recognition unit 14 or the vehicle control unit 24 by executing a computer program stored in the ROM or the like. Alternatively, a single microcomputer can function as both the recognition unit 14 and the vehicle control unit 24. (1-2. Recognition process)

[0025] Below is a recognition process carried out in recognition unit 14 with reference to one in the Fig. The process is described in the flowchart shown in section 4. The recognition process can be repeated at any predetermined time interval.

[0026] First, in step S101, the value of a variable i is set to 1 and the value of a variable j is also set to 1. The variable i represents a vehicle number assigned to a communication vehicle to be processed and takes a positive integer greater than or equal to 1 and less than or equal to a maximum number imax x, the total number of communication vehicles (i.e., 1 ≤ i ≤ imax). The variable j represents an object number assigned to a detection vehicle to be processed and takes a positive integer greater than or equal to 1 and less than or equal to a maximum number jmax, the total number of detection vehicles (i.e., 1 ≤ j ≤ jmax).

[0027] Subsequently, in step S102, a degree-of-correction calculation process is performed (described in more detail below) to calculate a variance V as an indicator value that shows the probability that the communicating vehicle with vehicle number i (hereinafter referred to as communication vehicle i) and the sensing vehicle with object number j (hereinafter referred to as sensing vehicle j) are the same vehicle. The variance V is calculated based on a speed of communication vehicle i, indicated by the information received by the wireless communication unit 23, and a speed of sensing vehicle j, detected by the peripheral monitoring sensor 21. In the present embodiment, the calculated variance V decreases, as described above, with an increasing probability that communication vehicle i and sensing vehicle j are the same vehicle.

[0028] Subsequently, in step S103, it is determined whether the variance V calculated in step S102 is below a threshold value V1 (a third predetermined threshold). The threshold value V1 is a guideline used to determine whether the communication vehicle i and the detection vehicle j are the same vehicle. In the present embodiment, if the variance V is below the threshold value V1, then the communication vehicle i and the detection vehicle j are the same vehicle.

[0029] If step S103 determines that the variance V is greater than or equal to the threshold V1, step S104 then determines whether the value of the variable j is greater than or equal to the maximum number jmax. The maximum number jmax refers to the total number of vehicles for which information is stored in the monitoring information storage unit 11. That is, step S104 determines whether the operations in steps S102 and S103 have been performed for all of the vehicles j (j = 1, ..., jmax).

[0030] If, in step S104, it is determined that the value of the variable j is below the maximum number jmax, then in step S105 the value of the variable j is incremented by one. The process then returns to step S102, in which the agreement-degree calculation process is repeated for a different detection vehicle.

[0031] Furthermore, if in step S103 it is determined that the variance V is below the threshold V1, then in step S106 it is determined that the communication vehicle i and the detection vehicle j are the same vehicle. The process then proceeds to step S107. Furthermore, if in step S104 it is determined that the value of the variable j is greater than or equal to the maximum count jmax, the process proceeds to step S107.

[0032] Step S107 determines whether the value of the variable i is greater than or equal to the maximum number imax. The maximum number imax refers to the total number of communication vehicles for which information is stored in the communication information storage unit 13. That is, step S107 determines whether the operations in steps S102 to S106 have been performed for all communication vehicles i (i = 1, ..., imax).

[0033] If, in step S107, it is determined that the value of variable i is less than the maximum number imax, then in step S108 the value of variable i is incremented by one, and subsequently, in step S109, the value of variable i is reset to 1. The process then returns to step S102, in which the matching rate calculation process is repeated for another communication vehicle. However, if, in step S107, it is determined that the value of variable i is greater than or equal to the maximum number imax, the recognition process is terminated.

[0034] Once again, the one in the Fig. The recognition process shown in Figure 4 is executed in the recognition unit 14. In the recognition unit 14, the computing unit 141 is primarily responsible for executing the degree of agreement calculation process in step S102, and the determination unit 142 is primarily responsible for executing the determination process in step S103.

[0035] The following is the agreement-degree calculation process that is performed in step S102 of the recognition process (see flowchart in the Fig. 4), described in more detail. In the degree of agreement calculation process, the variances V are calculated based on the speeds of the detection vehicles, as recorded by the peripheral monitoring sensor 21, relative to the subject vehicle 1, and the speeds of the communication vehicles, as indicated by the information received from the wireless communication unit 23. More precisely, the variances V are calculated based on changes over time in the speeds of the detection vehicles and changes over time in the speeds of the communication vehicles.

[0036] It can be assumed, for example, that, as in Fig. Figure 2 shows two other vehicles 2 driving side by side. In such a scenario, even if the drivers of the two other vehicles 2 try to keep their respective vehicle speeds as constant as possible, a small difference between their respective vehicle speed behavior (changes in the speeds of the other vehicles 2 over time) can occur. Using the peripheral monitoring sensor 21 and the condition monitoring sensor 22 makes it possible, as shown in Figure 2, to detect this difference. Fig. As shown in section 5, it is possible to detect their respective vehicle speed behavior on a small scale. Consequently, by correlating the change over time in the speed of each detection vehicle with the change over time in the speed of each communication vehicle, the variance V as a function of the difference in vehicle speed behavior during a specific time interval can be calculated.

[0037] More precisely, the variance V can be calculated using the following procedure. 1. Conversion from relative to absolute speed

[0038] The absolute speed of the recording vehicle j is calculated, as shown in equation (1), by adding the relative speed of the recording vehicle j to the speed (absolute speed) of the subject vehicle 1. In equation (1), Vjmr(t) is the relative speed of the recording vehicle j at time t, Vo(t) is the speed of the subject vehicle 1 at time t, and Vjm(t) is the absolute speed of the recording vehicle j at time t. Vjm(t)=Vjmr(t)+Vo(t) 2. Calculation of the speed ratio

[0039] As shown in equation (2), a speed ratio R is calculated, which describes the ratio of the speed (absolute speed) of the communication vehicle i to the speed (absolute speed) of the detection vehicle j. In equation (2), Vic(t) is the speed of the communication vehicle i at time t and Rj(t) is the ratio of the speed of the communication vehicle i to the speed of the detection vehicle j at time t. Rj(t)=Vic(t)Vjm(t) 3. Calculation of the variance of the velocity ratio R

[0040] Fig. Figure 6 shows the speed ratio R1(t) of the speed of the communication vehicle i=1 to the speed of the detection vehicle j=1, which differs from that of communication vehicle i=1, and the speed ratio R2(t) of the speed of communication vehicle i=1 to the speed of detection vehicle j=2, which is the same vehicle as communication vehicle i=1. The speed ratio R is essentially constant over time if the communication vehicle and the detection vehicle are the same vehicle. That is, the change in the speed ratio R decreases as the probability that the communication vehicle and the detection vehicle are the same vehicle increases.

[0041] It should be noted that in the Fig. 6. The speed ratio R2(t) of the speed of the communicating vehicle i=1 to the speed of the detecting vehicle j=2 is a substantially constant value other than 1, which is caused by a deviation of the speed detected by the speed sensor from the actual speed. That is, if the communicating vehicle and the detecting vehicle are the same vehicle, the speed ratio R is substantially constant even if there is a deviation of the detected speed from the actual speed. The deviation of the detected speed from the actual speed can be caused by a change in the outer diameter of a tire due to tire wear.

[0042] In the present embodiment, as in Fig. Figure 7 shows the variance V of the speed ratio R over a computation period T (a change in the speed ratio of the communicating vehicle to the detecting vehicle). The computation period T is a time interval corresponding to the information acquired in the last T cycles (including the current cycle). The variance V of the speed ratio R over the computation period T is a variance calculated using the information acquired in the last T cycles (including the (T-1)th previous cycle, the (T-2)th previous cycle, ..., the current cycle), as described by equation (3). A process for determining the computation period T is described below. In equation (3), RjA describes a mean value of the speed ratio Rj(t) over the computation period T. Vj(t)=1T∑n=0T−1{Rj(t−n)−RjA}2

[0043] The above-described degree-of-conformity calculation process, i.e., the process for calculating the variance V at time t, is explained in more detail below with reference to a [reference to a document in the text]. Fig. The flowchart shown in Figure 8 describes the process. The degree of agreement calculation process is executed in the recognition unit 14.

[0044] First, in step S201, a calculation period determination process is executed, in which the calculation period T, which is used to calculate the variance V, is determined or set. The calculation period determination process is described in more detail below.

[0045] Subsequently, in step S202, the value of a variable n is set to 0. Following this, in step S203, the absolute speed of the detection vehicle at time tn (at the time of the nth previous cycle) is calculated in accordance with equation (4). Vjm(t−n)=Vjmr(t−n)+Vo(t−n)

[0046] Subsequently, in step S205, the velocity ratio R at time tn is calculated in accordance with equation (5). Rj(t−n)=Vic(t−n) / Vjm(t−n)

[0047] Subsequently, in step S205, the value of variable n is incremented by one, and in step S206, it is determined whether the value of variable n is greater than or equal to the value of the computation period T. That is, in step S206, for all stored information in the last T cycles, in monitoring information storage unit 11, acquisition information storage unit 12, and communication information storage unit 13, it is determined whether the operations in steps S203 and S204 have been executed. If in step S206 it is determined that the value of variable n is less than the value of the computation period T, the process returns to step S203.

[0048] If in step S206 it is determined that the value of the variable n is greater than or equal to the value of the calculation period T, then in step S207 the variance V of the velocity ratio R is calculated in accordance with equation (3).

[0049] Then, in step S208, it is determined whether the value of the calculation period T is greater than 0. If step S208 determines that the value of the calculation period T is greater than 0, the degree of agreement calculation process then ends. Fig. 8. If in step S208 it is determined that the value of the calculation period T is greater than or equal to 0, is the value of the variance V then set to infinity and the degree of agreement calculation process ends? Fig. 8. An infinite value of the variance V leads to the minimum probability (i.e., a probability of 0) that the detection vehicle and the communication vehicle are the same vehicle. A computation period T of less than or equal to 0 means that the computation period T is set to 0 in the operation of step S305, which is described below.

[0050] Alternatively, the operations in steps S208 to S209 can be performed in advance, for example, immediately after the operation in step S201. Subsequently, if the value of the computation period T is less than or equal to 0, the operations in steps S202 to S207 are skipped.

[0051] The calculation period determination process, which is executed in step S201 of the degree of agreement calculation process (see Fig. 8), is described in more detail below. In the calculation period determination process, the calculation period T is determined or set as follows. (i) The value of the calculation period T is a duration during which the recording vehicle j is continuously recorded without being lost. (ii) If the detection vehicle j is lost due to detection conditions or the like, a lost vehicle flag indicating that the detection vehicle j is lost is detected by the peripheral monitoring sensor 21. Simultaneously, the computation period T is reset. The lost vehicle flag indicating that the detection vehicle j is lost can be sent by the peripheral monitoring sensor 21 not only when the detection vehicle j is permanently lost, but also when the detection vehicle is temporarily lost. (iii) The computation period T is used to calculate the variance V, provided that the value of the computation period T is above a predetermined threshold (as a first predetermined threshold). The predetermined threshold is determined to prevent incorrect determinations (that the communication vehicle and the detection vehicle are the same vehicle) from occurring due to the calculated variance V.

[0052] The above accounting period determination process is described below with reference to the one in the Fig. The flowchart shown in Figure 9 describes the process in more detail. The calculation period determination process is executed in the recognition unit 14 and is used to determine or set the calculation period T in order to calculate the variance V for the detection vehicle j.

[0053] First, in step S301, it is determined whether or not the lost vehicle flag L(t), which indicates that the detection vehicle j is lost at time t, is detected. More precisely, a lost vehicle flag L(t) with a value of 1, i.e., L(t)=1, indicates that the detection vehicle j is lost at time t, and a lost vehicle flag L with a value of 0, i.e., L(t)=0, indicates that the detection vehicle j is not lost at time t.

[0054] If, in step S301, it is determined that the lost vehicle flag L(t) with a value of 1 (L(t) = 1), indicating that the detection vehicle j is lost at time t, then in step S302 a final lost vehicle detection time Ltime is updated to time t, after which the process proceeds to step S303. Furthermore, if, in step S301, it is determined that the lost vehicle flag L(t) with a value of 1 is not detected, the process skips step S302 and proceeds to step S303.

[0055] In step S303, the calculation period T is calculated by subtracting the last lost vehicle detection time Ltime from the current time t. That is, the calculation period T for calculating the variance V for the detection vehicle j is the duration during which the detection vehicle j is continuously detected without being lost. The time T-Ltime is calculated in units of the predetermined time interval. For example, if the lost vehicle flag L(t) with a value of 1 (L(t)=1) is detected in the first previous cycle, then T=t-Ltime=1. If the lost vehicle flag L(t) with a value of 1 (L(t)=1) is detected in the second previous cycle, then T=t-Ltime=2.

[0056] In step S304, it is then determined whether the calculation period T calculated in step S303 exceeds a predefined threshold (a minimum setting value for the calculation period T as the first predetermined threshold) Tmin. If step S304 determines that the calculation period T exceeds the predefined threshold Tmin, the process then ends. Fig. 9 shown calculation period determination process.

[0057] Furthermore, if in step S304 it is determined that the calculation period T is less than or equal to the predefined threshold Tmin, the value of the calculation period T is set to 0, whereupon the Fig. The calculation period determination process shown in Figure 9 ends. Setting the value of the calculation period T to 0 leads to the value of the variance V, which is set to infinity in steps S208 to S209 of the degree of agreement calculation process (see Figure 9). Fig. 8), which leads to the determination that the communication vehicle and the detection vehicle are not the same vehicle. That is, in the degree of agreement calculation process, provided that the value of the calculation period T is above the threshold value Tmin, a change in the speed of the detection vehicle over time is correlated with a change in the speed of the communication vehicle over time during the calculation period T, so that the variance V can be calculated as a function of a difference in the speed behavior between the two. More precisely, if the value of the calculation period T is less than or equal to the threshold value Tmin, compared to the case where the value of the calculation period T is above the threshold value Tmin, the variance V is set to a value that results in a low probability that the detection vehicle and the communication vehicle are the same vehicle (infinite in the present embodiment). (1-3 advantages)

[0058] The embodiment described above can offer the following advantages.

[0059] (1A) The degree of agreement calculation process is performed (in step S102), in which the variance V is calculated, which is an indicator value of the probability that the detection vehicle and the communication vehicle are the same vehicle. Based on the calculated variance V, it is determined (in step S103) whether or not the detection vehicle and the communication vehicle are the same vehicle. More precisely, in the degree of agreement calculation process (in step S102), the variance V is calculated based on the speed of the detection vehicle, as recorded by the peripheral monitoring sensor 21, and the speed of the communication vehicle, as indicated by the information received from the wireless communication unit 23 (in steps S202 to S207).With the vehicle recognition device 10 of the first embodiment, it is also possible to determine more accurately whether or not the detection vehicle and the communication vehicle are the same vehicle in situations where several vehicles, which differ from the subject vehicle, are driving close together in the same direction, compared to the case where the determination is based solely on GPS location information.

[0060] (1B) In the degree of agreement calculation process, the variance V is calculated based on the change over time of the speed of the detection vehicle and the change over time of the speed of the communication vehicle (in steps S202 to S207). Consequently, with the vehicle recognition device 10 of the first embodiment, it can be accurately determined whether or not the detection vehicle and the communication vehicle are the same vehicle.

[0061] (1C) In the degree of agreement calculation process, the variance V is calculated by correlating the change over time in the speed of the detection vehicle with the change over time in the speed of the communication vehicle during the computation period T in which the variance V is calculated (in steps S202 to S207). Consequently, with the vehicle detection device 10 of the first embodiment, it can be accurately determined whether or not the detection vehicle and the communication vehicle are the same vehicle.

[0062] (1D) In ​​the degree of agreement calculation process, the variance V is calculated based on the change in the speed ratio of the communicating vehicle's speed to the detecting vehicle's speed over the calculation period T (in steps S202 to S207). Consequently, with the vehicle detection device 10 of the first embodiment, it is relatively easy to determine a degree of correlation between the change over time of the detecting vehicle's speed and the change over time of the communicating vehicle's speed. Furthermore, relatively accurate determination results can be obtained even if there is a deviation between the detected speed and the actual speed.

[0063] (1E) In the degree of agreement calculation process, the computation period T, in which the variance V for the detection vehicle and the communication vehicle is calculated, is calculated in accordance with the detection states of the detection vehicle (in step S201). Consequently, with the vehicle recognition device 10 of the first embodiment, the accuracy in determining whether or not the detection vehicle and the communication vehicle are the same vehicle can be improved compared to the case where the computation period T is determined independently of the detection states of the detection vehicle.

[0064] (1F) In the degree of agreement calculation process, the computation period T for calculating the variance V for the detection vehicle and the communication vehicle is set to a duration during which the detection vehicle is continuously detected by the peripheral monitoring sensor 21 without being lost (in steps S301 to S303). Consequently, with the vehicle detection device 10 of the first embodiment, the accuracy in determining whether or not the detection vehicle and the communication vehicle are the same vehicle can be improved compared to the case where the computation period T can be determined such that it includes a period during which the detection vehicle is lost.

[0065] (1G) In the degree of agreement calculation process, the computation period T for calculating the variance V for the detection vehicle and the communication vehicle is set to a duration during which the detection vehicle is continuously detected by the peripheral monitoring sensor 21 without being lost (in steps S301 to S303). Consequently, with the vehicle recognition device 10 of the first embodiment, the accuracy in determining whether or not the detection vehicle and the communication vehicle are the same vehicle can be improved compared to the case where the computation period T is set to a segment of the duration during which the detection vehicle is continuously detected by the peripheral monitoring sensor 21 without being lost.

[0066] (1H) In the degree of agreement calculation process, provided that the computation period T is above the threshold value Tmin (in step S304), the variance V is calculated by correlating the change over time in the speed of the detecting vehicle with the change over time in the speed of the communicating vehicle during the computation period T (in step S208). Consequently, with the vehicle detection device 10 of the first embodiment, the accuracy in determining whether or not the detecting vehicle and the communicating vehicle are the same vehicle can be improved compared to the case where the computation period T can be set to a lower value than the threshold value Tmin.

[0067] (11) In the degree of agreement calculation process, when the computation period T is less than or equal to the threshold Tmin (in step S304), compared to the case where the computation period T is greater than the threshold Tmin, the variance V is set to a value that results in a low probability that the detection vehicle and the communication vehicle are the same vehicle (in step S209). Consequently, with the vehicle recognition device 10 of the first embodiment, when the computation period T is less than or equal to the threshold Tmin, the determination that the detection vehicle and the communication vehicle are the same vehicle can be prevented.

[0068] (1J) If the variance V is below the threshold V1, it is determined that the communication vehicle and the detection vehicle are the same vehicle (in steps S103, S106). The probability that the communication vehicle and the detection vehicle are the same vehicle when the variance V is below the threshold V1 is higher than the probability that the communication vehicle and the detection vehicle are the same vehicle when the variance V is equal to the threshold V1. Accordingly, with the vehicle detection device 10 of the first embodiment, since it does not have to determine for all of the pairs of detection vehicles and communication vehicles whether or not the detection vehicle and the communication vehicle are the same vehicle, the computational load can be reduced. (2. Second embodiment)(2-1. Differences from the first embodiment)

[0069] A second embodiment of the present invention is described below, which differs from the fact that one of the Fig. 10. Recognition process shown instead of the one in the Fig. The recognition process shown in section 4 has a configuration identical to the first embodiment. The only differences between the second and first embodiments are described below. (2-2. Recognition process)

[0070] Below is a recognition process carried out in the recognition unit 14 of the second embodiment, with reference to the one described in the Fig. The flowchart shown in section 10 describes the operations described in steps S401, S403, S404, S407, S408, S410, S412-S414 of the diagram. Fig. 10 equal to the operations in steps S101-S109 of the Fig. The four points mentioned below will not be discussed again.

[0071] First, in step S401, the value of variable i, which describes a communication vehicle to be processed, is set to 1, and the value of variable j, which describes a detection vehicle to be processed, is also set to 1. Then, in step S402, the value of variable m, used to count the number of candidate objects, is set to 0.

[0072] In step S403, the agreement calculation process is then executed. Following this, in step S404, it is determined whether the calculated variance V is below the threshold V1. If step S404 determines that the variance V is below the threshold V1, the value of the variable m is incremented by one in step S405. After the detection vehicle j is registered as a candidate object in step S406, the process proceeds to step S407. That is, if it is likely that the communication vehicle i and the detection vehicle j are the same vehicle, the detection vehicle j is registered as a candidate object. Conversely, if step S404 determines that the variance V is greater than or equal to the threshold V1, the process skips steps S405-S406 and proceeds to step S407.

[0073] Step S407 determines whether the value of the variable j is greater than or equal to the maximum number jmax. If step S407 determines that the value of the variable j is less than the maximum number jmax, the value of the variable j is incremented by one, and the process returns to step S403.

[0074] However, if in step S407 it is determined that the value of the variable j is greater than or equal to the maximum number jmax, then in step S409 it is determined whether or not the value of the variable m is equal to 1.

[0075] If in step S409 it is determined that the value of variable m is equal to 1 (i.e., one candidate object is registered), then in step S410 it is determined that the communication vehicle i and the detection vehicle j are the same vehicle, after which the process proceeds to step S412. If in step S409 it is determined that the value of variable m is not equal to 1 (i.e., there are no registered candidate objects or multiple registered candidate objects), then in step S411 further detection processes for the communication vehicle i are suspended, and the process proceeds to step S412. In this way, if there are no registered candidate objects or multiple registered candidate objects for the communication vehicle i, the detection unit 14 cannot determine that only one of the detection vehicles and the communication vehicle i are the same vehicle.

[0076] In step S412, it is determined whether the value of variable i is greater than or equal to the maximum number imax. If step S412 determines that the value of variable i is less than the maximum number imax, the value of variable i is incremented by one, and the process returns to step S402. Furthermore, if step S412 determines that the value of variable i is greater than or equal to the maximum number imax, then the process terminates. Fig. 10. (2-3 advantages)

[0077] The second embodiment can produce the same advantages (1A)-(1I) as the first embodiment.

[0078] (2A) If no detection vehicles or multiple detection vehicles are present, each with a variance V below the threshold V1, further detection processes for the communication vehicle i being processed are suspended. Consequently, the vehicle detection device 10 of the second embodiment prevents incorrect determinations, such as the detection vehicle being identified as the same vehicle, when in fact the communication vehicle and the detection vehicle are different. (3. Third embodiment) (3-1. Differences from the first embodiment)

[0079] A third embodiment of the present invention is described below, which differs from the fact that one of the Fig. 11. Recognition process shown instead of the one in the Fig. The recognition process shown in section 4 has a configuration identical to the first embodiment. The only differences between the third and first embodiments are described below. (3-2. Recognition process)

[0080] Below is a recognition process carried out in the recognition unit 14 of the third embodiment, with reference to one in the Fig. The flowchart shown in section 11 describes the operations in steps S501, S504, S508, S509, S511, S513-S515. Fig. 11 equal to the operations in steps S101, S102, S104-S109 of the Fig. The number 4 is not discussed again below.

[0081] First, in step S501, the value of variable i, which describes a communication vehicle to be processed, is set to 1, and the value of variable j, which describes a detection vehicle to be processed, is also set to 1. Then, in step S502, the value of variable Vmin, which is described below, is set to infinity, and in step S503, the value of variable jsel, which is described below, is set to zero (indicating that there is nothing left to process).

[0082] In step S504, the degree of agreement calculation process is then executed. Following this, in step S505, it is determined whether the calculated variance V is below the threshold Vmin. If step S505 determines that the variance V is below the threshold Vmin, the value of the threshold Vmin is set to the current value of the variance V in step S506, and the value of the variable jsel is set to the current value of the variable j in step S507. The process then proceeds to step S508. This means that the value of the threshold Vmin is reduced to the current value of the variance V, and the current value of the variable j is correspondingly set in place of the variable jsel. These adjustments result in the threshold Vmin being set to the lowest value of the variance V, and the variable jsel being set to the value of the variable i corresponding to the lowest value of the variance V.

[0083] If in step S505 it is determined that the variance V is greater than or equal to the threshold Vmin, the process then skips steps S506-S507 and proceeds to step S508.

[0084] Step S508 determines whether the value of the variable j is greater than or equal to the maximum number jmax. If step S508 determines that the value of the variable j is less than the maximum number jmax, then step S509 increments the value of the variable j by one, and the process returns to step S504.

[0085] In contrast, if step S508 determines that the value of the variable j is greater than or equal to the maximum number jmax, step S510 determines whether or not the value of the variable jsel is zero.

[0086] If in step S510 it is determined that the value of the variable jsel is not equal to zero, then in step S511 it is determined that the communication vehicle i and the detection vehicle jsel are the same vehicle, and the process proceeds to step S513. That is, it is determined that one of the detection vehicles j = 1, ..., jmax with the highest degree of agreement (or the lowest variance V) is the same as the communication vehicle i.

[0087] In contrast, if step S510 determines that the value of the variable jsel is zero, further recognition processes for the communication vehicle i are prevented in step S512, whereupon the process proceeds to step S5113. That is, if the value of the variance V for each of the detection vehicles j = 1, ..., jmax is infinite, the recognition unit 14 cannot determine that one of the detection vehicles and the communication vehicle being processed are the same vehicle, and therefore the recognition unit 14 prevents further recognition processes for the communication vehicle i.

[0088] In step S513, it is determined whether the value of variable i is greater than or equal to the maximum number imax. If step S513 determines that the value of variable i is less than the maximum number imax, then the value of variable i is incremented by one, and the value of variable j is set to 1 in step S515. The process then returns to step S504. In contrast, if step S513 determines that the value of variable i is greater than or equal to the maximum number imax, the process ends. Fig. 11 processes shown. (3-3 advantages)

[0089] The third embodiment can provide the same advantages (1A)-(1I) as the first embodiment. The third embodiment can also provide the following additional advantages.

[0090] (3A) A pairwise combination of the detection vehicle and the communication vehicle with a lowest value of the variance V corresponding to the highest probability that both are the same vehicle is determined, whereby for this combination it is determined that the detection vehicle and the communication vehicle are the same vehicle (in steps S504-S509, S511). Consequently, with the vehicle recognition device 10 of the third embodiment, only one pairwise combination of the detection vehicle and the communication vehicle is determined for which there is the highest probability that they are the same vehicle. (4. Fourth embodiment)(4-1. Differences from the first embodiment)

[0091] A fourth embodiment of the present invention is described below, with the exception that, as in Fig. Figure 12 shows that a weighting for a section of the computation period T, which exhibits a velocity change greater than a weighting for a remaining part of the computation period T, has a configuration equal to the first embodiment. More precisely, the one in the Fig. The recognition process shown in section 8 is carried out by the process described in the Fig. The recognition process shown in section 13 is replaced, and is described below. Consequently, the differences between the fourth embodiment and the first embodiment are described below. (4-2. Agreement Calculation Process)

[0092] Below is a degree-of-compatibility calculation process carried out in the recognition unit 14 of the fourth embodiment, with reference to the one described in the Fig. The flowchart shown in step 13 is described. Since operations differ from the operation in step S607 of the Fig. 10 equal to the operations different from the operation in step S207 of the Fig. The fact that there are 8 of them will not be discussed again below.

[0093] In step S607, a variance calculation process is performed, in which a variance V of the velocity ratio R is calculated, taking into account a section of the computation period T in which the velocity changes characteristically over time (referred to as the characteristic time interval). More precisely, the velocity Vic(t) of the communication vehicle i is, as in Fig. As shown in Equation 14, the acceleration Aic(t) is differentiated to obtain an acceleration Aic(t). A time interval during which the acceleration Aic(t) is greater than or equal to a threshold A1 (as a second predetermined threshold) is considered a characteristic time interval with a significant change in velocity over time. The threshold A1 is a threshold defined as a criterion for determining whether or not the change in velocity over time is characteristic. The velocity ratio R is weighted, as shown in Equation (6), to calculate the variance of the velocity ratio R. Weights can be defined, for example, such that WAC=W1 (W1>1) for Aic(t)≥A1 and WAC=1 for Aic(t) <A1. Vj(t)=1T∑n=0T−1WAc{Rj(t−n)−RjA}2

[0094] Such a variance calculation process is described below with reference to the one in the Fig. The flowchart shown in section 15 is described in more detail.

[0095] First, in step S701, an average value RjA of the velocity ratio R over the calculation period T is calculated. Then, in step S702, the value of the variable n is set to 0. Subsequently, in step S703, an absolute value of the acceleration of the communication vehicle i is calculated according to equation (7). |Aic(t−n)|=|dVic(t−n) / dt|

[0096] Subsequently, in step S704, it is determined whether the absolute value of the calculated acceleration is greater than or equal to the threshold value A1. If step S704 determines that the absolute value of the acceleration is greater than or equal to the threshold value A1, then in step S705 the weighting factor WAC is set to W1, i.e., WAC = W1. If step S704 determines that the absolute value of the acceleration is less than the threshold value A1, then in step S706 the weighting factor WAC is set to 1, i.e., WAC = 1.

[0097] Subsequently, in step S707, a deviation of the velocity ratio from the mean value RjA is calculated taking into account the weighting factor WAC according to equation (8). σ(t−n)=WAc{Rj(t−n)−RjA}2

[0098] Then, in step S708, the value of variable n is incremented by one. Next, in step S709, it is determined whether the value of variable n is greater than or equal to the computation period T. That is, for all the information stored in the last T cycles, it is determined whether the operations in steps S703-S707 have been executed. If step S709 determines that the value of variable n is less than the value of the computation period T, the process then returns to step S703.

[0099] In contrast, if in step S709 it is determined that the value of the variable n is greater than or equal to the value of the calculation period T, in step S710 a variance V of the velocity ratio R is calculated taking into account the weighting factor WAC according to equation (9). The process then ends in the Fig. Variance calculation process shown in section 15. V=1T∑n=0T−1σ(t−n) (4-3 advantages)

[0100] The fourth embodiment can have the same advantages (1A)-(1J) as the first embodiment. The fourth embodiment can further offer the following additional advantages.

[0101] (4A) In the above-described degree-of-compliance calculation process, the variance V is calculated based on characteristics of the change over time of the speed of the communicating vehicle being processed. Consequently, with the vehicle recognition device 10 of the fourth embodiment, the accuracy in determining whether or not the detection vehicle and the communicating vehicle are the same vehicle can be improved compared to the case where the variance V is calculated independently of characteristics of the change over time of the speed of the communicating vehicle.

[0102] (4A) When calculating the variance V, the weighting factor set for a portion of the computation period T in which the acceleration Aic(t) is greater than or equal to the threshold A1 is set larger than the weighting factor set for the remaining portion of the computation period T. Consequently, even if the time-varying velocity of the communicating vehicle is relatively small, it can be determined more accurately whether the sensing vehicle and the communicating vehicle are the same vehicle. In some alternative embodiments, the variance V may be calculated not based on the time-varying characteristics of the communicating vehicle being processed, but rather on the time-varying characteristics of the sensing vehicle being processed.This can produce advantages similar to those of the present embodiment. (5. Fifth embodiment)(5-1. Differences from the first embodiment)

[0103] A fifth embodiment of the present invention is described below, which, with the exception that pairwise combinations of communication vehicle and detection vehicle, which are likely to be the same vehicle, are limited by comparing the position of the detection vehicle and the position of the communication vehicle, has a configuration equal to the first embodiment.

[0104] For example, as in Fig. Figure 16 shows candidates, each a pairwise combination of the detection vehicle and the communication vehicle, which are likely to be the same vehicle, restricted by comparing the absolute position of the other vehicle (communication vehicle) 2, as indicated by the information received by the wireless communication unit 23, and the absolute position of the other vehicle (detection vehicle) 2, as detected by the peripheral monitoring sensor 21. In the example of the Fig. 16. Candidates, each a pairwise combination of the detection vehicle and the communication vehicle i, which are likely to be the same vehicle, are limited to two candidates such that for each candidate the detection vehicle is located within a disk-shaped area in the center of which the communication vehicle i is located. For such candidates, it is determined whether or not the detection vehicle and the communication vehicle are the same vehicle based on the position information of both. That is, in the fifth embodiment, before determining whether or not the detection vehicle and the communication vehicle are the same vehicle based on their speed behavior, candidates are limited based on the position information, i.e., their number is reduced. (5-2. Recognition process)

[0105] The fifth embodiment of the present invention is described below, with the exception that one in the Fig. 17 shown recognition process instead of the one in the Fig. The recognition process shown in section 4 exhibited a configuration identical to the first embodiment. In the recognition process of the Fig. 17 additional operations are performed in steps S802-S803, compared to the one in the Fig. The recognition process shown in Figure 4 is described below. Only the differences between the fifth embodiment and the first embodiment are described below.

[0106] In step S802, a position information determination process is executed, in which a probability that the communication vehicle i and the detection vehicle j are the same vehicle is determined based on the position information. If, in step S803, it is determined that the communication vehicle i and the detection vehicle j are likely to be the same vehicle, then the degree-of-correction calculation process is executed in step S804. If, in step S803, it is determined that the communication vehicle i and the detection vehicle j are unlikely to be the same vehicle, then the process skips the degree-of-correction calculation process.

[0107] The one in step S802 of the Fig. The position information determination process carried out in section 17 is described below with reference to the one in the Fig. The flowchart shown in Figure 18 describes this process. In step S901, a relative distance Dc and a relative lateral distance Lc of the communication vehicle i are calculated from the absolute position of the subject vehicle 1 and the communication vehicle i itself. In a horizontal plane with an x-axis extending in a forward direction of the subject vehicle 1 and a y-axis extending perpendicular to the x-axis (i.e., in a latitude direction of the subject vehicle 1), the relative lateral distance Lc and the relative distance Dc are x-coordinates and y-coordinates, respectively.

[0108] Subsequently, in step S902, a difference Ddif between a relative distance Dr of the detection vehicle j and a relative distance Dc of the communication vehicle i is calculated, and in step S903 it is determined whether or not the calculated difference Ddif is below a threshold value D1. The threshold value D1 is defined as a criterion on the basis of which it is determined whether or not the detection vehicle j and the communication vehicle i are likely to be the same vehicle.

[0109] If, in step S903, it is determined that the difference Ddif is below the threshold D1, then in step S904 a difference Ldif is calculated between a relative lateral distance Lr of the detection vehicle j and a relative lateral distance Lc of the communication vehicle i. In step S905, it is determined whether or not the calculated difference Ldif is below a threshold L1. The threshold L1 is defined as a criterion used to determine whether or not the detection vehicle j and the communication vehicle i are likely to be the same vehicle.

[0110] If in step S905 it is determined that the difference Ldif is below the threshold L1, then in step S906 it is determined that the communication vehicle i and the detection vehicle j are probably the same vehicle. The process then ends in the Fig. 18 shown position information determination process.

[0111] If in step S903 it is determined that the difference Ddif is greater than or equal to the threshold D1, or if in step S905 it is determined that the difference Ldif is greater than or equal to the threshold L1, the process proceeds to step S907, in which it is determined that the communication vehicle i and the detection vehicle j are unlikely to be the same vehicle. The process then ends in the Fig. 18 shown position information determination process. (5-3 advantages)

[0112] The fifth embodiment described above can provide the same advantages (1A)-(1J) as the first embodiment and the following additional advantages.

[0113] (5A) Candidates, each a pairwise combination of detection vehicle and communication vehicle, which are likely to be the same vehicle, are narrowed down or restricted based on the position of the detection vehicle, as detected by the peripheral monitoring sensor 21, and the position of the communication vehicle, as indicated by the information received by the wireless communication unit 23. According to the fifth embodiment, the computational load can be reduced and incorrect determinations can be prevented. (6. Other embodiments)

[0114] Further embodiments are described below that can be realized without departing from the scope of protection of the present invention. Only the differences from the embodiments described above are presented.

[0115] (6A) In the embodiments described above, the computation period T is set to a duration during which the other vehicle 2 being processed is continuously detected without being lost. Alternatively, the computation period T can be set to a segment of such duration during which the other vehicle 2 being processed is continuously detected without being lost.

[0116] (6B) Those skilled in the art will recognize from the teaching of the present application various modifications and further embodiments of the invention. Consequently, the present invention should be understood as not being limited to the specific embodiments disclosed herein, but rather within its

[0117] The scope of protection, as set out in the attached claims, may be modified in various ways. Although certain terms are used herein, they are used in a general and descriptive sense and are not limiting.

Claims

[1] Vehicle detection device (10) mounted in a vehicle (1) comprising: - a detection unit (21) designed to detect a speed of a first other vehicle, and - a communication unit (23) configured to receive information indicating a speed of a second other vehicle from the second other vehicle, wherein the vehicle detection device (10) comprises: - a computing unit (141, S102) configured to calculate an indication value indicating a probability that the first other vehicle and the second other vehicle are the same vehicle, the indication value being defined as a function of the speed of the first other vehicle detected by the detection unit (21) and the speed of the second other vehicle indicated by the information received by the communication unit (23); and - a determination unit (142, S103) configured to determine whether or not the first other vehicle and the second other vehicle are the same vehicle on the basis of the indication value calculated by the calculation unit (141, S102), wherein - the computing unit (141, S102) is designed to calculate the display value on the basis of a change over time in the speed of the first other vehicle and a change over time in the speed of the second other vehicle, - the computing unit (141, S102) is designed to calculate the display value by correlating the change over time in the speed of the first other vehicle with the change over time in the speed of the second other vehicle during a computing period in which the display value is calculated, - the calculation unit (141, S102) is designed to calculate the display value based on characteristics of either the change over time in the speed of the first other vehicle or the change over time in the speed of the second other vehicle, and - the computing unit (141, S102) is designed to set a weighting factor for a characteristic portion of the computing period in which an acceleration of the first other vehicle or an acceleration of the second other vehicle is greater than or equal to a second predetermined threshold value, greater than a weighting factor for the remaining part of the computing period in which the acceleration is below the second predetermined threshold value. [2] Device according to claim 1, characterized by that the computing unit (141, S102) is designed to determine the computing period as a function of a detection state of the first other vehicle before calculating the display value. [3] Device according to claim 2, characterized byin that the computing unit (141, S102) is designed to determine the computing period within a duration in which the first other vehicle is continuously detected by the detection unit (21) without being lost. [4] Device according to claim 2 or 3, characterized by that the computing unit (141, S102) is designed to set the computing period to a duration in which the first other vehicle is continuously detected by the detection unit (21) without being lost. [5] Device according to one of claims 1 to 4, characterized by in that the calculation unit (141, S102) is designed, when the calculation period is above a first predetermined threshold, to calculate the display value by correlating the change over time in the speed of the first other vehicle with the change over time in the speed of the second other vehicle during the calculation period. [6] Device according to claim 5, characterized by in that the calculation unit (141, S102) is designed, when the calculation period is less than or equal to the first predetermined threshold value, to set the indication value to a value which indicates a lower probability that the first and the second other vehicle are the same vehicle, compared to the case where the calculation period is above the predetermined threshold value. [7] Device according to one of claims 1 to 6, characterized by , that - the probability that the first other vehicle and the second other vehicle are the same vehicle increases with a decreasing display value; and - the determination unit (142, S103) is designed to determine, when the indication value is below a third threshold value (V1), that the first other vehicle and the second other vehicle are the same vehicle. [8] Device according to one of claims 1 to 6, characterized by , that - the detection unit (21) is capable of detecting speeds of a plurality of first other vehicles; - the communication unit (23) is capable of receiving information indicating speeds of a plurality of second other vehicles from the respective second other vehicles; - the computing unit (141, S102) is designed to calculate, for each pairwise combination of the first and the second other vehicles, the display value indicating a probability that the first and the second other vehicle of the pairwise combination are the same vehicle; and - the determination unit (142, S103) is configured to determine that the first and second other vehicles are the same vehicle for the pairwise combination of the first and second other vehicles having a maximum probability that the first and second other vehicles are the same vehicle, which is indicated by the indication value calculated by the calculation unit (141, S102). [9] Device according to one of claims 1 to 8, characterized by , that - the detection unit (21) is capable of detecting positions of a plurality of first other vehicles; - the communication unit (23) is capable of receiving information indicating positions of a plurality of second other vehicles from the respective second other vehicles; - the determination unit (142, S103) is configured to restrict candidates each being a pairwise combination of the first and second other vehicles that are likely to be the same vehicle based on the positions of the first other vehicles detected by the detection unit (21) and the positions of the second other vehicles indicated by the information received from the communication unit (23). [10] Vehicle recognition method carried out in a vehicle (1) comprising: - a detection unit (21) designed to detect a speed of a first other vehicle, and - a communication unit (23) adapted to receive information indicating a speed of a second other vehicle from the second other vehicle, the vehicle recognition method comprising the following steps: - calculating (S102) an indication value indicating a probability that the first other vehicle and the second other vehicle are the same vehicle, the indication value being defined as a function of the speed of the first other vehicle detected by the detection unit (21) and the speed of the second other vehicle indicated by the information received by the communication unit (23); - determining (S103) whether or not the first other vehicle and the second other vehicle are the same vehicle based on the calculated display value; - calculating (S102) the display value based on a change over time in the speed of the first other vehicle and a change over time in the speed of the second other vehicle; - calculating (S102) the display value by correlating the change over time in the speed of the first other vehicle with the change over time in the speed of the second other vehicle during a calculation period in which the display value is calculated, - calculating (S102) the display value based on characteristics of either the change over time in the speed of the first other vehicle or the change over time in the speed of the second other vehicle, and - Setting (S102) a weighting factor for a characteristic portion of the calculation period in which an acceleration of the first other vehicle or an acceleration of the second other vehicle is greater than or equal to a second predetermined threshold value, greater than a weighting factor for the remaining part of the calculation period in which the acceleration is below the second predetermined threshold value.

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