Method for determining the time it takes for a public vehicle to pass through a road intersection and edge computing equipment

Abstract

The present application discloses a method for determining the duration of time a public vehicle takes to pass through a road intersection and an edge computing device, which relate to the field of vehicle technology. The edge computing device can determine the second driving parameters of at least one reference vehicle from the second driving parameters of a plurality of vehicles based on the first driving parameters of the public vehicle, and the at least one reference vehicle includes a vehicle whose position is between the position of the first driving parameter and the position of the stop line. Afterwards, the edge computing device can determine the target duration required for the public vehicle to pass through the stop line based on the driving parameters of the public vehicle, the position of the stop line, and the second driving parameters of at least one reference vehicle. It can be seen that the method provided by the present application can take into account the driving parameters of the public vehicle and the second driving parameters of the reference vehicle in the process of determining the target duration, thereby ensuring that the accuracy of the determined target duration is high, and then ensuring that the public vehicle can effectively have priority passage.

Description

Technical Field

[0001] The present application relates to the field of transportation technology, and in particular to a method for determining the time it takes for a public vehicle to pass through a road intersection and an edge computing device. Background Art

[0002] By improving the efficiency of bus traffic at intersections, traffic congestion can be effectively alleviated. When a bus approaches an intersection, if the current traffic light is green, the traffic signal controller can extend the green light by a certain amount; if the previous traffic light is red, the traffic signal controller can shorten the red light by a certain amount to allow the bus to pass first.

[0003] However, this method does not take into account the speed of buses approaching intersections, which may result in buses not being able to effectively have priority. Summary of the Invention

[0004] This application provides a method for determining the time it takes for a public vehicle to pass through a road intersection and an edge computing device, which can solve the problem of buses not being able to effectively give priority to other technologies. The technical solution is as follows:

[0005] In one aspect, a method for determining the duration of a public vehicle passing through a road intersection is provided. The method is applied to an edge computing device, wherein the edge computing device is respectively connected to a roadside unit and a radar detection component located at the road intersection, and the coverage range of the roadside unit is within the detection range of the radar detection component. The method comprises:

[0006] If a first driving parameter of a public vehicle sent by the roadside unit is received, then obtaining second driving parameters of multiple vehicles whose collection time is closest to the collection time of the first driving parameter from the driving parameters collected by the radar detection component, the first driving parameter including: the position and driving speed of the public vehicle, and the second driving parameter of each of the vehicles including: the position and driving speed of the vehicle;

[0007] Based on the position in the first driving parameter and the position of the stop line at the road intersection, obtaining a second driving parameter of at least one reference vehicle from the second driving parameters of the plurality of vehicles, the at least one reference vehicle including a vehicle located between the position of the public vehicle and the position of the stop line;

[0008] A target time required for the public vehicle to pass the stop line is determined based on the driving parameter of the public vehicle, the position of the stop line, and the second driving parameter of the at least one reference vehicle.

[0009] In another aspect, an edge computing device is provided. The edge computing device is respectively connected to a roadside unit and a radar detection component located at a road intersection, wherein the coverage range of the roadside unit is within the detection range of the radar detection component. The edge computing device includes a processor configured to:

[0010] If a first driving parameter of a public vehicle sent by the roadside unit is received, then obtaining second driving parameters of multiple vehicles whose collection time is closest to the collection time of the first driving parameter from the driving parameters collected by the radar detection component, the first driving parameter including: the position and driving speed of the public vehicle, and the second driving parameter of each of the vehicles including: the position and driving speed of the vehicle;

[0011] Based on the position in the first driving parameter and the position of the stop line at the road intersection, obtaining a second driving parameter of at least one reference vehicle from the second driving parameters of the plurality of vehicles, the at least one reference vehicle including a vehicle located between the position of the public vehicle and the position of the stop line;

[0012] A target time required for the public vehicle to pass the stop line is determined based on the driving parameter of the public vehicle, the position of the stop line, and the second driving parameter of the at least one reference vehicle.

[0013] Optionally, the processor is configured to:

[0014] determining a second driving parameter of the public vehicle from the second driving parameters of the plurality of vehicles, wherein a distance between a position in the second driving parameter of the public vehicle and a position in the first driving parameter is less than a distance threshold;

[0015] Based on the position of the second driving parameter of the public vehicle and the position of the stop line of the road intersection, the second driving parameter of at least one reference vehicle is determined from the second driving parameters of the plurality of vehicles.

[0016] Optionally, the first driving parameter and the position in the second driving parameter of each vehicle include: longitude coordinates and latitude coordinates; the processor is configured to:

[0017] within a target longitude interval and a target latitude interval, encoding the position in the first driving parameter and the position in the second driving parameter of each of the vehicles using a geohashing algorithm to obtain a first character string corresponding to the position in the first driving parameter and a second character string corresponding to each position in the second driving parameter;

[0018] determining a second driving parameter of the public vehicle from a plurality of second driving parameters based on a matching degree between the first character string and each of the second character strings, wherein a matching degree between a second character string corresponding to a position in the second driving parameter of the public vehicle and the first character string is greater than a matching degree threshold;

[0019] Among them, the upper limit of the target longitude interval is the maximum longitude of the target area, the lower limit of the target longitude interval is the minimum longitude of the target area, the upper limit of the target latitude interval is the maximum latitude of the target area, and the lower limit of the target latitude interval is the minimum latitude of the target area. The target area refers to the intersection area of the detection range of the radar detection component and the area where the road is located.

[0020] Optionally, the processor is configured to:

[0021] determining a candidate character string from the plurality of second character strings based on a matching degree between the first character string and each of the second character strings, wherein the matching degree between the candidate character string and the first character string is higher than a matching degree threshold;

[0022] Acquire a first driving trajectory of the public vehicle and a second driving trajectory of the candidate vehicle to which the position corresponding to the candidate character string belongs, wherein the first driving trajectory includes the first driving parameter, and the second driving trajectory includes the second driving parameter of the candidate vehicle;

[0023] Processing the first driving trajectory and the second driving trajectory using a dynamic time warping algorithm to obtain a similarity between the first driving trajectory and the second driving trajectory;

[0024] If the similarity is less than the similarity threshold, the second driving parameter of the candidate vehicle is determined as the second driving parameter of the public vehicle.

[0025] Optionally, the processor is configured to:

[0026] determining a first distance from the public vehicle to the stop line based on a position in the driving parameter of the public vehicle and a position of the stop line;

[0027] determining a first initial time required for the public vehicle to pass through the stop line based on the first distance and a travel speed among the travel parameters of the public vehicle;

[0028] For each of the reference vehicles, determining a second distance from the reference vehicle to the stop line based on a position in the second driving parameter and a position of the stop line;

[0029] determining a second initial time required for the reference vehicle to pass the stop line based on the second distance and a driving speed in a second driving parameter of the reference vehicle;

[0030] If the maximum duration of at least one of the second initial durations is greater than or equal to the first initial duration, the sum of the first initial duration and a target value is determined as the target duration required for the public vehicle to pass the stop line, the target value being the quotient of a target distance and a driving speed in a driving parameter of the public vehicle, and the target distance being the distance between the vehicle to which the maximum duration belongs and the public vehicle;

[0031] If the maximum duration is less than the first initial duration, the first initial duration is determined as the target duration required for the public vehicle to pass through the stop line.

[0032] Optionally, the first driving parameter further includes: a depth of a pedal of the public vehicle; and the processor is configured to:

[0033] determining an acceleration of the public vehicle based on the depth of the pedal;

[0034] A first initial time duration required for the public vehicle to pass through the stop line is determined based on the first distance, the acceleration, and a travel speed among the travel parameters of the public vehicle.

[0035] Optionally, the at least one reference vehicle includes: a vehicle whose position is between the position in the driving parameters of the public vehicle and the position of the stop line at the road intersection and has not changed lanes to an adjacent lane, and a vehicle whose position is in a target lane and changes lanes to the lane where the public vehicle is located, and after the lane change, is between the position in the driving parameters of the public vehicle and the position of the stop line at the road intersection;

[0036] The target lane is adjacent to the lane where the public vehicle is located.

[0037] On the other hand, an edge computing device is provided, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method for determining the duration of a public vehicle passing through a road intersection as described in the above aspects is implemented.

[0038] On the other hand, a computer-readable storage medium is provided, in which a computer program is stored. The computer program is loaded and executed by a processor to implement the method for determining the duration of a public vehicle passing through a road intersection as described in the above aspects.

[0039] On the other hand, a computer program product containing instructions is provided. When the computer program product is run on an edge computing device, the edge computing device executes the method for determining the duration of a public vehicle passing through a road intersection as described in the above aspects.

[0040] The beneficial effects of the technical solution provided by this application include at least:

[0041] The present application provides a method for determining the duration of time a public vehicle takes to pass through a road intersection and an edge computing device. The edge computing device can determine the second driving parameters of at least one reference vehicle from the second driving parameters of multiple vehicles based on the first driving parameters of the public vehicle. The at least one reference vehicle includes a vehicle whose position is between the position of the first driving parameter and the position of the stop line. Afterwards, the edge computing device can determine the target duration required for the public vehicle to pass through the stop line based on the driving parameters of the public vehicle, the position of the stop line, and the second driving parameters of at least one reference vehicle. It can be seen that the method provided by the present application can take into account the driving parameters of the public vehicle and the second driving parameters of the reference vehicle in the process of determining the target duration, thereby ensuring that the accuracy of the determined target duration is high, and then ensuring that the public vehicle can effectively have priority passage. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0043] Figure 1 This is a schematic diagram of the structure of a system for determining the time it takes a public vehicle to pass through a road intersection, provided in an embodiment of the present application;

[0044] Figure 2 This is a schematic diagram of the layout of a device for detecting driving parameters of a vehicle at a road intersection provided by an embodiment of the present application;

[0045] Figure 3 This is a flow chart of a method for determining the time it takes for a public vehicle to pass through a road intersection, provided by an embodiment of the present application;

[0046] Figure 4 This is a flow chart of another method for determining the time it takes for a public vehicle to pass through a road intersection provided by an embodiment of the present application;

[0047] Figure 5 This is a schematic diagram of encoding a position using a Geohash algorithm provided in an embodiment of the present application;

[0048] Figure 6 is a schematic diagram of a target area provided in an embodiment of the present application;

[0049] Figure 7 This is a distribution diagram of multiple locations provided in an embodiment of the present application. DETAILED DESCRIPTION

[0050] In order to make the objectives, technical solutions and advantages of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0051] Figure 1 This is a structural diagram of a system for determining the time it takes a public vehicle to pass through a road intersection, provided in an embodiment of the present application. Figure 2 This is a schematic diagram of the layout of a vehicle driving parameter detection device at a road intersection provided by an embodiment of the present application. Figure 1 and Figure 2 As can be seen, the system includes: edge computing device 01, RSU 02 located at Road A, and radar detection component 03. RSU 02 and radar detection component 03 both establish communication connections with edge computing device 021 via wireless or wired means. For example, RSU 02 and radar detection component 03 both establish communication connections with edge computing device 021 via a wired network.

[0052] RSU02 is located at the intersection of the road, and the coverage range of RSU02 (also known as the communication range) can be located within the detection range (also known as the acquisition range) of the radar detection component 03. The radar detection component 03 can include multiple radars 031, each of which can be connected to the edge computing device 01. The multiple radars 031 are distributed on the side of different roads. For example, Figure 2 As shown, the intersection of the road is a crossroads, and the radar detection component 03 includes four radars 031, each of which can be installed on a traffic light pole at the intersection.

[0053] Among them, RSU02 can receive the first driving parameter sent by the public vehicle within its detection range, and can upload the received first driving parameter and the collection time of the first driving parameter to the edge computing device 01. The first driving parameter may include the position and driving speed of the public vehicle. The position can reach the centimeter level. The public vehicle may refer to a vehicle equipped with an OBU. Among them, the OBU can communicate with RSU02 through cellular vehicle to everything (C-V2X) wireless communication technology, and the sampling rate of the OBU can be millisecond level.

[0054] Each radar 031 can collect second driving parameters of vehicles within its detection range, and can upload the collected second driving parameters and the time of collection of the second driving parameters to the edge computing device 01. The second driving parameters may include the location and driving speed of the vehicle.

[0055] Optionally, the edge computing device 01 may be a multi-access edge computing (MEC) device. Each radar 031 may be a multi-target wide-area microwave radar. The sampling rate of the radar 031 may be in the millisecond level.

[0056] The embodiment of the present application provides a method for determining the time length of a public vehicle passing through a road intersection, which is applied to an edge computing device, such as Figure 1 The edge computing device 01 shown is connected to the roadside unit and the radar detection component at the road intersection. The coverage of the roadside unit is within the detection range of the radar detection component. Figure 2 , the method comprising:

[0057] Step 101: If a first driving parameter of a public vehicle is received from an RSU, second driving parameters of multiple vehicles whose collection time is closest to the collection time of the first driving parameter are obtained from the driving parameters collected by the radar detection component.

[0058] Because the coverage area of an RSU at an intersection falls within the detection range of the radar detection component, a public vehicle that enters the coverage area of the RSU at the intersection also falls within the detection range of the radar detection component. Therefore, after receiving the first driving parameters of a public vehicle from the RSU, the edge computing device can obtain the second driving parameters of multiple vehicles whose collection times are closest to the collection time of the first driving parameters from the driving parameters collected by the radar detection component.

[0059] The first driving parameter may be collected in real time or periodically by an OBU installed in a public vehicle. The first driving parameter includes the location and speed of the public vehicle. The second driving parameter of each vehicle may include the location and speed of the vehicle. Optionally, the public vehicle may include at least one of a bus and a special vehicle, and the special vehicle may include at least one of an ambulance, a rescue vehicle, and a fire truck.

[0060] Step 102: Based on the position in the first driving parameter and the position of the stop line at the road intersection, obtain the second driving parameter of at least one reference vehicle from the second driving parameters of multiple vehicles.

[0061] The at least one reference vehicle includes a vehicle located between a position of the public vehicle and a position of the stop line.

[0062] Optionally, after obtaining the second driving parameters of multiple vehicles collected by the radar detection component, the edge computing device can directly determine each vehicle located between the position of the first driving parameter and the stop line as a reference vehicle, thereby obtaining the second driving parameter of at least one reference vehicle. In other words, the position of each reference vehicle in the second driving parameter is located between the position of the first driving parameter and the stop line.

[0063] Step 103: Determine a target time required for the public vehicle to pass the stop line based on the driving parameters of the public vehicle, the position of the stop line, and a second driving parameter of at least one reference vehicle.

[0064] The edge computing device may determine a first initial time required for the public vehicle to pass through the stop line based on the driving parameters of the public vehicle and the position of the stop line, and may determine a second initial time required for each reference vehicle to pass through the stop line based on the second driving parameters of each reference vehicle and the position of the stop line. The driving parameters of the public vehicle may be the first driving parameters of the public vehicle or the second driving parameters of the public vehicle.

[0065] Then, the edge computing device can determine the maximum duration from at least one second initial duration, and compare the maximum duration with the first initial duration. If the edge computing device determines that the first initial duration is greater than the maximum duration, the first initial duration is directly determined as the target duration required for the public vehicle to pass the stop line. If the edge computing device determines that the maximum duration is greater than the first initial duration, the sum of the first initial duration and the target value can be determined as the target duration required for the public vehicle to pass the stop line. The target value can be the quotient of the target distance and the driving speed in the driving parameters of the public vehicle. The target distance is the distance between the public vehicle and the vehicle to which the maximum duration belongs.

[0066] The edge computing device then sends a priority request to the traffic signal controller, including the target duration. Upon receiving the priority request, the traffic signal controller controls the phase of the traffic lights to prioritize public vehicles.

[0067] In summary, an embodiment of the present application provides a method for determining the duration of time a public vehicle takes to pass through a road intersection. The edge computing device can determine the second driving parameters of at least one reference vehicle from the second driving parameters of a plurality of vehicles based on the first driving parameters of the public vehicle, and the at least one reference vehicle includes a vehicle whose position is between the position of the first driving parameter and the position of the stop line. Afterwards, the edge computing device can determine the target duration required for the public vehicle to pass through the stop line based on the driving parameters of the public vehicle, the position of the stop line, and the second driving parameters of at least one reference vehicle. It can be seen that the method provided by the embodiment of the present application can take into account the driving parameters of the public vehicle and the second driving parameters of the reference vehicle in the process of determining the target duration, thereby ensuring that the accuracy of the determined target duration is high, and then ensuring that the public vehicle can effectively have priority passage.

[0068] Figure 3 This is another method for determining the time it takes for a public vehicle to pass through a road intersection provided by an embodiment of the present application. This method can be applied to edge computing devices. Figure 3 , the method may include:

[0069] Step 201: If a first driving parameter of a public vehicle is received from a roadside unit, second driving parameters of multiple vehicles whose collection time is closest to the collection time of the first driving parameter are obtained from the driving parameters collected by the radar detection component.

[0070] Since the coverage area of the RSU at the intersection is within the detection range of the radar detection component, when a public vehicle enters the coverage area of the RSU at the intersection, it also enters the detection range of the radar detection component. In other words, when the RSU receives the first driving parameter sent by the OBU installed in the public vehicle, the radar detection component can collect the second driving parameter of the public vehicle.

[0071] Therefore, after receiving the first driving parameters of the public vehicle sent by the RSU, the edge computing device can obtain the second driving parameters of multiple vehicles whose collection time is closest to the collection time of the first driving parameters from the driving parameters collected by the radar detection component.

[0072] The first driving parameter includes the location and speed of the public vehicle. The second driving parameter of each vehicle may include the location and speed of the vehicle. Optionally, the public vehicle may be at least one of a bus and a special vehicle, and the special vehicle may include at least one of an ambulance, a rescue vehicle, and a fire truck. The second driving parameter of each vehicle may also include the length of the vehicle.

[0073] Step 202: Determine a second driving parameter of a public vehicle from second driving parameters of a plurality of vehicles.

[0074] After obtaining the second driving parameters of multiple vehicles, the edge computing device can determine the second driving parameter of a public vehicle from the multiple second driving parameters. The distance between the location of the public vehicle in the second driving parameter and the location in the first driving parameter is less than a distance threshold. For example, the distance threshold may be 0.1 meters (m).

[0075] In one optional implementation, the edge computing device can directly determine the distance between the location in the second driving parameter of each vehicle and the location in the first driving parameter. The edge computing device can then determine the second driving parameter including the target location as the second driving parameter of the public vehicle. The distance between the target location and the location in the first driving parameter is less than a distance threshold. For example, the target location is closest to the first driving location.

[0076] In another optional implementation, the first driving parameter and the position in the second driving parameter of each vehicle both include: longitude coordinates and latitude coordinates. The edge computing device can first use a geohash algorithm to encode the position in the first driving parameter and the position in the second driving parameter of each vehicle to obtain a string corresponding to the position in the first driving parameter and a string corresponding to the position in each second driving parameter. Afterwards, the edge computing device can determine the second driving parameter of the public vehicle from the second driving parameters of multiple vehicles based on the matching degree of the string corresponding to the position in the first driving parameter and the string corresponding to the position in each second driving parameter.

[0077] The character string corresponding to the position in the second driving parameter of the public vehicle has a matching degree greater than a matching degree threshold with the character string corresponding to the position in the first driving parameter. For example, the second character string corresponding to the position in the second driving parameter of the public vehicle is the second character string with the highest matching degree with the character string corresponding to the position in the first driving parameter among multiple second character strings. The matching degree threshold may be pre-stored in the edge computing device.

[0078] Since edge computing devices can encode each location to obtain the string corresponding to each location, on the one hand, two-dimensional data can be converted into one-dimensional data, which facilitates the storage and search of locations; on the other hand, it can facilitate the search for locations in the vicinity of the area where a certain location is located, reducing the complexity of the search; on the other hand, the coordinates are fuzzy processed, which is conducive to privacy protection.

[0079] In an embodiment of the present application, the edge computing device can encode the position in the first driving parameter and the position in the second driving parameter of each of the multiple vehicles on a global scale. That is, when the edge computing device uses the Geohash algorithm to encode the various positions mentioned above (i.e., the position in the first driving parameter and the position in each second driving parameter), the longitude interval used is [-180, 180] and the latitude interval is [-90, 90]. That is, the longitude is greater than or equal to -180 degrees (°) and less than or equal to 180°, and the latitude is greater than or equal to -90° and less than or equal to 90°.

[0080] Combine Figure 5 , the process of encoding the location (39.923201, 116.390705) using the Geohash algorithm on the edge computing device is illustrated as follows:

[0081] First, the edge computing device can encode the latitude coordinate 39.923201 of the location. The edge computing device first divides the latitude interval [-90, 90] into two intervals, [-90, 0) and [0, 90]. If the latitude coordinate is in the left interval, it is marked as 0, and if the latitude coordinate is in the right interval, it is marked as 1. Since the latitude coordinate 39.923201 is in the interval [0, 90], it is encoded as 1. Since the string obtained at this time cannot accurately represent the latitude coordinate 39.923201, that is, the accuracy of the string is low, the interval [0, 90] is further divided into two intervals, [0, 45) and [45, 90]. Since the latitude coordinate 39.923201 is in the interval [0, 45), it is encoded as 0, and the resulting string is 10. By analogy, the range of the interval is continuously narrowed until the resulting interval approaches 39.92320. This results in the string 10111000110001111001 encoding the latitude coordinate 39.923201. Similarly, the edge computing device can encode the longitude coordinate 116.390705 at that location as the string 11010010110001000100. The length of the string is positively correlated with the number of interval divisions.

[0082] Then, the edge computing device can merge the string 10111000110001111001 obtained based on the latitude coordinate and the string 11010010110001000100 obtained based on the longitude coordinate to obtain the string corresponding to the location (39.923201, 116.390705). When merging the string 10111000110001111001 and the string 11010010110001000100, the edge computing device can place the string 10111000110001111001, obtained based on the latitude coordinates, in even positions, and place the string 11010010110001000100, obtained based on the longitude coordinates, in odd positions, resulting in the merged string 1110011101001000111100000011010101100001. The edge computing device can then convert the combined binary string into a base-32 string, wx4g0ec1. That is, for the combined binary string, the edge computing device can convert each five-bit group into a base-32 number using base32 encoding, resulting in a base-32 string.

[0083] It is understood that within the same encoding range (e.g., global range), the longer the string obtained by encoding the location, the smaller and more accurate the range represented by the string. For example, a 5-digit string can represent a rectangular area of 10 square kilometers, while a 6-digit string can represent a rectangular area of 0.34 square kilometers.

[0084] Alternatively, the edge computing device can use the Geohash algorithm to encode the position in the first driving parameter and the position in the second driving parameter of each vehicle within the target longitude interval and the target latitude interval to obtain a first character string corresponding to the position in the first driving parameter and a second character string corresponding to the position in each second driving parameter. The upper limit of the target longitude interval is the maximum longitude of the target area, the lower limit of the target longitude interval is the minimum longitude of the target area, the upper limit of the target latitude interval is the maximum latitude of the target area, and the lower limit of the target latitude interval is the minimum latitude of the target area. The target area refers to the intersection area of the detection range of the radar detection component and the area where the road is located.

[0085] In this way, the computational complexity of the edge computing device can be reduced while ensuring that the accurate second driving parameters of the public vehicle are obtained, thereby reducing the overhead of the edge computing device.

[0086] It can be understood that the implementation process of the edge computing device using the Geohash algorithm to encode the various locations mentioned above within the target longitude range and the target latitude range can refer to the implementation process of the edge computing device encoding the various locations globally, and the embodiments of this application will not be repeated here.

[0087] In the embodiment of the present application, the target longitude interval and the target latitude interval can be pre-stored by the edge computing device. Assume that the intersection area of the detection range of the radar detection component and the area where the road is located is Figure 6 The rectangular area shown. The position of the first vertex A of the rectangular area is (x1, y1), the position of the second vertex B is (x2, y2), the position of the third vertex C is (x3, y3), and the position of the fourth vertex D is (x4, y4). The horizontal coordinate of the position of any vertex from the first vertex A to the fourth vertex D is the latitude coordinate, and the vertical coordinate is the longitude coordinate.

[0088] The lower limit of the target latitude interval is min(x1, x2, x3, x4), the upper limit of the target latitude interval is max(x1, x2, x3, x4), the lower limit of the target longitude interval is min(y1, y2, y3, y4), and the upper limit of the target longitude interval is max(y1, y2, y3, y4).

[0089] In the embodiment of this application, according to Figure 5 It can be seen that the use of the Geohash algorithm to encode the position to obtain the string corresponding to the position is to continuously divide a rectangular area into multiple rectangular sub-areas until the position is located in a sub-area. Figure 7 , assuming the position in the first driving parameter is Figure 7 Position P in the image is located at the boundary of the region where it is located. Position Q in the region above position P is closest to position P, while the distance from position O in the same region as position P to position P is greater than the distance from position P to position Q. However, since position O and position P are in the same region, the string corresponding to position P has the highest match with the string corresponding to position Q.

[0090] Therefore, it can be seen that determining the second driving parameter of a public vehicle based on the matching degree between the character strings may result in an error in the second driving parameter. Based on this, in an embodiment of the present application, the edge computing device can determine the second driving parameter of the public vehicle through the following process:

[0091] The edge computing device may first determine, based on the degree of match between the first string and each second string, an alternative string from multiple second strings, where the degree of match between the alternative string and the first string exceeds a matching threshold. For example, the alternative string has the highest degree of match with the first string. Next, the edge computing device may obtain a first driving trajectory of the public vehicle and a second driving trajectory of the alternative vehicle to which the location corresponding to the alternative string belongs. The first driving trajectory includes first driving parameters, and the second driving trajectory includes second driving parameters of the alternative vehicle.

[0092] The edge computing device can then use a dynamic time warping (DTW) algorithm to process the first and second driving trajectories to determine the similarity between the first and second driving trajectories. The edge computing device can then compare the similarity with a similarity threshold. If the edge computing determines that the similarity is less than the similarity threshold, the second driving parameters of the candidate vehicle can be determined as the second driving parameters of the public vehicle.

[0093] If the edge computing device determines that the similarity is greater than or equal to the similarity threshold, it may determine a new candidate string from the multiple other second strings and repeat the aforementioned operations of determining the similarity between the first trajectory and the second trajectory of the candidate vehicle corresponding to the location of the new candidate string, and comparing the similarity with the similarity threshold, until the similarity between the first trajectory and the newly determined second trajectory is less than the similarity threshold. The other second strings may refer to second strings other than the already determined candidate strings.

[0094] In an embodiment of the present application, the first trajectory includes at least one location of a public vehicle, and the second trajectory includes at least one location of an alternative vehicle. The edge computing device can determine the distance between each location in the first trajectory and each location in the second trajectory, thereby obtaining a distance matrix between the first and second trajectories. The edge computing device can then determine a loss matrix based on this distance matrix and use the value in the lower right corner of the loss matrix as the similarity between the first and second trajectories.

[0095] Optionally, the distance between each position in the first trajectory and each position in the second trajectory may be a Euclidean distance.

[0096] It is understandable that, combined with Figure 7 For the case where the position P in the first driving parameter is located at the boundary of the area where it is located, the edge computing device can not only search for the character strings corresponding to the positions in the same area as the position P, but also search for the character strings corresponding to the positions in other areas adjacent to the area where the position P is located.

[0097] Step 203: Determine the second driving parameter of at least one reference vehicle from the second driving parameters of a plurality of vehicles based on the position of the second driving parameter of the public vehicle and the position of the stop line at the road intersection.

[0098] The at least one reference vehicle includes a vehicle located between the position of the public vehicle and the position of the stop line. The position of the public vehicle can be a position in the first driving parameter of the public vehicle or a position in the second driving parameter of the public vehicle.

[0099] In an optional implementation, the edge computing device may directly determine the vehicles located between the public vehicle and the stop line as reference vehicles. That is, each reference vehicle may be located in the same lane as the public vehicle.

[0100] In another optional implementation, the edge computing device may first determine the lane where the public vehicle is located based on the position in the driving parameters of the public vehicle, and determine the lane where the vehicle is located based on the position in the second driving parameters of each of the multiple vehicles. Afterwards, the edge computing device may determine a vehicle that is located between the position of the public vehicle and the position of the stop line and has not changed lanes to an adjacent lane as a reference vehicle, and may determine a vehicle that is located in a target lane (i.e., an adjacent lane to the lane where the public vehicle is located), changes lanes to the lane where the public vehicle is located, and is located between the position of the public vehicle and the position of the stop line after the lane change as a reference vehicle. In this way, the accuracy of the reference vehicle can be ensured, and then the accuracy of the target time required for the public vehicle to pass the stop line can be ensured to be high.

[0101] In an embodiment of the present application, for a public vehicle, the edge computing device can directly determine whether the public vehicle has changed lanes and the location of the public vehicle after the lane change based on the steering angle of the public vehicle's steering wheel. For a non-public vehicle, the edge computing device can determine whether the non-public vehicle has changed lanes and the location of the non-public vehicle after the lane change based on the steering angle of the public vehicle's driving trajectory. The steering angle of the driving trajectory can be determined based on at least one recent location of the non-public vehicle.

[0102] Optionally, for a public vehicle, the edge computing device can determine whether the public vehicle changes lanes and the position of the public vehicle after changing lanes based on the steering angle of the steering wheel and the status of the turn signal of the public vehicle.

[0103] Step 204: Determine a first distance from the public vehicle to the stop line based on the position of the public vehicle's driving parameters and the position of the stop line.

[0104] The edge computing device can determine the distance between the position in the driving parameters of the public vehicle and the position of the stop line as the distance from the public vehicle to the stop line.

[0105] Step 205: Determine a first initial time required for the public vehicle to pass the stop line based on the first distance and the driving speed in the driving parameters of the public vehicle.

[0106] The first initial duration is positively correlated with the first distance and negatively correlated with the travel speed of the public vehicle.

[0107] In an embodiment of the present application, the edge computing device can directly determine the quotient of the first distance and the driving speed as the first initial time required for the public vehicle to pass the stop line.

[0108] Alternatively, the first driving parameter of the public vehicle may further include the depth of a pedal. The edge computing device may first determine the acceleration of the public vehicle based on the pedal depth. Subsequently, the edge computing device may determine a first initial time required for the public vehicle to pass the stop line based on the first distance, the acceleration, and the speed of the public vehicle. The pedal may be an accelerator pedal or a brake pedal.

[0109] It can be seen from this that when determining the first initial time required for the public vehicle to pass the stop line, the acceleration of the public vehicle can also be considered, thereby ensuring that the accuracy of determining the first initial time is high.

[0110] Optionally, the edge computing device can determine the acceleration of the public vehicle based on a pre-stored correspondence between pedal depth and acceleration.

[0111] Optionally, the first driving parameter of the public vehicle may further include at least one of the following data: gear position, steering wheel angle, size, and type of the public vehicle. For example, the first driving parameter may further include the gear position, steering wheel angle, size, and type of the public vehicle. The gear position and heading angle of the public vehicle may be collected by an OBU installed in the public vehicle. The size and type of the public vehicle may be pre-stored in the OBU.

[0112] Step 206 : For each reference vehicle's second driving parameter, determine a second distance from the reference vehicle to the stop line based on the position in the second driving parameter and the position of the stop line.

[0113] For each reference vehicle, the edge computing device may determine the distance between the position of the reference vehicle in the second driving parameter and the position of the stop line as the second distance from the reference vehicle to the stop line.

[0114] Step 207: Determine a second initial time required for the reference vehicle to pass the stop line based on the second distance and the driving speed in the second driving parameter of the reference vehicle.

[0115] The second initial time required for each reference vehicle to pass through the stop line is positively correlated with the second distance and negatively correlated with the driving speed of the reference vehicle.

[0116] Step 208: Detect whether the maximum duration of at least one second initial duration is smaller than the first initial duration.

[0117] After the edge computing device obtains the first initial time required for the connected vehicle to pass the stop line and the second initial time required for each reference vehicle to pass the stop line, it can first determine the maximum time from the multiple second initial time. The edge computing device can then compare the first initial time with the maximum time. If the edge computing device determines that the maximum time is less than the first initial time, step 209 can be executed. If the edge computing device determines that the maximum time is greater than or equal to the first initial time, step 210 can be executed.

[0118] Step 209: Determine the first initial duration as the target duration required for the public vehicle to pass the stop line.

[0119] If the edge computing device determines that the maximum duration among the multiple second initial durations is less than the first initial duration, the first initial duration can be directly determined as the target duration required for the public vehicle to pass the stop line.

[0120] Step 210: The sum of the first initial duration and the target value is determined as the target duration required for the public vehicle to pass the stop line.

[0121] If the edge computing device determines that the maximum duration among the multiple second initial durations is greater than or equal to the first initial duration, the sum of the first initial duration and the target value may be determined as the target duration required for the public vehicle to pass the stop line. The target value is the quotient of the target distance and the driving speed in the driving parameters of the public vehicle, and the target distance is the distance between the vehicle with the maximum duration and the public vehicle.

[0122] In this embodiment of the present application, after the edge computing device obtains the target time required for a public vehicle to pass through the stop line, it can send a priority passage request to the traffic signal controller, including the target time. After receiving the priority passage request, the traffic signal controller can control the phase of the traffic light to shorten the waiting time for public vehicles to pass through the road intersection, thereby allowing public vehicles to pass first.

[0123] Optionally, the edge computing device can also be connected to a monitoring device, which can transmit received vehicle driving parameters to the monitoring device. The monitoring device pre-stores a map of the intersection. After receiving driving parameters for multiple vehicles, the monitoring device can display a vehicle icon at the location of each vehicle's driving parameter on the map. This allows for a visual display of vehicle distribution at the intersection.

[0124] Optionally, the map may be a high-precision map. The high-precision map may be a three-dimensional map obtained by processing pre-collected road information. The road information may include road surface information and roadside information. The road surface information includes lanes, medians located on the highway, curbs, road slope, road curvature, and road traffic signs.

[0125] It should be noted that the order of the steps of the method for determining the duration of a public vehicle passing through a road intersection provided in the embodiment of the present application can be appropriately adjusted, and the steps can be increased or decreased accordingly according to the circumstances. For example, step 202 can be deleted according to the circumstances, and the edge computing device can determine the second driving parameter of the reference vehicle based on the position in the first driving parameter of the public vehicle in step 203. Any person skilled in the art who can easily think of a method of variation within the technical scope disclosed in this application should be included in the scope of protection of this application, and therefore will not be described in detail.

[0126] In summary, an embodiment of the present application provides a method for determining the duration of time a public vehicle takes to pass through a road intersection. The edge computing device can determine the second driving parameters of at least one reference vehicle from the second driving parameters of multiple vehicles based on the first driving parameters of the public vehicle. The at least one reference vehicle includes a vehicle whose position is between the position of the first driving parameter and the position of the stop line. Afterwards, the edge computing device can determine the target duration required for the public vehicle to pass through the stop line based on the driving parameters of the public vehicle, the position of the stop line, and the second driving parameters of at least one reference vehicle. It can be seen that the method provided in the embodiment of the present application can take into account the second driving parameters of the reference vehicle in the process of determining the target duration, thereby ensuring that the accuracy of the determined target duration is high, and then ensuring that public vehicles can effectively have priority passage.

[0127] The present application also provides an edge computing device, which is connected to a roadside unit and a radar detection component at a road intersection, respectively. The coverage range of the roadside unit is within the detection range of the radar detection component. The edge computing device includes: a processor. The processor is used to:

[0128] If a first driving parameter of a public vehicle sent by a roadside unit is received, then second driving parameters of multiple vehicles whose collection time is closest to the collection time of the first driving parameter are obtained from the driving parameters collected by the radar detection component, where the first driving parameter includes: the position and driving speed of the public vehicle, and the second driving parameter of each vehicle includes: the position and driving speed of the vehicle;

[0129] Based on the position in the first driving parameter and the position of a stop line at the road intersection, obtaining a second driving parameter of at least one reference vehicle from second driving parameters of a plurality of vehicles, the at least one reference vehicle including a vehicle located between the position of the public vehicle and the position of the stop line;

[0130] A target time required for the public vehicle to pass the stop line is determined based on the driving parameter of the public vehicle, the position of the stop line, and a second driving parameter of at least one reference vehicle.

[0131] Optionally, the processor can be used to:

[0132] determining a second driving parameter of the public vehicle from the second driving parameters of the plurality of vehicles, wherein a distance between a position of the public vehicle in the second driving parameter and a position of the public vehicle in the first driving parameter is less than a distance threshold;

[0133] Based on the position in the second driving parameter of the public vehicle and the position of the stop line at the road intersection, the second driving parameter of at least one reference vehicle is determined from the second driving parameters of the plurality of vehicles.

[0134] Optionally, the first driving parameter and the second driving parameter of each vehicle each include a longitude coordinate and a latitude coordinate. The processor may be configured to:

[0135] Encoding the position in the first driving parameter and the position in the second driving parameter of each vehicle using a geohashing algorithm within the target longitude interval and the target latitude interval to obtain a first character string corresponding to the position in the first driving parameter and a second character string corresponding to each position in the second driving parameter;

[0136] determining a second driving parameter of the public vehicle from the plurality of second driving parameters based on a matching degree between the first character string and each second character string, wherein a matching degree between the second character string corresponding to a position in the second driving parameter of the public vehicle and the first character string is greater than a matching degree threshold;

[0137] Among them, the upper limit of the target longitude interval is the maximum longitude of the target area, the lower limit of the target longitude interval is the minimum longitude of the target area, the upper limit of the target latitude interval is the maximum latitude of the target area, and the lower limit of the target latitude interval is the minimum latitude of the target area. The target area refers to the intersection area of the detection range of the radar detection component and the road area.

[0138] Optionally, the processor can be used to:

[0139] determining a candidate character string from the plurality of second character strings based on a degree of matching between the first character string and each second character string, wherein a degree of matching between the candidate character string and the first character string is greater than a matching degree threshold;

[0140] Obtaining a first driving trajectory of a public vehicle and a second driving trajectory of an alternative vehicle to which the position corresponding to the alternative character string belongs, wherein the first driving trajectory includes a first driving parameter and the second driving trajectory includes a second driving parameter of the alternative vehicle;

[0141] The first driving trajectory and the second driving trajectory are processed by a dynamic time warping algorithm to obtain a similarity between the first driving trajectory and the second driving trajectory;

[0142] If the similarity is less than the similarity threshold, the second driving parameter of the candidate vehicle is determined as the second driving parameter of the public vehicle.

[0143] Optionally, the processor can be used to:

[0144] determining a first distance from the public vehicle to the stop line based on a position in the driving parameters of the public vehicle and a position of the stop line;

[0145] Determining a first initial time required for the public vehicle to pass the stop line based on the first distance and a driving speed in the driving parameters of the public vehicle;

[0146] For each reference vehicle's second driving parameter, determining a second distance from the reference vehicle to the stop line based on a position in the second driving parameter and a position of the stop line;

[0147] determining a second initial time required for the reference vehicle to pass the stop line based on the second distance and a driving speed in a second driving parameter of the reference vehicle;

[0148] If the maximum duration of at least one of the second initial durations is greater than or equal to the first initial duration, the sum of the first initial duration and the target value is determined as the target duration required for the public vehicle to pass the stop line, the target value is the quotient of the target distance and the driving speed in the driving parameters of the public vehicle, and the target distance is the distance between the vehicle to which the maximum duration belongs and the public vehicle;

[0149] If the maximum duration is less than the first initial duration, the first initial duration is determined as the target duration required for the public vehicle to pass the stop line.

[0150] Optionally, the first driving parameter further includes: the depth of the pedal of the public vehicle. The processor can be used to:

[0151] Determine the acceleration of a public vehicle based on the depth of the pedal;

[0152] A first initial time length required for the public vehicle to pass through the stop line is determined based on the first distance, the acceleration, and a travel speed among the travel parameters of the public vehicle.

[0153] Optionally, the at least one reference vehicle includes: a vehicle whose position is between a position in the driving parameters of the public vehicle and a position of a stop line at a road intersection and which has not changed lanes to an adjacent lane, and a vehicle whose position is in the target lane and which changes lanes to the lane where the public vehicle is located and, after the lane change, is between a position in the driving parameters of the public vehicle and a position of a stop line at the road intersection;

[0154] Among them, the target lane is adjacent to the lane where public vehicles are located.

[0155] In summary, an embodiment of the present application provides an edge computing device, which can determine the second driving parameters of at least one reference vehicle from the second driving parameters of multiple vehicles based on the first driving parameters of the public vehicle, and the at least one reference vehicle includes a vehicle whose position is between the position of the first driving parameter and the position of the stop line. Afterwards, the edge computing device can determine the target duration required for the public vehicle to pass the stop line based on the driving parameters of the public vehicle, the position of the stop line, and the second driving parameters of at least one reference vehicle. It can be seen that the edge computing device provided by the embodiment of the present application can consider the driving parameters of the public vehicle and the second driving parameters of the reference vehicle in the process of determining the target duration, so as to ensure that the accuracy of the determined target duration is high, and then ensure that the public vehicle can effectively have priority passage.

[0156] The embodiment of the present application further provides an edge computing device, which may include a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method for determining the duration of a public vehicle passing through a road intersection as provided in the above embodiment is implemented, for example Figure 3 or Figure 4 The method shown.

[0157] The embodiment of the present application provides a computer-readable storage medium storing a computer program, which is loaded by a processor and executes the method for determining the time length of a public vehicle passing through a road intersection provided in the above embodiment, for example Figure 3 or Figure 4 The method shown.

[0158] The present application also provides a computer program product including instructions. When the computer program product is run on an edge computing device, the edge computing device executes the method for determining the duration of a public vehicle passing through a road intersection provided in the above method embodiment, for example: Figure 3 or Figure 4 The method shown.

[0159] Those skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware, or by a program to instruct the relevant hardware, and the program may be stored in a computer-readable storage medium, which may be a read-only memory, a disk, or an optical disk, etc.

[0160] It should be understood that the term "and / or" used herein indicates that three relationships can exist. For example, "A and / or B" can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following objects are in an "or" relationship. Furthermore, the term "at least one" in this application means one or more, and the term "plurality" in this application means two or more.

[0161] In this application, the terms "first," "second," and the like are used to distinguish between identical or similar items with substantially the same purpose and function. It should be understood that "first," "second," and "nth" do not have a logical or temporal dependency, nor do they limit the quantity or order of execution. For example, without departing from the scope of the various examples described, a first driving parameter may be referred to as a second driving parameter, and similarly, a second driving parameter may be referred to as a first driving parameter.

[0162] The above description is merely an exemplary embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for determining the time it takes a public vehicle to pass through a road intersection, characterized in that: The method is applied to an edge computing device, wherein the edge computing device is respectively connected to a roadside unit and a radar detection component located at the road intersection, and the coverage range of the roadside unit is within the detection range of the radar detection component; the method includes: If a first driving parameter of a public vehicle sent by the roadside unit is received, then obtaining second driving parameters of multiple vehicles whose collection time is closest to the collection time of the first driving parameter from the driving parameters collected by the radar detection component, the first driving parameter including: the position and driving speed of the public vehicle, and the second driving parameter of each of the vehicles including: the position and driving speed of the vehicle; Based on the position in the first driving parameter and the position of the stop line at the road intersection, obtaining a second driving parameter of at least one reference vehicle from the second driving parameters of the plurality of vehicles, the at least one reference vehicle including a vehicle located between the position of the public vehicle and the position of the stop line; determining a first initial time required for the public vehicle to pass through the search stop line based on the driving parameters of the public vehicle and the position of the stop line; and determining a second initial time required for each reference vehicle to pass through the search stop line based on the second driving parameters of each reference vehicle in the at least one reference vehicle and the position of the stop line; If the maximum duration of at least one of the second initial durations is greater than or equal to the first initial duration, the sum of the first initial duration and the target value is determined as the target duration required for the public vehicle to pass the stop line, the target value is the quotient of the target distance and the driving speed in the driving parameters of the public vehicle, and the target distance is the distance between the vehicle to which the maximum duration belongs and the public vehicle; if the maximum duration is less than the first initial duration, the first initial duration is determined as the target duration required for the public vehicle to pass the stop line.

2. The method according to claim 1, characterized in that The acquiring, based on the position in the first driving parameter and the position of the stop line at the road intersection, the second driving parameter of at least one reference vehicle from the second driving parameters of the plurality of vehicles comprises: determining a second driving parameter of the public vehicle from the second driving parameters of the plurality of vehicles, wherein a distance between a position in the second driving parameter of the public vehicle and a position in the first driving parameter is less than a distance threshold; Based on the position of the second driving parameter of the public vehicle and the position of the stop line of the road intersection, the second driving parameter of at least one reference vehicle is determined from the second driving parameters of the plurality of vehicles.

3. The method according to claim 2, characterized in that The first driving parameter and the position in the second driving parameter of each of the vehicles include: longitude coordinates and latitude coordinates; determining the second driving parameter of the public vehicle from the second driving parameters of the plurality of vehicles includes: within a target longitude interval and a target latitude interval, encoding the position in the first driving parameter and the position in the second driving parameter of each of the vehicles using a geohashing algorithm to obtain a first character string corresponding to the position in the first driving parameter and a second character string corresponding to each position in the second driving parameter; determining a second driving parameter of the public vehicle from a plurality of second driving parameters based on a matching degree between the first character string and each of the second character strings, wherein a matching degree between a second character string corresponding to a position in the second driving parameter of the public vehicle and the first character string is greater than a matching degree threshold; Among them, the upper limit of the target longitude interval is the maximum longitude of the target area, the lower limit of the target longitude interval is the minimum longitude of the target area, the upper limit of the target latitude interval is the maximum latitude of the target area, and the lower limit of the target latitude interval is the minimum latitude of the target area. The target area refers to the intersection area of the detection range of the radar detection component and the area where the road is located.

4. The method according to claim 3, characterized in that The determining the second driving parameter of the public vehicle from a plurality of second driving parameters based on the matching degree between the first character string and each of the second character strings includes: determining a candidate character string from the plurality of second character strings based on a matching degree between the first character string and each of the second character strings, wherein the matching degree between the candidate character string and the first character string is higher than a matching degree threshold; Acquire a first driving trajectory of the public vehicle and a second driving trajectory of the candidate vehicle to which the position corresponding to the candidate character string belongs, wherein the first driving trajectory includes the first driving parameter, and the second driving trajectory includes the second driving parameter of the candidate vehicle; Processing the first driving trajectory and the second driving trajectory using a dynamic time warping algorithm to obtain a similarity between the first driving trajectory and the second driving trajectory; If the similarity is less than the similarity threshold, the second driving parameter of the candidate vehicle is determined as the second driving parameter of the public vehicle.

5. The method according to any one of claims 1 to 4, characterized in that: determining a first initial time required for the public vehicle to pass through the search stop line based on the driving parameters of the public vehicle and the position of the stop line; Determining a second initial time required for each reference vehicle to pass through the stop line based on a second driving parameter of each reference vehicle in the at least one reference vehicle and a position of the stop line includes: determining a first distance from the public vehicle to the stop line based on a position in the driving parameter of the public vehicle and a position of the stop line; determining a first initial time required for the public vehicle to pass through the stop line based on the first distance and a travel speed among the travel parameters of the public vehicle; For each of the reference vehicles, determining a second distance from the reference vehicle to the stop line based on a position in the second driving parameter and a position of the stop line; A second initial time period required for the reference vehicle to pass through the stop line is determined based on the second distance and a driving speed among the second driving parameters of the reference vehicle.

6. The method according to claim 5, characterized in that The first driving parameter further includes: a depth of a pedal of the public vehicle; and determining a first initial time required for the public vehicle to pass through the stop line based on the first distance and a driving speed in the driving parameter of the public vehicle includes: determining an acceleration of the public vehicle based on the depth of the pedal; A first initial time duration required for the public vehicle to pass through the stop line is determined based on the first distance, the acceleration, and a travel speed among the travel parameters of the public vehicle.

7. The method according to any one of claims 1 to 4, characterized in that: The at least one reference vehicle includes: a vehicle located between a position in the driving parameters of the public vehicle and a position of a stop line at the road intersection and not changing lanes to an adjacent lane, and a vehicle located in a target lane and changing lanes to the lane where the public vehicle is located, and after the lane change, located between a position in the driving parameters of the public vehicle and a position of a stop line at the road intersection; The target lane is adjacent to the lane where the public vehicle is located.

8. An edge computing device, characterized in that: The edge computing device is connected to a roadside unit and a radar detection component located at a road intersection, respectively. The coverage range of the roadside unit is within the detection range of the radar detection component. The edge computing device includes a processor, which is configured to: If a first driving parameter of a public vehicle sent by the roadside unit is received, then obtaining second driving parameters of multiple vehicles whose collection time is closest to the collection time of the first driving parameter from the driving parameters collected by the radar detection component, the first driving parameter including: the position and driving speed of the public vehicle, and the second driving parameter of each of the vehicles including: the position and driving speed of the vehicle; Based on the position in the first driving parameter and the position of the stop line at the road intersection, obtaining a second driving parameter of at least one reference vehicle from the second driving parameters of the plurality of vehicles, the at least one reference vehicle including a vehicle located between the position of the public vehicle and the position of the stop line; determining a first initial time required for the public vehicle to pass through the search stop line based on the driving parameters of the public vehicle and the position of the stop line; and determining a second initial time required for each reference vehicle to pass through the search stop line based on the second driving parameters of each reference vehicle in the at least one reference vehicle and the position of the stop line; If the maximum duration of at least one of the second initial durations is greater than or equal to the first initial duration, the sum of the first initial duration and the target value is determined as the target duration required for the public vehicle to pass the stop line, the target value is the quotient of the target distance and the driving speed in the driving parameters of the public vehicle, and the target distance is the distance between the vehicle to which the maximum duration belongs and the public vehicle; if the maximum duration is less than the first initial duration, the first initial duration is determined as the target duration required for the public vehicle to pass the stop line.

9. The edge computing device according to claim 8, characterized in that The processor is configured to: determining a second driving parameter of the public vehicle from the second driving parameters of the plurality of vehicles, wherein a distance between a position in the second driving parameter of the public vehicle and a position in the first driving parameter is less than a distance threshold; Based on the position of the second driving parameter of the public vehicle and the position of the stop line of the road intersection, the second driving parameter of at least one reference vehicle is determined from the second driving parameters of the plurality of vehicles.

10. The edge computing device according to claim 9, characterized in that The first driving parameter and the position in the second driving parameter of each vehicle include: longitude coordinates and latitude coordinates; the processor is configured to: within a target longitude interval and a target latitude interval, encoding the position in the first driving parameter and the position in the second driving parameter of each of the vehicles using a geohashing algorithm to obtain a first character string corresponding to the position in the first driving parameter and a second character string corresponding to each position in the second driving parameter; determining a second driving parameter of the public vehicle from a plurality of second driving parameters based on a matching degree between the first character string and each of the second character strings, wherein a matching degree between a second character string corresponding to a position in the second driving parameter of the public vehicle and the first character string is greater than a matching degree threshold; Among them, the upper limit of the target longitude interval is the maximum longitude of the target area, the lower limit of the target longitude interval is the minimum longitude of the target area, the upper limit of the target latitude interval is the maximum latitude of the target area, and the lower limit of the target latitude interval is the minimum latitude of the target area. The target area refers to the intersection area of the detection range of the radar detection component and the area where the road is located.

Images