Vehicle meeting point determination method, device and equipment and computer storage medium

Abstract

The invention discloses a meeting point determination method, device and equipment and a computer storage medium, a cloud platform obtains real-time vehicle driving information of a first vehicle and a second vehicle under the condition that a collected vehicle driving-in signal indicates that at least two vehicles enter a narrow road area and the driving directions of the at least two vehicles are different, and the real-time vehicle driving information of the first vehicle and the second vehicle is sent to the cloud platform. Future path information and theoretical conflict points are generated according to the real-time vehicle driving information of the first vehicle and the second vehicle, and before the first vehicle and the second vehicle drive to the theoretical conflict points, target vehicle meeting points are obtained through screening according to the future path information and the theoretical conflict points and then sent to the first vehicle and the second vehicle; and the first vehicle and the second vehicle output the position information of the target meeting point. Thus, the first vehicle and the second vehicle output the position information, dynamically generated by the cloud platform, of the target meeting point to the driver, then the vehicles are guided to alternately pass at the target meeting point, and the vehicle passing efficiency of the narrow road area can be improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of Internet of Vehicles and artificial intelligence, and particularly relates to a meeting point determination method and device, equipment and a computer storage medium. BACKGROUND

[0002] The meeting behavior is highly dependent on the experience, visual communication and even tacit understanding of the individual driver, and is communicated through primitive methods such as honking and flashing lights, so as to temporarily select a relatively wide area on the roadside for avoidance.

[0003] The prior art realizes vehicle scheduling by presetting a meeting point at a fixed position. A sensing device such as a camera and a microwave radar is usually installed on a relatively wide area selected by a human or a convex meeting area constructed on a road section, so as to monitor and analyze the vehicles entering the area, and then guide the vehicles to alternate passing through an indicator or a simple communication method. However, the effective meeting point of a rural narrow road is not fixed. In addition to the fixed meeting area constructed by a human, a large number of meeting points are natural wide areas formed by the geological conditions of the roadside, the empty space in front of a farmer's house, etc. These areas may dynamically appear or fail due to non-human factors such as crop accumulation, slope landslide and vehicle parking. The static and fixed meeting point selection mode of the prior art cannot adapt to this dynamic nature at all. SUMMARY

[0004] The embodiments of the present application provide a meeting point determination method, device, equipment and computer storage medium, which can generate a dynamic meeting point through dynamic analysis, and can improve the vehicle passing efficiency.

[0005] In a first aspect, the embodiments of the present application provide a meeting point determination method applied to a cloud platform, which can include: Collecting a vehicle entering signal, the vehicle entering signal being used to indicate the number of vehicles entering a narrow road area and the driving direction of each vehicle, the narrow road area being a road section with an effective passing width less than a preset safety threshold; In a case where the vehicle entering signal indicates that at least two vehicles enter the narrow road area and the driving directions of the at least two vehicles are different, acquiring real-time vehicle driving information of a first vehicle and real-time vehicle driving information of a second vehicle, the first vehicle being any one of the at least two vehicles entering the narrow road area, and the second vehicle being any one of the at least two vehicles entering the narrow road area except the first vehicle; Generating future path information and a theoretical conflict point according to the real-time vehicle driving information of the first vehicle and the real-time vehicle driving information of the second vehicle, the future path information being used to indicate the predicted driving paths of the first vehicle and the second vehicle and the widths of the first vehicle and the second vehicle, and the theoretical conflict point being used to indicate the meeting position of the first vehicle and the second vehicle in theory; Before the first vehicle and the second vehicle travel to the theoretical conflict point, a target meeting point is screened out from a meeting point list according to the future path information and the theoretical conflict point, the meeting point list being generated according to historical vehicle driving information of a plurality of vehicles entering the narrow road area, and the meeting point list including a plurality of potential meeting points and a passing width of each potential meeting point; Position information of the target meeting point is sent to the first vehicle and the second vehicle, so that the first vehicle and the second vehicle output the position information of the target meeting point.

[0006] In one of the embodiments, before the target meeting point is screened out from the meeting point list according to the future path information and the theoretical conflict point, the method further includes: At a plurality of time points, the following steps are performed respectively: when the vehicle entering signal indicates that at least two vehicles enter the narrow road area and the driving directions of the at least two vehicles are different, historical vehicle driving information of a third vehicle and historical vehicle driving information of a fourth vehicle are collected, the third vehicle being any one of the at least two vehicles entering the narrow road area, and the fourth vehicle being any one of the at least two vehicles entering the narrow road area except the third vehicle, the vehicle driving information being used to indicate a driving trajectory of a vehicle and a width of the vehicle; a meeting trajectory is matched according to the historical vehicle driving information of the third vehicle and the historical vehicle driving information of the fourth vehicle, and position information of a potential meeting point is calculated; The meeting point list is generated according to the position information of the potential meeting point corresponding to each vehicle entering the narrow road area at the plurality of time points and the width of each vehicle.

[0007] In one of the embodiments, the historical vehicle driving information includes high-precision position information, a driving speed, a heading angle, and vehicle information of the vehicle, and the matching of the meeting trajectory according to the historical vehicle driving information of the third vehicle and the historical vehicle driving information of the fourth vehicle to calculate the position information of the potential meeting point includes: After a first time point, the driving speed and the heading angle of the third vehicle and the fourth vehicle at a plurality of time points are obtained, the first time point being a time point at which the third vehicle and the fourth vehicle are first apart by a first preset threshold; When the driving speed of a target vehicle is lower than a second preset threshold and the heading angle of the target vehicle changes by an angle greater than a preset angle, a current state of the target vehicle is determined as a reverse driving state, the target vehicle being any one of the third vehicle and the fourth vehicle. after the second time, the heading angle of the target vehicle at the current time is compared with the heading angle of the target vehicle between the first time and the second time, to obtain a comparison result, the second time being the time when the state of the target vehicle is determined to be the reversing state; According to the comparison result, the high-precision position information of the third vehicle, and the high-precision position information of the fourth vehicle, generate meeting trajectory information, the meeting trajectory information including a set of driving trajectory points of the third vehicle, a set of driving trajectory points of the fourth vehicle, a width of the third vehicle, a width of the fourth vehicle, a preset safety distance, and a safety distance coefficient, the set of driving trajectory points including a plurality of position points and time information corresponding to each position point; According to the width of the third vehicle, the width of the fourth vehicle, the preset safety distance, and the safety distance coefficient, calculate the minimum meeting distance; Iterate through each trajectory point in the set of driving trajectory points of the third vehicle, and perform the following operations: create a time window for a first trajectory point, the first trajectory point being any position point in the set of driving trajectory points of the third vehicle; match a second trajectory point in the set of driving trajectory points of the fourth vehicle based on the time window; calculate the spatial distance between the first trajectory point and the second trajectory point according to the longitude and latitude corresponding to the first trajectory point and the second trajectory point; and in the case that the spatial distance is less than or equal to the minimum meeting distance, calculate the position information of the potential meeting point.

[0008] In one of the embodiments, the above-mentioned generation of meeting trajectory information according to the comparison result, the high-precision position information of the third vehicle, and the high-precision position information of the fourth vehicle includes: In the case that the comparison result indicates that the heading angle of the target vehicle at the current time is the same as the heading angle of the target vehicle between the first time and the second time, and the high-precision position information of the third vehicle and the fourth vehicle indicates that the third vehicle and the fourth vehicle are continuously approaching, generate a first meeting trajectory, the first meeting trajectory being the meeting trajectory information of the third vehicle and the fourth vehicle between the third time and the fourth time, or between the fifth time and the fourth time, the third time being the time when the heading angle of the target vehicle changes to the heading angle of the target vehicle between the first time and the second time after the second time, the fourth time being the time when the third vehicle and the fourth vehicle are again at a first preset threshold distance, and the fifth time being the time when the driving speed of the target vehicle becomes 0 after the second time; In a case where the driving speed of the target vehicle is higher than or equal to a second preset threshold value, and / or the change angle of the heading angle of the target vehicle is less than or equal to a preset angle, a second meeting track is generated, the second meeting track being meeting track information of the third vehicle and the fourth vehicle between the first time and the fourth time.

[0009] In one of the embodiments, after the above-mentioned generation of the list of meeting points according to the potential meeting points of the vehicles driving into the narrow road area at the plurality of times and the widths of the vehicles, the method further comprises: According to the plurality of potential meeting points in the list of meeting points and the passing widths of the potential meeting points, a training sample set is constructed, the training sample set comprising a plurality of training samples, each training sample comprising a meeting point feature vector and a meeting point label, the meeting point feature vector being an input of a to-be-trained meeting point prediction model, the meeting point label being an output of the to-be-trained meeting point prediction model, and the meeting point label being used to indicate whether the meeting is successful; For each training sample, the following steps are performed: the meeting point feature vector is input into the to-be-trained meeting point prediction model, and a predicted meeting success probability is calculated through forward propagation; According to the cross entropy between the meeting point label of each training sample and the predicted meeting success probability, a loss function is generated, the loss function being: wherein, is the number of training samples, is the meeting point label, is the predicted meeting success probability: According to the loss function, the to-be-trained meeting point prediction model is iteratively updated until the loss function meets a preset training stop condition, and a meeting point prediction model is obtained. The screening of the target meeting point from the list of meeting points according to the future path information and the theoretical conflict point before the first vehicle and the second vehicle drive to the theoretical conflict point comprises: The screening of the target meeting point from the list of meeting points according to the future path information and the theoretical conflict point before the first vehicle and the second vehicle drive to the theoretical conflict point comprises:

[0010] In one of the embodiments, the screening of the target meeting point from the list of meeting points according to the future path information and the theoretical conflict point comprises: Before the first vehicle and the second vehicle travel to the theoretical conflict point, all potential meeting points in the meeting point list are traversed to select the potential meeting point closest to the theoretical conflict point and having a passing width greater than the sum of the widths of the first vehicle and the second vehicle as the target meeting point.

[0011] In one of the embodiments, after the target meeting point is selected from the meeting point list according to the future path information and the theoretical conflict point, the method further includes: generating a warning information according to the position information of the theoretical conflict point and the target meeting point, the warning information including a driving suggestion for the first vehicle and the second vehicle, the driving suggestion indicating whether the vehicle needs to stop at the target meeting point to wait; sending the warning information to the first vehicle and the second vehicle to make the first vehicle and the second vehicle output the driving suggestion.

[0012] In a second aspect, the embodiments of the present application provide a meeting point determination method, applied to a vehicle-mounted device, the vehicle-mounted device being arranged on a vehicle entering a narrow road area, and the method can include: receiving position information of a target meeting point sent by a cloud platform, the position information of the target meeting point being generated by the cloud platform based on real-time vehicle driving information of a first vehicle and real-time vehicle driving information of a second vehicle, the cloud platform being configured to generate future path information and a theoretical conflict point in a case that a vehicle entering signal indicates that at least two vehicles enter the narrow road area and driving directions of the at least two vehicles are different, the narrow road area being a road section with an effective passing width less than a preset safety threshold, the first vehicle being any one of the at least two vehicles entering the narrow road area, the second vehicle being any one of the at least two vehicles entering the narrow road area except the first vehicle, the future path information being used to indicate predicted driving paths of the first vehicle and the second vehicle and widths of the first vehicle and the second vehicle, the theoretical conflict point being used to indicate a meeting position of the first vehicle and the second vehicle in theory, the meeting point list being generated according to historical vehicle driving information of a plurality of vehicles entering the narrow road area, and the meeting point list including a plurality of potential meeting points and passing widths of the potential meeting points; outputting the position information of the target meeting point through an interactive interface.

[0013] In a third aspect, the embodiments of the present application provide a meeting point determination device, applied to a cloud platform, and the device can include: The collection module is configured to collect a vehicle entry signal, the vehicle entry signal being used to indicate a number of vehicles entering a narrow road area and driving directions of the vehicles, and the narrow road area being a road section with an effective passing width less than a preset safety threshold; The acquisition module is configured to acquire real-time vehicle driving information of a first vehicle and real-time vehicle driving information of a second vehicle when the vehicle entry signal indicates that at least two vehicles enter the narrow road area and driving directions of the at least two vehicles are different, the first vehicle being any one of the at least two vehicles entering the narrow road area, and the second vehicle being any one of the at least two vehicles entering the narrow road area except the first vehicle; The generation module is configured to generate future path information and a theoretical conflict point according to the real-time vehicle driving information of the first vehicle and the real-time vehicle driving information of the second vehicle, the future path information being used to indicate predicted driving paths of the first vehicle and the second vehicle and widths of the first vehicle and the second vehicle, and the theoretical conflict point being used to indicate a theoretically meeting position of the first vehicle and the second vehicle; The determination module is configured to filter a target meeting point from a meeting point list according to the future path information and the theoretical conflict point before the first vehicle and the second vehicle drive to the theoretical conflict point, the meeting point list being generated according to historical vehicle driving information of a plurality of vehicles entering the narrow road area, and the meeting point list including a plurality of potential meeting points and passing widths of the potential meeting points. The sending module is configured to send position information of the target meeting point to the first vehicle and the second vehicle, so that the first vehicle and the second vehicle output the position information of the target meeting point.

[0014] In a fourth aspect, an embodiment of the present application provides a meeting point determination apparatus applied to a vehicle-mounted device, the vehicle-mounted device being arranged on a vehicle entering a narrow road area, and the apparatus can include: The receiving module is configured to receive position information of a target meeting point sent by a cloud platform, wherein the position information of the target meeting point is generated by the cloud platform based on real-time vehicle driving information of a first vehicle and real-time vehicle driving information of a second vehicle, in a case that the vehicle entering signal indicates that at least two vehicles enter the narrow road area and driving directions of the at least two vehicles are different, and the target meeting point is obtained by screening a future path information and a theoretical conflict point in a meeting point list before the first vehicle and the second vehicle drive to the theoretical conflict point, the narrow road area is a road section with an effective passing width less than a preset safety threshold, the first vehicle is any one of the at least two vehicles entering the narrow road area, the second vehicle is any one of the at least two vehicles entering the narrow road area except the first vehicle, the future path information is used to indicate predicted driving paths of the first vehicle and the second vehicle and widths of the first vehicle and the second vehicle, the theoretical conflict point is used to indicate a theoretically meeting position of the first vehicle and the second vehicle, and the meeting point list is generated based on historical vehicle driving information of a plurality of vehicles entering the narrow road area, and the meeting point list includes a plurality of potential meeting points and passing widths of the potential meeting points. The output module is configured to output the position information of the target meeting point through an interactive interface.

[0015] In a fifth aspect, an electronic device is provided, and the device includes: a processor; a memory for storing processor-executable instructions; The processor is configured to execute the instructions to implement the meeting point determination method as shown in any one of the embodiments of the first aspect and the second aspect.

[0016] In a sixth aspect, an embodiment of the present application provides a computer storage medium, and a computer program is stored on the computer readable storage medium. The computer program is executed by a processor to implement the meeting point determination method as shown in any one of the embodiments of the first aspect and the second aspect.

[0017] In a seventh aspect, an embodiment of the present application further provides a computer program product, and the computer program product includes a computer program stored in a readable storage medium. At least one processor of a device reads and executes the computer program from the storage medium, so that the device executes the meeting point determination method as shown in any one of the embodiments of the first aspect and the second aspect.

[0018] The embodiment of the application provides a meeting point determination method, device and equipment and a computer storage medium. The cloud platform collects a vehicle entering signal, obtains real-time vehicle driving information of a first vehicle and real-time vehicle driving information of a second vehicle in the case that the vehicle entering signal indicates that at least two vehicles enter the narrow road area and driving directions of the at least two vehicles are different, generates future path information and a theoretical conflict point according to the real-time vehicle driving information of the first vehicle and the real-time vehicle driving information of the second vehicle, screens a target meeting point in a meeting point list according to the future path information and the theoretical conflict point before the first vehicle and the second vehicle drive to the theoretical conflict point, and finally sends position information of the target meeting point to the first vehicle and the second vehicle, so that the first vehicle and the second vehicle output the position information of the target meeting point.

[0019] In this way, the future path information and the theoretical conflict point are dynamically generated based on the obtained real-time vehicle driving information of the first vehicle and the second vehicle, the target meeting point is determined and sent to the first vehicle and the second vehicle, so that the first vehicle and the second vehicle output the position information of the target meeting point to the driver, and then the drivers of the first vehicle and the second vehicle are guided to alternately pass through the target meeting point, thereby improving the vehicle passing efficiency of the narrow road area. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the application, the drawings needed to be used in the embodiments of the application will be briefly introduced. Those skilled in the art can obtain other drawings according to these drawings without creating any creative labor.

[0021] Figure 1 is a schematic diagram of a meeting point determination system architecture provided by an embodiment of the application; Figure 2 is a schematic diagram of a meeting point determination method provided by an embodiment of the application; Figure 3 is a schematic diagram of another meeting point determination system architecture provided by an embodiment of the application; Figure 4 is a schematic diagram of another meeting point determination method provided by an embodiment of the application; Figure 5 is a schematic diagram of a narrow road electronic fence provided by an embodiment of the application; Figure 6 is a schematic diagram of another meeting point determination method provided by an embodiment of the application; Figure 7 is a schematic diagram of another meeting point determination method provided by an embodiment of the application; Figure 8 is a flowchart of another method for determining a meeting point according to an embodiment of the present application; Figure 9 is a schematic diagram of a meeting point according to an embodiment of the present application; Figure 10 is a flowchart of another method for determining a meeting point according to an embodiment of the present application; Figure 11 is a flowchart of another method for determining a meeting point according to an embodiment of the present application; Figure 12 is a flowchart of another method for determining a meeting point according to an embodiment of the present application; Figure 13 is a schematic diagram of a meeting point scheduling according to an embodiment of the present application; Figure 14 is a schematic diagram of a meeting point determining apparatus according to an embodiment of the present application; Figure 15 is a schematic diagram of another meeting point determining apparatus according to an embodiment of the present application; Figure 16 is a schematic diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0022] The features and exemplary embodiments of the various aspects of the present application will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely intended to explain the present application, and are not intended to limit the present application. The present application can be implemented without some of the specific details described below. The following description of the embodiments is merely provided to give a better understanding of the present application by showing examples of the present application.

[0023] It should be noted that the terms such as first and second, etc., are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Also, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such a process, method, article or device. Without more limitations, the elements defined by the statement "include" do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0024] Based on the background section, in rural areas, there are a large number of narrow roads with narrow roads, irregular width, poor visibility and complex road conditions. Such roads usually lack formal traffic signs, markings and dedicated passing facilities. When multiple vehicles meet on such roads, passing behavior becomes a great challenge. Passing behavior is highly dependent on the individual experience of the driver, visual communication and even tacit understanding, through primitive means such as honking and flashing lights to temporarily select a relatively wide area on the roadside for avoidance.

[0025] The prior art realizes vehicle scheduling by presetting passing points at fixed positions, usually installing sensing devices such as cameras and microwave radars at relatively wide areas or constructed convex passing strips selected by humans in advance, monitoring and analyzing vehicles entering the area, and then guiding vehicles to alternate by means of signs or simple communication. However, the effective passing points of rural narrow roads are not fixed. In addition to the fixed passing strips constructed by humans, a large number of passing points are natural wide areas formed by roadside geological conditions, farmer's front yard, etc. These areas may dynamically appear or fail due to non-human factors such as crop accumulation, slope landslide and vehicle parking. The static and fixed passing point selection mode of the prior art cannot adapt to this dynamic nature.

[0026] In order to solve the problems existing in the prior art, the embodiments of the present application provide a passing point determination method, device, equipment and computer storage medium. The cloud platform acquires a vehicle entering signal, obtains real-time vehicle driving information of a first vehicle and real-time vehicle driving information of a second vehicle when at least two vehicles enter the narrow road area and the driving directions of the at least two vehicles are different, generates future path information and a theoretical conflict point according to the real-time vehicle driving information of the first vehicle and the real-time vehicle driving information of the second vehicle, screens a target passing point from a passing point list according to the future path information and the theoretical conflict point before the first vehicle and the second vehicle drive to the theoretical conflict point, and finally sends position information of the target passing point to the first vehicle and the second vehicle to make the first vehicle and the second vehicle output the position information of the target passing point.

[0027] In this way, based on the obtained real-time vehicle driving information of the first vehicle and the second vehicle, the future path information and the theoretical conflict point are dynamically generated, and then the target passing point is determined and sent to the first vehicle and the second vehicle, so that the first vehicle and the second vehicle output the position information of the target passing point to the driver, and then guide the drivers of the first vehicle and the second vehicle to alternate at the target passing point, thereby improving the vehicle passing efficiency of the narrow road area.

[0028] The passing point determination method provided by the embodiments of the present application will be introduced first.

[0029] Specifically, the meeting point determination method provided by the embodiments of the present application can be based on Figure 1 The meeting point determination system is shown in the implementation. As shown in the figure Figure 1 The meeting point determination system 100 includes: a cloud platform 110; and a plurality of vehicle-mounted devices 120; The cloud platform 110 can establish a communication connection with the plurality of vehicle-mounted devices 120 through a network or other wireless communication methods. The vehicle-mounted device 120 is arranged on a vehicle entering a narrow road area.

[0030] The cloud platform 110 can be used to perform the following operations: Collecting vehicle entry signals, the vehicle entry signals being used to indicate the number of vehicles entering a narrow road area and the driving directions of each vehicle, the narrow road area being a road section with an effective passing width less than a preset safety threshold; In the case where the vehicle entry signals indicate that at least two vehicles enter the narrow road area and the driving directions of the at least two vehicles are different, obtaining real-time vehicle driving information of a first vehicle and real-time vehicle driving information of a second vehicle, the first vehicle being any one of the at least two vehicles entering the narrow road area, and the second vehicle being any one of the at least two vehicles entering the narrow road area except the first vehicle; According to the real-time vehicle driving information of the first vehicle and the real-time vehicle driving information of the second vehicle, generating future path information and a theoretical conflict point, the future path information being used to indicate the predicted driving paths of the first vehicle and the second vehicle and the widths of the first vehicle and the second vehicle, and the theoretical conflict point being used to indicate the theoretically meeting position of the first vehicle and the second vehicle; Before the first vehicle and the second vehicle drive to the theoretical conflict point, according to the future path information and the theoretical conflict point, screening a target meeting point from a meeting point list, the meeting point list being generated according to historical vehicle driving information of a plurality of vehicles entering the narrow road area, and the meeting point list including a plurality of potential meeting points and the passing widths of the potential meeting points; Sending the position information of the target meeting point to the first vehicle and the second vehicle, so as to make the first vehicle and the second vehicle output the position information of the target meeting point.

[0031] The plurality of vehicle-mounted devices 120 can be used to perform the following operations: receive location information of a target meeting point sent by a cloud platform, the location information of the target meeting point being generated by the cloud platform based on real-time vehicle driving information of a first vehicle and real-time vehicle driving information of a second vehicle in a case where the vehicle entering signal indicates that at least two vehicles enter the narrow road area and the driving directions of the at least two vehicles are different, the future path information being used to indicate predicted driving paths of the first vehicle and the second vehicle and widths of the first vehicle and the second vehicle, the theoretical conflict point being used to indicate a theoretically meeting position of the first vehicle and the second vehicle, the meeting point list being generated according to historical vehicle driving information of a plurality of vehicles entering the narrow road area, and the meeting point list including a plurality of potential meeting points and passing widths of the potential meeting points; output the location information of the target meeting point through an interactive interface.

[0032] Based on the above meeting point determination system, the meeting point determination method provided by the embodiments of the present application will be introduced first. As shown in the figure, Figure 2 the meeting point determination method provided by the embodiments of the present application includes the following steps: S201: The cloud platform collects a vehicle entering signal, the vehicle entering signal being used to indicate a number of vehicles entering a narrow road area and driving directions of the vehicles, and the narrow road area being a road section with an effective passing width less than a preset safety threshold; S202: The cloud platform obtains real-time vehicle driving information of a first vehicle and real-time vehicle driving information of a second vehicle in a case where the vehicle entering signal indicates that at least two vehicles enter the narrow road area and the driving directions of the at least two vehicles are different, the first vehicle being any one of the at least two vehicles entering the narrow road area, and the second vehicle being any one of the at least two vehicles entering the narrow road area except the first vehicle; S203: The cloud platform generates future path information and a theoretical conflict point according to the real-time vehicle driving information of the first vehicle and the real-time vehicle driving information of the second vehicle, the future path information being used to indicate predicted driving paths of the first vehicle and the second vehicle and widths of the first vehicle and the second vehicle, and the theoretical conflict point being used to indicate a theoretically meeting position of the first vehicle and the second vehicle; S204: Before the first vehicle and the second vehicle reach the theoretical conflict point, the cloud platform filters the target meeting point from the meeting point list based on the future path information and the theoretical conflict point. The meeting point list is generated based on the historical vehicle driving information of multiple vehicles entering the narrow road area. The meeting point list includes multiple potential meeting points and the passage width of each potential meeting point. S205: The cloud platform sends the location information of the target meeting point to the first vehicle and the second vehicle; S206: The on-board equipment on the first vehicle and the second vehicle outputs the location information of the target meeting point through the interactive interface.

[0033] The above is a method for determining a meeting point provided by an embodiment of this application. The cloud platform collects vehicle entry signals. When the vehicle entry signals indicate that at least two vehicles have entered the narrow road area and the driving directions of the at least two vehicles are different, it obtains the real-time vehicle driving information of the first vehicle and the real-time vehicle driving information of the second vehicle. Then, based on the real-time vehicle driving information of the first vehicle and the second vehicle, it generates future path information and theoretical conflict points. Before the first vehicle and the second vehicle reach the theoretical conflict point, the target meeting point is selected from the meeting point list based on the future path information and the theoretical conflict point. Finally, the location information of the target meeting point is sent to the first vehicle and the second vehicle so that the first vehicle and the second vehicle can output the location information of the target meeting point.

[0034] Thus, based on the real-time vehicle driving information of the first and second vehicles, future path information and theoretical conflict points are dynamically generated, and then the target meeting point is determined and sent to the first and second vehicles, so that the first and second vehicles output the location information of the target meeting point to the driver, thereby guiding the drivers of the first and second vehicles to take turns passing at the target meeting point, improving the vehicle traffic efficiency in narrow road areas.

[0035] In S201, in one example, such as Figure 3As shown, the cloud platform can be a Vehicle-to-Everything (V2X) vehicle-road cooperative operation and management platform 310, which may include a vehicle management module 311, an equipment management module 312, a road information management module 313, a road electronic fence module 314, a vehicle meeting behavior analysis module 315, and an early warning module 316. Correspondingly, the on-board equipment 320 may also include a Vehicle-to-Everything Software Development Kit (V2X-SDK) 321, a high-precision positioning module 322, and a data communication module 323.

[0036] In a specific embodiment, the meeting point determination system, which consists of a vehicle-road cooperative operation and management platform and multiple vehicle-mounted devices, includes the following simplified scheme: (1) collecting historical and real-time trajectories and analyzing vehicle driving behavior to confirm meeting points. (2) calculating the minimum road width based on the width of the passing vehicles and aggregating the meeting areas. (3) monitoring vehicles passing through narrow roads, predicting the meeting position without vehicle intervention, and recommending the nearest possible meeting area in advance based on the meeting position. The actual meeting trajectory of the vehicles will be re-entered into the vehicle driving behavior analysis system to update the situation where the historical meeting area is invalid due to force majeure factors (landslides, road subsidence, etc.).

[0037] like Figure 4 As shown, the vehicle-road cooperative operation and management platform will execute the following specific steps: S401, collect historical and real-time vehicle trajectory data; S402, analyze vehicle driving behavior; S403, match meeting trajectories; S404, calculate meeting points; S405, aggregate, eliminate, and update meeting points; S406, predict the positions of encountering vehicles; S407, analyze actual meeting; S408, complete early warning and dispatch control.

[0038] Furthermore, in one example, the V2X platform administrator can maintain vehicle information, equipment information, and road information on the operation and management platform. During vehicle operation, V2X onboard devices can transmit their high-precision location information, speed, heading angle, and vehicle information to the V2X Server platform at a frequency of 10Hz. The V2X platform can analyze vehicle meeting behavior based on historical vehicle trajectories and real-time data from narrow roads, combined with deep learning algorithms, and determine the meeting point and the minimum passable width at that point based on information such as the width of the meeting vehicles.

[0039] In one example, the cloud platform can collect vehicle entry signals via lane electronic fences. These signals indicate the number of vehicles entering the narrow road area and the direction of travel for each vehicle. Figure 5As shown, the cloud platform can collect historical vehicle location data by setting up lane electronic fences on narrow road sections. These lane electronic fences can be virtual polygons or linear areas pre-drawn for a specific narrow road section on the cloud platform's digital map. They act like an invisible "detection gate," serving as the logical boundary for system monitoring and determining whether a vehicle has entered the narrow road area. In a specific example, lane electronic fences can be manually drawn using existing electronic map services. After running for a period, historical trajectory data mining can be used to discover overlooked or narrower road sections, automatically generating or suggesting new electronic fences. Furthermore, high-precision maps can be introduced into key road sections to generate electronic lane fences based on actual needs.

[0040] In one example, a narrow road area is a road segment where the effective passage width is less than a preset safety threshold. For instance, the "effective passage width" can be taken as a low quantile (e.g., the 5th percentile) of the lateral distance of all trajectories on a given road segment. This means that in 95% of cases, the road is at least this wide. If this "effective passage width" is less than (standard vehicle width * 2 + safety margin), it is marked as a narrow road area. For example, if the standard vehicle width is 1.8 meters (for a sedan) and the safety margin is 0.5 meters, then the threshold is 1.8 * 2 + 0.5 = 4.1 meters. If the calculated effective passage width is less than 4.1 meters, the system automatically marks it as a "narrow road".

[0041] In S202, when a vehicle entry signal collected by the lane electronic fence indicates that at least two vehicles have entered the narrow road area, and the at least two vehicles are traveling in opposite directions, real-time vehicle driving information of the first vehicle and the second vehicle are acquired. It should be noted that the first vehicle here refers to any one of the at least two vehicles entering the narrow road area, and the second vehicle refers to any one of the at least two vehicles entering the narrow road area other than the first vehicle, and the first and second vehicles are traveling in opposite directions. When more than two vehicles have entered the narrow road area, the meeting point determination method described in this scheme is applied to any pair of vehicles traveling in opposite directions. For example, when vehicles A, B, and C enter the narrow road area, and vehicles A and B are traveling from south to north, while vehicle C is traveling from north to south, then vehicles A and C are marked as the first vehicle and the second vehicle, respectively, and the meeting point determination method described in this scheme is applied; similarly, vehicles B and C are marked as the first vehicle and the second vehicle, and the meeting point determination method described in this scheme is applied. It should be noted that although the first and second vehicles are used as examples in this solution, it does not mean that the number of vehicles is limited. If there are more than two vehicles, the meeting point determination method provided in this solution will be implemented through the above example.

[0042] In one example, when the lane electronic fence detects that two or more vehicles are traveling in opposite directions within a narrow road area, the cloud platform begins to collect real-time vehicle driving information. This real-time vehicle driving information includes vehicle positioning information. Positioning data that deviates from the nearest lane by more than R1 meters in both horizontal and vertical distances are removed to reduce noise. The location points in the original data are compressed and resampled. The trajectory of vehicles in the first 3 seconds before their first encounter (which can be the time when the first vehicle and the second vehicle are first separated by R2 meters) is discarded to reduce the amount of data and improve efficiency. The remaining trajectory is stored using a spatiotemporal index R-tree to efficiently store and query trajectory data.

[0043] In S203, the cloud platform generates future path information and theoretical conflict points based on the real-time driving information of the first and second vehicles. The future path information indicates the predicted driving paths and widths of the first and second vehicles, while the theoretical conflict point indicates the theoretical meeting point of the first and second vehicles. The cloud platform performs real-time analysis of the meeting risk based on the real-time driving information of the first and second vehicles, calculating the possible future intersection points of the first and second vehicles, i.e., the future path information and theoretical conflict points. Then, based on the latitude and longitude of the theoretical conflict point, it selects the nearest location from the meeting list whose maximum meeting width is greater than the widths of vehicles A and B. Once the meeting position is calculated, a reminder distance of M meters is set. The platform communicates with the vehicle terminals via the V2X platform, sending the corresponding meeting position to both vehicles and suggesting that the arriving vehicle stop and wait. The same logic applies if multiple vehicles are involved.

[0044] In one example, the future position is predicted using a function (predictPosition) that calculates the future position (both vehicle car1 and vehicle car2 contain latitude, longitude, speed, and orientation information): predictedPos1 = predictPosition(car1, predictionTime) predictedPos2 = predictPosition(car2, predictionTime) Calculate the intersection point: meetingPoint = findIntersection(predictedPos1, predictedPos2) The `findIntersection` function calculates the position of the intersection of two future points, and can be used to find the intersection position of the first vehicle and the second vehicle.

[0045] In S204, before the first vehicle and the second vehicle reach the theoretical conflict point, the cloud platform, based on the future path information and the theoretical conflict point, filters a target meeting point from a meeting point list. This meeting point list is generated based on the historical vehicle driving information of multiple vehicles entering the narrow road area, and includes multiple potential meeting points and the passage width of each potential meeting point. In one example, the position closest to the theoretical conflict point is selected from the meeting point list from top to bottom, and the meeting width at this position must be greater than the sum of the widths of the first and second vehicles. This position is determined as the optimal meeting position, i.e., the target meeting point. In another example, the meeting point list is generated based on the historical vehicle driving information of multiple vehicles entering the narrow road area; that is, the meeting point list includes multiple potential meeting points in the narrow road area and their corresponding passage widths.

[0046] In S205, the cloud platform sends the location information of the target meeting point to the first vehicle and the second vehicle. In one example, the cloud platform can send the latitude and longitude coordinates of the target meeting point to the V2X vehicle terminals of the first and second vehicles via an IP network through a cellular network base station.

[0047] In S206, the onboard devices on the first and second vehicles output the location information of the target meeting point through an interactive interface. In one example, the V2X-SDK and application software of the V2X onboard terminal are responsible for processing the location information of the target meeting point sent by the cloud platform. The V2X-SDK is responsible for parsing the message and extracting key information such as latitude and longitude, suggested actions, etc. The received latitude and longitude coordinates of the target meeting point are matched with the vehicle's local navigation map and converted into a specific location on the map. In one example, the location of the "target meeting point" can also be marked with a prominent icon on the navigation interface of the vehicle's central control screen or instrument panel, while guide lines or arrows indicate the direction and path.

[0048] To improve the accuracy of determining meeting points and maximize efficiency, such as Figure 6 As shown, as an example, before S204, it may also include: S601: At multiple times, perform the following steps respectively: When the vehicle entry signal indicates that at least two vehicles have entered the narrow road area, and the at least two vehicles have different travel directions, collect the historical vehicle travel information of a third vehicle and the historical vehicle travel information of a fourth vehicle. The third vehicle is any one of the at least two vehicles that have entered the narrow road area, and the fourth vehicle is any one of the at least two vehicles that have entered the narrow road area other than the third vehicle. The vehicle travel information is used to indicate the vehicle's travel trajectory and the vehicle's width. Based on the historical vehicle travel information of the third vehicle and the historical vehicle travel information of the fourth vehicle, match the meeting trajectory and calculate the location information of the potential meeting point. S602: Generate the meeting point list based on the location information of potential meeting points corresponding to vehicles entering the narrow road area at the multiple times, and the width of each vehicle.

[0049] In S601, it should be noted that the third and fourth vehicles are vehicles that historically entered the narrow road area, and are not essentially different from the first and second vehicles, but rather vehicles that entered the narrow road area at different times.

[0050] In one example, the passing trajectories of vehicles entering a narrow road area are collected and matched multiple times at different times to calculate multiple potential passing points in the narrow road area. The following steps are performed at each of the multiple times: When the vehicle entry signal indicates that at least two vehicles have entered the narrow road area, and the at least two vehicles are traveling in different directions, historical vehicle driving information of a third vehicle and historical vehicle driving information of a fourth vehicle are collected. The third vehicle is any one of the at least two vehicles that have entered the narrow road area, and the fourth vehicle is any one of the at least two vehicles that have entered the narrow road area other than the third vehicle. The vehicle driving information is used to indicate the vehicle's driving trajectory and the vehicle's width. Based on the historical vehicle driving information of the third vehicle and the fourth vehicle, the passing trajectories are matched to calculate the location information of potential passing points.

[0051] In S602, a meeting point list is generated based on the location information of potential meeting points corresponding to vehicles entering the narrow road area at the multiple times, and the width of each vehicle. In one example, the meeting point list is generated based on multiple potential meeting points that may exist in the narrow road area calculated in S601, and the vehicle widths of the third and fourth vehicles. For example, in a narrow rural road, three potential meeting points P1, P2, and P3 are identified through S601, and the width of the third vehicle is 1.9 meters, and the width of the fourth vehicle is 1.7 meters. The total width of the combined vehicles is 1.9m + 1.7m = 3.6 meters. The generated meeting point list includes the latitude and longitude of P1, P2, and P3, and the successful meeting width of 3.6 meters.

[0052] To further improve the accuracy of determining meeting points and maximize efficiency, such as Figure 7 As shown, as an example, S601 may include: S6011: After the first moment, obtain the driving speed and heading angle of the third vehicle and the fourth vehicle at multiple moments, wherein the first moment is the moment when the distance between the third vehicle and the fourth vehicle first reaches a first preset threshold. S6012: When the speed of the target vehicle is lower than the second preset threshold and the heading angle of the target vehicle changes by a greater than a preset angle, the current state of the target vehicle is determined to be a reversing state, and the target vehicle is either the third vehicle or the fourth vehicle. S6013: After the second moment, compare the heading angle of the target vehicle at the current moment with the heading angle of the target vehicle between the first moment and the second moment to obtain a comparison result. The second moment is the moment when the state of the target vehicle is determined to be the reversing state. S6014: Based on the comparison results, the high-precision location information of the third vehicle and the high-precision location information of the fourth vehicle, generate meeting trajectory information. The meeting trajectory information includes the driving trajectory point set of the third vehicle, the driving trajectory point set of the fourth vehicle, the width of the third vehicle, the width of the fourth vehicle, a preset safety distance and a safety distance coefficient. The driving trajectory point set includes multiple location points and the time information corresponding to each location point. S6015: The minimum passing distance is calculated based on the width of the third vehicle, the width of the fourth vehicle, the preset safety distance, and the safety distance coefficient; S6016: Traverse each trajectory point in the set of travel trajectory points of the third vehicle and perform the following operations: create a time window for a first trajectory point, where the first trajectory point is any location point in the set of travel trajectory points of the third vehicle; match a second trajectory point in the set of travel trajectory points of the fourth vehicle based on the time window; calculate the spatial distance between the first trajectory point and the second trajectory point according to the latitude and longitude corresponding to the first trajectory point and the second trajectory point; if the spatial distance is less than or equal to the minimum passing distance, calculate the location information of the potential passing point.

[0053] In S6011, after the first moment, the driving speed and heading angle of the third and fourth vehicles at multiple moments are acquired, where the first moment is the moment when the distance between the third and fourth vehicles first reaches a first preset threshold. In one example, starting from the moment the third and fourth vehicles first meet, the driving speed and heading angle of the third and fourth vehicles are continuously monitored at multiple moments via lane electronic fences. In a specific example, the moment when the distance between the third and fourth vehicles first reaches the first preset threshold (interval R2 meters) can be considered the first meeting.

[0054] In S6012, if the target vehicle's speed is lower than a second preset threshold and the target vehicle's heading angle changes by a greater than a preset angle, the target vehicle's current state is determined to be in reverse. The target vehicle is either the third vehicle or the fourth vehicle. After the third and fourth vehicles first meet, their speeds and heading angles are continuously monitored. When the target vehicle's speed is detected to be lower than the second preset threshold (e.g., 0.5 m / s) and the heading angle changes by a greater than a preset angle (e.g., a change in direction of 180 degrees or close to 180 degrees), the target vehicle's current state is determined to be in reverse.

[0055] In S6013, after the second time point, the heading angle of the target vehicle at the current time point is compared with the heading angle of the target vehicle between the first and second time points to obtain a comparison result. The second time point is the time when the target vehicle is determined to be in a reversing state. After the second time point, the heading angle of the target vehicle at the current time point is compared with the heading angle of the target vehicle before reversing. When the heading angle of the target vehicle returns to the direction before reversing, it is determined that the target vehicle meets the conditions for meeting oncoming traffic.

[0056] In S6014, meeting trajectory information is generated based on the comparison result, the high-precision position information of the third vehicle, and the high-precision position information of the fourth vehicle. The meeting trajectory information includes the driving trajectory point set of the third vehicle, the driving trajectory point set of the fourth vehicle, the width of the third vehicle, the width of the fourth vehicle, a preset safety distance, and a safety distance coefficient. The driving trajectory point set includes multiple position points and the time information corresponding to each position point.

[0057] In one example, such as Figure 8 As shown, S6014 may include: S60141: When the comparison result indicates that the heading angle of the target vehicle at the current time is the same as the heading angle of the target vehicle between the first time and the second time, and the high-precision position information of the third vehicle and the fourth vehicle indicates that the third vehicle and the fourth vehicle are continuously approaching each other, a first meeting trajectory is generated. The first meeting trajectory is the meeting trajectory information of the third vehicle and the fourth vehicle between the third time and the fourth time, or between the fifth time and the fourth time. The third time is the time after the second time when the heading angle of the target vehicle changes to the heading angle between the first time and the second time. The fourth time is the time when the distance between the third vehicle and the fourth vehicle is again the first preset threshold. The fifth time is the time after the second time when the driving speed of the target vehicle becomes 0. S60142: When the speed of the target vehicle is higher than or equal to the second preset threshold, and / or the heading angle of the target vehicle changes by less than or equal to the preset angle, a second passing trajectory is generated. The second passing trajectory is the passing trajectory information of the third vehicle and the fourth vehicle between the first time and the fourth time.

[0058] In S60141, if the comparison result indicates that the heading angle of the target vehicle at the current moment is the same as the heading angle of the target vehicle between the first and second moments, and the high-precision position information of the third and fourth vehicles indicates that the third and fourth vehicles are continuously approaching each other, a first meeting trajectory is generated. When the heading angle of the target vehicle returns to the initial detection direction before reversing, and the third and fourth vehicles continue to approach each other, the trajectory after the second change in heading angle or after the first change when the speed is 0 m / s is stored, until the third and fourth vehicles are again separated by R2 meters.

[0059] In S60142, a second meeting trajectory is generated when the target vehicle's speed is higher than or equal to a second preset threshold, and / or the target vehicle's heading angle change is less than or equal to a preset angle. If the target vehicle does not reverse, the trajectory from the first encounter (R2 meters) to the second separation (R2 meters) is stored.

[0060] In one example, such as Figure 9 As shown, the meeting trajectory information includes the set of trajectory points of the third vehicle, the set of trajectory points of the fourth vehicle, the width of the third vehicle, the width of the fourth vehicle, a preset safety distance, and a safety distance coefficient. The set of trajectory points includes multiple location points and the time information corresponding to each location point. In a specific embodiment, the meeting trajectory information may include: 1) trajectory1, the set of points for the third vehicle trajectory, each point contains location and time information.

[0061] 2) trajectory2, the point set of the fourth vehicle trajectory, in the same format as above.

[0062] 3) car_width1, the width of the third vehicle.

[0063] 4) car_width2, the width of the fourth vehicle.

[0064] 5) safety_margin, the assumed extra safety distance (because the actual road width is unknown, and the road width may change due to time and weather).

[0065] 6) safety_factor, safety distance coefficient, used to further increase the safety distance.

[0066] In S6015, the minimum passing distance is calculated based on the width of the third vehicle, the width of the fourth vehicle, a preset safety distance, and a safety distance coefficient. In one example, the minimum passing distance at the passing point is calculated as follows: min_distance = car_width1 + car_width2 + safety_margin + (car_width1+ car_width2 + safety_margin) * safety_factor In S6016, each trajectory point in the set of driving trajectory points of the third vehicle is traversed, and the following operations are performed: a time window is created for a first trajectory point, where the first trajectory point is any location point in the set of driving trajectory points of the third vehicle; a second trajectory point is obtained by matching the second trajectory point in the set of driving trajectory points of the fourth vehicle based on the time window; the spatial distance between the first trajectory point and the second trajectory point is calculated based on the latitude and longitude corresponding to the first trajectory point and the second trajectory point; if the spatial distance is less than or equal to the minimum passing distance, the location information of the potential passing point is calculated.

[0067] In one example, by traversing each point in the first trajectory (i.e., the set of points on the trajectory of the third vehicle), a small time window is used to find points in the second trajectory (i.e., the set of points on the trajectory of the fourth vehicle) with similar times. First, the time window of each point in the first trajectory is obtained as time_window = (point1.time - delta_t, point1.time + delta_t), where delta_t is the size of the time window. Then, the points in the second trajectory that are within the time window are traversed. When the time point in the second trajectory satisfies time_window[0] <= point2.time <= time_window[1], the distance between the two points is calculated as distance = calculate_distance(point1.position, point2.position). (calculate_distance is a common method for calculating distance using latitude and longitude). If the distance between the two points is less than or equal to the minimum distance, the position information and the width of the third vehicle + the fourth vehicle that can meet are added to the potential_meeting_points potential meeting list.

[0068] To improve the accuracy of meeting point determination, such as Figure 10 As shown, as an example, after S206, it may also include: S1001: Based on the multiple potential meeting points in the meeting point list and the passage width of each potential meeting point, a training sample set is constructed. The training sample set includes multiple training samples. Each training sample includes a meeting point feature vector and a meeting point label. The meeting point feature vector is the input of the meeting point prediction model to be trained, and the meeting point label is the output of the meeting point prediction model to be trained. The meeting point label is used to indicate whether the meeting point will pass successfully. S1002: Perform the following steps for each training sample: input the passing point feature vector into the passing point prediction model to be trained, and calculate the predicted probability of successful passing through forward propagation; S1003: Generate a loss function based on the cross-entropy between the meeting point label and the predicted successful meeting probability of each training sample. The loss function is: in, The number of training samples. Label the meeting point. The predicted probability of successful vehicle meeting is: S1004: Iteratively update the trainable vehicle meeting point prediction model according to the loss function until the loss function meets the preset training stopping condition to obtain the vehicle meeting point prediction model. Accordingly, S204 may include: S1005: Before the first vehicle and the second vehicle reach the theoretical conflict point, the target meeting point is obtained by filtering from the meeting point list based on the future path information and the theoretical conflict point, according to the meeting point prediction model.

[0069] In S1001, a training sample set is constructed based on multiple potential meeting points in the meeting point list and the passage width of each potential meeting point. The training sample set includes multiple training samples, each of which includes a meeting point feature vector and a meeting point label. The meeting point feature vector is the input to the meeting point prediction model to be trained, and the meeting point label is the output of the meeting point prediction model to be trained. The meeting point label is used to indicate whether the meeting is successful.

[0070] In one specific embodiment, a list of meeting points is obtained, which contains multiple potential meeting points P_i (i=1,2, ..., N) and the historically verified passage width W_i corresponding to each potential meeting point. All meeting event records for each meeting point P_i within the past period T (e.g., 3 months) are obtained, including information such as vehicle width, speed, and success or failure of each meeting.

[0071] Define and calculate the "meeting point label" y_i: For a meeting point P_i, count the total number of meeting attempts (TotalAttempts_i) and the number of successful meetings (Success_i) within the time window T. Calculate the success rate: SuccessRate_i = Success_i / TotalAttempts_i. Assignment: If SuccessRate_i >= θ_success (e.g., threshold θ_success = 0.8), then define the label y_i = 1 (positive sample, indicating a "reliable meeting point"). If SuccessRate_i < θ_success, then define y_i = 0 (negative sample, indicating an "unreliable meeting point").

[0072] Constructing a "meeting point feature vector" X_i: For each meeting point P_i, construct a multi-dimensional feature vector X_i = [x_i1, x_i2, ..., x_id]. Features may include: Basic geometric features x_i1: W_i (historically verified passage width). Dynamic behavior features x_i2, x_i3: Average relative speed and average meeting speed of the two vehicles in successful meeting events at this point. Trajectory morphology features x_i4, x_i5: Curvature of the road near this point and road width variance extracted from historical trajectories. Contextual features x_i6, x_i7: Line of sight openness index calculated based on satellite imagery and temporal features (such as the proportion of nighttime meeting points). Vehicle interaction features x_i8: Complexity of typical vehicle width combinations for meeting at this point.

[0073] In one example, based on the above list of potential meeting points, data cleaning and optimization of subsequent meeting point additions can be performed. Deep learning algorithms, such as Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Convolutional Neural Network (CNN), can be used to build a risk prediction model. Historical data is then used to train the model, optimize its parameters, and improve prediction accuracy.

[0074] In S1002, the following steps are performed for each training sample: the passing point feature vector is input into the passing point prediction model to be trained, and the predicted passing success probability is calculated through forward propagation. The predicted passing success probability corresponding to the passing point feature vector in each training sample is obtained.

[0075] In a specific embodiment, a deep learning model (such as a multilayer perceptron, MLP) is initialized. Assume its structure is: an input layer (dimension d), two fully connected hidden layers (with ReLU activation function), and an output layer (one neuron with Sigmoid activation function). The feature vector X_i of the i-th sample is input into the model. The data sequentially passes through the input layer and hidden layers, undergoing weighted summation and activation function transformation. Finally, it reaches the output layer, where the Sigmoid function compresses the output to the (0,1) interval, yielding the predicted probability p_i of successful meeting for that sample.

[0076] In S1003, a loss function is generated based on the cross-entropy between the meeting point label and the predicted successful meeting probability of each training sample. The loss function is: in, The number of training samples. Label the meeting point. The predicted probability of successful vehicle meeting is: In S1004, the trainable meeting point prediction model is iteratively updated according to the loss function until the loss function meets the preset training stopping condition, thus obtaining the meeting point prediction model.

[0077] In one specific embodiment, the Adam optimization algorithm is used to update the model parameters: in, and These are the first and second moment estimates of the gradient, respectively. and It is a hyperparameter that controls the exponential decay rate. It's the learning rate. It is a very small constant used to avoid division by zero. Using a trained meeting point prediction model, the system recommends passable meeting point locations where meeting risks are likely to occur in the near future.

[0078] In S1005, before the first vehicle and the second vehicle reach the theoretical conflict point, the target meeting point is selected from the meeting point list based on the future path information and the theoretical conflict point, according to the meeting point prediction model.

[0079] To improve the accuracy of meeting point determination, such as Figure 11 As shown, as an example, S204 may include: S2041: Before the first vehicle and the second vehicle reach the theoretical conflict point, all potential meeting points are traversed and selected from the meeting point list, and the potential meeting point that is closest to the theoretical conflict point and whose passage width is greater than the sum of the widths of the first vehicle and the second vehicle is determined as the target meeting point.

[0080] In S2041, before the first vehicle and the second vehicle reach the theoretical conflict point, all potential meeting points in the meeting point list are traversed and selected. The potential meeting point closest to the theoretical conflict point and whose passage width is greater than the sum of the widths of the first vehicle and the second vehicle is determined as the target meeting point. In a specific embodiment, assume that the system has predicted that vehicle A and vehicle B will meet at point CP (Conflict Point). Vehicle A is 2.2 meters wide, vehicle B is 1.8 meters wide, and the total width of the vehicles is 4.0 meters. There are 5 potential meeting points in the meeting point list. The total width of the vehicles is calculated as: 2.2m + 1.8m = 4.0m. The list is traversed, and the "passage width" of each point is checked to see if it is greater than 4.0 meters. The distance between each candidate point and the theoretical conflict point CP is calculated. Then, the points are sorted in ascending order according to the distance. From the sorted list, the first point, i.e., the closest point, is selected, and the target meeting point is finally determined.

[0081] To guide the drivers of the first and second vehicles to take turns passing at the target meeting point, such as Figure 12 As shown, as an example, after S204, it may also include: S1201: Based on the location information of the theoretical conflict point and the target meeting point, generate warning information, the warning information including driving suggestions for the first vehicle and the second vehicle, the driving suggestions being used to indicate whether the vehicles need to stop and wait at the target meeting point; S1202: Send the warning information to the first vehicle and the second vehicle so that the first vehicle and the second vehicle output the driving suggestion.

[0082] In S1201, a warning message is generated based on the location information of the theoretical conflict point and the target meeting point. The warning message includes driving suggestions for the first vehicle and the second vehicle, which indicate whether the vehicles need to stop and wait at the target meeting point.

[0083] In one example, such as Figure 13As shown, at time T0, vehicles closer to the target meeting point receive driving suggestions that may include stopping and waiting at the target meeting point, while vehicles farther away receive driving suggestions that may include continuing to drive and the distance to the target meeting point. For example, on the navigation interface of the vehicle's central control screen or instrument panel, the location of the "target meeting point" is marked with a prominent icon. Guide lines or arrows are used to indicate the direction and path. The suggested actions are clearly displayed on the side of the screen, such as: "Please proceed to the meeting point 150 meters ahead and wait" or "Please drive at a constant speed; the meeting point is 200 meters ahead of you."

[0084] In S1202, the warning information is sent to the first vehicle and the second vehicle, causing the first vehicle and the second vehicle to output the driving suggestion. In one example, the warning information can be output as an image using an image playback component. Alternatively, the warning information can be played back by voice using a voice broadcast component.

[0085] The above describes a specific implementation of a meeting point determination method provided in this application. Based on the meeting point determination method provided in the above embodiments, this application also provides a specific implementation of a meeting point determination device, as described in the following embodiments.

[0086] like Figure 14 As shown in the embodiment of this application, a meeting point determination device 1400 is provided and applied to a cloud platform. The device 1400 includes: The acquisition module 1401 is used to acquire vehicle entry signals. The vehicle entry signals are used to indicate the number of vehicles entering the narrow road area and the driving direction of each vehicle. The narrow road area is a road segment with an effective passage width of less than a preset safety threshold. The acquisition module 1402 is used to acquire real-time vehicle driving information of a first vehicle and real-time vehicle driving information of a second vehicle when the vehicle entry signal indicates that at least two vehicles have entered the narrow road area and the at least two vehicles have different driving directions. The first vehicle is any one of the at least two vehicles that have entered the narrow road area, and the second vehicle is any one of the at least two vehicles that have entered the narrow road area other than the first vehicle. The generation module 1403 is used to generate future path information and theoretical conflict points based on the real-time vehicle driving information of the first vehicle and the real-time vehicle driving information of the second vehicle. The future path information is used to indicate the predicted driving paths of the first vehicle and the second vehicle and the width of the first vehicle and the second vehicle. The theoretical conflict points are used to indicate the theoretical meeting position of the first vehicle and the second vehicle. The determination module 1404 is used to filter the target meeting point from the meeting point list according to the future path information and the theoretical conflict point before the first vehicle and the second vehicle reach the theoretical conflict point. The meeting point list is generated based on the historical vehicle driving information of multiple vehicles entering the narrow road area. The meeting point list includes multiple potential meeting points and the passage width of each potential meeting point. The sending module 1405 is used to send the location information of the target meeting point to the first vehicle and the second vehicle, so that the first vehicle and the second vehicle output the location information of the target meeting point.

[0087] Thus, the meeting point determination device provided in this application embodiment involves a cloud platform collecting vehicle entry signals. When the vehicle entry signals indicate that at least two vehicles have entered the narrow road area and the at least two vehicles are traveling in different directions, the cloud platform acquires real-time vehicle driving information of the first vehicle and the second vehicle. Based on the real-time vehicle driving information of the first and second vehicles, it generates future path information and theoretical conflict points. Before the first and second vehicles reach the theoretical conflict points, it filters the meeting point list to obtain a target meeting point based on the future path information and the theoretical conflict points. Finally, it sends the location information of the target meeting point to the first and second vehicles so that the first and second vehicles can output the location information of the target meeting point.

[0088] Thus, based on the real-time vehicle driving information of the first and second vehicles, future path information and theoretical conflict points are dynamically generated, and then the target meeting point is determined and sent to the first and second vehicles, so that the first and second vehicles output the location information of the target meeting point to the driver, thereby guiding the drivers of the first and second vehicles to take turns passing at the target meeting point, improving the vehicle traffic efficiency in narrow road areas.

[0089] In another embodiment of this application, the above-described device 1400 may further include: The historical data acquisition module is used to perform the following steps at multiple times: when the vehicle entry signal indicates that at least two vehicles have entered the narrow road area, and the at least two vehicles are traveling in different directions, the module acquires historical vehicle driving information of a third vehicle and a fourth vehicle. The third vehicle is any one of the at least two vehicles entering the narrow road area, and the fourth vehicle is any one of the at least two vehicles entering the narrow road area other than the third vehicle. The vehicle driving information is used to indicate the vehicle's trajectory and width. Based on the historical vehicle driving information of the third vehicle and the fourth vehicle, the module matches the meeting trajectories and calculates the location information of potential meeting points. The meeting point list generation module is used to generate the meeting point list based on the location information of potential meeting points corresponding to vehicles entering the narrow road area at the multiple times, and the width of each vehicle.

[0090] As another embodiment of this application, the above-mentioned historical data acquisition module may further include: The acquisition unit is used to acquire the driving speed and heading angle of the third vehicle and the fourth vehicle at multiple time points after the first time point, wherein the first time point is the time when the distance between the third vehicle and the fourth vehicle first reaches a first preset threshold. The determining unit is used to determine the state of the target vehicle at the current moment as a reversing state when the driving speed of the target vehicle is lower than a second preset threshold and the heading angle of the target vehicle changes by a greater than a preset angle. The target vehicle is either the third vehicle or the fourth vehicle. The comparison unit is used to compare the heading angle of the target vehicle at the current time with the heading angle of the target vehicle between the first time and the second time after the second time, and obtain the comparison result. The second time is the time when the state of the target vehicle is determined to be the reversing state. The generation unit is used to generate meeting trajectory information based on the comparison result, the high-precision location information of the third vehicle and the high-precision location information of the fourth vehicle. The meeting trajectory information includes the driving trajectory point set of the third vehicle, the driving trajectory point set of the fourth vehicle, the width of the third vehicle, the width of the fourth vehicle, a preset safety distance and a safety distance coefficient. The driving trajectory point set includes multiple location points and the time information corresponding to each location point. The calculation unit is used to calculate the minimum passing distance based on the width of the third vehicle, the width of the fourth vehicle, the preset safety distance, and the safety distance coefficient. The traversal unit is used to traverse each trajectory point in the set of travel trajectory points of the third vehicle and perform the following operations: create a time window for a first trajectory point, where the first trajectory point is any location point in the set of travel trajectory points of the third vehicle; match a second trajectory point in the set of travel trajectory points of the fourth vehicle based on the time window; calculate the spatial distance between the first trajectory point and the second trajectory point according to the latitude and longitude corresponding to the first trajectory point and the second trajectory point; and calculate the location information of potential meeting points if the spatial distance is less than or equal to the minimum meeting distance.

[0091] As another embodiment of this application, the above-described generation unit can be specifically used for: If the comparison result indicates that the heading angle of the target vehicle at the current time is the same as the heading angle of the target vehicle between the first time and the second time, and the high-precision position information of the third vehicle and the fourth vehicle indicates that the third vehicle and the fourth vehicle are continuously approaching each other, a first meeting trajectory is generated. The first meeting trajectory is the meeting trajectory information of the third vehicle and the fourth vehicle between the third time and the fourth time, or between the fifth time and the fourth time. The third time is the time after the second time when the heading angle of the target vehicle changes to the heading angle of the target vehicle between the first time and the second time. The fourth time is the time when the distance between the third vehicle and the fourth vehicle is again the first preset threshold. The fifth time is the time after the second time when the driving speed of the target vehicle becomes 0. When the target vehicle's speed is higher than or equal to a second preset threshold, and / or the target vehicle's heading angle change is less than or equal to a preset angle, a second passing trajectory is generated. The second passing trajectory is the passing trajectory information of the third vehicle and the fourth vehicle between the first time and the fourth time.

[0092] In another embodiment of this application, the above-described device 1400 may further include: The training sample construction module is used to construct a training sample set based on multiple potential meeting points in the meeting point list and the passage width of each potential meeting point. The training sample set includes multiple training samples, each of which includes a meeting point feature vector and a meeting point label. The meeting point feature vector is the input of the meeting point prediction model to be trained, and the meeting point label is the output of the meeting point prediction model to be trained. The meeting point label is used to indicate whether the meeting point will pass successfully. The model training module is used to perform the following steps for each training sample: inputting the feature vector of the meeting point into the meeting point prediction model to be trained, and calculating the predicted probability of successful meeting through forward propagation; The loss function generation module is used to generate a loss function based on the cross-entropy between the meeting point label and the predicted successful meeting probability of each training sample. The loss function is: in, The number of training samples. Label the meeting point. The predicted probability of successful vehicle meeting is: The iterative update module is used to iteratively update the trainable meeting point prediction model according to the loss function until the loss function meets the preset training stopping condition, so as to obtain the meeting point prediction model. Module 1404 can be specifically used for: Before the first vehicle and the second vehicle reach the theoretical conflict point, the target meeting point is selected from the meeting point list based on the future path information and the theoretical conflict point, using the meeting point prediction model.

[0093] As another embodiment of this application, the determination module 1404 described above can also be specifically used for: Before the first vehicle and the second vehicle reach the theoretical conflict point, all potential meeting points are traversed and selected from the meeting point list. The potential meeting point that is closest to the theoretical conflict point and whose passage width is greater than the sum of the widths of the first vehicle and the second vehicle is determined as the target meeting point.

[0094] In another embodiment of this application, the above-described device 1400 may further include: The warning information generation module is used to generate warning information based on the location information of the theoretical conflict point and the target meeting point. The warning information includes driving suggestions for the first vehicle and the second vehicle, which are used to indicate whether the vehicles need to stop and wait at the target meeting point. The warning information sending module is used to send the warning information to the first vehicle and the second vehicle, so that the first vehicle and the second vehicle can output the driving suggestions.

[0095] like Figure 15 As shown in the embodiment of this application, a meeting point determination device 1500 is provided, which is applied to vehicle-mounted equipment. The vehicle-mounted equipment is installed on a vehicle entering a narrow road area. The device 1500 includes: The receiving module 1501 is used to receive the location information of the target meeting point sent by the cloud platform. The location information of the target meeting point is generated by the cloud platform based on the real-time vehicle driving information of the first vehicle and the real-time vehicle driving information of the second vehicle, when at least two vehicles are indicated by a vehicle entry signal to enter the narrow road area and the at least two vehicles are traveling in different directions. The cloud platform then generates future path information and theoretical conflict points, and before the first and second vehicles reach the theoretical conflict point, it filters from a meeting point list based on the future path information and theoretical conflict points. The narrow road area is defined as an area with an effective passage width less than a preset safety limit. In the threshold road segment, the first vehicle is any one of at least two vehicles entering the narrow road area, and the second vehicle is any one of at least two vehicles entering the narrow road area other than the first vehicle. The future path information is used to indicate the predicted driving paths of the first vehicle and the second vehicle, as well as the width of the first vehicle and the second vehicle. The theoretical conflict point is used to indicate the theoretical meeting position of the first vehicle and the second vehicle. The meeting point list is generated based on the historical vehicle driving information of multiple vehicles entering the narrow road area. The meeting point list includes multiple potential meeting points and the passage width of each potential meeting point. The output module 1502 is used to output the location information of the target meeting point through an interactive interface.

[0096] Based on the meeting point determination method and apparatus provided in the above embodiments, this application also provides an electronic device 1600, such as... Figure 16 As shown: It includes a processor 1601, a memory 1602, and a computer program stored in the memory 1602 and executable on the processor 1601. When the computer program is executed by the processor 1601, it implements the various processes of the above-described method embodiment for determining the meeting point and achieves the same technical effect.

[0097] Specifically, the processor 1601 may include a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application. The memory 1602 may include mass storage for data or instructions. For example, and not limitingly, the memory 1602 may include a hard disk drive (HDD), a floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 1602 may include removable or non-removable (or fixed) media. Where appropriate, the memory 1602 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, the memory 1602 is a non-volatile solid-state memory.

[0098] In certain embodiments, the memory may include read-only memory (ROM), random access memory (RAM), disk storage media devices, optical storage media devices, flash memory devices, and electrical, optical, or other physical / tangible memory storage devices. Thus, generally, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to one aspect of this application.

[0099] The processor 1601 reads and executes computer program instructions stored in the memory 1602 to implement any of the meeting point determination methods in the above embodiments.

[0100] In one example, the electronic device may also include a communication interface 1603 and a bus 1610. As an example, such as... Figure 16 As shown, the processor 1601, memory 1602, and communication interface 1603 are connected through bus 1610 and complete communication with each other.

[0101] The communication interface 1603 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0102] Bus 1610 includes hardware, software, or both, that couples components of an online data traffic metering device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 1610 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, any suitable bus or interconnect is contemplated herein.

[0103] This application also provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the various processes of the above-described meeting point determination method embodiments and achieves the same technical effects. To avoid repetition, it will not be described again here. The computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0104] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0105] The functional blocks shown in the above block diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0106] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0107] The aspects of this application have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus, and computer program products according to embodiments of this application. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by dedicated hardware performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0108] The above are merely specific embodiments of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for determining a meeting point, characterized in that, Applied to a cloud platform, the method includes: The system collects vehicle entry signals, which are used to indicate the number of vehicles entering the narrow road area and the driving direction of each vehicle. The narrow road area is a road segment with an effective passage width less than a preset safety threshold. When the vehicle entry signal indicates that at least two vehicles have entered the narrow road area, and the at least two vehicles are traveling in different directions, real-time vehicle driving information of the first vehicle and real-time vehicle driving information of the second vehicle are obtained. The first vehicle is any one of the at least two vehicles that have entered the narrow road area, and the second vehicle is any one of the at least two vehicles that have entered the narrow road area other than the first vehicle. Based on the real-time vehicle driving information of the first vehicle and the real-time vehicle driving information of the second vehicle, future path information and theoretical conflict points are generated. The future path information is used to indicate the predicted driving paths of the first vehicle and the second vehicle and the width of the first vehicle and the second vehicle. The theoretical conflict points are used to indicate the theoretical meeting position of the first vehicle and the second vehicle. Before the first vehicle and the second vehicle reach the theoretical conflict point, a target meeting point is obtained by filtering from the meeting point list based on the future path information and the theoretical conflict point. The meeting point list is generated based on the historical vehicle driving information of multiple vehicles entering the narrow road area. The meeting point list includes multiple potential meeting points and the passage width of each potential meeting point. The location information of the target meeting point is sent to the first vehicle and the second vehicle, so that the first vehicle and the second vehicle output the location information of the target meeting point.

2. The method according to claim 1, characterized in that, Before selecting the target meeting point from the meeting point list using the trained meeting point model based on the future path information and theoretical conflict points, the process also includes: At multiple times, the following steps are performed respectively: When the vehicle entry signal indicates that at least two vehicles have entered the narrow road area, and the at least two vehicles are traveling in different directions, historical vehicle driving information of a third vehicle and historical vehicle driving information of a fourth vehicle are collected. The third vehicle is any one of the at least two vehicles entering the narrow road area, and the fourth vehicle is any one of the at least two vehicles entering the narrow road area other than the third vehicle. The vehicle driving information is used to indicate the vehicle's driving trajectory and the vehicle's width. Based on the historical vehicle driving information of the third vehicle and the historical vehicle driving information of the fourth vehicle, the meeting trajectory is matched to calculate the location information of the potential meeting point. The meeting point list is generated based on the location information of potential meeting points corresponding to vehicles entering the narrow road area at the multiple times, and the width of each vehicle.

3. The method according to claim 2, characterized in that, The historical vehicle driving information includes high-precision vehicle location information, driving speed, heading angle, and vehicle information. The process of matching the meeting trajectories based on the historical vehicle driving information of the third and fourth vehicles to calculate the location information of potential meeting points includes: After the first moment, the driving speed and heading angle of the third vehicle and the fourth vehicle are obtained at multiple moments, where the first moment is the moment when the distance between the third vehicle and the fourth vehicle first reaches a first preset threshold. If the target vehicle's speed is lower than the second preset threshold and the target vehicle's heading angle changes by a greater than a preset angle, the target vehicle's current state is determined to be a reversing state. The target vehicle is either the third vehicle or the fourth vehicle. After the second moment, the heading angle of the target vehicle at the current moment is compared with the heading angle of the target vehicle between the first moment and the second moment to obtain the comparison result. The second moment is the moment when the state of the target vehicle is determined to be reverse. Based on the comparison results, the high-precision location information of the third vehicle, and the high-precision location information of the fourth vehicle, passing trajectory information is generated. The passing trajectory information includes the driving trajectory point set of the third vehicle, the driving trajectory point set of the fourth vehicle, the width of the third vehicle, the width of the fourth vehicle, a preset safety distance, and a safety distance coefficient. The driving trajectory point set includes multiple location points and the time information corresponding to each location point. The minimum passing distance is calculated based on the width of the third vehicle, the width of the fourth vehicle, the preset safety distance, and the safety distance coefficient. Traverse each trajectory point in the set of trajectory points of the third vehicle and perform the following operations: create a time window for a first trajectory point, where the first trajectory point is any location point in the set of trajectory points of the third vehicle; match a second trajectory point in the set of trajectory points of the fourth vehicle based on the time window; calculate the spatial distance between the first trajectory point and the second trajectory point according to the latitude and longitude corresponding to the first trajectory point and the second trajectory point; if the spatial distance is less than or equal to the minimum passing distance, calculate the location information of the potential passing point.

4. The method according to claim 3, characterized in that, The step of generating meeting trajectory information based on the comparison result, the high-precision location information of the third vehicle, and the high-precision location information of the fourth vehicle includes: If the comparison result indicates that the heading angle of the target vehicle at the current time is the same as the heading angle of the target vehicle between the first time and the second time, and the high-precision position information of the third vehicle and the fourth vehicle indicates that the third vehicle and the fourth vehicle are continuously approaching each other, a first meeting trajectory is generated. The first meeting trajectory is the meeting trajectory information of the third vehicle and the fourth vehicle between the third time and the fourth time, or between the fifth time and the fourth time. The third time is the time after the second time when the heading angle of the target vehicle changes to the heading angle of the target vehicle between the first time and the second time. The fourth time is the time when the distance between the third vehicle and the fourth vehicle is again the first preset threshold. The fifth time is the time after the second time when the driving speed of the target vehicle becomes 0. When the target vehicle's speed is higher than or equal to a second preset threshold, and / or the target vehicle's heading angle changes by an angle less than or equal to a preset angle, a second passing trajectory is generated. The second passing trajectory is the passing trajectory information of the third vehicle and the fourth vehicle between the first time and the fourth time.

5. The method according to claim 4, characterized in that, After generating the meeting point list based on the potential meeting points corresponding to vehicles entering the narrow road area at the multiple times and the width of each vehicle, the method further includes: Based on multiple potential meeting points in the meeting point list and the passage width of each potential meeting point, a training sample set is constructed. The training sample set includes multiple training samples, each of which includes a meeting point feature vector and a meeting point label. The meeting point feature vector is the input to the meeting point prediction model to be trained, and the meeting point label is the output of the meeting point prediction model to be trained. The meeting point label is used to indicate whether the meeting point will pass successfully. For each training sample, perform the following steps: input the feature vector of the meeting point into the meeting point prediction model to be trained, and calculate the predicted probability of successful meeting through forward propagation; A loss function is generated based on the cross-entropy between the meeting point label and the predicted successful meeting probability of each training sample. The loss function is as follows: in, The number of training samples. Label the meeting point. The predicted probability of successful vehicle meeting is: The meeting point prediction model to be trained is iteratively updated according to the loss function until the loss function meets the preset training stopping condition, and the meeting point prediction model is obtained. Before the first vehicle and the second vehicle reach the theoretical conflict point, the process of selecting a target meeting point from the meeting point list based on the future path information and the theoretical conflict point includes: Before the first vehicle and the second vehicle reach the theoretical conflict point, the target meeting point is selected from the meeting point list based on the future path information and the theoretical conflict point, using the meeting point prediction model.

6. The method according to claim 5, characterized in that, The step of selecting target meeting points from the meeting point list based on the future path information and theoretical conflict points includes: Before the first vehicle and the second vehicle reach the theoretical conflict point, all potential meeting points are traversed and selected from the meeting point list. The potential meeting point that is closest to the theoretical conflict point and whose passage width is greater than the sum of the widths of the first vehicle and the second vehicle is determined as the target meeting point.

7. The method according to claim 6, characterized in that, After selecting the target meeting point from the meeting point list based on the future path information and theoretical conflict points, the process further includes: Based on the location information of the theoretical conflict point and the target meeting point, a warning message is generated. The warning message includes driving suggestions for the first vehicle and the second vehicle, which are used to indicate whether the vehicles need to stop and wait at the target meeting point. The warning information is sent to the first vehicle and the second vehicle so that the first vehicle and the second vehicle can output the driving suggestions.

8. A method for determining a meeting point, characterized in that, The method, applicable to in-vehicle equipment installed on a vehicle entering a narrow road area, includes: The system receives the location information of the target meeting point from the cloud platform. This target meeting point is generated by the cloud platform based on real-time vehicle driving information of the first and second vehicles, assuming at least two vehicles are entering the narrow road area indicated by a vehicle entry signal and the at least two vehicles are traveling in different directions. The system generates future path information and theoretical conflict points, and before the first and second vehicles reach the theoretical conflict point, it filters from a meeting point list based on the future path information and theoretical conflict points. The narrow road area is a road segment with an effective passage width less than a preset safety threshold. The first vehicle is any one of at least two vehicles entering the narrow road area, and the second vehicle is any one of at least two vehicles entering the narrow road area other than the first vehicle. The future path information is used to indicate the predicted driving paths of the first vehicle and the second vehicle, as well as the width of the first vehicle and the second vehicle. The theoretical conflict point is used to indicate the theoretical meeting position of the first vehicle and the second vehicle. The meeting point list is generated based on the historical vehicle driving information of multiple vehicles entering the narrow road area, and the meeting point list includes multiple potential meeting points and the passage width of each potential meeting point. The location information of the target meeting point is output through the interactive interface.

9. A device for determining a meeting point, characterized in that, The device, applied to a cloud platform, includes: The acquisition module is used to acquire vehicle entry signals, which are used to indicate the number of vehicles entering the narrow road area and the driving direction of each vehicle. The narrow road area is a road segment with an effective passage width of less than a preset safety threshold. The acquisition module is used to acquire real-time vehicle driving information of a first vehicle and real-time vehicle driving information of a second vehicle when the vehicle entry signal indicates that at least two vehicles have entered the narrow road area and the at least two vehicles have different driving directions. The first vehicle is any one of the at least two vehicles that have entered the narrow road area, and the second vehicle is any one of the at least two vehicles that have entered the narrow road area other than the first vehicle. The generation module is used to generate future path information and theoretical conflict points based on the real-time vehicle driving information of the first vehicle and the real-time vehicle driving information of the second vehicle. The future path information is used to indicate the predicted driving paths of the first vehicle and the second vehicle and the width of the first vehicle and the second vehicle. The theoretical conflict points are used to indicate the theoretical meeting position of the first vehicle and the second vehicle. The determination module is used to filter the target meeting point from the meeting point list based on the future path information and the theoretical conflict point before the first vehicle and the second vehicle reach the theoretical conflict point. The meeting point list is generated based on the historical vehicle driving information of multiple vehicles entering the narrow road area. The meeting point list includes multiple potential meeting points and the passage width of each potential meeting point. The sending module is used to send the location information of the target meeting point to the first vehicle and the second vehicle, so that the first vehicle and the second vehicle output the location information of the target meeting point.

10. A device for determining a meeting point, characterized in that, A device for use in vehicles, the device being installed on a vehicle entering a narrow road area, the device comprising: The receiving module is used to receive the location information of the target meeting point sent by the cloud platform. This target meeting point location information is generated by the cloud platform based on real-time vehicle driving information of the first and second vehicles, when at least two vehicles are indicated to enter the narrow road area by a vehicle entry signal and the at least two vehicles are traveling in different directions. The cloud platform generates future path information and theoretical conflict points, and selects these from a meeting point list before the first and second vehicles reach the theoretical conflict point. The narrow road area is defined as an area with an effective passage width less than a preset safety threshold. In the narrow road section, the first vehicle is any one of at least two vehicles entering the narrow road area, and the second vehicle is any one of at least two vehicles entering the narrow road area other than the first vehicle. The future path information is used to indicate the predicted driving paths of the first vehicle and the second vehicle, as well as the width of the first vehicle and the second vehicle. The theoretical conflict point is used to indicate the theoretical meeting position of the first vehicle and the second vehicle. The meeting point list is generated based on the historical vehicle driving information of multiple vehicles entering the narrow road area. The meeting point list includes multiple potential meeting points and the passage width of each potential meeting point. The output module is used to output the location information of the target meeting point through an interactive interface.

11. A device for determining meeting points, characterized in that, The device includes: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, it implements the meeting point determination method as described in any one of claims 1-8.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions, which, when executed by a processor, implement the meeting point determination method as described in any one of claims 1-8.

13. A computer program product, characterized in that, When the instructions in the computer program product are executed by the processor of the electronic device, the electronic device performs the meeting point determination method as described in any one of claims 1-8.

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