Moving track generation method and device, terminal equipment and storage medium

Abstract

The invention discloses a moving track generation method and device, terminal equipment and a storage medium. The method comprises the steps that S1, change data of a vehicle and static data of a target parking lot are acquired in real time; s2, the change data and the static data are preprocessed, and the moving direction of the vehicle track point in the static data is obtained according to the change data; and S3, establishing a coordinate matching relationship, fusing and matching the vehicle track points to a target parking lot road, determining the current road of the vehicle and the driving path at each moment, and generating a preliminary moving track. The invention belongs to the technical field of positioning, and aims to solve the problem that in the prior art, the movement data of a vehicle in a parking lot cannot be accurately obtained, so that the accuracy of the movement track of the vehicle in the parking lot is poor. The technical effects are that the positioning effect of the vehicle in the target parking lot is improved, and the purpose of accurately generating the moving track of the vehicle in the target parking lot is achieved.

Description

Technical Field

[0001] The present application belongs to the field of positioning technology, and specifically relates to a mobile trajectory generation method, device, terminal equipment and storage medium. Background Art

[0002] With the continuous advancement of positioning technology, mobile trajectory data has been widely used in many fields such as urban planning, traffic management, and behavioral analysis. In the field of urban planning, by analyzing the movement trajectories of a large number of individuals, the dynamics of the flow of people in the city can be revealed, and the gathering and diffusion of people in different time periods can be observed. In the field of traffic management, mobile trajectory data provides key information for the construction of intelligent transportation systems. Among them, parking lots are an important part of urban transportation, and their management efficiency and service quality directly affect people's travel experience. By collecting and analyzing the movement trajectory data of vehicles in parking lots, the internal conditions of parking lots can be monitored in real time, congestion can be detected in time, and rapid response can be made. In the field of behavioral analysis, by analyzing the movement trajectory of individuals, their daily activity patterns, living habits, and social behaviors can be revealed. This is of great significance to personalized recommendations, marketing, and social network analysis.

[0003] However, due to the complexity of the parking lot environment and the diversity of data, most mobile trajectory generation methods cannot accurately obtain the movement data of vehicles in the parking lot, resulting in poor accuracy of the vehicle's movement trajectory in the parking lot, which not only affects the operating efficiency of the parking lot, but also often causes traffic congestion in the parking lot. Therefore, the present invention provides a mobile trajectory generation method, device, terminal device and storage medium to solve the above problems. Summary of the invention

[0004] The present application provides a mobile trajectory generation method, device, terminal device and storage medium, aiming to solve the problem that the existing technology cannot accurately obtain the movement data of the vehicle in the parking lot, resulting in poor accuracy of the vehicle's movement trajectory in the parking lot.

[0005] In a first aspect, a method, an apparatus, a terminal device and a storage medium for generating a mobile trajectory are provided, the method comprising:

[0006] S1: Real-time acquisition of vehicle change data and target parking lot static data;

[0007] S2: pre-process the change data and the static data respectively, and obtain the moving direction of the vehicle trajectory point in the static data according to the change data;

[0008] S3: Establishing a coordinate matching relationship, integrating and matching the vehicle trajectory points to the target parking lot road, determining the current road where the vehicle is located and the driving path at each moment, and generating a preliminary moving trajectory;

[0009] S4: Optimize the preliminary moving trajectory according to the coordinate matching relationship in S3 and the actual layout of the parking lot, obtain the final moving trajectory and store it;

[0010] S5: Apply the generated final movement trajectory of the vehicle to the target parking lot management system to provide managers with intuitive vehicle travel information.

[0011] Optionally, the change data includes the real-time position and driving speed of the vehicle, and the static data includes the on-site layout of the target parking lot and the road distribution. The vehicle's change data is acquired by sensors and a GPS receiver on the vehicle, and the GPS receiver is used to acquire the vehicle's latitude and longitude coordinate sequence in real time.

[0012] Optionally, the S2 specifically includes the following steps:

[0013] S2.1: preset data acquisition time interval;

[0014] S2.2: obtaining a plurality of vehicle trajectory data according to a preset time interval, and then determining the latitude and longitude coordinate sequence of the trajectory according to the GPS data at the same time, to obtain a plurality of trajectory points;

[0015] S2.3: Determine the moving direction according to the position change of two adjacent trajectory points.

[0016] Optionally, S3 specifically includes the following steps:

[0017] S3.1: Obtain the latitude and longitude coordinate sequences of all road segments in the target parking lot, divide the road area of ​​the entire target parking lot into a series of regular grid cells according to the latitude and longitude coordinate sequences, and assign each road segment to a corresponding grid cell;

[0018] S3.2: Establish a unique identification number for each grid unit and record the road information within the unit;

[0019] S3.3: Establishing a mapping relationship between the trajectory points and the grid cells according to the latitude and longitude coordinate sequence of the trajectory points of the vehicle;

[0020] S3.4: Connect the matched trajectory points in time order to form the preliminary movement trajectory of the vehicle.

[0021] Optionally, the S4 specifically includes the following steps:

[0022] S4.1: preset a distance threshold and connect two adjacent trajectory points to form a trajectory segment;

[0023] S4.2: Compare the latitude and longitude coordinate sequence of the vehicle trajectory segment with the latitude and longitude coordinate sequence of the grid unit corresponding to the road area, and identify the trajectory segment that obviously deviates from the road and the repeated travel road;

[0024] S4.3: Delete the trajectory segments that obviously deviate from the road and the repeated travel road to form the final movement trajectory.

[0025] Optionally, the preprocessing includes data cleaning, data denoising and data format conversion.

[0026] In a second aspect, a mobile trajectory generation device includes a data acquisition processing module, a trajectory matching module, a trajectory optimization module and an application module, wherein the data acquisition processing module includes a real-time data acquisition submodule and a static data acquisition submodule;

[0027] The data acquisition and processing module is mainly responsible for collecting the vehicle change data and the static data of the target parking lot in real time, and performing necessary preprocessing on these data;

[0028] The trajectory matching module is based on the matching algorithm of the hidden Markov model, which can establish the coordinate matching relationship between the vehicle trajectory points and the parking lot road segments, determine the current road where the vehicle is located and the driving path at each time;

[0029] The trajectory optimization module can identify the trajectory segments that obviously deviate from the road and repeat the road, and optimize the preliminary movement trajectory;

[0030] The application module is applied to the target parking lot management system to display the generated final movement trajectory of the vehicle in the target parking lot management system in an intuitive manner.

[0031] In a third aspect, a terminal device comprises a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method according to any one of claims 1 to 6.

[0032] In a fourth aspect, a computer-readable storage medium is provided, wherein a computer program is stored on the storage medium, and when the computer program is executed by a computer, the movement trajectory generation method according to any one of claims 1 to 6 is executed.

[0033] Compared with the prior art, this application has at least the following beneficial effects:

[0034] This application is based on further analysis and research on the existing technical problems. By adopting a method of matching the latitude and longitude coordinate sequences of the vehicle and the target parking lot road, the purpose of accurately generating the movement trajectory of the vehicle in the target parking lot is achieved, thereby improving the positioning effect of the vehicle in the target parking lot, facilitating the observation of the vehicle's driving route from the entrance to the exit of the target parking lot through a clear movement trajectory, facilitating the management personnel to perform parking behavior analysis and parking space utilization evaluation, providing data for the planning and design of the target parking lot, and effectively preventing traffic congestion in the target parking lot. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A flow chart of a method, apparatus, terminal device, and storage medium for generating a mobile trajectory provided in one embodiment of the present application;

[0036] Figure 2 A schematic diagram of a module of a mobile trajectory generation method, apparatus, terminal device, and storage medium provided in one embodiment of the present application. DETAILED DESCRIPTION

[0037] In order to make the objectives, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0038] like Figure 1 As shown, the present application provides a method, apparatus, terminal device and storage medium for generating a mobile trajectory, comprising the following steps:

[0039] S1: Obtain the vehicle's changing data and the target parking lot's static data in real time. The changing data includes the vehicle's real-time location and driving speed, and the static data includes the target parking lot's on-site layout and road distribution. The vehicle's changing data is obtained by sensors and GPS receivers on the vehicle. The sensors are used to collect the vehicle's speed, acceleration, and steering information. The GPS receiver is used to obtain the vehicle's latitude and longitude coordinate sequence in real time as the basic data for the vehicle's location. The target parking lot's static data is obtained from the construction data publicly available in the urban traffic planning section.

[0040] S2: Preprocess the change data and the static data respectively, and obtain the moving direction of the vehicle trajectory point in the static data according to the change data.

[0041] Preprocessing includes data cleaning, data denoising and data format conversion. Data cleaning can remove outliers and erroneous data in vehicle motion data.

[0042] For example, the vehicle speed is negative or the location data exceeds the area range. This step ensures the integrity and accuracy of the data and provides a reliable basis for subsequent analysis.

[0043] At the same time, data denoising includes sliding average and Kalman filtering, which can smooth the vehicle motion data to reduce noise and jitter, making the trajectory smoother and more realistic.

[0044] Data format conversion requires the use of conversion tools to ensure that the GPS data format is converted into coordinate format for subsequent analysis and processing.

[0045] S2 specifically includes the following steps:

[0046] S2.1: preset data acquisition time interval;

[0047] S2.2: Acquire a plurality of vehicle trajectory data according to a preset time interval, and then determine the longitude and latitude coordinate sequence of the trajectory according to the GPS data at the same time to obtain a plurality of trajectory points.

[0048] S2.3: Determine the moving direction according to the position change of two adjacent trajectory points.

[0049] S3: Establish a coordinate matching relationship, integrate and match the vehicle trajectory points to the target parking lot road, determine the current road the vehicle is on and the driving path at each moment, and generate a preliminary movement trajectory. Through the coordinate matching relationship, the vehicle's movement trajectory can be more accurately combined with the target parking lot road, thereby eliminating errors and inaccuracies in the trajectory and making the final movement trajectory more accurate.

[0050] S3 specifically includes the following steps:

[0051] S3.1: Obtain the longitude and latitude coordinate sequences of all road segments in the target parking lot, divide the road area of ​​the entire target parking lot into a series of regular grid cells according to the longitude and latitude coordinate sequences, and assign each road segment to a corresponding grid cell. When the road network data changes (such as adding new roads, modifying roads, etc.), the coordinate matching relationship needs to be updated in time to ensure its accuracy and effectiveness.

[0052] S3.2: Establish a unique identification number for each grid unit and record the road information within the unit to facilitate rapid retrieval and positioning.

[0053] S3.3: Establish a mapping relationship between the trajectory points and the grid cells according to the latitude and longitude coordinate sequence of the trajectory points of the vehicle.

[0054] S3.4: Connect the matched trajectory points in time order to form a preliminary moving trajectory of the vehicle, so as to ensure that the generated trajectory can truly reflect the driving state of the vehicle.

[0055] S4: Optimize the preliminary movement trajectory according to the coordinate matching relationship in S3 and the actual layout of the parking lot, obtain the final movement trajectory and store it. The optimized final movement trajectory is crucial for subsequent user navigation, vehicle search, and target parking lot search services, thereby improving the user experience.

[0056] S4 specifically includes the following steps:

[0057] S4.1: Preset a distance threshold and connect two adjacent trajectory points to form a trajectory segment.

[0058] S4.2: Compare the latitude and longitude coordinate sequence of the vehicle trajectory segment with the latitude and longitude coordinate sequence of the grid unit corresponding to the road area, and identify the trajectory segments that obviously deviate from the road and the repeated travel road. During the identification process, the distance h between the trajectory segment and the grid unit is calculated based on the difference between the latitude and longitude coordinate sequences of the two. When the distance h ≥ the distance threshold, it is considered as deviation. If the latitude and longitude coordinate sequences of the trajectory segments at both ends overlap, it is considered as repeated travel.

[0059] S4.3: Delete the trajectory segments that obviously deviate from the road and the repeated travel road to form the final movement trajectory.

[0060] S5: Apply the generated final vehicle movement trajectory to the target parking lot management system to provide managers with intuitive vehicle driving information. Use the generated final vehicle movement trajectory data to perform parking behavior analysis, parking space utilization evaluation and other applications to provide data support for parking lot planning and design.

[0061] In the above-mentioned movement trajectory generation method, the latitude and longitude coordinate sequence matching method of the vehicle and the target parking lot road is adopted to achieve the purpose of accurately generating the movement trajectory of the vehicle in the target parking lot, which is convenient for observing the driving route of the vehicle from the entrance to the exit of the target parking lot through a clear movement trajectory, and is convenient for management personnel to conduct parking behavior analysis and parking space utilization evaluation, provide data for the planning and design of the target parking lot, and effectively prevent traffic congestion in the target parking lot.

[0062] like Figure 2 As shown, in one embodiment, a mobile trajectory generation device is also provided, including a data acquisition processing module, a trajectory matching module, a trajectory optimization module and an application module;

[0063] The data acquisition processing module includes a real-time data acquisition submodule and a static data acquisition submodule, which are mainly responsible for collecting the vehicle change data and the static data of the target parking lot in real time, and performing necessary preprocessing on these data for subsequent analysis and application;

[0064] Real-time data acquisition submodule: responsible for acquiring vehicle change data in real time, including location, speed, direction and other change information. This is achieved through GPS and various vehicle sensor technologies.

[0065] Static data acquisition submodule: responsible for acquiring the static data of the target parking lot, including the layout of the lot and the information on road distribution, which is the basis for subsequent trajectory matching and optimization.

[0066] The trajectory matching module is based on the matching algorithm of the hidden Markov model, which can establish the coordinate matching relationship between the vehicle trajectory points and the parking lot road segments, and determine the current road where the vehicle is located and the driving path at each time.

[0067] The trajectory optimization module can identify trajectory segments that obviously deviate from the road and repeat the road, optimize the preliminary movement trajectory to obtain a more accurate and practical final movement trajectory, and is responsible for storing the optimized final movement trajectory data for subsequent analysis and application.

[0068] The application module is applied to the target parking lot management system to display the generated final vehicle movement trajectory in the target parking lot management system in an intuitive manner, so as to facilitate in-depth analysis of the stored vehicle movement trajectory data.

[0069] In one embodiment, a terminal device is further provided, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method of the above embodiment.

[0070] In one embodiment, a computer-readable storage medium is further provided, on which a computer program is stored. When the computer program is executed by a computer, the steps of the movement trajectory generation method according to any one of claims 1 to 6 are executed.

[0071] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

Claims

1. A method for generating a moving trajectory, characterized in that: The method comprises: S1: Real-time acquisition of vehicle change data and target parking lot static data; S2: pre-process the change data and the static data respectively, and obtain the moving direction of the vehicle trajectory point in the static data according to the change data; S3: Establishing a coordinate matching relationship, integrating and matching the vehicle trajectory points to the target parking lot road, determining the current road where the vehicle is located and the driving path at each moment, and generating a preliminary moving trajectory; S4: Optimize the preliminary moving trajectory according to the coordinate matching relationship in S3 and the actual layout of the parking lot, obtain the final moving trajectory and store it; S5: Apply the generated final movement trajectory of the vehicle to the target parking lot management system to provide managers with intuitive vehicle travel information.

2. A moving trajectory generation method according to claim 1, characterized in that: The change data includes the real-time position and driving speed of the vehicle, and the static data includes the layout of the target parking lot and the distribution of roads. The change data of the vehicle is acquired by sensors and GPS receivers on the vehicle. The GPS receiver is used to acquire the latitude and longitude coordinate sequence of the vehicle in real time.

3. A moving trajectory generation method according to claim 1, characterized in that: The S2 specifically includes the following steps: S2.1: preset data acquisition time interval; S2.2: obtaining a plurality of vehicle trajectory data according to a preset time interval, and then determining the latitude and longitude coordinate sequence of the trajectory according to the GPS data at the same time, to obtain a plurality of trajectory points; S2.3: Determine the moving direction according to the position change of two adjacent trajectory points.

4. The method for generating a moving trajectory according to claim 1, characterized in that: The S3 specifically includes the following steps: S3.1: Obtain the latitude and longitude coordinate sequences of all road segments in the target parking lot, divide the road area of ​​the entire target parking lot into a series of regular grid cells according to the latitude and longitude coordinate sequences, and assign each road segment to a corresponding grid cell; S3.2: Establish a unique identification number for each grid unit and record the road information within the unit; S3.3: Establishing a mapping relationship between the trajectory points and the grid cells according to the latitude and longitude coordinate sequence of the trajectory points of the vehicle; S3.4: Connect the matched trajectory points in time order to form a preliminary moving trajectory of the vehicle.

5. The method for generating a moving trajectory according to claim 1, characterized in that: The S4 specifically comprises the following steps: S4.1: preset a distance threshold and connect two adjacent trajectory points to form a trajectory segment; S4.2: Compare the latitude and longitude coordinate sequence of the vehicle trajectory segment with the latitude and longitude coordinate sequence of the grid unit corresponding to the road area, and identify the trajectory segment that obviously deviates from the road and the repeated travel road; S4.3: Delete the trajectory segments that obviously deviate from the road and the repeated travel road to form the final movement trajectory.

6. A moving trajectory generation method according to claim 1, characterized in that: The preprocessing includes data cleaning, data denoising and data format conversion.

7. A mobile trajectory generation device, comprising a data acquisition processing module, a trajectory matching module, a trajectory optimization module and an application module, characterized in that: The data acquisition processing module includes a real-time data acquisition submodule and a static data acquisition submodule; The data acquisition and processing module is mainly responsible for collecting the vehicle change data and the static data of the target parking lot in real time, and performing necessary preprocessing on these data; The trajectory matching module is based on the matching algorithm of the hidden Markov model, which can establish the coordinate matching relationship between the vehicle trajectory points and the parking lot road segments, determine the current road where the vehicle is located and the driving path at each time; The trajectory optimization module can identify the trajectory segments that obviously deviate from the road and repeat the road, and optimize the preliminary movement trajectory; The application module is applied to the target parking lot management system to display the generated final movement trajectory of the vehicle in the target parking lot management system in an intuitive manner.

8. A terminal device, comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a computer, the movement trajectory generation method according to any one of claims 1 to 6 is executed.

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