A long-distance maneuver path planning method and system fusing dop information

Abstract

The application discloses a long-distance maneuver path planning method and system fusing DOP information and belongs to the technical field of path planning and navigation. The method comprises the following steps: collecting special vehicle information, GNSS DOP information, geographic information and traffic information; performing primary screening on roads based on DOP values and traffic conditions, integrating slope, slope direction, height limit, load capacity, turning radius and DOP information; converting road condition information into constraint conditions and fusing DOP information into a heuristic cost function of an improved algorithm as an optimization target; obtaining a path with the best navigation effect through path searching, visually displaying the path on a geographic information system map and displaying DOP information changes of each key point on the path in real time. The application can effectively avoid GNSS signal blind areas, improve the feasibility and navigation accuracy of path planning in combination with vehicle dynamics constraints and is suitable for long-distance maneuver tasks of special vehicles.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of path planning and navigation, and particularly relates to a long-distance maneuver path planning method and system fusing DOP information. BACKGROUND

[0002] Long-distance maneuver path planning is a key technology in the execution of long-range tasks by special vehicles, and its core lies in comprehensively processing multi-source information (such as road slope, slope direction, height limit, load capacity, turning radius, etc.) and using planning algorithms to generate a feasible path that is excellent in distance, time and reliability.

[0003] In the prior art, path planning systems for special vehicles usually rely on static road network models. These models, although taking into account basic road properties and vehicle physical constraints, generally have two main defects: first, they fail to fully consider the spatiotemporal dynamic variation characteristics of global navigation satellite system (GNSS) signal quality. The dilution of precision (DOP) value of GNSS will change significantly with satellite geometry, time lapse and terrain obstruction (such as urban canyons, tunnels), and existing systems lack dynamic perception and processing capabilities for this factor, leading to the vehicle easily entering GNSS signal blind areas or areas with sharply decreased precision during driving, resulting in loss of positioning or insufficient navigation precision, seriously threatening task safety and efficiency.

[0004] Secondly, some existing technologies attempt to introduce DOP value as an evaluation index, but often fail to deeply integrate and cooperatively optimize it with the dynamics constraints of special vehicles (such as minimum turning radius, maximum allowable slope, etc.). This disconnection may lead to the planned path, although showing acceptable satellite signal quality, being unfeasible in actual driving due to the inability to meet the maneuvering characteristics of the vehicle, or being forced to pass through signal blind areas to meet the dynamics constraints, increasing driving risks and uncertainties.

[0005] In addition, existing systems also have deficiencies in the real-time performance of path planning, adaptability to dynamic traffic information, and intuitive visual display of planning results, making it difficult for drivers to quickly and comprehensively understand the comprehensive situation on the path, especially the potential changes in GNSS signal precision.

[0006] Therefore, there is an urgent need in the field for a long-distance maneuver path planning scheme that can effectively fuse dynamic GNSS signal quality information and vehicle dynamics constraints, achieve multi-factor cooperative optimization, and provide intuitive and real-time path display. SUMMARY

[0007] To solve the above technical problems, the application provides a long-distance maneuver path planning method and system fusing DOP information, which significantly improves the navigation accuracy, path planning success rate and path optimization efficiency of long-distance special vehicle path planning by fusing GNSS DOP information and vehicle dynamics constraints. At the same time, by supporting multi-satellite systems, real-time traffic information fusion and visual display, the flexibility, real-time performance and user experience of the system are further enhanced.

[0008] To achieve the above object, the technical scheme adopted by the application is as follows:

[0009] A long-distance maneuver path planning method fusing DOP information, the method comprising:

[0010] Step 1, acquiring special vehicle information data, GNSS DOP information data, geographic information data and traffic information data;

[0011] Step 2, using the GNSS DOP information data and traffic information data, preliminarily screening available roads, and outputting available road data set;

[0012] Step 3, based on the available road data set, setting constraint conditions including terrain constraints, vehicle dynamics constraints and GNSS satellite service performance constraints, and fusing road GNSS DOP information into the heuristic cost function of the path planning algorithm as an optimization target;

[0013] Step 4, based on the set constraint conditions and cost function, searching for a path from the starting point to the destination of the special vehicle, and obtaining the best path;

[0014] Step 5, visualizing the best path on the geographic information system map, and displaying the GNSS DOP information of the path key points in real time.

[0015] On the other hand, the application provides a long-distance maneuver path planning system fusing DOP information, comprising:

[0016] An information acquisition module is configured to acquire special vehicle information data, GNSS DOP information data, geographic information data and traffic information data, and preliminarily screen available roads by using the GNSS DOP information data and traffic information data, and output available road data set;

[0017] The long-distance maneuver path planning module is configured to set constraint conditions including terrain constraints, vehicle dynamics constraints and GNSS satellite service performance constraints based on available road data sets, and to integrate road GNSS DOP information into a heuristic cost function of a path planning algorithm as an optimization target; based on the set constraint conditions and the cost function, a path search is performed from a starting point to a destination of the special vehicle to obtain an optimal path.

[0018] The planning result display module is configured to visually display the optimal path on a geographic information system (GIS) map and to display GNSS DOP information of key points of the path in real time.

[0019] In a third aspect, the present application provides an electronic device, comprising: one or more processors; a memory for storing one or more programs; wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the long-distance maneuver path planning method with fused DOP information as described above.

[0020] In a fourth aspect, the present application provides a computer-readable storage medium having stored executable instructions thereon, which, when executed by a processor, enable the processor to implement the long-distance maneuver path planning method with fused DOP information as described above.

[0021] The present application has the following beneficial effects:

[0022] The navigation accuracy and reliability of path planning are significantly improved. The core of the present application is to deeply fuse dynamic GNSS DOP information with vehicle dynamics constraints, and to realize multi-factor collaborative optimization through an improved algorithm. This effectively solves the problem of vehicle misentry into a signal blind area caused by ignoring the spatiotemporal variation of GNSS signals in the prior art, and ensures that the special vehicle can obtain stable and reliable navigation services throughout the entire voyage.

[0023] The feasibility and safety of the planned path are enhanced. By taking the slope, slope direction, height limit, load capacity and accurately calculated minimum turning radius of the vehicle as hard constraint conditions, it is ensured that the generated path fully meets the maneuvering characteristics of the special vehicle, and the situation of being unable to pass or being dangerous due to unsatisfied road conditions is avoided, thereby fundamentally improving the practicability and driving safety of the path.

[0024] More intuitive decision support and user experience are provided. The system can visually display the planned path on a GIS map and display the DOP information and its variation trend of key points in real time. This graphical display method helps the driver quickly and clearly understand the satellite signal accuracy throughout the journey, facilitates making decisions in advance, and greatly improves the usability and decision efficiency of the system. BRIEF DESCRIPTION OF DRAWINGS

[0025] Figure 1 A long-distance maneuver path planning method flow chart of fusing DOP information according to the present application;

[0026] Figure 2 A long-distance maneuver path planning system block diagram of fusing DOP information according to the present application. DETAILED DESCRIPTION

[0027] The present application will be further described below in combination with the drawings and examples.

[0028] As shown in the long-distance maneuver path planning method flow chart of fusing DOP information according to the present application, the implementation method steps are as follows: Figure 1

[0029] Step 1, information collection: obtaining special vehicle information data, GNSS DOP information data, geographic information data and traffic information data.

[0030] Step 2, road preliminary screening: using the GNSS DOP information data and traffic information data to preliminarily screen the available roads, screening out signal blind areas and impassable roads, and integrating road condition information, and outputting available road data set; the specific steps are as follows:

[0031] Step 21, determining the GNSS satellite coverage range in the current time window through the GNSS DOP information data and traffic information data;

[0032] Step 22, selecting one or more satellite systems, if multiple satellite systems are selected, the ephemeris data needs to be converted to the same coordinate system, and then the geometric relationships of different satellites are integrated into the same geometric matrix A;

[0033] Step 23, according to the geometric matrix A, pre-calculating the DOP value in the future 24h according to the specified time window, storing it as a space-time grid, and associating the space-time grid DOP value to the road key point according to the vehicle expected arrival time;

[0034] Step 24, sampling the DOP value at the road key point (such as urban canyons, tunnels, etc.), and associating it to the corresponding road key point to generate a DOP information table;

[0035] Step 25, preliminarily screening out the signal blind area with high DOP value, the temporarily closed road affected by traffic congestion or construction, etc., and outputting the available road information;

[0036] Step 26, using the preliminarily screened available road information in combination with the analysis of the geographic information data to integrate and store the slope, slope direction, height limit, load capacity, turning radius, DOP information and other road condition information in the data;

[0037] ​Step 27, output available road data set.

[0038] Step 3, constraint setting: convert road conditions such as slope, slope direction, height limit, load capacity, turning radius, etc. into constraint condition expression, and then integrate road DOP information as optimization target into the improved heuristic cost function of the algorithm.

[0039] Among them, the constraint conditions are as follows:

[0040] Terrain constraints:

[0041] ,

[0042] ,

[0043] ,

[0044] In the formula, is the maximum allowable slope of the special vehicle, is the road slope of the road section at position , is the road slope constraint coefficient; is the height of the special vehicle, is the height limit of the road section at position , is the road height constraint coefficient; is the rated load of the special vehicle, is the road load of the road section at position , is the road load constraint coefficient.

[0045] Dynamic constraints:

[0046] 1) Minimum turning radius of small special vehicle :

[0047] ,

[0048] In the formula, is the wheelbase; is the maximum turning angle of the outer wheel of the steering wheel; is the front track; is the kingpin center distance (the distance between the kingpins of the two steering shafts).

[0049] 2) Minimum turning radius of semi-trailer or articulated special vehicle:

[0050] First, the vehicle is divided into two parts: the tractor and the semi-trailer, and the critical wheelbase of the semi-trailer is :

[0051] ,

[0052] wherein, is the front overhang of the tractor; is the wheelbase of the tractor; is the maximum outer wheel turning angle of the steering wheel of the tractor; is the kingpin center distance of the steering wheel of the tractor; is the wheelbase of the semi-trailer.

[0053] When , the minimum turning radius of the tractor is the minimum turning radius of the tractor, i.e. ; when , the minimum turning radius of the semi-trailer is:

[0054] ,

[0055] wherein, is the distance between the center of the ground contact of the steering wheel and the kingpin center, so that the minimum turning path width of the semi-trailer can be obtained as:

[0056] ,

[0057] wherein, is the cross-sectional width of the tire; is the track of the steering wheel; is the outer width of the vehicle wheel. The calculation of the turning radius and the turning path circle of the articulated vehicle is consistent with that of the semi-trailer.

[0058] ,

[0059] wherein, is the road turning path width at the position; is the road turning radius at the position; is the vehicle dynamics constraint coefficient.

[0060] GNSS satellite service performance constraints:

[0061] ,

[0062] wherein, is a pre-set threshold value for determining the performance of the road satellite service in the current time period; is the task requirement deadline; is the current time; is the remaining time of the task. If the task needs to be completed within a specific period of time (such as the satellite transit period), the path time needs to be ensured not to exceed .

[0063] Objective function setting: design its cost function including current path cost, estimated path cost, GNSS satellite service cost.

[0064] Road cost function, including current path cost, estimated path cost:

[0065] ,

[0066] ,

[0067] In the formula, is the current road cost function; is the road slope constraint coefficient of the road segment at the position; is the road height constraint coefficient of the road segment at the position; is the road load constraint coefficient of the road segment at the position; is the vehicle dynamics constraint coefficient of the road segment at the position; is the road cost function; is the estimated cost function of the best path from the current position to the target point .

[0068] GNSS satellite service cost function:

[0069] ,

[0070] In the formula, is the coordination coefficient; is the GNSS satellite service cost function.

[0071] Total cost function:

[0072] ,

[0073] In the formula, is the weight factor between the road cost and the GNSS satellite service cost.

[0074] Step 4, path search: based on the set constraint conditions and cost functions, according to the special vehicle starting point and destination, based on the improved algorithm for path planning, judge whether to reach the termination condition, if yes, then according to the processing result to get the best path of navigation effect, and enter step S5, otherwise, the path planning fails, end the process, the specific steps are as follows:

[0075] Step 41, initialize the start point and the end point, set the open list and the close list as empty, define the heuristic function, and set the initial cost as 0;

[0076] Step 42, move the start point into the open list, set its parent node as empty, and set the heuristic value as infinite (for subsequent node expansion);

[0077] Step 43, move the start point into the close list and start searching from the start point;

[0078] Step 44, detect the adjacent nodes of the node with the minimum heuristic value in the open list. If the adjacent node is not reachable, ignore it; if the adjacent node is reachable and in the open list, calculate the current heuristic value , if is greater than , update the parent node of the adjacent node stored in the open list, otherwise do not update; if the adjacent node is reachable and not in the forward_open list and the backward_open list, calculate its heuristic value, add it to the open list, and set the current node as its parent node;

[0079] Step 45, repeat step 44;

[0080] Step 46, stop the search when the following two conditions are met: 1) the target point appears in the open list (the path has been found); 2) the adjacent nodes are traversed and cannot be expanded or the nodes are traversed and no reachable path is found.

[0081] Step 47, if the path is successfully planned, backtrack from the current node to the parent node according to the close list until the start point to obtain the final planned path path.

[0082] Step 5, path output and display: intuitively display the planned long-distance maneuvering path and real-time display the change of GNSS DOP value information of the key points of the path. Specifically, it includes: drawing the planned long-distance maneuvering path in an intuitive way on the basis of geographic information system (GIS) map, distinguishing different parts of the path by different colors, line types or icons, real-time displaying the GNSS DOP information of each key point on the path, and displaying the change trend of DOP value in a graphical way to help users intuitively understand the accuracy change of GNSS signal on the path and update the path status in real time.

[0083] Referring to Figure 2The present application provides a long-distance maneuver path planning system fusing DOP information, which comprises an information acquisition module, a long-distance maneuver path planning module and a planning result display module, and each module can realize each step of the foregoing method. The information acquisition module completes acquisition of special vehicle information data, GNSS DOP information data, geographic information data and traffic information data, and analysis, integration and storage of road information. The long-distance maneuver path planning module realizes expression of a cost function table of road information data fusion and path planning in a long-distance maneuver situation. The planning result display module completes display of a final path planning result and demonstration of navigation application.

[0084] The information acquisition module completes acquisition of special vehicle information data, GNSS DOP information data, geographic information data and traffic information data, and determines GNSS satellite coverage range in a current time window through the GNSS DOP information data and the traffic information data. Signal blind areas with high DOP values, temporarily closed roads affected by traffic congestion or construction and the like are preliminarily screened out and output. Then, the preliminarily screened available road information is combined with analysis of the geographic information data to integrate and store road condition information such as slope, slope direction, height limit, load capacity, turning radius and DOP information in the data.

[0085] The long-distance maneuver path planning module realizes conversion of road condition information such as slope, slope direction, height limit, load capacity and turning radius into constraint condition expression, and fuses road DOP information as an optimization target into a heuristic cost function of an algorithm. The heuristic cost function of the algorithm includes current path cost, estimated path cost and GNSS satellite signal quality cost, and finally plans a path with the best navigation effect.

[0086] The planning result display module completes drawing of a planned long-distance maneuver path in an intuitive way on the basis of a geographic information system (GIS) map, distinguishes different parts of the path through different colors, line types or icons, displays GNSS DOP information of each key point on the path in real time, shows a change trend of DOP values in a graphical way, helps a user to intuitively understand a change situation of GNSS signal accuracy on the path and update a path state in real time.

[0087] In a third aspect, the present application provides an electronic device, comprising: one or more processors; a memory for storing one or more programs; wherein when the one or more programs are executed by the one or more processors, the one or more processors realize the foregoing long-distance maneuver path planning method fusing DOP information.

[0088] In a fourth aspect, the present application provides a computer readable storage medium having stored thereon executable instructions that, when executed by a processor, enable the processor to implement the long-distance maneuver path planning method of fusing DOP information as described above.

[0089] The above-described embodiments of the present application are merely intended to further illustrate the purposes, technical solutions and beneficial effects of the present application, and should not be used to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method of long distance maneuver path planning fusing DOP information, characterized in that, The method comprises: Step 1, obtaining special vehicle information data, GNSS DOP information data, geographic information data and traffic information data; Step 2, using the GNSS DOP information data and traffic information data to preliminarily screen available roads and output an available road data set; Step 3, based on the available road data set, setting constraint conditions including terrain constraints, vehicle dynamics constraints and GNSS satellite service performance constraints, and integrating road GNSS DOP information into a heuristic cost function of a path planning algorithm as an optimization target; including: Converting road slope, height limit and load capacity into terrain constraints by setting penalty coefficients; converting minimum turning radius and minimum turning channel width calculated based on special vehicle parameters into vehicle dynamics constraints by setting penalty coefficients; expressing GNSS satellite service performance constraints as DOP values of each point on the path being not greater than a preset threshold, and the total time of the path meeting the task time window requirement; The heuristic cost function is a total cost function, and its expression is a weighted sum of road cost, estimated path cost and GNSS satellite service cost; wherein the road cost is the cumulative cost after fusing terrain constraints and vehicle dynamics constraint coefficients on the current path and the estimated path; the GNSS satellite service cost is the cumulative cost calculated based on the DOP values of each point on the path; Step 4, based on the set constraint conditions and cost function, searching for a path from the starting point to the destination of the special vehicle to obtain the best path; Step 5, visualizing the best path on a geographic information system map and displaying GNSS DOP information of key points of the path in real time.

2. The long-range maneuvering path planning method of fusing DOP information according to claim 1, wherein, The step 2 comprises: pre-calculating GNSS DOP values in a future specific time window and storing them as a space-time grid; associating the DOP values in the space-time grid to key points of corresponding road sections according to the vehicle's expected arrival time; based on the associated DOP information and traffic information, screening out signal blind area roads with DOP values exceeding a preset threshold and roads closed due to traffic or construction; integrating the slope, slope direction, height limit, load capacity, turning radius and DOP information of the remaining available roads to form the available road data set.

3. The method of claim 1, wherein, The terrain constraints are that the road slope, height limit and load capacity meet the maximum allowable slope, vehicle height and rated load requirements of the special vehicle; the vehicle dynamics constraints are that the turning radius and turning channel width of the road are greater than the minimum turning radius and minimum turning channel width calculated for the special vehicle.

4. The method of claim 1, wherein, The step 4 employs a modified A The algorithm performs a path search, including: Initializing the starting point, the ending point, the open list and the closed list; adding the starting point to the open list, and repeatedly executing the following steps until the path is found or the search fails: selecting the node with the minimum total cost from the open list as the current node and moving it to the closed list; traversing the adjacent nodes of the current node, ignoring the adjacent nodes that are not reachable, and calculating the total cost of the adjacent nodes that are reachable, and updating the open list accordingly; if the target point is found in the open list, generating the final planning path as the best path by backtracking from the target node to the parent node to the starting point.

5. The method of claim 1, wherein, The step 5: drawing the planned optimal path on a GIS map; differentiating different sections of the path by different colors, line types or icons; displaying the GNSS DOP value at key points of the path in the form of labels or charts in real time; displaying the change of the DOP value along the entire path in the form of a trend chart, and supporting the updating of the path status and DOP information according to real-time traffic information.

6. A long-range maneuver path planning system fusing DOP information for performing the method of any one of claims 1-5, characterized by The method comprises the following steps: an information collection module for acquiring special vehicle information data, GNSS DOP information data, geographic information data and traffic information data; using the GNSS DOP information data and the traffic information data to preliminarily filter available roads and output an available road data set; a long-distance maneuver path planning module for setting constraint conditions including terrain constraints, vehicle dynamics constraints and GNSS satellite service performance constraints based on the available road data set, integrating road GNSS DOP information into a heuristic cost function of a path planning algorithm as an optimization target, and searching for a path from a starting point to a destination based on the set constraint conditions and the cost function to obtain an optimal path; a planning result display module for visualizing the optimal path on a GIS map and displaying GNSS DOP information of key points of the path in real time.

7. An electronic device, comprising: The method comprises the following steps: one or more processors; a memory for storing one or more programs; wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the long-distance maneuver path planning method with fused DOP information according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, A computer readable storage medium having stored thereon executable instructions that, when executed by a processor, enable the processor to implement the long-distance maneuver path planning method with fused DOP information according to any one of claims 1-5.

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