CN116337093A

CN116337093A - Path planning method, device, equipment, storage medium and product

Info

Publication number: CN116337093A
Application number: CN202111590279.XA
Authority: CN
Inventors: 方君; 陶涛; 马楠; 高睿鹏; 孙付勇; 李群; 柴华
Original assignee: Beijing Didi Infinity Technology and Development Co Ltd
Current assignee: Beijing Didi Infinity Technology and Development Co Ltd
Priority date: 2021-12-23
Filing date: 2021-12-23
Publication date: 2023-06-27

Abstract

The present disclosure provides a path planning method, apparatus, device, storage medium, and product, where under the condition that a traffic anomaly event is detected in a target road network area where a first target road section in a first planned path for a user traveling is located, event related information of the traffic anomaly event, historical space-time influence information and current traffic flow information of each historical anomaly event occurring in the target road network area, and estimated traffic flow information are obtained, so as to obtain space-time influence information of the traffic anomaly event, and further determine whether a traveling path needs to be planned again for the user. Therefore, whether the traffic abnormal event can reach the travel of the user or not can be judged rapidly, appropriate countermeasures are taken, and the evaluation is carried out through two dimensions of time and space, so that the evaluation of space-time influence information is more comprehensive and accurate, the influence of the traffic abnormal event on the travel of the user is reduced, and intelligent, convenient and efficient travel experience is brought to the user.

Description

Path planning method, device, equipment, storage medium and product

Technical Field

The present disclosure relates to the field of mobile communications technologies, and in particular, to a path planning method, apparatus, device, storage medium, and product.

Background

With the rapid development of mobile communication technology, more and more users choose to use navigation products for assistance in the driving process, wherein the navigation products can display an electronic map through a display according to a map database and acquire the position of an automobile through a global positioning system (Global Positioning System, GPS). In the running process of the automobile, the navigation product can calculate a route according to the departure place and the destination input by the user and generate a navigation path, and the user can arrive at the destination according to the navigation path provided by the navigation product.

In the aspect of path planning, the existing navigation products can plan a plurality of paths, an optimal path and a plurality of alternative paths, and the optimal path and the alternative paths are not greatly different, but only the differences of individual road sections. In practical application, when an abnormal emergency such as a traffic accident occurs on a path, contents such as real-time road condition information are mostly only displayed on the path, and aiming at the abnormal emergency, targeted adjustment suggestions and countermeasures are lacking, so that the travel time of a user is easily increased, and the travel experience of the user is not facilitated.

Disclosure of Invention

The embodiment of the disclosure at least provides a path planning method, a path planning device, path planning equipment, a storage medium and a path planning product.

The embodiment of the disclosure provides a path planning method, which comprises the following steps:

in the process that a user travels according to a first planning path, if a traffic abnormal event is detected to occur in a target road network area where a first target road section in the first planning path is located, acquiring event related information of the traffic abnormal event and historical space-time influence information of each historical abnormal event occurring in the target road network area;

determining estimated influence road network areas and estimated influence time for event road segments based on historical space-time influence information of each historical abnormal event, wherein the event road segments are road segments in the target road network areas, and the traffic abnormal event occurs in the road segments;

determining current traffic flow information in the estimated influence road network area and estimated traffic flow information of the estimated influence road network area in the estimated influence time;

estimating time-space influence information of the traffic abnormal event aiming at the first target road section based on the event related information, the historical time-space influence information, the current traffic flow information and the estimated traffic flow information;

and determining whether a travel path needs to be re-planned for the user based on the space-time influence information.

In an alternative embodiment, before the acquiring the event related information of the traffic abnormal event and the historical space-time influence information of each historical abnormal event occurring in the target road network area, the method includes:

a first planned path from a departure point to a destination is planned for a user based on the departure point and the destination set by the user.

In an alternative embodiment, the event related information of the traffic anomaly event is determined by:

acquiring historical event information of each historical abnormal event, on-site information of the traffic abnormal event and road attribute information of the first target road section, wherein the historical event information comprises event types of the historical abnormal events;

matching the traffic abnormal event with the plurality of historical abnormal events based on the field information and the historical field information indicated in the historical event information, and determining a target abnormal event with the same type as the traffic abnormal event from the plurality of historical abnormal events;

taking the event type of the target abnormal event as the event type of the traffic abnormal event;

Event related information of the traffic abnormality event is determined based on the event type of the traffic abnormality event, the on-site information and the road attribute information.

In an alternative embodiment, the determining the estimated impact road network area and the estimated impact time for the event road segments based on the historical space-time impact information of each historical abnormal event includes:

analyzing historical influence road network areas and historical influence time of the historical abnormal events from the historical space-time influence information of the historical abnormal events aiming at each historical abnormal event;

based on the event type of each historical abnormal event, carrying out aggregation processing on the acquired plurality of historical abnormal events to obtain at least one abnormal event set, wherein each abnormal event set comprises at least one historical abnormal event;

selecting a target event set from the at least one abnormal event set based on the event type of the traffic abnormal event indicated by the event related information, wherein the historical abnormal event in the target event set is the same as the event type of the traffic abnormal event;

and determining the estimated influence road network area and the estimated influence time which take the event road section as the center based on the historical influence road network area and the historical influence time of each historical abnormal event in the target event set.

In an alternative embodiment, the estimated traffic information of the estimated affected road network area within the estimated affected time is determined by:

determining an extended influence road network region outside the estimated influence road network region based on the estimated influence road network region and the estimated influence time;

acquiring vehicle running information of each first vehicle in the extended influence road network area;

determining at least one second vehicle from a plurality of first vehicles in the extended influence road network area based on vehicle running information of each first vehicle, wherein the second vehicle is a vehicle which can enter the estimated influence road network area in the estimated influence time;

and obtaining the estimated vehicle flow information based on the number of the at least one second vehicle.

In an optional implementation manner, the estimating the spatiotemporal influence information of the traffic abnormal event for the first target road segment based on the event related information, the historical spatiotemporal influence information, the current traffic flow information and the estimated traffic flow information includes:

determining a time-space feature sequence of the traffic abnormal event based on the event related information, the historical time-space influence information, the current traffic flow information and the estimated traffic flow information;

And inputting the space-time characteristic sequence into a trained space-time prediction model for convolution processing to obtain space-time influence information of the traffic abnormal event on the first target road section.

In an alternative embodiment, the determining whether the travel path needs to be re-planned for the user based on the spatiotemporal influence information includes:

determining the driving time required by the user to drive from the current position to the first target road section according to the first planning path;

detecting whether the influence time indicated by the space-time influence information is greater than or equal to the running time;

and if the influence time is greater than or equal to the driving time, determining that a travel path needs to be planned again for the user.

In an alternative embodiment, in case it is determined that a travel path needs to be re-planned for the user, the method further comprises:

and planning a second planning path from the current position to a destination in the first planning path for the user based on the influence road network area indicated by the space-time influence information.

In an alternative embodiment, after the planning of a second planned path for the user from a current location to a destination in the first planned path based on the estimated impact road network area indicated by the spatio-temporal impact information, the method includes:

Determining a first travel time and a first travel distance required by the user to travel from the current position to the destination according to the first planned path based on the estimated influence time indicated by the space-time influence information;

determining a second travel time and a second travel distance of the user traveling according to the second planning path;

and if the travel cost of the second planning path is smaller than the travel cost of the first planning path based on the first travel time, the first travel distance, the second travel time and the second travel distance, pushing the second planning path to the user.

In an alternative embodiment, in case the second planned path is pushed to the user, the method comprises:

generating prompt information aiming at the traffic abnormal event and the second planning path;

and pushing the prompt information to the user so as to explain the traffic abnormal event to the user.

The embodiment of the disclosure also provides a path planning device, which comprises:

the detection module is used for acquiring event related information of the traffic abnormal event and historical space-time influence information of each historical abnormal event occurring in a target road network area when detecting that the traffic abnormal event occurs in the target road network area where a first target road section in a first planning path exists in the process of traveling according to a first planning path by a user;

The first determining module is used for determining a predicted influence road network area and a predicted influence time for an event road section based on the historical space-time influence information of each historical abnormal event, wherein the event road section is the road section in the target road network area where the traffic abnormal event occurs;

the second determining module is used for determining current traffic flow information in the estimated influence road network area and estimated traffic flow information of the estimated influence road network area in the estimated influence time;

the estimating module is used for estimating the time-space influence information of the traffic abnormal event aiming at the first target road section based on the event related information, the historical time-space influence information, the current traffic flow information and the estimated traffic flow information;

and the adjusting module is used for determining whether the travel path needs to be planned again for the user or not based on the space-time influence information.

In an alternative embodiment, the apparatus further comprises a first planning module for:

In an alternative embodiment, the detection module is configured to determine the event related information of the traffic anomaly event by:

In an alternative embodiment, the first determining module is specifically configured to:

In an alternative embodiment, the second determining module is configured to determine the estimated traffic information of the estimated affected road network area within the estimated affected time by:

In an alternative embodiment, the prediction module is specifically configured to:

In an alternative embodiment, the adjusting module is specifically configured to:

In an alternative embodiment, the apparatus further comprises a second planning module for:

In an alternative embodiment, the second planning module is further configured to:

In an alternative embodiment, the device further includes a prompting module, where the prompting module is configured to:

The embodiment of the disclosure also provides an electronic device, including: the system comprises a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, when the electronic device is running, the processor and the memory are communicated through the bus, and the machine-readable instructions are executed by the processor to execute the steps of the path planning method.

The disclosed embodiments also provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the path planning method described above.

The disclosed embodiments also provide a computer program product comprising a computer program/instructions which, when executed by a processor, implement the steps of the path planning method described above.

In the path planning method, device, equipment, storage medium and product provided by the embodiment of the disclosure, if a traffic abnormal event is detected to occur in a target road network area where a first target road section in a first planned path is located in a process that a user travels according to a first planned path, acquiring event related information of the traffic abnormal event and historical space-time influence information of each historical abnormal event occurring in the target road network area; determining estimated influence road network areas and estimated influence time for event road segments based on historical space-time influence information of each historical abnormal event, wherein the event road segments are road segments in the target road network areas, and the traffic abnormal event occurs in the road segments; determining current traffic flow information in the estimated influence road network area and estimated traffic flow information of the estimated influence road network area in the estimated influence time; estimating time-space influence information of the traffic abnormal event aiming at the first target road section based on the event related information, the historical time-space influence information, the current traffic flow information and the estimated traffic flow information; and determining whether a travel path needs to be re-planned for the user based on the space-time influence information.

In this way, when a traffic abnormal event occurs in a target road network area where a certain road section in a planned path is located in a process of traveling according to the planned path by a user, the time-space influence information of the traffic abnormal event on the road section can be estimated by combining the acquired event related information of the traffic abnormal event, the historical time-space influence information of each historical abnormal event occurring in the target road network area, the current traffic flow information and the estimated traffic flow information, so that the influence of the traffic abnormal event on the traveling of the user can be accurately estimated, and therefore whether the traffic abnormal event affects the user travel at the time or not can be rapidly judged, and appropriate countermeasures can be taken.

Further, the time-space influence information of the traffic abnormal event is integrated, the information of the traffic abnormal event, the information of the historical event, the current traffic flow information and the estimated traffic flow information are evaluated through two dimensions of time and space, so that the judgment of the congestion influence range caused by the traffic abnormal event is more comprehensive and accurate, a user can conveniently avoid and keep away from the traffic abnormal event in time, the influence of the traffic abnormal event on the user trip is reduced, a planning path reaching a destination can be provided for the user, meanwhile, explanation about corresponding path planning and explanation about the traffic abnormal event condition can be provided for the user, the urban congestion problem is slowed down to a certain extent, the road utilization rate is improved, and more intelligent, convenient and efficient trip experience is provided for the user.

The foregoing objects, features and advantages of the disclosure will be more readily apparent from the following detailed description of the preferred embodiments taken in conjunction with the accompanying drawings.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings required for the embodiments are briefly described below, which are incorporated in and constitute a part of the specification, these drawings showing embodiments consistent with the present disclosure and together with the description serve to illustrate the technical solutions of the present disclosure. It is to be understood that the following drawings illustrate only certain embodiments of the present disclosure and are therefore not to be considered limiting of its scope, for the person of ordinary skill in the art may admit to other equally relevant drawings without inventive effort.

FIG. 1 illustrates a flow chart of a path planning method provided by an embodiment of the present disclosure;

FIG. 2 illustrates a schematic diagram of a target road network area provided by an embodiment of the present disclosure;

FIG. 3 is a flowchart of a specific method for determining a predicted impact road network area and a predicted impact time in a path planning method according to an embodiment of the present disclosure;

Fig. 4 is a flowchart illustrating a specific method for determining estimated traffic flow information in the path planning method according to the embodiment of the present disclosure;

FIG. 5 illustrates a flow chart of another path planning method provided by an embodiment of the present disclosure;

FIG. 6 shows one of the schematic diagrams of a path planning apparatus provided by an embodiment of the present disclosure;

FIG. 7 shows a second schematic diagram of a path planning apparatus according to an embodiment of the disclosure;

FIG. 8 illustrates a third schematic diagram of a path planning apparatus provided by an embodiment of the present disclosure;

fig. 9 shows a schematic diagram of an electronic device provided by an embodiment of the disclosure.

Detailed Description

For the purposes of making the objects, technical solutions and advantages of the embodiments of the present disclosure more apparent, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is apparent that the described embodiments are only some embodiments of the present disclosure, but not all embodiments. The components of the embodiments of the present disclosure, which are generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present disclosure provided in the accompanying drawings is not intended to limit the scope of the disclosure, as claimed, but is merely representative of selected embodiments of the disclosure. All other embodiments, which can be made by those skilled in the art based on the embodiments of this disclosure without making any inventive effort, are intended to be within the scope of this disclosure.

It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures.

The term "and/or" is used herein to describe only one relationship, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist together, and B exists alone. In addition, the term "at least one" herein means any one of a plurality or any combination of at least two of a plurality, for example, including at least one of A, B, C, and may mean including any one or more elements selected from the group consisting of A, B and C.

According to research, at present, when a traffic abnormal event occurs, the occurrence of the traffic abnormal event is only regarded as a single point, and the single point is predicted and evaluated, however, the occurrence of the traffic abnormal event has strong randomness, the accuracy of the direct prediction is low, and the influence caused by the traffic abnormal event is difficult to accurately judge under the condition that the traffic abnormal event actually occurs only according to the prediction method, and the completeness and the accuracy of the influence judgment of the traffic abnormal event are lacked.

Based on the above study, the disclosure provides a path planning method, in the process that a user travels according to a planned path, when a traffic abnormal event occurs in a target road network area where a certain road section in the planned path is located, the time-space influence information of the traffic abnormal event, the current traffic flow information and the estimated traffic flow information of each historical abnormal event occurring in the target road network area can be combined to obtain the time-space influence information of the traffic abnormal event on the road section in an estimated mode, so that the influence of the traffic abnormal event on the user travel can be accurately estimated, whether the traffic abnormal event can reach the user travel at the time can be rapidly judged, and appropriate countermeasures can be taken.

The present invention is directed to a method for manufacturing a semiconductor device, and a semiconductor device manufactured by the method.

For the sake of understanding the present embodiment, first, a detailed description will be given of a path planning method disclosed in an embodiment of the present disclosure, where an execution body of the path planning method provided in the embodiment of the present disclosure is generally an electronic device with a certain computing capability, and the electronic device includes, for example: the terminal equipment or the server or other processing equipment can be a mobile phone terminal, a vehicle-mounted equipment and the like. In some possible implementations, the path planning method may be implemented by a processor in the electronic device invoking computer readable instructions stored in a memory.

The path planning method provided by the embodiment of the present disclosure is described below.

Referring to fig. 1, a flowchart of a path planning method according to an embodiment of the present disclosure is shown, where the method includes steps S101 to S105, where:

s101: and in the process that the user travels according to the first planning path, if detecting that a traffic abnormal event occurs in a target road network area where a first target road section in the first planning path is located, acquiring event related information of the traffic abnormal event and historical space-time influence information of each historical abnormal event occurring in the target road network area.

In the step, a first planning path can be provided for a user according to a travel request submitted by the user, and traffic conditions in a road network area where each road section in the first planning path is located can be detected in real time in the process that the user travels according to the first planning path.

The real-time detection of the traffic condition in the road network area where each road section in the first planned path is located may be through networking of vehicles driven by the user, and a uniformly issued notice is obtained based on a networking network, so that real-time detection of each road section is achieved.

Alternatively, images and videos acquired by a vehicle recorder, a vehicle-mounted camera and the like mounted on other vehicles can be acquired, so that real-time detection of each road section is realized.

Here, it should be noted that, in an actual application scenario, each path may be divided into a plurality of road segments, that is, each path may be formed by a plurality of road segments, further, it may be understood that the first planned path is formed by a plurality of first road segments, and positioning and detecting may be performed on a plurality of first road segments in the first planned path respectively.

Here, the first road segment includes the first target road segment.

Then, in the case that a traffic abnormality event is detected in a target road network area where a first target road segment in the first planned path is located, it can be understood that, in the case that the traffic abnormality event and the first target road segment are in the same target road network area, the traffic abnormality event may affect the first target road segment, and in order to determine an affecting range of the traffic abnormality event, event related information of the traffic abnormality event and historical space-time affecting information of each historical abnormality event that has occurred in the target road network area may be obtained.

The types of the traffic abnormal events can be various, such as scratch, rear-end collision, control, blocking, ponding and other accidents, natural disasters such as earthquake, storm, flood, typhoon and the like, artificial events such as attack, violence, injury and the like, and the traffic abnormal events are not limited in any way.

Here, the target road network area where the first target road section is located is an area where the traffic abnormality occurs.

Optionally, the target road network area may also be an area that may be affected by the traffic abnormal event. Thus, in one possible implementation, the target road network region may include the first target road segment, at least one primary road segment directly connected to the first target road segment, and at least one secondary road segment indirectly connected to the first target road segment through the primary road segment.

For example, referring to fig. 2, fig. 2 is a schematic diagram of a target road network area according to an embodiment of the disclosure. As shown in fig. 3, in the road network area 200 (the drawing summaries show only a partial road network), taking the road points 1 to 6 as a part of the first planned path as an example, in the case where the road points 3 to 4 are the first target road segments, it can be known that the road points 3 to 7, the road points 2 to 3, the road points 3 to 8, the road points 4 to 5, the road points 9 to 10, the road points 11 to 12, the road points 4 to 13 are the first stage road segments directly connected to the first target road segments, the road points 5 to 6, the road points 5 to 12, the road points 8 to 12, the road points 2 to 10, the road points 8 to 14 are the second stage road segments indirectly connected to the first target road segments through the first stage road segments, and the target road network area marked with the dashed line frame 210 can be obtained based on the first stage road segments and the second stage road segments.

The historical space-time influence information of each historical abnormal event occurring in the target road network area can comprise influence conditions of each historical abnormal event in a space dimension and a time dimension.

The event related information of the traffic abnormal event may include all information related to the traffic abnormal event, and may include occurrence time, occurrence place, event type, event related vehicle type, event affected lane, event scene status, event current progress, etc. of the traffic abnormal event.

In order to obtain the event related information of the traffic abnormality event, in some possible embodiments, the event related information of the traffic abnormality event may be determined by:

In this step, in the case of determining the target road network area, history event information of each history abnormal event that has occurred in the target road network area, and scene information of the traffic abnormal event and road attribute information of the first target road segment may be acquired.

Here, the history event information of the history abnormal event may include all information related to the history abnormal event, and may include a history occurrence time, a history occurrence place, a history event type, a history event related vehicle type, a history event affected lane condition, a history event affected vehicle condition, history field information, a history event complete process, and the like of the history abnormal event.

The site information of the traffic abnormal event can comprise all information related to the site of the traffic abnormal event, and can comprise the occurrence time, the occurrence place, the vehicle type related to the traffic abnormal event, the condition of the event affecting the lane, the congestion length caused by the event, the number of the vehicles caused by the event, the site condition of the event, the current progress of the event and the like.

Here, the road attribute information of the first target link is an inherent attribute of the first target link, and may include a name, a length, a width, a passing direction, a level, the number of lanes, a traffic abnormality related to a lane condition, and the like of the first target link.

The site information may be obtained based on an image acquisition device, a video acquisition device, etc. set in the target road network area, for example, a camera, a video recorder, etc., and the image and the video acquired by the image acquisition device, the video acquisition device, etc. are obtained, so as to obtain the site information.

Furthermore, images and videos acquired by the automobile data recorder, the vehicle-mounted camera and the like can be acquired based on the automobile data recorder, the vehicle-mounted camera and the like installed on the automobile entering the target road network area, so that the field information is obtained.

Then, the traffic abnormal event and the plurality of historical abnormal events may be matched based on the field information and the historical field information indicated in the historical event information, and further a target abnormal event of which the type is the same as that of the traffic abnormal event may be determined from the plurality of historical abnormal events, so that the event type of the target abnormal event may be used as the event type of the traffic abnormal event based on the event type of the target abnormal event, and further the event related information of the traffic abnormal event may be determined based on the event type of the traffic abnormal event, the field information and the road attribute information.

Here, the event related information of the traffic abnormality event may be obtained based on the event type of the traffic abnormality event, the scene information, and the road attribute information based on a manual analysis or the like.

Optionally, event related information of the traffic abnormal event can be obtained based on the event type of the traffic abnormal event, the on-site information and the road attribute information by a neural network model, artificial intelligence algorithm analysis and other modes.

Further, in order to determine the event type of the traffic abnormal event, the on-site information of the traffic abnormal event may be obtained by analyzing the on-site information in a neural network model, an artificial intelligence algorithm or the like.

S102: and determining estimated influence road network areas and estimated influence time aiming at event road segments based on the historical space-time influence information of each historical abnormal event, wherein the event road segments are road segments in the target road network areas, and the traffic abnormal event occurs.

In the step, under the condition that the historical space-time influence information of each historical abnormal event occurring in the target road network area is determined, the historical space-time influence information of each historical abnormal event can be integrated according to the event type of each historical abnormal event, so that the estimated influence road network area and the estimated influence time of the event road section are obtained.

In order to obtain the estimated influence road network area and the estimated influence time, referring to fig. 3, a flowchart of a specific method for determining the estimated influence road network area and the estimated influence time in the path planning method provided by the embodiment of the disclosure is shown. As shown in fig. 3, in some possible embodiments, the determining, based on the historical spatiotemporal influence information of each historical abnormal event, the estimated influence road network area and the estimated influence time for the event road segment includes:

s1021: and analyzing the historical time-space influence information of the historical abnormal event according to each historical abnormal event to obtain a historical influence road network area and a historical influence time of the historical abnormal event.

In the step, for the historical space-time information of each historical abnormal event occurring in the target road network area, the historical influence road network area and the historical influence time of the historical abnormal event can be obtained through analysis.

The historical space-time influence information of each historical abnormal event can comprise a historical influence road network area and a historical influence time of each historical abnormal event, and it can be understood that the historical influence road network area can describe the influence of the historical abnormal event on the road network area, including congestion length, number of congestion vehicles and the like, and the historical influence time can describe the influence of the historical abnormal event on time, including congestion duration and the like.

Optionally, in order to obtain the historical influence road network area and the historical influence time of the historical abnormal event, the historical influence road network area and the historical influence time of the historical abnormal event can be obtained by analyzing the historical space-time influence information of the historical abnormal event in a neural network model, an artificial intelligence algorithm analyzing mode and the like.

Optionally, the historical influence road network area and the historical influence time of the historical abnormal event can be obtained by analyzing the historical space-time influence information of the historical abnormal event in a manual analysis mode or the like.

S1022: and carrying out aggregation processing on the acquired plurality of historical abnormal events based on the event type of each historical abnormal event to obtain at least one abnormal event set, wherein each abnormal event set comprises at least one historical abnormal event.

In this step, in order to improve accuracy of the estimated influence road network area and the estimated influence time, the acquired plurality of historical abnormal events may be aggregated according to event types based on event types of each historical abnormal event, so as to obtain at least one abnormal event set, where it may be understood that each abnormal event set includes a historical abnormal event of an event type.

For example, the acquired plurality of historical abnormal events may be aggregated to obtain three sets of abnormal events including a rear-end collision set, a control abnormal set, and a blocking set, each including at least one historical abnormal event.

S1023: and selecting a target event set from the at least one abnormal event set based on the event type of the traffic abnormal event indicated by the event related information, wherein the historical abnormal event in the target event set is the same as the event type of the traffic abnormal event.

In the step, under the condition that the event related information is determined, the traffic abnormal event and the at least one abnormal event set can be matched according to the event type of the traffic abnormal event indicated by the event related information, so that a target event set which is the same as the event type of the traffic abnormal event is selected from the at least one abnormal event set.

For example, in the above example, in the case where the event related information indicates that the traffic abnormal event is an event type of a rear-end collision, the rear-end collision set may be determined as a target event set from the above three abnormal event sets.

S1024: and determining the estimated influence road network area and the estimated influence time which take the event road section as the center based on the historical influence road network area and the historical influence time of each historical abnormal event in the target event set.

In the step, under the condition that the target event set is determined, based on each historical abnormal event in the target event set, the historical influence road network area and the historical influence time of each historical abnormal event in the target event set can be integrated, and then the event road section is taken as the center, so that the estimated influence road network area and the estimated influence time are comprehensively obtained.

The above steps S102 and S103 are carried out: and determining current traffic flow information in the estimated influence road network area and estimated traffic flow information at the estimated influence time.

In this step, under the condition that the estimated influence road network area and the estimated influence time are determined, current traffic information in the estimated influence road network area may be determined, where it may be understood that, based on the number of current vehicles in the estimated influence road network area, current traffic information in the estimated influence road network area may be determined.

Further, estimated traffic flow information at the estimated time of influence may also be determined. Here, in the case of determining the estimated influence road network area, the distance and the estimated arrival time of the vehicle that would enter the estimated influence road network area from the estimated influence road network area may be determined, and the estimated influence time may be combined, thereby determining the estimated vehicle flow information.

In order to obtain the estimated traffic flow, referring to fig. 4 specifically, a flowchart of a specific method for determining the estimated traffic flow information in the path planning method provided by the embodiment of the disclosure is shown. As shown in fig. 4, in some possible embodiments, the estimated traffic information of the estimated affected road network area within the estimated affected time is determined by:

s1031: and determining an extended influence road network area outside the estimated influence road network area based on the estimated influence road network area and the estimated influence time.

In this step, since the influence of the traffic abnormal event has a certain space and time range, and the possibility that a certain traffic abnormal event affects all areas and all time periods is small, the extended influence road network area outside the estimated influence road network area can be determined based on the estimated influence road network area and the estimated influence time.

It is understood that the expansion affects vehicles in the road network area that include the estimated traffic flow information.

Specifically, the expansion influence road network area of multiple levels may be divided in advance, for example, a circular road network area of one kilometer, three kilometers, five kilometers, or the like centered on the estimated influence road network area is used as the expansion influence road network area. Aiming at the difference of the area sizes of the estimated influence road network areas and the difference of the time length of the estimated influence time, the proper extended influence road network area can be selected based on manual experience.

Optionally, a suitable expansion influence road network area can be selected from the expansion influence road network areas of a plurality of levels in a neural network model, artificial intelligence algorithm analysis and other modes.

S1032: and acquiring vehicle running information of each first vehicle in the extended influence road network area.

In this step, in the case where the expansion influence road network area is determined, vehicle travel information of each first vehicle in the expansion influence road network area may be acquired.

The vehicle driving information of each first vehicle may include all information related to each first vehicle, and may include a current position, a planned path, a destination, an estimated driving time, and the like of each first vehicle.

S1033: and determining at least one second vehicle from a plurality of first vehicles in the extended influence road network area based on the vehicle running information of each first vehicle, wherein the second vehicle is a vehicle which can enter the estimated influence road network area in the estimated influence time.

In this step, in the case of determining the vehicle travel information of each first vehicle, at least one second vehicle that will enter the estimated influence road network area within the estimated influence time may be determined from among the plurality of first vehicles.

Further, in order to determine more vehicles that may be involved in the traffic anomaly event and improve the comprehensiveness of the estimated traffic flow information, an extended influence time beyond the estimated influence time may be determined, and specifically, a plurality of levels of extended influence time may be divided in advance, for example, ten minutes, thirty minutes, one hour, etc. after the estimated influence time. For the different area sizes of the estimated influence road network areas and the different time lengths of the estimated influence time, the suitable extended influence time can be selected based on manual experience, and at least one vehicle which can enter the estimated influence road network areas within the extended influence time is also used as the second vehicle.

Optionally, a suitable expansion influence time can be selected from expansion influence times of a plurality of preset levels in a neural network model, artificial intelligence algorithm analysis and other modes.

S1034: and obtaining the estimated vehicle flow information based on the number of the at least one second vehicle.

In the step, under the condition that at least one second vehicle is determined, the number of the at least one second vehicle can be acquired, so that the estimated vehicle flow information is obtained.

The above steps S103 and S104 are carried out: based on the event related information, the historical space-time influence information, the current traffic flow information and the estimated traffic flow information, estimating space-time influence information of the traffic abnormal event on the first target road section.

In the step, under the condition that the event related information, the historical space-time influence information, the current traffic flow information and the estimated traffic flow information are determined, estimating the space-time influence information of the traffic abnormal event on the first target road section can be obtained through a neural network model, artificial intelligence algorithm analysis and other modes, namely estimating the influence of the traffic abnormal event on the first target road section.

S105: and determining whether a travel path needs to be re-planned for the user based on the space-time influence information.

In the step, under the condition of determining the space-time influence information, whether the influence of the traffic abnormal event on the user reaches the degree of requiring planning of the travel path again for the user can be judged based on the influence time indicated by the space-time influence information and the influence road network area.

In the path planning method provided by the embodiment of the disclosure, if a traffic abnormal event is detected to occur in a target road network area where a first target road section in a first planned path is located in a process that a user travels according to the first planned path, event related information of the traffic abnormal event and historical space-time influence information of each historical abnormal event occurring in the target road network area are obtained; determining estimated influence road network areas and estimated influence time for event road segments based on historical space-time influence information of each historical abnormal event, wherein the event road segments are road segments in the target road network areas, and the traffic abnormal event occurs in the road segments; determining current traffic flow information in the estimated influence road network area and estimated traffic flow information of the estimated influence road network area in the estimated influence time; estimating time-space influence information of the traffic abnormal event aiming at the first target road section based on the event related information, the historical time-space influence information, the current traffic flow information and the estimated traffic flow information; and determining whether a travel path needs to be re-planned for the user based on the space-time influence information.

In this way, when a traffic abnormal event occurs in a target road network area where a certain road section in a planned path is located in a process of traveling according to the planned path by a user, the time-space influence information of the traffic abnormal event on the road section can be estimated by combining the acquired event related information of the traffic abnormal event, the historical time-space influence information of each historical abnormal event occurring in the target road network area, the current traffic flow information and the estimated traffic flow information, so that the influence of the traffic abnormal event on the traveling of the user can be accurately estimated, and therefore whether the traffic abnormal event affects the user travel at the time or not can be rapidly judged, and appropriate countermeasures can be taken. Further, the time-space influence information of the traffic abnormal event is integrated, the information of the traffic abnormal event, the information of the historical event, the current traffic flow information and the estimated traffic flow information are evaluated through two dimensions of time and space, so that the judgment of the congestion influence range caused by the traffic abnormal event is more comprehensive and accurate, a user can conveniently avoid and keep away from the traffic abnormal event in time, the influence of the traffic abnormal event on the user trip is reduced, a planning path reaching a destination can be provided for the user, meanwhile, explanation about corresponding path planning and explanation about the traffic abnormal event condition can be provided for the user, the urban congestion problem is slowed down to a certain extent, the road utilization rate is improved, and more intelligent, convenient and efficient trip experience is provided for the user.

Referring to fig. 5, a flowchart of another path planning method according to an embodiment of the disclosure is shown, where the method includes steps S501 to S506, where:

s501: a first planned path from a departure point to a destination is planned for a user based on the departure point and the destination set by the user.

In this step, a user may input a departure place and a destination through an input device on a navigation terminal, and a first planned path from the departure place to the destination may be planned for the user based on the departure place and the destination set by the user.

It will be appreciated that the departure point and the destination may be displayed on a display screen of a navigation terminal used by the user, and that the first planned path may be an uninterrupted line from the departure point to the destination, or a series of points displayed on the display screen of the navigation terminal

The input device may be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged outside the display screen, or an external keyboard, a touch pad or a mouse.

S502: and in the process that the user travels according to the first planning path, if detecting that a traffic abnormal event occurs in a target road network area where a first target road section in the first planning path is located, acquiring event related information of the traffic abnormal event and historical space-time influence information of each historical abnormal event occurring in the target road network area.

S503: and determining estimated influence road network areas and estimated influence time aiming at event road segments based on the historical space-time influence information of each historical abnormal event, wherein the event road segments are road segments in the target road network areas, and the traffic abnormal event occurs.

S504: and determining current traffic flow information in the estimated influence road network area and estimated traffic flow information of the estimated influence road network area in the estimated influence time.

S505: based on the event related information, the historical space-time influence information, the current traffic flow information and the estimated traffic flow information, estimating space-time influence information of the traffic abnormal event on the first target road section.

S506: and determining whether a travel path needs to be re-planned for the user based on the space-time influence information.

The descriptions of the steps S502 to S506 may refer to the descriptions of the steps S101 to S105, and may achieve the same technical effects and solve the same technical problems, which are not described herein.

Next, the present embodiment will be further described with reference to some specific embodiments.

In order to obtain the spatiotemporal impact information, in some possible embodiments, the estimating the spatiotemporal impact information of the traffic anomaly event for the first target road segment based on the event related information, the historical spatiotemporal impact information, the current traffic flow information, and the estimated traffic flow information includes:

In this step, the time-space feature sequence of the traffic anomaly event may be determined based on the event related information, the historical time-space effect information, the current traffic flow information and the estimated traffic flow information, where, because the time-space effect information may include an effect time of the traffic anomaly event in a time dimension and an effect road network area in a space dimension, the time sequence and the space sequence may be obtained by parsing based on the event related information, the historical time-space effect information, the current traffic flow information and the estimated traffic flow information, and then mapping the two sequences onto the same two-dimensional table, so as to construct the time-space feature sequence of the traffic anomaly event, where, it may be understood that the time-space feature sequence is a two-dimensional sequence.

And then, based on the trained space-time prediction model, inputting the space-time characteristic sequence into the trained space-time prediction model, and carrying out convolution processing by using the space-time prediction model so as to obtain space-time influence information of the traffic abnormal event on the first target road section.

For the constructed space-time characteristic sequence, convolution processing can be performed on different channels based on a selected proper convolution kernel, convolution processing and pooling processing are performed through at least one convolution layer and pooling layer, and loss is weighted by adopting a mean square error function as a loss function, so that the space-time influence information is obtained.

In order to accurately determine whether the impact of the traffic abnormal event on the user reaches the extent that the travel path needs to be re-planned for the user, in some possible implementations, the determining, based on the spatio-temporal impact information, whether the travel path needs to be re-planned for the user includes:

In this step, the current position of the user may be obtained first, then, based on the first planned path, a travel time required for the user to travel from the current position to the first target road section according to the first planned path may be determined, and based on the influence time indicated by the time-space influence information, whether the influence time is greater than or equal to the travel time may be detected.

It is understood that, if the influence time is greater than or equal to the travel time, when the user travels from the current location to the first target road section according to the first planned route, the influence caused by the traffic abnormal event is still not solved, so it is determined that the travel route needs to be planned again for the user.

Further, it can be understood that, if the influence time is smaller than the travel time, the influence caused by the traffic abnormal event is already solved when the user travels from the current position to the first target road section according to the first planned path, so that it is not necessary to re-plan the travel path for the user.

In some possible embodiments, in a case where it is determined that the travel path needs to be re-planned for the user, the method further includes:

In the step, under the condition that the travel path needs to be planned again for the user, a second planned path from the current position to the destination can be planned for the user according to the destination in the first planned path based on the influence road network area indicated by the space-time influence information.

It will be appreciated that in an actual scenario, the first target road segment and at least one first road segment connected to the first target road segment need to be adjusted, i.e. the first planned path includes a first road segment that needs to be adjusted and a first road segment that does not need to be adjusted. And analyzing based on the space-time influence information, wherein the first road section without adjustment can be completely reserved under the condition that the first road section without adjustment and the traffic abnormal event do not have intersection, and only the first road section with adjustment is adjusted, so that a second planning path from the current position to the destination is planned for the user.

Optionally, a second planned path, which is completely different from the first planned path, may also be planned again for the user based on the spatio-temporal impact information.

After obtaining the second planned path, in order to improve accuracy and perfection of path planning, a travel cost of the first planned path and a travel cost of the second planned path may be compared to push a better planned path for the user, and in some possible implementations, after the estimating the influence road network area based on the space-time influence information indicates, the method includes:

In this step, the estimated time of influence indicated by the time-space influence information may be determined first, based on the estimated time of influence, a first travel time and a first travel distance required for the user to travel from the current position to the destination according to the first planned path may be determined, then a second travel time and a second travel distance for the user to travel according to the second planned path may be determined, based on the first travel time and the first travel distance, a travel cost of the first planned path may be determined, and based on the second travel time and the second travel distance, a travel cost of the second planned path may be determined, if the travel cost of the second planned path is smaller than the travel cost of the first planned path, here, it may be understood that the second planned path is better than the first planned path, and the second planned path may be further pushed to the user.

It will be appreciated that the travel cost of the first planned path and the travel cost of the second planned path represent the effect of the first planned path and the second planned path on the travel of the user.

In order to determine the travel cost of the first planned path, the ratio of the first travel time to the first travel distance, for example, 1/2, 1/5, 1/10, etc., may be calculated based on the pre-divided cost level, so as to obtain the travel cost of the first planned path.

In order to determine the travel cost of the second planned path, a calculation mode which is the same as the travel cost of the first planned path may be adopted based on the second travel time and the second travel distance, so as to obtain the travel cost of the second planned path.

Further, if the travel cost of the first planned path is less than the travel cost of the second planned path, it may be understood here that the first planned path is better than the second planned path, and the first planned path may still be continuously pushed to the user.

In order for the user to learn about the current driving situation, in some possible embodiments, in case the second planned path is pushed to the user, the method comprises:

In this step, a prompt message may be generated for the traffic abnormality event and the second planned path, and the prompt message may be pushed to the user, so as to explain the traffic abnormality event and the path adjustment to the user.

The prompt information may include information of the traffic abnormal event and the second planned path related to the user, and may include occurrence time, occurrence place, event type, event site status, current progress of an event, time-space influence information, and the like of the traffic abnormal event.

It can be understood that, when the path switching is performed on the user, that is, the second planned path is pushed to the user, explanation about the traffic abnormal event and path adjustment can be performed on the user at the same time, so that the travel experience of the user is improved.

Furthermore, no matter whether the travel path is required to be planned for the user again, prompt information about the traffic abnormal event can be given to the user, so that the user can know the corresponding situation under the condition that the traffic abnormal event occurs.

It will be appreciated by those skilled in the art that in the above-described method of the specific embodiments, the written order of steps is not meant to imply a strict order of execution but rather should be construed according to the function and possibly inherent logic of the steps.

Based on the same inventive concept, the embodiments of the present disclosure further provide a path planning device corresponding to the path planning method, and since the principle of solving the problem by the device in the embodiments of the present disclosure is similar to that of the path planning method in the embodiments of the present disclosure, the implementation of the device may refer to the implementation of the method, and the repetition is omitted.

Referring to fig. 6, 7 and 8, fig. 6 is a schematic diagram of a path planning apparatus according to an embodiment of the disclosure, fig. 7 is a schematic diagram of a second path planning apparatus according to an embodiment of the disclosure, and fig. 8 is a schematic diagram of a third path planning apparatus according to an embodiment of the disclosure. As shown in fig. 6, a path planning apparatus 600 provided by an embodiment of the present disclosure includes:

the detection module 610 is configured to, when a user detects that a traffic anomaly event occurs in a target road network area where a first target road segment in a first planned path is located during a travel process according to a first planned path, obtain event related information of the traffic anomaly event and historical space-time influence information of each historical anomaly event that occurs in the target road network area.

The first determining module 620 is configured to determine, based on the historical spatiotemporal impact information of each historical abnormal event, an estimated impact road network area and an estimated impact time for an event road segment, where the event road segment is a road segment in the target road network area in which the traffic abnormal event occurs.

A second determining module 630 is configured to determine current traffic information in the estimated affected road network area, and estimated traffic information of the estimated affected road network area in the estimated affected time.

And the estimating module 640 is configured to estimate the spatiotemporal influence information of the traffic abnormality event for the first target road segment based on the event related information, the historical spatiotemporal influence information, the current traffic flow information and the estimated traffic flow information.

And an adjustment module 650, configured to determine, based on the spatiotemporal impact information, whether a trip path needs to be re-planned for the user.

In an alternative embodiment, the detection module 610 is configured to determine the event related information of the traffic anomaly event by:

In an alternative embodiment, the first determining module 620 is specifically configured to:

In an alternative embodiment, the second determining module 630 is configured to determine the estimated traffic information of the estimated affected road network area within the estimated affected time by:

In an alternative embodiment, the estimating module 640 is specifically configured to:

In an alternative embodiment, the adjusting module 650 is specifically configured to:

In an alternative embodiment, as shown in fig. 7, the path planning apparatus 600 further includes a first planning module 660, where the first planning module 660 is configured to:

In an alternative embodiment, as shown in fig. 8, the path planning apparatus 600 further includes a second planning module 670 and a prompting module 680, where the second planning module 670 is configured to:

In an alternative embodiment, the second planning module 670 is further configured to:

The prompting module 680 is specifically configured to:

Here, the path planning apparatus may be an independent apparatus that is pre-installed on a navigation terminal used by a user, such as a mobile phone device, an in-vehicle device, or the like, in the form of a plug-in.

Optionally, the path planning device may also be used as an additional function of a navigation software product in the navigation terminal used by the user, and the functions thereof may be loaded by updating the navigation software product, and the like.

The process flow of each module in the apparatus and the interaction flow between the modules may be described with reference to the related descriptions in the above method embodiments, which are not described in detail herein.

In the path planning device provided by the embodiment of the disclosure, if a traffic abnormal event is detected to occur in a target road network area where a first target road section in a first planned path is located in a process that a user travels according to the first planned path, event related information of the traffic abnormal event and historical space-time influence information of each historical abnormal event occurring in the target road network area are obtained; determining estimated influence road network areas and estimated influence time for event road segments based on historical space-time influence information of each historical abnormal event, wherein the event road segments are road segments in the target road network areas, and the traffic abnormal event occurs in the road segments; determining current traffic flow information in the estimated influence road network area and estimated traffic flow information of the estimated influence road network area in the estimated influence time; estimating time-space influence information of the traffic abnormal event aiming at the first target road section based on the event related information, the historical time-space influence information, the current traffic flow information and the estimated traffic flow information; and determining whether a travel path needs to be re-planned for the user based on the space-time influence information.

Corresponding to the path planning methods in fig. 1 and fig. 5, the embodiment of the present disclosure further provides an electronic device 900, as shown in fig. 9, which is a schematic structural diagram of the electronic device 900 provided in the embodiment of the present disclosure, including:

a processor 910, a memory 920, and a bus 930; memory 920 is used to store execution instructions, including memory 921 and external memory 922; the memory 921 is also referred to as an internal memory, and is used for temporarily storing operation data in the processor 910 and data exchanged with an external memory 922 such as a hard disk, and the processor 910 exchanges data with the external memory 922 through the memory 921, and when the electronic device 900 operates, the processor 910 and the memory 920 communicate with each other through the bus 930, so that the processor 910 may execute the steps of the path planning method described above.

It should be understood that the structures illustrated in the embodiments of the present application do not constitute a specific limitation on the electronic device 900. In other embodiments of the present application, electronic device 900 may include more or less components than illustrated, or certain components may be combined, or certain components may be split, or different arrangements of components. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

The disclosed embodiments also provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the path planning method described in the method embodiments above. Wherein the storage medium may be a volatile or nonvolatile computer readable storage medium.

The embodiments of the present disclosure further provide a computer program product, where the computer program product includes computer instructions, where the computer instructions, when executed by a processor, may perform the steps of the path planning method described in the foregoing method embodiments, and specifically, reference the foregoing method embodiments will not be described herein.

Wherein the above-mentioned computer program product may be realized in particular by means of hardware, software or a combination thereof. In an alternative embodiment, the computer program product is embodied as a computer storage medium, and in another alternative embodiment, the computer program product is embodied as a software product, such as a software development kit (Software Development Kit, SDK), or the like.

It will be clearly understood by those skilled in the art that, for convenience and brevity of description, specific working processes of the apparatus, device and storage medium described above may refer to corresponding processes in the foregoing method embodiments, which are not described herein again. In the several embodiments provided in the present disclosure, it should be understood that the disclosed method, apparatus, device, and storage medium may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and there may be other manners of division in actual implementation, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present disclosure may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer readable storage medium executable by a processor. Based on such understanding, the technical solution of the present disclosure may be embodied in essence or a part contributing to the prior art or a part of the technical solution, or in the form of a software product stored in a storage medium, including several instructions for causing an electronic device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in the embodiments of the present disclosure. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

Finally, it should be noted that: the foregoing examples are merely specific embodiments of the present disclosure, and are not intended to limit the scope of the disclosure, but the present disclosure is not limited thereto, and those skilled in the art will appreciate that while the foregoing examples are described in detail, it is not limited to the disclosure: any person skilled in the art, within the technical scope of the disclosure of the present disclosure, may modify or easily conceive changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features thereof; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the disclosure, and are intended to be included within the scope of the present disclosure. Therefore, the protection scope of the present disclosure shall be subject to the protection scope of the claims.

Claims

1. A method of path planning, the method comprising:

2. The method of claim 1, wherein prior to the acquiring event related information of the traffic anomaly event and historical spatiotemporal impact information of each historical anomaly event that occurred in the target road network region, the method comprises:

3. The method of claim 1, wherein the event related information of the traffic anomaly event is determined by:

4. The method of claim 1, wherein determining the predicted impact road network area and the predicted impact time for the event road segment based on the historical spatiotemporal impact information for each historical anomaly event comprises:

5. The method of claim 4, wherein the estimated traffic information for the estimated affected road network area over the estimated time of impact is determined by:

6. The method of claim 1, wherein the predicting the spatiotemporal impact information of the traffic anomaly event for the first target segment based on the event related information, the historical spatiotemporal impact information, the current traffic flow information, and the predicted traffic flow information comprises:

7. The method of claim 1, wherein the determining whether a travel path needs to be rescheduled for the user based on the spatio-temporal impact information comprises:

8. The method of claim 1, wherein in the event that it is determined that a travel path needs to be re-planned for the user, the method further comprises:

9. The method of claim 8, wherein after planning a second planned path for the user from a current location to a destination in the first planned path based on the estimated impact road network area indicated by the spatio-temporal impact information, the method comprises:

10. The method according to claim 9, wherein in case the second planned path is pushed to the user, the method comprises:

11. A path planning apparatus, the apparatus comprising:

12. An electronic device, comprising: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory in communication over the bus when the electronic device is running, the machine-readable instructions when executed by the processor performing the steps of the path planning method of any of claims 1 to 10.

13. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when executed by a processor, performs the steps of the path planning method according to any one of claims 1 to 10.

14. A computer program product comprising computer instructions which, when executed by a processor, implement the steps of the path planning method of any one of claims 1 to 10.