Path planning method and device, electronic equipment and storage medium

Abstract

The invention provides a path planning method and device, electronic equipment, a storage medium and a program product, and relates to the technical field of intelligent traffic, in particular to the technical field of Internet of Vehicles, the technical field of navigation, the technical field of big data processing and the like. According to the specific implementation scheme, under the condition that it is determined that a congested road section is of a propagation congestion type, congestion diffusion information of a road network topology is determined based on the road network topology of the congested road section and passing time sequence information of each road section on the road network topology, the propagation congestion type represents that the congestion state can be propagated from the congested road section to the type of other road sections of the network topology, and the congestion diffusion information comprises a congestion diffusion path and a congestion time period; performing path planning on the target vehicle passing through the congestion diffusion path in the congestion period to obtain path planning information of bypassing the congestion diffusion path; and displaying the path planning information and the congestion diffusion information on a navigation interface.

Description

Technical Field

[0001] The present disclosure relates to the field of intelligent transportation technology, in particular to the fields of vehicle networking technology, navigation technology, big data processing technology, etc., and can be applied to scenarios such as vehicle navigation and path planning, and in particular to a path planning method, device, electronic device, storage medium, and program product. Background Art

[0002] With the rapid growth of the vehicle population, road congestion is becoming increasingly frequent and prominent. Current navigation systems can identify road conditions and provide guidance on congested sections of a planned route, but the rationality of route planning still needs to be improved. Summary of the Invention

[0003] The present disclosure provides a path planning method, device, electronic device, storage medium, and program product.

[0004] According to one aspect of the present disclosure, a path planning method is provided. When a congested road section is determined to be a propagation congestion type, congestion diffusion information of the road network topology is determined based on the road network topology of the congested road section and the traffic timing information of each road section on the road network topology, wherein the propagation congestion type characterizes the type of congestion state that will propagate from the congested road section to other road sections of the network topology, and the congestion diffusion information includes the congestion diffusion path and the congestion period; path planning is performed on target vehicles that pass through the congestion diffusion path during the congestion period to obtain path planning information for detouring the congestion diffusion path; and the path planning information and congestion diffusion information are displayed on a navigation interface.

[0005] According to another aspect of the present disclosure, a path planning device is provided, including a congestion diffusion determination module for determining congestion diffusion information of a road network topology based on the road network topology of the congested road section and the traffic timing information of each road section on the road network topology when a congested road section is determined to be a propagation congestion type, wherein the congestion diffusion information includes a congestion diffusion path and a congestion period; a path planning module for performing path planning for a target vehicle passing through the congestion diffusion path during the congestion period based on the congestion diffusion information, and obtaining path planning information for detouring the congestion diffusion path; and a display module for displaying the path planning information and congestion diffusion information on a navigation interface.

[0006] According to another aspect of the present disclosure, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the above method.

[0007] According to another aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to cause a computer to execute the above method.

[0008] According to another aspect of the present disclosure, a computer program product is provided, including a computer program, which implements the above method when executed by a processor.

[0009] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The accompanying drawings are provided to facilitate a better understanding of the present invention and do not constitute a limitation of the present disclosure.

[0011] Figure 1 Schematically illustrates an exemplary system architecture to which the path planning method and apparatus according to an embodiment of the present disclosure may be applied;

[0012] Figure 2 The following schematically shows a flow chart of a path planning method according to an embodiment of the present disclosure;

[0013] Figure 3 Schematically shows a road network topology diagram according to an embodiment of the present disclosure;

[0014] Figure 4 Schematically shows a scenario diagram based on path planning according to an embodiment of the present disclosure;

[0015] Figure 5 Schematically shows a flow chart of a path planning method according to another embodiment of the present disclosure;

[0016] Figure 6 A block diagram schematically illustrates a path planning device according to an embodiment of the present disclosure; and

[0017] Figure 7 A block diagram of an electronic device suitable for implementing a path planning method according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0018] The following description of exemplary embodiments of the present disclosure is made in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding. These details should be considered as merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0019] Figure 1 An exemplary system architecture to which the road condition identification method and apparatus according to an embodiment of the present disclosure can be applied is schematically shown.

[0020] It should be noted that Figure 1 The examples shown are merely examples of system architectures to which the embodiments of the present disclosure may be applied, to help those skilled in the art understand the technical content of the present disclosure, but do not mean that the embodiments of the present disclosure may not be used in other devices, systems, environments or scenarios.

[0021] like Figure 1 As shown, the system architecture 100 according to this embodiment may include a vehicle 101, a network 102, and a server 103. The network 102 is used to provide a medium for a communication link between the vehicle 101 and the server 105. The network 104 may include various connection types, such as wired and / or wireless communication links, etc.

[0022] Users can use vehicle 101 to interact with server 103 via network 102 to receive or send messages, etc. Vehicle 101 may be installed with various communication client applications, such as knowledge reading applications, web browser applications, search applications, instant messaging tools, email clients, and / or social platform software (for example only). It should be noted that users can also use other terminal devices, such as mobile phones and tablets, to interact with server 103 via network 102 to receive or send messages, as long as the server 103 can obtain driving status information of vehicle 101.

[0023] The vehicle 101 may be a vehicle driven by a person, but is not limited thereto. The vehicle 101 may also be an autonomous driving vehicle, and the type of vehicle is not limited thereto.

[0024] Server 103 may be a server that provides various services, such as a background management server that supports content viewed by users in vehicle 101 (for example only). The background management server may analyze and process received data such as user requests, and provide feedback to vehicle 101 on the processing results (e.g., web pages, information, or data obtained or generated based on user requests).

[0025] It should be noted that the road condition identification method provided in the embodiment of the present disclosure can generally be executed by the server 103. Accordingly, the road condition identification device provided in the embodiment of the present disclosure can also be set in the server 103.

[0026] It should be understood that Figure 1 The number of vehicles, networks and servers in the embodiment is only illustrative. Any number of vehicles, networks and servers may be provided as needed.

[0027] In the technical solution disclosed herein, the collection, storage, use, processing, transmission, provision, disclosure and application of user personal information involved comply with the provisions of relevant laws and regulations, take necessary confidentiality measures, and do not violate public order and good morals.

[0028] In the technical solution disclosed herein, the user's authorization or consent is obtained before obtaining or collecting the user's personal information.

[0029] It should be noted that the sequence numbers of the operations in the following method are only used to indicate the operation for the purpose of description, and should not be regarded as indicating the order in which the operations should be performed. Unless explicitly stated, the method does not need to be performed in the order shown.

[0030] Figure 2 The flowchart of the path planning method according to the embodiment of the present disclosure is schematically shown.

[0031] like Figure 2 As shown, the method includes operations S210 to S240.

[0032] In operation S210 , when it is determined that the congested road segment is of the propagation congestion type, congestion diffusion information of the road network topology is determined based on the road network topology of the congested road segment and the traffic timing information of each road segment on the road network topology.

[0033] The propagation congestion type characterizes the type of congestion state that will spread from the congested road segment to other road segments in the network topology. The congestion diffusion information includes the congestion diffusion path and congestion period.

[0034] Optionally, a road network topology can include edges and the connection points between them. Edges represent road segments, while connection points represent the connections between road segments. A road network topology can reflect the spatial adjacency of roads, hierarchical relationships (e.g., trunk road, branch road, expressway), and capacity differences.

[0035] Traffic time series information represents a collection of information about the dynamic changes in traffic status over time on a road section. Traffic time series information can provide a temporal basis for congestion diffusion prediction.

[0036] The congestion diffusion path refers to the dynamic trajectory of congestion spreading from a congested road section to surrounding sections. For example, congestion spreads spatially along upstream and downstream sections and adjacent branches.

[0037] The congestion period refers to the time range when congestion occurs on the road section on the congestion diffusion path. The congestion period can include the starting time of congestion, the peak period of congestion and the end time of congestion.

[0038] Based on the road network topology, we can identify road segments connected to congested sections. Congestion may spread to one or more road segments connected to the congested section, forming a congestion diffusion path. Based on the traffic timing information of each road segment along the congestion diffusion path, we can determine the current traffic status of each road segment. Based on the traffic status information of each road segment, we can determine whether congestion is currently occurring or is likely to occur, and predict the congestion period when congestion will occur.

[0039] In operation S220 , a path planning is performed for a target vehicle that passes through the congestion diffusion path during the congestion period, and path planning information for bypassing the congestion diffusion path is obtained.

[0040] For example, based on the network topology and the traffic sequence information of each road segment in the road network topology, a non-congested diffusion path or a path during a non-congested period can be determined. Based on the non-congested diffusion path or the path during a non-congested period, path planning information for detouring around the congested diffusion path can be determined.

[0041] For example, if trunk road A is congested at time T1, the congestion will spread to branch road B connected to the trunk road and continue until time T2. If the target vehicle's original route would pass through branch road B and reach branch road B at any time between T1 and T2, the target vehicle can be routed to choose branch road C, which is a non-congested diffusion path, for detour.

[0042] In operation S230 , the route planning information and the congestion diffusion information are displayed on the navigation interface.

[0043] Route planning information can include detour routes and detour times. Route planning information and congestion diffusion information can be displayed in different colors on the navigation interface. For example, route planning information can be displayed in green on the map, while congestion diffusion information can be displayed in red.

[0044] For example, based on the congestion diffusion information, path planning information for multiple detours around the congestion diffusion path may be generated and displayed on the navigation interface.

[0045] According to the embodiments of the present disclosure, by determining congestion diffusion information based on the road network topology of the congested road sections and the traffic timing information of each road section on the road network topology, the road sections to which the congestion may spread can be identified based on the congestion diffusion information, and reasonable path planning can be given according to the identification results, thereby improving the early warning capability of path planning and improving the rationality of path planning.

[0046] According to an embodiment of the present disclosure, the congestion type of a congested road section can be identified in the following manner: based on the traffic timing information of multiple congested road sections in different time periods, determining the first congestion status information of the congested road section; based on the traffic timing information of multiple adjacent road sections in different time periods, determining the second congestion status information of the adjacent road section; and based on the first congestion status information and the second congestion status information, determining the congestion type identification result of the congested road section.

[0047] According to an embodiment of the present disclosure, the road network topology of a congested road section can be determined in the following manner: based on a map of the area where the congested road section is located and the association relationship between multiple road sections, an initial road network topology centered on the congested road section is generated; based on real-time acquired road traffic information, the initial road network topology is updated to obtain the road network topology.

[0048] The map includes information such as the geographic locations and relationships of multiple road segments. A map of the area where the congested road segment is located can be created by drawing a circle with a predetermined radius R, centered on the congested road segment. Information such as the length of each road segment, the relationships between multiple road segments, and the locations of connections can be extracted from the map to generate an initial road network topology centered on the congested road segment, with edges representing the road segments and nodes representing the connections.

[0049] Integrate real-time data into the initial road network topology and dynamically modify the road network status to reflect the current real-world traffic conditions. For example, it can recalculate travel times based on real-time vehicle speeds, bind events like accidents and construction to specific road sections or nodes, or update road section statuses such as "unblocked," "congested," or "closed."

[0050] Figure 3 A road network topology diagram according to an embodiment of the present disclosure is schematically shown.

[0051] like Figure 3 As shown, with congested road section 310 as the center, the congested road section 310 is expanded outward using connection points A and B. For example, the first road section 320 is obtained from connection point B to connection point C, and the second road section 330 is obtained from connection point B to connection point D. This process is repeated until the initial road network topology is obtained. Based on real-time road traffic information, the initial road network topology is updated to obtain the road network topology.

[0052] According to the embodiments of the present disclosure, a basic framework of the initial road network topology is provided by utilizing a static map and the association relationship between multiple road segments, and then dynamic road traffic information is injected into the initial road network topology. Since the static basic framework ensures the basic logical correctness of the road network, real-time road traffic information can correct local anomalies, thereby improving the accuracy of road network topology modeling.

[0053] According to an embodiment of the present disclosure, the traffic sequence information for each road segment in a road network topology can be determined by obtaining multiple traffic information for each road segment in the road network topology at different times within a preset time period; and arranging the traffic sequence information in a time sequence. The traffic information includes at least one of vehicle speed, traffic volume, lane occupancy, and vehicle travel direction.

[0054] There are no restrictions on the preset time period. For example, it can include 5 minutes or 6 minutes. Furthermore, there are no restrictions on how the multiple collection moments within the preset time period are divided. For example, the collection moments can be divided at equal intervals or randomly. As long as multiple traffic information is collected at different times within the preset time period, it is sufficient.

[0055] For example, the longer the preset time period, the higher the reference value and the higher the accuracy of identifying abnormal road sections. However, on the contrary, the recognition efficiency is lower. To balance recognition accuracy and processing efficiency, the preset time period can be set to 5 minutes.

[0056] Preferably, the traffic information may include vehicle speed, traffic volume, lane occupancy, and vehicle travel direction. The more information referenced in the traffic information, the higher the accuracy of abnormal road section identification.

[0057] In addition, arranging multiple traffic information in time sequence to obtain traffic time sequence information can significantly improve the changing trend of the vehicle's driving status over time in the time dimension and improve the accuracy of identifying abnormal road sections.

[0058] For example, multiple traffic information of each road section in the road network topology at different times within a preset time period can be obtained through IoT devices configured on the road section (such as cameras, sensors, etc.) or through an API (Application Programming Interface) interface from a third-party traffic information platform.

[0059] According to an embodiment of the present disclosure, obtaining multiple traffic information of each road section on the road network topology within a preset time period may include: when it is determined that there is a moment of missing information, based on the historical traffic information of the road section at the historical moment, completing the information of the moment of missing information.

[0060] For example, if an IoT device is damaged or loses power, or if a communication link is interrupted, data transmission fails, resulting in a loss of real-time traffic information for a road section. Alternatively, environmental factors such as heavy rain or snow obscuring IoT devices can cause a loss of real-time traffic information for a road section. Furthermore, a lack of IoT devices on remote sections or small roads can lead to a loss of real-time traffic information for a road section.

[0061] Missing information can be supplemented based on the historical average of data from the same period. For example, if traffic information for road section X is missing from 08:00 to 08:15 due to a camera malfunction, the missing traffic information can be supplemented using the historical average of the same period from the previous week. The present disclosure is not limited to this, and supplementation can also be performed based on a weighted average of historical data from the same period, for example, with closer time intervals being given a higher weight and more distant time intervals being given a lower weight.

[0062] According to the embodiments of the present disclosure, missing data can cause a break in the time series and affect statistical analysis. By supplementing historical data, the congestion status of the missing period can be restored, thereby improving the accuracy of congestion detection and prediction.

[0063] According to an embodiment of the present disclosure, before executing operation S210, it may also include: in response to receiving multiple abnormal congestion feedback information sent through the navigation interface; and when the multiple abnormal congestion feedback information all represent abnormal congested road sections, executing the operation of determining the congestion diffusion information of the road network topology.

[0064] For example, abnormal congestion feedback information can be submitted by a user while using navigation by clicking the "Report Congestion" button on the navigation interface or by using a voice command (such as "Severe congestion ahead"). The navigation system can automatically associate the location, time, current vehicle speed, and other information at the time of reporting.

[0065] If multiple users report abnormal congestion feedback information, it is determined that the current road section is congested. At this time, the congestion diffusion information of the road network topology is determined based on the road network topology of the congested road section and the traffic timing information of each road section on the road network topology.

[0066] According to an embodiment of the present disclosure, responding to received abnormal congestion feedback information can help quickly identify sudden congestion, and verification based on multiple abnormal congestion feedback information can achieve cross-verification to avoid inaccurate congestion information due to false alarms or malicious reporting.

[0067] According to an embodiment of the present disclosure, with respect to the operation of determining the congestion diffusion information of the road network topology, the above-mentioned path planning method also includes: performing road condition identification on the congested road section based on the current traffic information and reference traffic information of the congested road section to obtain an initial identification result; and when the initial identification result indicates that the congested road section is abnormal, performing the operation of determining the congestion diffusion information of the road network topology.

[0068] The current traffic information is the traffic information at the current moment.

[0069] The reference traffic information can be the reference information under normal traffic status. The reference traffic information has the same information type as the current traffic information.

[0070] The current traffic information is compared with the reference traffic information. If there is a significant difference between the current traffic information and the reference traffic information, for example, the difference between the current traffic information and the reference traffic information is greater than a preset difference threshold, the recognition result is determined to indicate that the congested road section is abnormal. If the difference between the current traffic information and the reference traffic information is less than the preset difference threshold, the congested road section is determined to be normal.

[0071] For example, a congested road section is a major traffic section that experiences congestion during rush hour. The average vehicle speed of the reference traffic information is A km / h. The average vehicle speed of the current traffic information is B km / h. Although B km / h is relatively low, it indicates congestion on this road section. However, if the difference between the current traffic information B km / h and the reference traffic information A km / h is less than a preset difference threshold, the congested road section is determined to be normal.

[0072] By comparing the reference traffic information provided by the embodiment of the present disclosure with the current traffic information to determine whether the congested road section is abnormal, the recognition accuracy can be improved. At the same time, by referring to the same traffic information, the processing means can be simplified and the processing efficiency can be improved.

[0073] Alternatively, the reference traffic information can be determined based on historical traffic information corresponding to the same time point in different periods at the current moment. For example, the historical traffic information corresponding to the same time point in different periods can be used as the reference traffic information for the current moment. Alternatively, the historical traffic information from multiple historical moments at the same time point in different periods can be averaged to obtain the reference traffic information for the current moment.

[0074] For example, the historical moments of the same time point in different periods of the current moment may be: if the current moment is 15:00 on March 4, the historical moments of the same time point in different periods may include 15:00 on March 3 or 15:00 on March 2.

[0075] According to an embodiment of the present disclosure, the reference traffic information may also be determined in the following manner: based on the historical traffic sequence information of the congested road section in the historical period adjacent to the current moment and the environmental information at the current moment, the reference traffic information at the current moment is determined.

[0076] For example, the historical period adjacent to the current time may be: if the current time is 15:00 on March 4, the historical period adjacent to the current time may include 9:00-15:00 on March 4.

[0077] By utilizing historical traffic time series information from historical periods adjacent to the current moment, the current moment's traffic information can be predicted and used as reference traffic information. For example, the historical traffic time series information can be input into a traffic prediction model to obtain reference traffic information. However, this is not a limitation. Alternatively, the historical traffic time series information can be combined with the current moment's environmental information and input into the traffic prediction model to obtain reference traffic information.

[0078] Common prediction models may include Long Short-Term Memory (LSTM) networks, but are not limited thereto and may also include statistical models for time series analysis and prediction (Auto Regressive Integrated Moving Average Model, ARIMA).

[0079] Environmental information can include weather information such as rainfall and visibility, as well as time information such as holidays or peak traffic periods. By combining environmental information as a reference, we can consider the impact of factors such as special weather conditions, traffic control, and road construction on congestion.

[0080] The generation of reference traffic information provided by the embodiments of the present disclosure utilizes historical traffic time series information to reflect periodic patterns and potential nonlinear relationships, generating benchmark traffic information that closely reflects current conditions. Furthermore, the use of environmental information can fully reflect the dynamic changes in current traffic conditions, embodying real-time capabilities. Combining historical traffic time series information with environmental information provides comprehensive, dynamic, and accurate reference traffic information, thereby improving the accuracy and efficiency of identifying abnormal road sections.

[0081] According to an embodiment of the present disclosure, determining the congestion diffusion information of the road network topology based on the road network topology of the congested road section and the traffic timing information of each road section on the road network topology may include: determining the congestion diffusion path based on the road network topology and the traffic timing information of each road section on the road network topology; and determining the congestion period based on the diffusion speed of adjacent congested road sections of the congestion diffusion path and the distance of the congestion diffusion path.

[0082] The associated sections of a congested section can be determined based on the road network topology. By comparing the changes in the traffic timing information of adjacent sections, it can be determined whether the adjacent sections are congestion diffusion sections. By analyzing the congested sections as the source and the sections that propagate downstream in sequence, the diffusion path of the congestion can be determined.

[0083] For example, section A is a congested section, and section B is directly connected to section A. If the vehicle speed on section B starts to decrease and the traffic volume increases, it is judged that the congestion is spreading to section B. Furthermore, after a delay, section C connected to section B also starts to decrease in speed and increases in traffic volume, thus forming a diffusion path from sections A, B, and C.

[0084] The diffusion rate of congested roads can be determined by comparing the differences in the initial events of congestion on adjacent roads and the distance between them. The formula for calculating the diffusion rate is: diffusion rate = road distance / time difference, where the time difference refers to the difference in the start time of congestion on adjacent roads. The congestion period can be determined by dividing the distance of the congestion diffusion path by the diffusion rate.

[0085] According to an embodiment of the present disclosure, determining the congestion diffusion path based on the road network topology and the traffic timing information of each road section on the road network topology may include: determining the identification information of each road section based on the association relationship between each road section and the congested road section on the road network topology; determining the spatiotemporal correlation characteristics based on the identification information and traffic timing information of each road section; and performing congestion diffusion evaluation based on the spatiotemporal correlation characteristics to obtain the congestion diffusion path.

[0086] For example, identification information can be added to the edges representing road segments in the road network topology to highlight the fine-grained connection relationship between congested road segments and other connected road segments. For example, the congested road segment is assigned identification information 0, the directly connected road segment is assigned identification information 1, and so on. The road segments connected through the road segment with identification information 1 are assigned identification information 2, and so on, and so on. The number of identification information added is N, where N is an integer greater than or equal to 3.

[0087] By utilizing identification information, the association between multiple road sections and congested road sections in the road network topology can be improved, and the granularity of the road network topology in the spatial dimension can be improved.

[0088] Illustratively, the changing trends of the traffic sequence information for each marked road section can be statistically analyzed according to preset time windows. For example, the real-time dynamics of traffic volume, speed, and lane occupancy for each marked road section can be captured to determine the spatiotemporal correlation characteristics of each marked road section. Based on the spatiotemporal correlation characteristics, the traffic conditions of each marked road section can be assessed to determine whether they are improving, deteriorating, or remaining stable. For example, if the traffic conditions of a road section continue to deteriorate over several consecutive time windows, it can be predicted that the road section may become congested in the future, indicating that the road section is on a congestion diffusion path.

[0089] Preferably, the traffic sequence information and the identification information of each road segment can be encoded into a spatiotemporal feature matrix that represents the spatiotemporal correlation characteristics. The spatiotemporal feature matrix is ​​input into a spatial temporal graph convolutional network (ST-GCN) to obtain the congestion diffusion path.

[0090] According to the embodiments of the present disclosure, based on the identification information and traffic sequence information of the congested road sections, information in different dimensions of time and space can be combined to facilitate the analysis of the propagation range and impact of the congested road sections, thereby improving the comprehensiveness and accuracy of the congestion diffusion path assessment.

[0091] According to an embodiment of the present disclosure, before executing the aforementioned route planning for a target vehicle that traverses the congestion diffusion path during a congestion period, the route planning method further includes: determining a vehicle that traverses the congestion diffusion path from the plurality of candidate vehicles based on navigation information of each candidate vehicle. The navigation information includes the candidate vehicle's destination, origin, and intermediate routes between the destination and origin; and determining whether the vehicle is a target vehicle that traverses the congestion diffusion path during a congestion period based on the vehicle's driving speed and the distance to the congestion diffusion path.

[0092] For example, a spatial intersection analysis may be performed between the intermediate path of the candidate vehicle and the congestion diffusion path. If there is overlap in road sections, the corresponding candidate vehicle is marked as the initial target vehicle.

[0093] The initial target vehicle's speed can be obtained in real time. Based on the remaining distance from the initial target vehicle's current location to the congestion diffusion path, the initial target vehicle's arrival time on the congestion diffusion path is predicted. If the initial target vehicle's arrival time falls within the congestion period, the initial target vehicle is used as the target vehicle.

[0094] According to the embodiments of the present disclosure, by matching navigation information with congestion diffusion paths and combining the vehicle's real-time driving speed and remaining distance, the target vehicle can be accurately identified, thereby improving the user experience and optimizing the efficiency of traffic resource allocation.

[0095] According to an embodiment of the present disclosure, path planning is performed for a target vehicle that passes through a congestion diffusion path during a congestion period, and obtaining path planning information for bypassing the congestion diffusion path may include: based on a map and the current position of the target vehicle, determining path planning information for reaching the target vehicle's destination without passing through the congestion diffusion path.

[0096] Indicatively, multiple candidate paths may be generated based on a map in combination with the vehicle's current location and destination. Paths containing current congested sections and congestion diffusion paths may be excluded from the multiple candidate paths to obtain a target candidate path.

[0097] Candidate routes can also be scored based on their total distance, estimated travel time, number of traffic lights, road grade ratio, and other factors, selecting and recommending the best route or routes. This allows for precise avoidance of congestion-proliferating routes and provides users with optimal route planning information.

[0098] Figure 4 A schematic diagram of a scenario based on path planning according to an embodiment of the present disclosure is shown schematically.

[0099] Congestion occurs on the first road segment 410. At time T1, the congestion spreads to the second road segment 420 connected to the first road segment 410 and continues until time T2. If the original route of the target vehicle 430 passes through the second road segment 420 and reaches the second road segment 420 at any time between T1 and T2, the target vehicle can be routed to choose the third road segment 440, which is a non-congested diffusion path, for detour.

[0100] According to an embodiment of the present disclosure, displaying path planning information and congestion diffusion information for a congestion diffusion path on a navigation interface may include: displaying the congestion diffusion information on the navigation interface in the form of a pop-up window; and displaying the path planning information on the navigation interface in response to receiving a navigation request for re-navigation.

[0101] Illustratively, a pop-up window can be triggered before a vehicle enters a congestion diffusion path. The priority of the pop-up window can be dynamically adjusted based on the congestion level or time urgency of the congestion diffusion path. For example, a red high-risk pop-up window, an orange medium-risk pop-up window, and a yellow low-risk pop-up window can be set to indicate the congestion level of the congestion diffusion path or the time urgency of the vehicle approaching the congestion diffusion path.

[0102] Illustratively, a re-routing request can be triggered by a user's voice command, such as "re-route" or "avoid congestion." Alternatively, the request can be triggered by clicking the "Re-route" button on the navigation interface or the "Detour Now" option in a pop-up window.

[0103] Multiple route planning information can be displayed on the navigation interface, with the optimal route planning information highlighted and the reasons for the recommendation noted, such as shortest time, shortest distance, etc. Alternative route planning information can also be displayed in gray, with the reasons for the recommendation noted.

[0104] According to an embodiment of the present disclosure, a collaborative mechanism of real-time push of congestion diffusion information and triggering of dynamic path replanning through pop-up windows is used to enable users to actively perceive traffic risks and instantly adjust navigation strategies, thereby improving users' travel efficiency and decision-making initiative.

[0105] According to an embodiment of the present disclosure, before the vehicle travels, the above-mentioned path planning method also includes: in response to receiving a navigation request, performing path planning based on the map and the destination and origin in the navigation request to obtain a candidate planned path; in the case that the candidate planned path passes through a congested section or a congestion diffusion path, adding identification information to the candidate planned path, the identification information being used to characterize the congestion status information of the congested section or the congestion status information of the congestion diffusion path; and displaying the candidate planned path with the identification information on the navigation interface.

[0106] The identification information may include the severity level of the congestion and the estimated congestion duration. The identification information may also be updated in real time based on the congestion status information.

[0107] Illustratively, if a congestion diffusion path is included in the candidate planned routes, identification information is added to the congestion diffusion path to indicate its congestion status. This identification information is updated in real time based on the congestion status information while the vehicle is traveling. Based on the vehicle's current position and speed, it is assessed whether the congestion status of the congestion diffusion path can be restored to a non-congested state upon arrival. If this is not possible, a pop-up window will be displayed to remind the user to switch routes.

[0108] According to an embodiment of the present disclosure, before a vehicle travels, by adding identification information for characterizing a congestion state to a candidate planned path in the navigation phase, the vehicle can be given an early warning, thereby improving the warning capability of the vehicle travel.

[0109] According to an embodiment of the present disclosure, the above-mentioned path planning method also includes: when it is determined that the congested section is an isolated congestion type, determining the congestion period of the congested section; the isolated congestion type indicates that the congestion state will not spread from the congested section to other sections of the road network topology; based on the congestion period of the congested section, path planning is performed for vehicles passing through the congested section during the congestion period to obtain path planning information for the congested section.

[0110] Isolated congestion may be caused by a single event, such as a traffic accident, construction, or bad weather. Isolated congestion will not spread to other sections of the road network topology.

[0111] Illustratively, a mapping relationship between event type and congestion duration can be established based on historical data. The congestion duration of isolated congestion can be queried based on this mapping relationship. For example, the congestion duration of a minor accident is A minutes, the congestion duration of a vehicle breakdown is B minutes, and the congestion duration of a multi-vehicle rear-end collision is C minutes. Based on the starting event and duration of each accident, the congestion period of the isolated congestion is determined. The present disclosure is not limited to this. Data such as event type, occurrence time, road section attributes, and real-time processing status can also be input into a time series model, which can then output the remaining congestion duration. The congestion period is determined based on the remaining congestion duration.

[0112] Schematically, for a vehicle passing through a congested road section during a congested period, a route planning can be performed by generating multiple candidate routes through a map in combination with the vehicle's current location and destination. The routes of the congested road section are excluded from the multiple candidate routes to obtain a target candidate route.

[0113] According to an embodiment of the present disclosure, the congestion type can also be identified in the following manner: based on the traffic timing information of the congested section and the traffic timing information of the adjacent sections of the congested section, the congestion type identification result of the congested section is determined, and the congestion type identification result characterizes whether the congested section is a propagation congestion type or an isolated congestion type.

[0114] As mentioned above, the traffic sequence information is obtained by arranging multiple traffic information at different times in time sequence. The traffic information includes vehicle speed, traffic volume, lane occupancy, vehicle driving direction, etc.

[0115] For example, the congestion type of a congested road section can be determined by comparing the speed, traffic volume, and lane occupancy of the congested road section with the speed, traffic volume, and lane occupancy of adjacent sections to see if there is a time lag. If there is a time lag, the congested road section is a propagation type of congestion; if there is no time lag, the congested road section is an isolated type of congestion.

[0116] For example: after the speed of a congested section drops to a threshold, the speed of the adjacent sections of the congested section also drops to the threshold within Δt minutes. Alternatively, after the traffic volume of a congested section drops to a threshold, the traffic volume of the downstream sections also drops to the threshold within Δt minutes; or after the lane occupancy of a congested section increases to a threshold, the speed of the adjacent sections of the congested section also increases to the threshold within Δt minutes. In this case, the congested section is a propagation congestion type. If a congested section meets the above thresholds, but the adjacent sections are not triggered synchronously within Δt minutes, that is, the speed, traffic volume, and lane occupancy of the adjacent sections do not change significantly, then the congested section is an isolated congestion type.

[0117] According to the embodiments of the present disclosure, by integrating the traffic timing information of a congested road section and its adjacent road sections, the congestion type can be accurately identified as a propagation congestion type or an isolated congestion type, and the congestion propagation characteristics analysis based on spatiotemporal correlation can be realized, thereby improving the accuracy of congestion type identification and providing a decision-making basis for navigation, early warning, etc.

[0118] According to an embodiment of the present disclosure, the above-mentioned path planning method further includes: determining the congestion level based on the diffusion speed of the congestion diffusion path and a preset diffusion speed threshold; and sending an alarm message when the congestion level is greater than the predetermined level.

[0119] Illustratively, the congestion level may include a low risk level, a medium risk level, and a high risk level. The preset diffusion speed threshold may be set based on the congestion level.

[0120] For example, the diffusion speed threshold for a low risk level may be 5 km / h; the diffusion speed threshold for a medium risk level may be 10 km / h; and the diffusion speed threshold for a high risk level may be 20 km / h.

[0121] The predetermined level may be a medium risk level or a high risk level. When the diffusion speed of the congestion diffusion path is greater than a diffusion speed threshold of the medium risk level or a diffusion speed threshold of the high risk level, an alarm message may be issued.

[0122] Figure 5 The flowchart of a path planning method according to another embodiment of the present disclosure is schematically shown.

[0123] like Figure 5 Said method includes operations S510 to S570.

[0124] In operation S510 , a road condition recognition is performed on the congested road section based on the current traffic information and reference traffic information of the congested road section to obtain an initial recognition result.

[0125] If the initial recognition result indicates that the congested road section is abnormal, operation S520 is performed.

[0126] In operation S520 , a congestion type identification result of the congested road section is determined based on the passing time sequence information of the congested road section and the passing time sequence information of adjacent road sections of the congested road section.

[0127] In case the congestion type identification result is the propagation congestion type, operation S530 is performed.

[0128] In operation S530 , congestion diffusion information of the road network topology is determined based on the road network topology of the congested road segment and the traffic timing information of each road segment on the road network topology.

[0129] In operation S550 , a path planning is performed for a target vehicle that passes through the congestion diffusion path during a congestion period to obtain path planning information for bypassing the congestion diffusion path.

[0130] In case the congestion type identification result is an isolated congestion type, operation S540 is performed.

[0131] In operation S540 , a congestion period of the congested road section is determined.

[0132] In operation S560 , based on the congestion period of the congested road section, a route planning is performed for vehicles passing through the congested road section during the congestion period to obtain route planning information for the congested road section.

[0133] In operation S570, the route planning information and the congestion diffusion information are displayed on the navigation interface.

[0134] Figure 6 The block diagram of the path planning device according to an embodiment of the present disclosure is schematically shown.

[0135] like Figure 6 As shown, the path planning device 600 includes a congestion diffusion determination module 610 , a path planning module 620 and a display module 630 .

[0136] The congestion spread determination module 610 is configured to determine, when determining that the congested road segment is of the propagation congestion type, congestion spread information of the road network topology based on the road network topology of the congested road segment and the traffic timing information of each road segment in the road network topology, wherein the congestion spread information includes the congestion spread path and the congestion period;

[0137] A path planning module 620 is configured to plan a path for a target vehicle that passes through a congestion diffusion path during a congestion period based on the congestion diffusion information, and obtain path planning information for bypassing the congestion diffusion path; and

[0138] The display module 630 is used to display the path planning information and congestion diffusion information on the navigation interface.

[0139] According to an embodiment of the present disclosure, the congestion diffusion determination module 610 includes a diffusion path determination submodule and a congestion period determination submodule.

[0140] The diffusion path determination submodule is used to determine the congestion diffusion path based on the road network topology and the traffic timing information of each road section in the road network topology.

[0141] The congestion period determination submodule is used to determine the congestion period based on the diffusion speed of adjacent congested road sections of the congestion diffusion path and the distance of the congestion diffusion path.

[0142] According to an embodiment of the present disclosure, the diffusion path determination submodule includes an identification information determination unit, a spatiotemporal correlation feature determination unit, and a congestion diffusion path determination unit.

[0143] The identification information determining unit is used to determine the identification information of each road section based on the association relationship between each road section and the congested road section in the road network topology.

[0144] The spatiotemporal correlation feature determination unit is used to determine the spatiotemporal correlation feature based on the identification information and traffic sequence information of each road section.

[0145] The congestion diffusion path determination unit is used to perform congestion diffusion assessment based on spatiotemporal correlation characteristics to obtain the congestion diffusion path.

[0146] According to an embodiment of the present disclosure, the path planning device 600 further includes a response module and an execution module.

[0147] The response module is used to respond to receiving multiple abnormal congestion feedback information sent through the navigation interface.

[0148] The execution module is used to execute the operation of determining the congestion diffusion information of the road network topology when multiple pieces of abnormal congestion feedback information all indicate that the congested road section is abnormal.

[0149] According to an embodiment of the present disclosure, the path planning device 600 further includes an initial road network topology generation module and a road network topology update module.

[0150] an initial road network topology generation module, configured to generate an initial road network topology centered on the congested road section based on a map of the area where the congested road section is located and associations between multiple road sections; and

[0151] The road network topology updating module is used to update the initial road network topology based on the road traffic information obtained in real time to obtain the road network topology.

[0152] According to an embodiment of the present disclosure, the path planning device 600 further includes a traffic information acquisition module and a sorting module.

[0153] The traffic information acquisition module is used to obtain multiple traffic information of each road section in the road network topology at different times within a preset time period.

[0154] The sorting module is used to obtain traffic sequence information in a time sequence; wherein the traffic information includes at least one of the following: vehicle speed, traffic volume, lane occupancy, and vehicle driving direction.

[0155] According to an embodiment of the present disclosure, the traffic information acquisition module includes a completion module.

[0156] The completion module is used to complete the information of the missing time based on the historical traffic information of the historical time of the road section when it is determined that there is a time when the missing information exists.

[0157] According to an embodiment of the present disclosure, the path planning device 600 further includes a candidate vehicle determination module and a target vehicle determination module.

[0158] The candidate vehicle determination module is used to determine a vehicle passing through a congestion diffusion path from a plurality of candidate vehicles based on navigation information of each of the plurality of candidate vehicles, wherein the navigation information includes a destination, an origin, and an intermediate path between the destination and the origin of the candidate vehicle.

[0159] The target vehicle determination module is used to determine whether the vehicle is a target vehicle passing through the congestion diffusion path during the congestion period based on the vehicle's driving speed and the distance to the congestion diffusion path.

[0160] According to an embodiment of the present disclosure, the path planning module 620 includes a path planning information submodule.

[0161] The path planning information submodule is used to determine the path planning information for reaching the target vehicle's destination without passing through a congestion diffusion path based on the map and the current location of the target vehicle.

[0162] According to an embodiment of the present disclosure, the display module includes a pop-up display submodule and a path planning information display submodule.

[0163] The pop-up display submodule is used to display congestion diffusion information on the navigation interface in the form of pop-up windows.

[0164] The path planning information display submodule is used to display the path planning information on the navigation interface in response to receiving a navigation request for re-navigation.

[0165] According to an embodiment of the present disclosure, the path planning device 600 further includes a candidate path planning module, an identification information adding module, and an identification information display module.

[0166] a candidate path planning module, configured to, in response to receiving a navigation request, perform path planning based on a map and a destination and an origin in the navigation request to obtain a candidate planned path;

[0167] An identification information adding module is used to add identification information to a candidate planned path when the candidate planned path passes through a congested section or a congestion diffusion path, wherein the identification information is used to represent the congestion status information of the congested section or the congestion status information of the congestion diffusion path.

[0168] The identification information display module is used to display the candidate planning paths with identification information on the navigation interface.

[0169] According to an embodiment of the present disclosure, the path planning device 600 further includes a recognition module and a second execution module.

[0170] The recognition module is used to identify the road conditions of the congested road section based on the current traffic information and reference traffic information of the congested road section to obtain an initial recognition result.

[0171] The second execution module is used to execute the operation of determining congestion diffusion information of the road network topology when the initial recognition result indicates that the congested road section is abnormal.

[0172] According to an embodiment of the present disclosure, the path planning device 600 further includes a reference traffic information determination module.

[0173] The reference traffic information determination module is used to determine the reference traffic information at the current moment based on the historical traffic sequence information of the congested road section in the historical period adjacent to the current moment and the environmental information at the current moment.

[0174] According to an embodiment of the present disclosure, the path planning device 600 further includes a congestion period determination module and a path planning information determination module.

[0175] The congestion period determination module determines the congestion period of the congested road section when it is determined that the congested road section is of an isolated congestion type, wherein the isolated congestion type indicates that the congestion state will not spread from the congested road section to other road sections in the road network topology.

[0176] The path planning information determination module performs path planning for vehicles passing through the congested road section during the congested period based on the congested period of the congested road section, and obtains path planning information for the congested road section.

[0177] According to an embodiment of the present disclosure, the path planning device 600 further includes a type determination module.

[0178] The type determination module is used to determine the congestion type identification result of the congested section based on the traffic timing information of the congested section and the traffic timing information of the adjacent sections of the congested section. The congestion type identification result represents whether the congested section is a propagation congestion type or an isolated congestion type.

[0179] According to an embodiment of the present disclosure, the path planning device 600 further includes:

[0180] The congestion level determination module is used to determine the congestion level based on the diffusion speed of the congestion diffusion path and a preset diffusion speed threshold.

[0181] The alarm information sending module is used to send alarm information when the congestion level is greater than a predetermined level.

[0182] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0183] According to an embodiment of the present disclosure, an electronic device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the above method.

[0184] According to an embodiment of the present disclosure, a non-transitory computer-readable storage medium stores computer instructions, wherein the computer instructions are used to enable a computer to execute the above method.

[0185] According to an embodiment of the present disclosure, a computer program product includes a computer program, and the computer program implements the above method when executed by a processor.

[0186] Figure 7 A schematic block diagram of an example electronic device 700 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0187] like Figure 7 As shown, device 700 includes a computing unit 701, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 702 or a computer program loaded from a storage unit 708 into a random access memory (RAM) 703. RAM 703 may also store various programs and data required for the operation of device 700. Computing unit 701, ROM 702, and RAM 703 are connected to each other via a bus 704. An input / output (I / O) interface 705 is also connected to bus 704.

[0188] Various components in device 700 are connected to an input / output (I / O) interface 705, including an input unit 706, such as a keyboard and mouse; an output unit 707, such as various types of displays and speakers; a storage unit 708, such as a magnetic disk and optical disk; and a communication unit 709, such as a network card, a modem, a wireless communication transceiver, etc. Communication unit 709 allows device 700 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0189] The computing unit 701 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 701 performs the various methods and processes described above, such as the path planning method. For example, in some embodiments, the path planning method may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 708. In some embodiments, part or all of the computer program may be loaded and / or installed onto the device 700 via the ROM 702 and / or the communication unit 709. When the computer program is loaded into the RAM 703 and executed by the computing unit 701, one or more steps of the path planning method described above may be performed. Alternatively, in other embodiments, the computing unit 701 may be configured to perform the path planning method via any other suitable means (e.g., via firmware).

[0190] Various embodiments of the systems and techniques described above can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-a-chip systems (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0191] The program code for implementing the method of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device so that when the program code is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0192] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), optical fibers, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0193] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0194] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.

[0195] A computer system may include a client and a server. The client and server are generally remote from each other and typically interact through a communication network. The client-server relationship arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server in a distributed system, or a server integrated with a blockchain.

[0196] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved. This is not a limitation herein.

[0197] The above specific embodiments do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure shall be included within the scope of protection of this disclosure.

Claims

1. A path planning method, comprising: In the case where the congested road section is determined to be of the propagation congestion type, determining congestion diffusion information of the road network topology based on the road network topology of the congested road section and the traffic timing information of each road section on the road network topology, wherein the propagation congestion type represents the type of congestion state that will spread from the congested road section to other road sections in the network topology, and the congestion diffusion information includes the congestion diffusion path and the congestion period; Performing path planning for target vehicles that pass through the congestion diffusion path during the congestion period to obtain path planning information that detours the congestion diffusion path; and The path planning information and the congestion diffusion information are displayed on a navigation interface.

2. The method according to claim 1, wherein The determining of the congestion diffusion information of the road network topology based on the road network topology of the congested road section and the traffic timing information of each road section on the road network topology includes: Determining the congestion diffusion path based on the road network topology and the traffic timing information of each road segment on the road network topology; and The congestion period is determined based on the diffusion speed of adjacent congested road sections of the congestion diffusion path and the distance of the congestion diffusion path.

3. The method according to claim 2, wherein: The determining the congestion diffusion path based on the road network topology and the traffic timing information of each road section in the road network topology includes: Determining identification information of each road section based on an association relationship between each road section and the congested road section on the road network topology; Determining spatiotemporal correlation features based on identification information and travel time sequence information of each of the road sections; and Congestion diffusion assessment is performed based on the spatiotemporal correlation characteristics to obtain the congestion diffusion path.

4. The method according to any one of claims 1 to 3, further comprising: In response to receiving a plurality of abnormal congestion feedback information sent through the navigation interface; as well as In a case where a plurality of pieces of abnormal congestion feedback information all indicate that the congested road section is abnormal, an operation of determining congestion diffusion information of the road network topology is performed.

5. The method according to any one of claims 1 to 4, further comprising: generating an initial road network topology centered on the congested road section based on a map of the area where the congested road section is located and associations between multiple road sections; as well as Based on the road traffic information obtained in real time, the initial road network topology is updated to obtain the road network topology.

6. The method according to any one of claims 1 to 5, further comprising: Acquire multiple traffic information of each road section on the road network topology at different times within a preset time period; as well as Arrange the passage timing information in time sequence to obtain the passage timing information; The traffic information includes at least one of the following: Vehicle speed, traffic volume, lane occupancy, and vehicle direction.

7. The method according to claim 6, wherein: The acquiring of a plurality of traffic information of each road section on the road network topology within a preset time period includes: When it is determined that there is a time at which missing information exists, information of the time at which the missing information exists is supplemented based on historical traffic information of the historical time at the road section.

8. The method according to any one of claims 1 to 7, further comprising: Determining a vehicle that passes through the congestion diffusion path from the plurality of candidate vehicles based on navigation information of each of the plurality of candidate vehicles, wherein the navigation information includes a destination, an origin, and an intermediate path between the destination and the origin of the candidate vehicles; and Based on the driving speed of the vehicle and the distance to the congestion diffusion path, it is determined whether the vehicle is the target vehicle that passes through the congestion diffusion path during the congestion period.

9. The method according to claim 1 or 8, wherein The performing path planning for the target vehicle passing through the congestion diffusion path during the congestion period to obtain path planning information for detouring the congestion diffusion path includes: Based on a map and the current location of the target vehicle, the path planning information for reaching the target vehicle's destination without passing through the congestion diffusion path is determined.

10. The method according to any one of claims 1 to 9, wherein The displaying of the path planning information for the congestion diffusion path and the congestion diffusion information on the navigation interface includes: Displaying the congestion diffusion information on the navigation interface in a pop-up window; and In response to receiving the navigation request for re-navigation, the path planning information is displayed on the navigation interface.

11. The method according to any one of claims 1 to 10, further comprising: In response to receiving the navigation request, performing route planning based on a map and a destination and an origin in the navigation request to obtain a candidate planned route; In a case where the candidate planned path passes through the congested road section or the congestion diffusion path, adding identification information to the candidate planned path, wherein the identification information is used to represent the congestion status information of the congested road section or the congestion status information of the congestion diffusion path; as well as The candidate planned paths with identification information are displayed on the navigation interface.

12. The method according to any one of claims 1 to 11, further comprising: Based on the current traffic information and reference traffic information of the congested road section, a road condition identification is performed on the congested road section to obtain an initial identification result; as well as In a case where the initial recognition result indicates that the congested road section is abnormal, an operation of determining congestion diffusion information of the road network topology is performed.

13. The method according to claim 12, further comprising: The reference traffic information at the current moment is determined based on the historical traffic sequence information of the congested road section in a historical period adjacent to the current moment and the environmental information at the current moment.

14. The method according to any one of claims 1 to 13, further comprising: In the case where it is determined that the congested road segment is of an isolated congestion type, determining a congestion period of the congested road segment, wherein the isolated congestion type indicates that a congestion state will not spread from the congested road segment to other road segments of the road network topology; and Based on the congested period of the congested road section, path planning is performed for vehicles passing through the congested road section during the congested period to obtain path planning information for the congested road section.

15. The method according to claim 14, further comprising: Based on the traffic timing information of the congested road section and the traffic timing information of adjacent road sections of the congested road section, a congestion type identification result of the congested road section is determined, and the congestion type identification result indicates whether the congested road section is a propagation congestion type or an isolated congestion type.

16. The method according to any one of claims 1 to 15, further comprising: Determining a congestion level based on a diffusion speed of the congestion diffusion path and a preset diffusion speed threshold; as well as When the congestion level is greater than a predetermined level, an alarm message is sent.

17. A path planning device, comprising: a congestion diffusion determination module, configured to, when determining that a congested road section is of a propagation congestion type, determine congestion diffusion information of the road network topology based on the road network topology of the congested road section and the traffic timing information of each road section on the road network topology, wherein the congestion diffusion information includes a congestion diffusion path and a congestion period; a path planning module, configured to perform path planning for target vehicles passing through the congestion diffusion path during the congestion period based on the congestion diffusion information, and obtain path planning information for bypassing the congestion diffusion path; and A display module is used to display the path planning information and the congestion diffusion information on a navigation interface.

18. An electronic device comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 16.

19. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-16.

20. A computer program product comprising a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 16.

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