Path and lane association method and apparatus, electronic device, and storage medium

Abstract

Embodiments of the present disclosure disclose a path and lane association method and device, electronic equipment and storage medium. The method comprises: determining a target lane line affecting vehicle merging; determining a target intersection involving the target lane line from high-definition map data; determining, based on the high-definition map data, a high-definition target path in front of the target intersection affected by the target lane line and an affected lane segment on the high-definition target path; and establishing an association between the high-definition target path and lane information of the affected lane segment based on a mapping relationship between the high-definition map data and the standard-definition map data. This technical solution can determine the standard-definition path and the associated lane information, and prompt the user in advance when encountering a long solid line scenario, thereby reducing the yaw rate of the navigated object and improving the driving safety and traffic efficiency of the navigated object.

Description

Technical Field

[0001] This disclosure relates to the field of navigation technology, specifically to a method, apparatus, electronic device, and storage medium for associating paths and lanes. Background Technology

[0002] To provide better navigation services, if a long solid line in front of an intersection affects the route planning of the navigable object, a warning can be given in advance to avoid missing the warning opportunity and causing the navigable object to be unable to change lanes, thus resulting in deviation from the intended route.

[0003] Current technologies only support road-level path planning for high-resolution map data and cannot support lane-level planning in scenarios with long solid lines. Therefore, a solution is needed to enable early warning when encountering long solid line scenarios in road-level path planning using high-resolution map data, thereby reducing the deviation rate of the navigated object and improving its driving safety and traffic efficiency. Summary of the Invention

[0004] This disclosure provides a method, apparatus, electronic device, and storage medium for associating paths and lanes.

[0005] In a first aspect, this disclosure provides a method for associating paths and lanes, including:

[0006] Identify the target lane markings that affect vehicle lane changes;

[0007] Identify the target intersection involving the target lane line from high-precision map data;

[0008] Based on the high-precision map data, determine the high-precision target path before the target intersection that is affected by the target lane line, and the affected lane segments on the high-precision target path;

[0009] Based on the mapping relationship between the high-precision map data and the standard-precision map data, after mapping the high-precision target path to the standard-precision path, an association relationship is established between the standard-precision path and the lane information of the affected lane segment.

[0010] Secondly, this invention provides a navigation method, including:

[0011] Obtain navigation and route planning;

[0012] In response to the navigation planning path including a preset benchmark path, it is determined whether the recommended lane at the preset benchmark path matches the associated lane information of the preset benchmark path; the preset benchmark path and the associated lane information of the preset benchmark path are obtained based on the method described in the first aspect;

[0013] If the recommended lane matches the associated lane information, a prompt message is output before the navigable object is guided to the preset precision path; the prompt message includes a first prompt message indicating the existence of a target lane line, and a second prompt message indicating the associated lane information affected by the target lane line.

[0014] Thirdly, embodiments of the present invention provide a path and lane association device, comprising:

[0015] The first determining module is configured to determine the target lane line that affects vehicle lane changes;

[0016] The second determining module is configured to determine the target intersection involving the target lane line from high-precision map data;

[0017] The third determining module is configured to determine, based on the high-precision map data, the high-precision target path before the target intersection affected by the target lane line, and the affected lane segments on the high-precision target path;

[0018] The mapping module is configured to map the high-precision target path to the standard-precision path based on the mapping relationship between the high-precision map data and the standard-precision map data, and then establish the association between the standard-precision path and the lane information of the affected lane segment.

[0019] Fourthly, embodiments of the present invention provide a navigation device, comprising:

[0020] The acquisition module is configured to acquire the navigation planning path;

[0021] The fourth determining module is configured to, in response to the navigation planning path containing a preset precision path, determine whether the recommended lane at the preset precision path matches the associated lane information of the preset precision path; the preset precision path and the associated lane information of the preset precision path are obtained based on the device described in the third aspect;

[0022] The output module is configured to output a prompt message before guiding the navigable object to the preset precision path if the recommended lane matches the associated lane information; the prompt message includes a first prompt message indicating the existence of a target lane line, and a second prompt message indicating the associated lane information affected by the target lane line.

[0023] The function can be implemented by hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above function.

[0024] In one possible design, the above-described device includes a memory and a processor. The memory stores one or more computer instructions that support the device in performing the corresponding methods described above, and the processor is configured to execute the computer instructions stored in the memory. The device may also include a communication interface for communicating with other devices or communication networks.

[0025] Fifthly, embodiments of this disclosure provide an electronic device including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the method described in any of the preceding aspects.

[0026] In a sixth aspect, embodiments of this disclosure provide a computer-readable storage medium for storing computer instructions used by any of the above-described devices, which, when executed by a processor, are used to implement the methods described in any of the above aspects.

[0027] In a seventh aspect, embodiments of this disclosure provide application software for navigation, which includes computer instructions that, when executed by a processor, are used to implement the method described in the second aspect above.

[0028] The technical solutions provided in this disclosure may have the following beneficial effects:

[0029] In this embodiment, to provide advance warnings when encountering long solid lines in road-level path planning using high-precision map data, all target lane lines within the corresponding area can be extracted in advance using high-precision map data. Furthermore, all target intersections involving these target lane lines can be extracted using the same high-precision map data. For each target intersection, the high-precision target path before the intersection affected by the target lane line, as well as the affected lane segments on that path, can be determined using high-precision map data. Based on the mapping relationship between high-precision and high-precision map data, the high-precision target path is mapped to a high-precision path, establishing a correlation between the high-precision path and the lane information of the affected lane segments. Through this method, during road-level path planning and navigation, based on the high-precision path and associated lane information determined in this way, users can be warned in advance when encountering long solid lines, thereby reducing the deviation rate of the navigated object and improving driving safety and traffic efficiency.

[0030] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0031] Other features, objects, and advantages of this disclosure will become more apparent from the following detailed description of non-limiting embodiments, taken in conjunction with the accompanying drawings. In the drawings:

[0032] Figure 1 A flowchart illustrating a path and lane association method according to an embodiment of the present disclosure is shown.

[0033] Figures 2A-2C A schematic diagram showing the effect of a target intersection according to an embodiment of the present disclosure is provided.

[0034] Figure 3 This diagram illustrates the effect of the next longitudinal connecting lane of a high-precision road segment according to an embodiment of the present disclosure.

[0035] Figure 4 A flowchart illustrating a navigation method according to an embodiment of the present disclosure is shown.

[0036] Figure 5 A structural block diagram of a path and lane association device according to an embodiment of the present disclosure is shown.

[0037] Figure 6 A structural block diagram of an electronic device according to an embodiment of the present disclosure is shown.

[0038] Figure 7 This is a schematic diagram of the structure of a computer system suitable for implementing a path and lane association method and / or navigation method according to an embodiment of the present disclosure. Detailed Implementation

[0039] In the following, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings to enable those skilled in the art to readily implement them. Furthermore, for clarity, portions unrelated to the description of the exemplary embodiments have been omitted from the drawings.

[0040] In this disclosure, it should be understood that terms such as “comprising” or “having” are intended to indicate the presence of features, figures, steps, behaviors, components, parts or combinations thereof disclosed in this specification, and do not preclude the possibility of the presence or addition of one or more other features, figures, steps, behaviors, components, parts or combinations thereof.

[0041] It should also be noted that, unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other. This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0042] The user information (including but not limited to user device information such as location information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this disclosure are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data shall comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation portals shall be provided for users to choose to authorize or refuse.

[0043] The details of the embodiments of this disclosure are described in detail below through specific examples.

[0044] Figure 1 A flowchart illustrating a path and lane association method according to an embodiment of this disclosure is shown. Figure 1 As shown, the method for associating a path with a lane includes the following steps:

[0045] In step S101, the target lane line affecting the vehicle's lane change is determined;

[0046] In step S102, the target intersection involving the target lane line is determined from the high-precision map data;

[0047] In step S103, based on the high-precision map data, the high-precision target path before the target intersection affected by the target lane line is determined, as well as the affected lane segments on the high-precision target path;

[0048] In step S104, based on the mapping relationship between the high-precision map data and the standard-precision map data, the high-precision target path is mapped to the standard-precision path, and then the association relationship between the standard-precision path and the lane information of the affected lane segment is established.

[0049] In this embodiment, the path and lane association method can be executed by the server. High-precision map data is a data storage method that uses lanes as storage objects. It mainly includes: high-precision road data, high-precision lane data (lane lines, types, relationships, etc.), and high-precision component data (ground markings, facilities, etc.), often simply referred to as "HD data." Standard-precision map data, on the other hand, is a data storage method that uses roads as storage objects. It mainly includes: basic road network data, road attribute information (electronic eyes, guide lines, prohibition information, etc.), and public travel information such as cycling and walking, often simply referred to as "SD data."

[0050] The target lane line affecting vehicle lane changes can be a long solid traffic line. A long solid traffic line is a type of lane divider, a white solid line separating lanes traveling in the same direction. Line types include solid line, left dashed and right solid line, and left solid and right dashed line. According to traffic regulations, vehicles are not allowed to merge (or cross) from one side of a solid line to the other. In some embodiments, the target lane line can be obtained through road image recognition or by processing lane line information stored in high-precision map data.

[0051] The navigation service is concerned with the long solid line that affects vehicles changing lanes before the intersection. Therefore, after determining the target lane line based on high-precision map data, the target intersection involving the target lane line can be identified.

[0052] In some embodiments, a target intersection involving a target lane line can be understood as a high-precision road segment where the target lane line is located before the target intersection, meaning that a vehicle can travel from the lane segment on the high-precision road segment where the target lane line is located to the target intersection in the direction of travel. Typically, the end point of the target lane line is located before the stop line of the target intersection, or on the exit road segment of the target intersection.

[0053] It is understood that high-precision map data can be high-precision map data covering the entire area or within a defined area as needed, while the target lane line can be all long solid traffic lines within that area or defined area, i.e., all long solid traffic lines within the area covered by the high-precision map data. In some embodiments, all intersections can be extracted from the area covered by the high-precision map data. The high-precision map data stores the intersections involved in each high-precision road segment, and there is a correlation between the lane lines on each high-precision road segment and the high-precision road segment itself. Therefore, after extracting all intersections from the high-precision map data, the high-precision road segment involved in that intersection can be matched with the high-precision road segment involved in the target lane line, thereby identifying the target intersection involving the target lane line. Figure 2A The diagram illustrates the target intersection and corresponding high-precision road segments from high-precision map data. Only the high-precision road segments, target lane lines, high-precision lane line segments, and high-precision vehicle lane segments below the target intersection are shown schematically. The diagram shows the high-precision road segmented into three segments. Each high-precision road segment has three high-precision lane line segments: two dashed lines and one solid line. These three solid line segments can be merged into a single long solid line, which is the target lane line.

[0054] After identifying the target intersection, a high-precision target path can be determined for each target intersection, including the lanes affected by the target lane line and the lanes along that path. It's understood that the target lane line can be a long solid traffic line, preventing vehicles from crossing from one lane to the next. Therefore, during path planning, the adjacent lane is clearly affected by this long solid traffic line. Based on this, the lateral accessibility between lanes involved in the target lane line before the target intersection can be analyzed to determine whether the target lane line affects the high-precision target path before the intersection and the lanes along that path. A high-precision target path can be understood as a path starting from the lane segment involved in the target lane line's starting point and extending to the lane segment involved in the target lane line's ending point. This high-precision target path may include one or more high-precision road segments ordered by travel direction. It's understood that each high-precision road segment may include one or more lane segments, and due to the existence of the target lane line, some lane segments on the high-precision target path may be longitudinally inaccessible. Therefore, on this high-precision target path, starting from the lane segment involved at the starting point of the target lane line, the longitudinally inaccessible lane segments can be identified as the affected lane segments on the high-precision target path. It can be understood that a longitudinally inaccessible lane segment is defined as a lane segment where the lane line traversed when traveling from the vehicle's position to that lane segment is a solid line; such a lane segment can be identified as inaccessible. Affected lane segments can be understood as lanes where, due to the existence of the target lane line, not all lanes can merge into. For example, the path before the target intersection involved in the target lane line can be represented as G1->G2->G3->G4, where G1, G2, G3, and G4 are the high-precision road segments involved from the start to the end of the target lane line, respectively. G1 includes two lane segments l1 and l2, and G4 includes two lane segments l3 and l4. If lane segments l1 to l3 belong to the first lane on the actual road, and lane segments l2 to l4 belong to the second lane on the actual road, and there is a solid lane line between the first and second lanes on the actual road, then it is impossible to cross the solid line from lane segment l1 to l4, and it is impossible to cross the solid line from lane segment l2 to lane segment l3. Therefore, this path can be considered a high-precision target path, and the affected lanes on the high-precision target path G1->G2->G3->G4 are l3 and l4.

[0055] As mentioned above, current navigation services typically provide road-level navigation services based on high-precision map data. To adapt to road-level navigation services based on high-precision map data, the high-precision target path before the target intersection affected by the target lane line, as determined above, can be mapped to the high-precision path based on the mapping relationship between high-precision map data and high-precision map data. Furthermore, the lane information of the affected lane segments on the high-precision target path can be associated with the high-precision path. Therefore, when using high-precision map data for navigation services, if the navigation path matches the high-precision path, after guiding the navigator to the high-precision path, prompts can be output to the navigator based on the lane information of the affected lane segments associated with that high-precision path, such as a navigation voice prompt like "Long solid line ahead, please move into the rightmost lane in advance." The lane information of the affected lane segments can include information indicating the location of the affected lane segment on the high-precision road.

[0056] It should be noted that the mapping relationship between high-precision map data and standard-precision map data is known information, typically the mapping relationship between high-precision road segments and standard-precision roads. Since standard-precision map data lacks lane data, the identifiers of affected lane segments on the high-precision target path can be converted into relative lane information on that road. In other words, because standard-precision map data does not contain lane lines, lanes, or other related data on standard-precision roads, it is impossible to express the lane information using the data of the affected lane segment. Therefore, the relative lane information of the affected lane segment on the standard-precision road can be used, such as the nth lane, the rightmost lane, or the rightmost lane, second rightmost lane, etc., of the recommended lane segment.

[0057] In this embodiment, to provide advance warnings when encountering long solid lines in road-level path planning using high-precision map data, all target lane lines within the corresponding area can be extracted in advance using high-precision map data. Furthermore, all target intersections involving these target lane lines can be extracted using the same high-precision map data. For each target intersection, the high-precision target path before the intersection affected by the target lane line, as well as the affected lane segments on that path, can be determined using high-precision map data. Based on the mapping relationship between high-precision and high-precision map data, the high-precision target path is mapped to a high-precision path, establishing a correlation between the high-precision path and the lane information of the affected lane segments. Through this method, during road-level path planning and navigation, based on the high-precision path and associated lane information determined in this way, users can be warned in advance when encountering long solid lines, thereby reducing the deviation rate of the navigated object and improving driving safety and traffic efficiency.

[0058] In an optional implementation of this embodiment, step S101, namely the step of determining the target lane line affecting vehicle lane changing, can be implemented as follows:

[0059] Select multiple high-precision lane segments that affect vehicle lane changes from high-precision map data;

[0060] The multiple high-precision lane segments that are connected sequentially in spatial location are aggregated into the target lane line.

[0061] In this optional implementation, for ease of creation, a complete road in the real world is divided into multiple high-precision road segments when generating high-precision map data, and each high-precision road segment is then created separately. To represent the connections between these high-precision road segments in the real world within the high-precision map data, topological connectivity relationships between the high-precision road segments are typically created during the map compilation process. These topological connectivity relationships are used to represent the sequential connections between each high-precision road segment.

[0062] In some embodiments, the topological connectivity between high-precision road segments may include, but is not limited to, the entry road segment and the exit road segment of the current high-precision road segment. An entry road segment can be understood as the preceding high-precision road segment that is directly adjacent to the current high-precision road segment longitudinally in the direction of travel of the current high-precision road segment. Conversely, an exit road segment can be understood as the next high-precision road segment that is directly adjacent to the current high-precision road segment longitudinally in the direction of travel of the current high-precision road segment. In other words, in the real world, when a vehicle or intelligent driving object travels along the direction of travel of a high-precision road segment, it enters the current high-precision road segment from the entry road segment, exits the current high-precision road segment, and then enters the exit road segment.

[0063] It should also be noted that each high-precision road segment includes a set of horizontally adjacent high-precision lane segments, and the lane segment data of multiple high-precision lane segments are also stored in the high-precision map data. Lane segment data may include, but is not limited to, information such as the attributes of the lane segments included on the high-precision road segment and the attributes of the associated lane line segments. The attribute information of the lane line segments may include the type of lane line segments, such as solid line, left dashed and right solid, left solid and right dashed, etc.

[0064] Because lane lines in high-precision map data are also broken into lane segments, we can first extract the high-precision lane segments that affect vehicle lane changes based on the high-precision map data, such as solid lines, left-dashed-right-solid lines, and left-solid-right-dashed lines. Then, we connect these broken lane segments according to their spatial location to form a long solid line. In other words, we aggregate these lane segments according to their spatial location to form the target lane line. The target lane line can be a complete long solid line on the road.

[0065] In an optional implementation of this embodiment, step S103, which is to determine the high-precision target path before the target intersection affected by the target lane line, and the affected lane segments on the high-precision target path based on the high-precision map data, can be implemented as follows:

[0066] Based on the high-precision map data, determine the lane accessibility data between the high-precision lane segments involved in the target lane line corresponding to the target intersection;

[0067] Based on the lane accessibility data, the high-precision target path and the affected lane segments are determined.

[0068] In this optional implementation, as described above, the target intersection is an intersection with a target lane line. The high-precision map data includes data on each lane segment on the high-precision road segment, such as its type. Based on this data, the accessibility data between the high-precision lane segments corresponding to the target lane line can be determined. Based on the accessibility data between the high-precision lane segments, the high-precision target path affected by the target lane line and the affected lanes on the high-precision target path can be determined on the high-precision road segment from the start point to the end point of the target lane line.

[0069] In an optional implementation of this embodiment, the step of determining the lane accessibility data between the high-precision lane segments involved in the target lane line corresponding to the target intersection based on the high-precision map data can be implemented as follows:

[0070] Determine the start and end points of the target lane lines corresponding to the target intersection;

[0071] Based on the high-precision map data, the exploration path from the starting point to the ending point is determined. The exploration path includes multiple high-precision road segments with interconnected front and rear topologies in the path direction. Each high-precision road segment corresponds to a set of high-precision lane segments.

[0072] Determine the lane accessibility data between each high-precision lane segment in the first group of high-precision lane segments and each high-precision lane segment in the last group of high-precision lane segments on the exploration path.

[0073] In this optional implementation, for a target intersection with a target lane line, the start and end points of the target lane line can be determined, and based on high-precision map data, the exploration path from the start point to the end point can be determined. This exploration path includes multiple high-precision road segments that are topologically connected along the path direction, and each high-precision road segment corresponds to a set of high-precision lane segments. It can be understood that the multiple high-precision road segments that are topologically connected along the path direction belong to the same real road, and the set of high-precision lane segments corresponding to each high-precision road segment actually belongs to multiple lanes on that real road. Adjacent high-precision lane segments along the path direction can be understood as lane segments belonging to the same lane on that real road.

[0074] Therefore, based on the target lane line, the lane accessibility data between each high-precision lane segment in the first group of high-precision lane segments and each high-precision lane segment in the last group of high-precision lane segments on the exploration path can be determined.

[0075] The first set of high-precision lane segments on the exploration path can be a group of high-precision lane segments on the high-precision road segment where the starting point of the target lane line is located, while the last set of high-precision lane segments can be related to the end point of the target lane line. It can be a group of high-precision lane segments on the high-precision road segment where the end point is located, or it can be a group of high-precision lane segments on other high-precision road segments related to the high-precision road segment where the end point is located.

[0076] The lane accessibility data between each high-precision lane segment in the first high-precision lane group of the exploration path and each high-precision lane segment in the last high-precision lane group can reflect whether vehicles traveling on the exploration path will be affected by the target lane line, that is, whether the existence of the target lane line will prevent vehicles traveling in one or more lanes from reaching any lane on the exploration path.

[0077] In an optional implementation of this embodiment, the step of determining the lane accessibility data between each high-precision lane segment in the first group of high-precision lane segments and each high-precision lane segment in the last group of high-precision lane segments on the exploration path can be implemented as follows:

[0078] Based on the target lane line, determine the lateral accessibility data between adjacent high-precision lane segments in each group of high-precision lane segments on the exploration path;

[0079] Based on the target lane line, determine the longitudinally accessible data between adjacent high-precision lane segments from the first group to the last group on the exploration path in the path direction of the exploration path;

[0080] Based on the lateral accessibility data and the longitudinal accessibility data, the lane accessibility data is determined.

[0081] In this optional implementation, lateral accessibility data may include, but is not limited to, information on whether adjacent lane segments can be crossed laterally. If the lane line between two adjacent lane segments is a dashed line, the two adjacent lane segments are mutually accessible. If the lane line between two adjacent lane segments is a solid line, the two adjacent lane segments are not mutually accessible. If the lane line between two adjacent lane segments is dashed on the left and solid on the right, the left lane segment is accessible to the right adjacent lane, but the right adjacent lane is not accessible to the left lane. If the lane line between two adjacent lane segments is solid on the left and dashed on the right, the left lane segment is not accessible to the right adjacent lane, but the right adjacent lane is accessible to the left lane. It should be noted that adjacent lane segments laterally actually refer to adjacent lane segments within a group of high-precision lane segments belonging to the same high-precision road segment. Through the above method, the accessibility data between the high-precision lane segments involved in the target lane line corresponding to the target intersection can be determined, that is, the mutual accessibility data between each adjacent high-precision lane segment.

[0082] As mentioned above, the target lane line can be formed by aggregating multiple broken lane segments from high-precision map data. Therefore, the target lane line can correspond to multiple vertically connected high-precision lane segments before the target intersection. Since each high-precision lane segment corresponds to a high-precision road segment, and the lane line affects the traffic conditions of each lane on the road segment, the target lane line may affect multiple sets of high-precision lane segments before the target intersection, with each set of high-precision lane segments corresponding to the same high-precision road segment. Therefore, in some embodiments, the lateral accessibility data between adjacent high-precision lane segments in each set can be determined.

[0083] High-precision map data also stores the topological connectivity between high-precision road segments. Based on this topological connectivity, multiple sets of high-precision lane segments can be identified on multiple topologically connected high-precision road segments along the exploration path. Each high-precision road segment corresponds to a set of high-precision lane segments. This topological connectivity along the path of the exploration path is understood to mean that the multiple sets of high-precision lane segments on multiple topologically connected high-precision road segments are formed by longitudinally breaking multiple complete lanes in the real world. Therefore, longitudinally accessible data actually reflects the association between each high-precision lane segment in the first set of high-precision lane segments on the exploration path and the high-precision lane segments belonging to the same lane in the last set of high-precision lane segments. Longitudinally accessible high-precision lane segments are groups of high-precision lane segments on the same lane, while longitudinally inaccessible high-precision lane segments do not belong to the same lane. It can be understood that multiple high-precision lane segments belonging to the same lane refer to multiple high-precision lane segments belonging to the same lane in the real world.

[0084] After determining the lateral and longitudinal accessibility data of each high-precision lane segment group on the exploration path, the lane accessibility data from each high-precision lane segment in the first group of high-precision lane segments to any high-precision lane segment in the last group of high-precision lane segments on the exploration path can be determined.

[0085] like Figure 2B As shown, G1, G2, G3, and G4 are the high-precision road segments involved by the long solid lines. The long solid lines in the diagram only cross one target intersection, starting at G1 and ending at G3. Therefore, the exploration path before this target intersection is G1-G2-G3 or G1-G2-G4, with G4 being the exit road segment. The high-precision lane group corresponding to G1 includes 4 lane segments, denoted by 1-4; the high-precision lane group corresponding to G2 includes 3 lane segments, denoted by 5-7; the high-precision lane group corresponding to G3 includes 3 lane segments, denoted by 8-10; and the lane group corresponding to G4 includes 1 lane, denoted by 11.

[0086] The exploration path corresponds to a total of four high-precision lane groups, namely lane groups on G1, G2, G3 and G4, from which the following lateral accessibility data can be obtained:

[0087] G1: 1->2, 2->1, 3->4, 4->3; where “->” indicates reachability.

[0088] G2:5->6,6->5.

[0089] G3:8->9,9->8,9->10,10->9.

[0090] G4: None.

[0091] Next, the high-precision lane segments in the four high-precision lane groups corresponding to the exploration path can be determined, and the longitudinally accessible data of adjacent high-precision lane segments in the path direction of the exploration path can be obtained, as follows:

[0092] 1->5, 5->8.

[0093] 2->6, 6->9.

[0094] 3->7, 7->10.

[0095] 4->11.

[0096] Based on the aforementioned lateral and longitudinal accessibility data, the longitudinal connectivity between each high-precision lane segment group in the first high-precision lane segment group 1-4 (corresponding to G1) on the exploration path G1-G2-G3 and each high-precision lane segment in the last high-precision lane segment group 8-10 (corresponding to G3) can be determined. Furthermore, the lane accessibility data between each high-precision lane segment group in the first high-precision lane segment group 1-4 (corresponding to G1) on the exploration path G1-G2-G4 and each high-precision lane segment in the last high-precision lane segment group 11 (corresponding to G4) is as follows:

[0097] 1->8(√), 1->9(√), 1->10(×), 1->11(×), where lane segment 1 can reach lane segments 8 and 9, but cannot reach lane segments 10 and 11.

[0098] 2->8(√),2->9(√),2->10(×),2->11(×), Lane segment 2 can reach lane segments 8 and 9, but cannot reach lane segments 10 and 11.

[0099] 3->8(×),3->9(×),3->10(√),3->11(√); Lane segment 3 can reach lane segments 10 and 11, but cannot reach lanes 8 and 9.

[0100] 4->8(×),4->9(×),4->10(√),4->11(√); Lane segment 4 can reach lane segments 10 and 11, but cannot reach lanes 8 and 9.

[0101] like Figure 2C As shown in the diagram, the long solid line crosses multiple intersections. G1-G8 are the high-precision road segments involved by the long solid line. The starting point of the long solid line is at high-precision road segment G1, and the ending point is at high-precision road segment G7. Therefore, the exploration paths before the target intersection include G1-G8, G1-G2-G3-G4-G5-G6, and G1-G2-G3-G4-G5-G7. G1 is the high-precision road segment where the starting point of the long solid line is located, which is the entry road segment. G7 is the exit road segment where the ending point of the long solid line is located. G6 and G8 are exit road segments where the ending point of the long solid line is not located. The high-precision lane group corresponding to road segment G1 includes 4 lanes, denoted by 1-4; the high-precision lane group corresponding to G7 includes 3 lanes, denoted by 5-7; the high-precision lane group corresponding to G6 includes 4 lanes, denoted by 8-11; and the lane group corresponding to G8 includes 2 lanes, denoted by 12-13.

[0102] The exploration path corresponds to a total of eight high-precision lane groups, including the G1-G8 high-precision road segments. The lateral accessibility data is as follows:

[0103] G1:2->3,3->2,3->4,4->3; where “->” indicates reachability.

[0104] G6:6->7,7->6.

[0105] G7:8->9,9->8,9->10, 10->9,10->11,11->10.

[0106] G8:12->13,13->12.

[0107] Next, the longitudinal accessibility data of adjacent high-precision lane segments in the four high-precision lane groups corresponding to the exploration path can be determined, as follows (the longitudinal accessibility data of the intermediate high-precision road segment G4-G5 is omitted):

[0108] 1->5, 1->12, 1->13.

[0109] 2->6.

[0110] 3->7, 3->8.

[0111] 4->11, 4->12.

[0112] Based on the aforementioned lateral and longitudinal accessibility data, the longitudinal connectivity between each high-precision lane segment group in the first high-precision lane segment group 1-4 (the high-precision lane segment group corresponding to G1) on the exploration path G1-G8 and each high-precision lane segment in the last high-precision lane segment group 12-13 (the high-precision lane segment group corresponding to G8) can be determined. The longitudinal connectivity between each high-precision lane segment group and each high-precision lane segment in the last high-precision lane segment group 8-11 (the high-precision lane segment group corresponding to G6), and the lane accessibility data between each high-precision lane segment group 1-4 (the high-precision lane segment group corresponding to G1) in the first high-precision lane segment group G1-G2-G3-G4-G5-G7 and each high-precision lane segment in the last high-precision lane segment group 5-7 (the high-precision lane segment group corresponding to G7) are detailed below:

[0113] 1->11 / 12 / 4(√), 1->5 / 6 / 7 / 8 / 9 / 10(×); where lane segment 1 can reach lane segments 4, 11 and 12, but cannot reach lane segments 5-10.

[0114] 2->11 / 12 / 4(×), 2->5 / 6 / 7 / 8 / 9 / 10(√), Lane segment 2 can reach lane segments 5-10, but cannot reach lane segments 4, 11 and 12.

[0115] 3->11 / 12 / 4(×), 3->5 / 6 / 7 / 8 / 9 / 10(√), where lane segment 3 can reach lane segments 5-10, but cannot reach lane segments 4, 11 and 12.

[0116] 4->11 / 12 / 4(×), 4->5 / 6 / 7 / 8 / 9 / 10(√), where lane segment 4 can reach lane segments 5-10, but cannot reach lane segments 4, 11 and 12.

[0117] In an optional implementation of this embodiment, the step of determining the route from the starting point to the ending point based on the high-precision map data can be implemented as follows:

[0118] The high-precision lane segment group on the high-precision road section where the starting point is located is identified as the first high-precision lane segment group;

[0119] If the target intersection is a split intersection, then the high-precision lane segment group on the exit road section associated with the starting point and the ending point is determined as the last high-precision lane segment group;

[0120] If the target intersection is not a separated intersection, then the next longitudinal connecting lane of the high-precision road segment where the endpoint is located will be determined as the last high-precision lane segment.

[0121] The path from the first group of high-precision lane sections to the last group of high-precision lane sections is determined as the exploration path.

[0122] In this optional implementation, the exploration path includes multiple sets of high-precision lane segments, and the sets of high-precision lane segments vary depending on the type of the target intersection.

[0123] If the target intersection is a separating intersection, that is, an intersection with a separation point, such as... Figure 2BAs shown, the exploration path includes two types. One type includes multiple sets of high-precision lane segments from the high-precision road segment where the starting point is located to the high-precision road segment where the ending point is located. The other type includes multiple sets of high-precision lane segments from the high-precision road segment where the starting point is located to the exit road segment. The exit road segment can be an exit road segment associated with the starting point and the ending point. For example, at the separation intersection, if the high-precision road segment where the starting point is located is an entry road, or if a subsequent high-precision road segment where the starting point is located is an entry road segment, the exit road segment corresponding to that entry road segment, or the same exit road segment that is not located at the ending point as the entry road segment corresponding to the exit road segment where the ending point is located. Each set of high-precision lane segments includes multiple lane segments that are laterally adjacent on one of the high-precision road segments.

[0124] like Figure 2C As shown, G2 is the entry road segment, and its corresponding exit road segment is G8. G7 is the exit road segment where the destination is located, and its entry road segment is G5. G5 also has an exit road segment G6. Therefore, under this target intersection, we can get three exit road segments G8, G7 and G6, and we can also get three exploration paths G1-G8, G1-G2-G3-G4-G5-G6 and G1-G2-G3-G4-G5-G7.

[0125] If the target intersection is not a separated intersection, but rather a large intersection with stop lines and landmarks, and the landmark arrows for different lane segments are different, then the exploration path includes multiple sets of high-precision lane segments from the high-precision road segment where the starting point is located to the next longitudinal connecting lane segment of the high-precision road segment where the ending point is located. For example... Figure 3 As shown, the lane where 'a' is located is the high-precision lane segment where the end of the target lane line is located, and the next longitudinal connecting lane of the high-precision road segment corresponding to this high-precision lane segment is the lane segment where 'b' is located. This connection relationship is stored in the high-precision map data and can be directly obtained.

[0126] Therefore, the first set of high-precision lane segments in the exploration path are all high-precision lane segments on the high-precision road segment where the starting point is located, while the last set of high-precision lane segments is different. When the target intersection is a split intersection, in the high-precision map data, in the topological connectivity relationship of the high-precision road segment corresponding to the first set of high-precision lane segments as the entry road segment, at least two exit road segments are separated at the split point. The endpoint of the target lane line is one of these two exit high-precision road segments. Therefore, the exploration path can include paths from the entry road segment to at least two exit road segments. Thus, the high-precision lane segment group on the high-precision road segment where the starting point is located can be identified as the first set of high-precision lane segments in the high-precision map data, while the high-precision lane segment groups on the two exit road segments can be identified as the last set of high-precision lane segments. The path from the first set of high-precision lane segments to the last set of high-precision lane segments is the exploration path.

[0127] When the target intersection is not a dividing intersection but a large intersection, the endpoint of the target lane line is usually on the entry road section of the target intersection and before the stop line. In order to accurately determine the longitudinal connectivity, the next longitudinal connecting lane of the high-precision road segment where the endpoint of the target lane line is located can be identified as the last group of lane segments in the exploration path. The reason for identifying only the next longitudinal connecting lane segment as the last group of lane segments is that, according to the actual road conditions, if you can reach this next longitudinal connecting lane segment, you can also reach other lane segments on the high-precision road segment where this next longitudinal connecting lane segment is located. Therefore, only this next longitudinal connecting lane segment can be considered.

[0128] Figure 4 A flowchart illustrating a navigation method according to an embodiment of this disclosure is shown. Figure 4 As shown, the navigation method includes the following steps:

[0129] In step S401, the navigation planning path is obtained;

[0130] In step S402, in response to the navigation planning path containing a preset benchmark path, it is determined whether the recommended lane at the preset benchmark path matches the associated lane information of the preset benchmark path; the preset benchmark path and the associated lane information of the preset benchmark path are obtained based on the above path and lane association method.

[0131] In step S403, if the recommended lane matches the associated lane information, a prompt message is output before the navigable object is guided to the preset precision path; the prompt message includes a first prompt message indicating the existence of a target lane line, and a second prompt message indicating the associated lane information affected by the target lane line.

[0132] In this embodiment, the navigation method can be executed on a terminal device. The user can input the navigation origin and destination through a navigation application on the terminal device. After the terminal device sends the navigation origin and destination to the route planning server, the route planning server returns the planned navigation route. The terminal device can also pre-obtain at least one or more preset benchmark routes that have established lane association relationships. These preset benchmark routes are obtained based on the path-lane association method described above. In this method, the lane information that establishes an association relationship with the preset benchmark routes can be referred to as the associated lane information of the preset benchmark routes, and the lane corresponding to this associated lane information can be referred to as the associated lane. In some embodiments, the associated lane information can be relative lane information on the roads along the preset benchmark routes, such as lane number.

[0133] The terminal device can also match the planned navigation path with a preset benchmark path. If the planned navigation path includes the preset benchmark path, a prompt message will be output before guiding the navigated object to the preset benchmark path. This prompt message can indicate to the navigated object that there is a target lane line on the preset benchmark path ahead that could affect lane changing; for example, the target lane line could be a long solid line. Furthermore, to avoid deviation due to the influence of the target long solid line, the prompt message can also indicate to the navigated object a recommended lane to enter in advance on the preset benchmark path.

[0134] In some embodiments, after establishing the association between the preset precision path and the associated lane information using the above-described path and lane association method, the starting point of the target lane line on the preset precision path can also be recorded so that when the navigated object is guided to the starting point of the target lane line during the navigation process, the above-described prompt information is output.

[0135] For details regarding the path and lane association method described above, please refer to the relevant description in this embodiment. It will not be repeated here.

[0136] The following are embodiments of the apparatus disclosed herein, which can be used to execute the embodiments of the apparatus disclosed herein.

[0137] Figure 5 This diagram illustrates a structural block diagram of a path and lane association device according to an embodiment of the present disclosure. This device can be implemented as part or all of an electronic device through software, hardware, or a combination of both. Figure 5 As shown, the path and lane association device includes:

[0138] The first determining module 501 is configured to determine the target lane line that affects vehicle lane changing;

[0139] The second determining module 502 is configured to determine the target intersection involving the target lane line from high-precision map data;

[0140] The third determining module 503 is configured to determine, based on the high-precision map data, the high-precision target path before the target intersection affected by the target lane line, and the affected lane segments on the high-precision target path.

[0141] The mapping module 504 is configured to map the high-precision target path to the standard-precision path based on the mapping relationship between the high-precision map data and the standard-precision map data, and then establish the association relationship between the standard-precision path and the lane information of the affected lane segment.

[0142] In this embodiment, the path and lane association device can be executed by a server. High-precision map data is a data storage method that uses lanes as storage objects. It mainly includes high-precision road data, high-precision lane data (lane lines, types, relationships, etc.), and high-precision component data (ground markings, facilities, etc.), often simply referred to as "HD data." Standard-precision map data, on the other hand, is a data storage method that uses roads as storage objects. It mainly includes basic road network data, road attribute information (electronic eyes, guide lines, prohibition information, etc.), and public transportation information such as cycling and walking, often simply referred to as "SD data."

[0143] The target lane line affecting vehicle lane changes can be a long solid traffic line. A long solid traffic line is a type of lane divider, a white solid line separating lanes traveling in the same direction. Line types include solid line, left dashed and right solid line, and left solid and right dashed line. According to traffic regulations, vehicles are not allowed to merge (or cross) from one side of a solid line to the other. In some embodiments, the target lane line can be obtained through road image recognition or by processing lane line information stored in high-precision map data.

[0144] The navigation service is concerned with the long solid line that affects vehicles changing lanes before the intersection. Therefore, after determining the target lane line based on high-precision map data, the target intersection involving the target lane line can be identified.

[0145] In some embodiments, a target intersection involving a target lane line can be understood as a high-precision road segment where the target lane line is located before the target intersection, meaning that a vehicle can travel from the lane segment on the high-precision road segment where the target lane line is located to the target intersection in the direction of travel. Typically, the end point of the target lane line is located before the stop line of the target intersection, or on the exit road segment of the target intersection.

[0146] It is understood that high-precision map data can be high-precision map data covering the entire area or within a defined area as needed, while the target lane line can be all long solid traffic lines within that area or defined area, i.e., all long solid traffic lines within the area covered by the high-precision map data. In some embodiments, all intersections can be extracted from the area covered by the high-precision map data. The high-precision map data stores the intersections involved in each high-precision road segment, and there is a correlation between the lane lines on each high-precision road segment and the high-precision road segment itself. Therefore, after extracting all intersections from the high-precision map data, the high-precision road segment involved in that intersection can be matched with the high-precision road segment involved in the target lane line, thereby identifying the target intersection involving the target lane line. Figure 2A The diagram illustrates the target intersection and corresponding high-precision road segments from high-precision map data. Only the high-precision road segments, target lane lines, high-precision lane line segments, and high-precision vehicle lane segments below the target intersection are shown schematically. The diagram shows the high-precision road segmented into three segments. Each high-precision road segment has three high-precision lane line segments: two dashed lines and one solid line. These three solid line segments can be merged into a single long solid line, which is the target lane line.

[0147] After identifying the target intersection, a high-precision target path can be determined for each target intersection, including the lanes affected by the target lane line and the lanes along that path. It's understood that the target lane line can be a long solid traffic line, preventing vehicles from crossing from one lane to the next. Therefore, during path planning, the adjacent lane is clearly affected by this long solid traffic line. Based on this, the lateral accessibility between lanes involved in the target lane line before the target intersection can be analyzed to determine whether the target lane line affects the high-precision target path before the intersection and the lanes along that path. A high-precision target path can be understood as a path starting from the lane segment involved in the target lane line's starting point and extending to the lane segment involved in the target lane line's ending point. This high-precision target path may include one or more high-precision road segments ordered by travel direction. It's understood that each high-precision road segment may include one or more lane segments, and due to the existence of the target lane line, some lane segments on the high-precision target path may be longitudinally inaccessible. Therefore, on this high-precision target path, starting from the lane segment involved at the starting point of the target lane line, the longitudinally inaccessible lane segments can be identified as the affected lane segments on the high-precision target path. It can be understood that a longitudinally inaccessible lane segment is defined as a lane segment where the lane line traversed when traveling from the vehicle's position to that lane segment is a solid line; such a lane segment can be identified as inaccessible. Affected lane segments can be understood as lanes where, due to the existence of the target lane line, not all lanes can merge into. For example, the path before the target intersection involved in the target lane line can be represented as G1->G2->G3->G4, where G1, G2, G3, and G4 are the high-precision road segments involved from the start to the end of the target lane line, respectively. G1 includes two lane segments l1 and l2, and G4 includes two lane segments l3 and l4. If lane segments l1 to l3 belong to the first lane on the actual road, and lane segments l2 to l4 belong to the second lane on the actual road, and there is a solid lane line between the first and second lanes on the actual road, then it is impossible to cross the solid line from lane segment l1 to l4, and it is impossible to cross the solid line from lane segment l2 to lane segment l3. Therefore, this path can be considered a high-precision target path, and the affected lanes on the high-precision target path G1->G2->G3->G4 are l3 and l4.

[0148] As mentioned above, current navigation services typically provide road-level navigation services based on high-precision map data. To adapt to road-level navigation services based on high-precision map data, the high-precision target path before the target intersection affected by the target lane line, as determined above, can be mapped to the high-precision path based on the mapping relationship between high-precision map data and high-precision map data. Furthermore, the lane information of the affected lane segments on the high-precision target path can be associated with the high-precision path. Therefore, when using high-precision map data for navigation services, if the navigation path matches the high-precision path, after guiding the navigator to the high-precision path, prompts can be output to the navigator based on the lane information of the affected lane segments associated with that high-precision path, such as a navigation voice prompt like "Long solid line ahead, please move into the rightmost lane in advance." The lane information of the affected lane segments can include information indicating the location of the affected lane segment on the high-precision road.

[0149] It should be noted that the mapping relationship between high-precision map data and standard-precision map data is known information, typically the mapping relationship between high-precision road segments and standard-precision roads. Since standard-precision map data lacks lane data, the identifiers of affected lane segments on the high-precision target path can be converted into relative lane information on that road. In other words, because standard-precision map data does not contain lane lines, lanes, or other related data on standard-precision roads, it is impossible to express the lane information using the data of the affected lane segment. Therefore, the relative lane information of the affected lane segment on the standard-precision road can be used, such as the nth lane, the rightmost lane, or the rightmost lane, second rightmost lane, etc., of the recommended lane segment.

[0150] In this embodiment, to provide advance warnings when encountering long solid lines in road-level path planning using high-precision map data, all target lane lines within the corresponding area can be extracted in advance using high-precision map data. Furthermore, all target intersections involving these target lane lines can be extracted using the same high-precision map data. For each target intersection, the high-precision target path before the intersection affected by the target lane line, as well as the affected lane segments on that path, can be determined using high-precision map data. Based on the mapping relationship between high-precision and high-precision map data, the high-precision target path is mapped to a high-precision path, establishing a correlation between the high-precision path and the lane information of the affected lane segments. Through this method, during road-level path planning and navigation, based on the high-precision path and associated lane information determined in this way, users can be warned in advance when encountering long solid lines, thereby reducing the deviation rate of the navigated object and improving driving safety and traffic efficiency.

[0151] In an optional implementation of this embodiment, the first determining module may be implemented as follows:

[0152] Select multiple high-precision lane segments that affect vehicle lane changes from the high-precision map data;

[0153] The multiple high-precision lane segments that are connected sequentially in spatial location are aggregated into the target lane line.

[0154] In this optional implementation, for ease of creation, a complete road in the real world is divided into multiple high-precision road segments when generating high-precision map data, and each high-precision road segment is then created separately. To represent the connections between these high-precision road segments in the real world within the high-precision map data, topological connectivity relationships between the high-precision road segments are typically created during the map compilation process. These topological connectivity relationships are used to represent the sequential connections between each high-precision road segment.

[0155] In some embodiments, the topological connectivity between high-precision road segments may include, but is not limited to, the entry road segment and the exit road segment of the current high-precision road segment. An entry road segment can be understood as the preceding high-precision road segment that is directly adjacent to the current high-precision road segment longitudinally in the direction of travel of the current high-precision road segment. Conversely, an exit road segment can be understood as the next high-precision road segment that is directly adjacent to the current high-precision road segment longitudinally in the direction of travel of the current high-precision road segment. In other words, in the real world, when a vehicle or intelligent driving object travels along the direction of travel of a high-precision road segment, it enters the current high-precision road segment from the entry road segment, exits the current high-precision road segment, and then enters the exit road segment.

[0156] It should also be noted that each high-precision road segment includes a set of horizontally adjacent high-precision lane segments, and the lane segment data of multiple high-precision lane segments are also stored in the high-precision map data. Lane segment data may include, but is not limited to, information such as the attributes of the lane segments included on the high-precision road segment and the attributes of the associated lane line segments. The attribute information of the lane line segments may include the type of lane line segments, such as solid line, left dashed and right solid, left solid and right dashed, etc.

[0157] Because lane lines in high-precision map data are also broken into lane segments, we can first extract the high-precision lane segments that affect vehicle lane changes based on the high-precision map data, such as solid lines, left-dashed-right-solid lines, and left-solid-right-dashed lines. Then, we connect these broken lane segments according to their spatial location to form a long solid line. In other words, we aggregate these lane segments according to their spatial location to form the target lane line. The target lane line can be a complete long solid line on the road.

[0158] In an optional implementation of this embodiment, the third determining module may be implemented as follows:

[0159] Based on high-precision map data, determine the lane accessibility data between the high-precision lane segments involved in the target lane line corresponding to the target intersection;

[0160] Based on the lane accessibility data, the high-precision target path and the affected lane segments are determined.

[0161] In this optional implementation, as described above, the target intersection is an intersection with a target lane line. The high-precision map data includes data on each lane segment on the high-precision road segment, such as its type. Based on this data, the accessibility data between the high-precision lane segments corresponding to the target lane line can be determined. Based on the accessibility data between the high-precision lane segments, the high-precision target path affected by the target lane line and the affected lanes on the high-precision target path can be determined on the high-precision road segment from the start point to the end point of the target lane line.

[0162] In an optional implementation of this embodiment, determining the lane accessibility data between the high-precision lane segments involved in the target lane line corresponding to the target intersection based on the high-precision map data can be implemented as follows:

[0163] Determine the start and end points of the target lane lines corresponding to the target intersection;

[0164] Based on the high-precision map data, the exploration path from the starting point to the ending point is determined. The exploration path includes multiple high-precision road segments with interconnected front and rear topologies in the path direction. Each high-precision road segment corresponds to a set of high-precision lane segments.

[0165] Determine the lane accessibility data between each high-precision lane segment in the first group of high-precision lane segments and each high-precision lane segment in the last group of high-precision lane segments on the exploration path.

[0166] In this optional implementation, for a target intersection with a target lane line, the start and end points of the target lane line can be determined, and based on high-precision map data, the exploration path from the start point to the end point can be determined. This exploration path includes multiple high-precision road segments that are topologically connected along the path direction, and each high-precision road segment corresponds to a set of high-precision lane segments. It can be understood that the multiple high-precision road segments that are topologically connected along the path direction belong to the same real road, and the set of high-precision lane segments corresponding to each high-precision road segment actually belongs to multiple lanes on that real road. Adjacent high-precision lane segments along the path direction can be understood as lane segments belonging to the same lane on that real road.

[0167] Therefore, based on the target lane line, the lane accessibility data between each high-precision lane segment in the first group of high-precision lane segments and each high-precision lane segment in the last group of high-precision lane segments on the exploration path can be determined.

[0168] The first set of high-precision lane segments on the exploration path can be a group of high-precision lane segments on the high-precision road segment where the starting point of the target lane line is located, while the last set of high-precision lane segments can be related to the end point of the target lane line. It can be a group of high-precision lane segments on the high-precision road segment where the end point is located, or it can be a group of high-precision lane segments on other high-precision road segments related to the high-precision road segment where the end point is located.

[0169] The lane accessibility data between each high-precision lane segment in the first high-precision lane group of the exploration path and each high-precision lane segment in the last high-precision lane group can reflect whether vehicles traveling on the exploration path will be affected by the target lane line, that is, whether the existence of the target lane line will prevent vehicles traveling in one or more lanes from reaching any lane on the exploration path.

[0170] In an optional implementation of this embodiment, determining the lane accessibility data between each high-precision lane segment in the first group of high-precision lane segments and each high-precision lane segment in the last group of high-precision lane segments on the exploration path can be implemented as follows:

[0171] Based on the target lane line, determine the lateral accessibility data between adjacent high-precision lane segments in each group of high-precision lane segments on the exploration path;

[0172] Based on the target lane line, determine the longitudinally accessible data between adjacent high-precision lane segments in the path of the exploration path, from the first group of high-precision lane segments to the last group of high-precision lane segments.

[0173] Based on the lateral accessibility data and the longitudinal accessibility data, the lane accessibility data is determined.

[0174] In this optional implementation, lateral accessibility data may include, but is not limited to, information on whether adjacent lane segments can be crossed laterally. If the lane line between two adjacent lane segments is a dashed line, the two adjacent lane segments are mutually accessible. If the lane line between two adjacent lane segments is a solid line, the two adjacent lane segments are not mutually accessible. If the lane line between two adjacent lane segments is dashed on the left and solid on the right, the left lane segment is accessible to the right adjacent lane, but the right adjacent lane is not accessible to the left lane. If the lane line between two adjacent lane segments is solid on the left and dashed on the right, the left lane segment is not accessible to the right adjacent lane, but the right adjacent lane is accessible to the left lane. It should be noted that adjacent lane segments laterally actually refer to adjacent lane segments within a group of high-precision lane segments belonging to the same high-precision road segment. Through the above method, the accessibility data between the high-precision lane segments involved in the target lane line corresponding to the target intersection can be determined, that is, the mutual accessibility data between each adjacent high-precision lane segment.

[0175] As mentioned above, the target lane line can be formed by aggregating multiple broken lane segments from high-precision map data. Therefore, the target lane line can correspond to multiple vertically connected high-precision lane segments before the target intersection. Since each high-precision lane segment corresponds to a high-precision road segment, and the lane line affects the traffic conditions of each lane on the road segment, the target lane line may affect multiple sets of high-precision lane segments before the target intersection, with each set of high-precision lane segments corresponding to the same high-precision road segment. Therefore, in some embodiments, the lateral accessibility data between adjacent high-precision lane segments in each set can be determined.

[0176] High-precision map data also stores the topological connectivity between high-precision road segments. Based on this topological connectivity, multiple sets of high-precision lane segments can be determined on multiple topologically connected high-precision road segments along the exploration path. Each high-precision road segment corresponds to a set of high-precision lane segments. The topological connectivity along the path of the exploration path is understood to be such that the multiple sets of high-precision lane segments on multiple topologically connected high-precision road segments are formed by longitudinally breaking multiple complete lanes in the real world. Therefore, longitudinally accessible data actually reflects the relationship between each high-precision lane segment in the first set of high-precision lane segments on the exploration path and the high-precision lane segments belonging to the same lane in the last set of high-precision lane segments. Longitudinally accessible high-precision lane segments are groups of high-precision lane segments on the same lane, while longitudinally inaccessible high-precision lane segments do not belong to the same lane.

[0177] After determining the lateral and longitudinal accessibility data of each high-precision lane segment group on the exploration path, the lane accessibility data from each high-precision lane segment in the first group of high-precision lane segments to any high-precision lane segment in the last group of high-precision lane segments on the exploration path can be determined.

[0178] In an optional implementation of this embodiment, determining the route from the starting point to the ending point based on the high-precision map data can be carried out in the following manner:

[0179] The high-precision lane segment group on the high-precision road section where the starting point is located is identified as the first high-precision lane segment group;

[0180] If the target intersection is a split intersection, then the high-precision lane segment group on the exit road section associated with the starting point and the ending point is determined as the last high-precision lane segment group;

[0181] If the target intersection is not a separated intersection, then the next longitudinal connecting lane of the high-precision road segment where the endpoint is located will be determined as the last high-precision lane segment.

[0182] The path from the first group of high-precision lane sections to the last group of high-precision lane sections is determined as the exploration path.

[0183] In this optional implementation, the exploration path includes multiple sets of high-precision lane segments, and the sets of high-precision lane segments vary depending on the type of the target intersection.

[0184] If the target intersection is a separating intersection, that is, an intersection with a separation point, such as... Figure 2B As shown, the exploration path includes two types. One type includes multiple sets of high-precision lane segments from the high-precision road segment where the starting point is located to the high-precision road segment where the ending point is located. The other type includes multiple sets of high-precision lane segments from the high-precision road segment where the starting point is located to the exit road segment at the target intersection. Each set of high-precision lane segments includes multiple lane segments that are laterally adjacent on one of the high-precision road segments.

[0185] like Figure 2C As shown, G2 is the entry road segment, and its corresponding exit road segment is G8. G7 is the exit road segment where the destination is located, and its entry road segment is G5. G5 also has an exit road segment G6. Therefore, under this target intersection, we can get three exit road segments G8, G7 and G6, and we can also get three exploration paths G1-G8, G1-G2-G3-G4-G5-G6 and G1-G2-G3-G4-G5-G7.

[0186] If the target intersection is not a separated intersection, but rather a large intersection with stop lines and landmarks, and the landmark arrows for different lane segments are different, then the exploration path includes multiple sets of high-precision lane segments from the high-precision road segment where the starting point is located to the next longitudinal connecting lane segment of the high-precision road segment where the ending point is located. For example... Figure 3 As shown, the lane where 'a' is located is the high-precision lane segment where the end of the target lane line is located, and the next longitudinal connecting lane of the high-precision road segment corresponding to this high-precision lane segment is the lane segment where 'b' is located. This connection relationship is stored in the high-precision map data and can be directly obtained.

[0187] Therefore, the first set of high-precision lane segments in the exploration path are all high-precision lane segments on the high-precision road segment where the starting point is located, while the last set of high-precision lane segments is different. When the target intersection is a split intersection, in the high-precision map data, in the topological connectivity relationship of the high-precision road segment corresponding to the first set of high-precision lane segments as the entry road segment, at least two exit road segments are separated at the split point. The endpoint of the target lane line is one of these two exit high-precision road segments. Therefore, the exploration path can include paths from the entry road segment to at least two exit road segments. Thus, the high-precision lane segment group on the high-precision road segment where the starting point is located can be identified as the first set of high-precision lane segments in the high-precision map data, while the high-precision lane segment groups on the two exit road segments can be identified as the last set of high-precision lane segments. The path from the first set of high-precision lane segments to the last set of high-precision lane segments is the exploration path.

[0188] When the target intersection is not a dividing intersection but a large intersection, the endpoint of the target lane line is usually on the entry road section of the target intersection and before the stop line. In order to accurately determine the longitudinal connectivity, the next longitudinal connecting lane of the high-precision road segment where the endpoint of the target lane line is located can be identified as the last group of lane segments in the exploration path. The reason for identifying only the next longitudinal connecting lane segment as the last group of lane segments is that, according to the actual road conditions, if you can reach this next longitudinal connecting lane segment, you can also reach other lane segments on the high-precision road segment where this next longitudinal connecting lane segment is located. Therefore, only this next longitudinal connecting lane segment can be considered.

[0189] According to an embodiment of the present disclosure, a path and lane association device can be implemented as part or all of an electronic device through software, hardware, or a combination of both. The path and lane association device includes:

[0190] The acquisition module is configured to acquire the navigation planning path;

[0191] The fourth determining module is configured to, in response to the navigation planning path containing a preset precision path, determine whether the recommended lane at the preset precision path matches the associated lane information of the preset precision path; the preset precision path and the associated lane information of the preset precision path are obtained based on the aforementioned path and lane association device.

[0192] The output module is configured to output a prompt message before guiding the navigable object to the preset precision path if the recommended lane matches the associated lane information; the prompt message includes a first prompt message indicating the existence of a target lane line, and a second prompt message indicating the associated lane information affected by the target lane line.

[0193] In this embodiment, the navigation device can be executed on a terminal device. The user can input the navigation origin and destination through a navigation application on the terminal device. The terminal device then sends the navigation origin and destination to the route planning server, which returns the planned navigation route. The terminal device can also pre-obtain at least one or more preset benchmark routes that have established lane association relationships. These preset benchmark routes are obtained based on the path and lane association device described above. The lane information that has established an association relationship with the preset benchmark routes in the path and lane association device can be referred to as the associated lane information of the preset benchmark routes, and the lane corresponding to this associated lane information can be referred to as the associated lane. In some embodiments, the associated lane information can be relative lane information on the road along the preset benchmark route, such as lane number.

[0194] The terminal device can also match the planned navigation path with a preset benchmark path. If the planned navigation path includes the preset benchmark path, a prompt message is output before guiding the navigated object to the preset benchmark path. This prompt message can indicate to the navigated object that there is a target lane line on the preset benchmark path ahead that could affect lane merging. For example, the target lane line could be a long solid line. Furthermore, to avoid deviation due to the influence of the target long solid line, the prompt message can also indicate to the navigated object to enter an associated lane on the benchmark path in advance. This associated lane can be understood as a lane that, due to the presence of the target lane line, not all lanes before the starting point of the target lane line can be merged into. In some embodiments, the second prompt message regarding the associated lane information affected by the target lane line may include information prompting the navigated object to merge into the associated lane in advance to avoid being affected by the target lane line.

[0195] In some embodiments, after establishing the association between the preset precision path and the associated lane information using the path and lane association device, the starting point of the target lane line on the preset precision path can also be recorded so that when the navigated object is guided to the starting point of the target lane line during navigation, the above-mentioned prompt information is output.

[0196] For details regarding this embodiment, please refer to the description of the path and lane association device above, which will not be repeated here.

[0197] This disclosure also discloses an electronic device. Figure 6 This diagram illustrates a structural block diagram of an electronic device according to an embodiment of the present disclosure, such as... Figure 6 As shown, the electronic device 600 includes a memory 601 and a processor 602; wherein,

[0198] The memory 601 is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor 602 to implement the above method steps.

[0199] Figure 7 This is a schematic diagram of the structure of a computer system suitable for implementing a path and lane association method and / or navigation method according to an embodiment of the present disclosure.

[0200] like Figure 7 As shown, the computer system 700 includes a processing unit 701, which can be implemented as a CPU, GPU, FPGA, NPU, or other processing unit. The processing unit 701 can execute various processes according to any of the methods described above in this disclosure, based on a program stored in the read-only memory (ROM) 702 or a program loaded from the storage portion 708 into the random access memory (RAM) 703. The RAM 703 also stores various programs and data required for the operation of the computer system 700. The processing unit 701, ROM 702, and RAM 703 are interconnected via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0201] The following components are connected to the I / O interface 705: an input section 706 including a keyboard, mouse, etc.; an output section 707 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 708 including a hard disk, etc.; and a communication section 709 including a network interface card such as a LAN card, modem, etc. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the I / O interface 705 as needed. A removable medium 711, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 710 as needed so that computer programs read from it can be installed into the storage section 708 as needed.

[0202] In particular, according to embodiments of this disclosure, any of the methods described above in the embodiments of this disclosure can be implemented as a computer software program. For example, embodiments of this disclosure include a computer program product comprising a computer program tangibly embodied on a machine-readable medium, the computer program containing program code for performing any of the methods in the embodiments of this disclosure. In such an embodiment, the computer program can be downloaded and installed from a network via communication section 709, and / or installed from removable medium 711.

[0203] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0204] The units or modules described in the embodiments of this disclosure can be implemented in software or hardware. The described units or modules can also be located in a processor, and the names of these units or modules do not necessarily constitute a limitation on the unit or module itself.

[0205] In another aspect, this disclosure also provides a computer-readable storage medium, which may be a computer-readable storage medium included in the apparatus described in the above embodiments; or it may be a standalone computer-readable storage medium not assembled into a device. The computer-readable storage medium stores one or more programs that are used by one or more processors to perform the methods described in this disclosure.

[0206] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

Claims

1. A method for associating paths and lanes, wherein, include: Identify the target lane markings that affect vehicle lane changes; Identify the target intersection involving the target lane line from high-precision map data; Based on the high-precision map data, determine the high-precision target path before the target intersection that is affected by the target lane line, and the affected lane segments on the high-precision target path; Based on the mapping relationship between the high-precision map data and the standard-precision map data, after mapping the high-precision target path to the standard-precision path, an association relationship is established between the standard-precision path and the lane information of the affected lane segment.

2. The method according to claim 1, wherein, The determination of the target lane line affecting vehicle lane changes includes: Select multiple high-precision lane segments that affect vehicle lane changes from high-precision map data; The multiple high-precision lane segments that are connected sequentially in spatial location are aggregated into the target lane line.

3. The method according to claim 1 or 2, wherein, The step of determining, based on the high-precision map data, the high-precision target path before the target intersection affected by the target lane line, and the affected lane segments on the high-precision target path, includes: Based on the high-precision map data, determine the lane accessibility data between the high-precision lane segments involved in the target lane line corresponding to the target intersection; Based on the lane accessibility data, the high-precision target path and the affected lane segments are determined.

4. The method according to claim 3, wherein, The step of determining lane accessibility data between high-precision lane segments involved in the target lane line corresponding to the target intersection based on the high-precision map data includes: Determine the start and end points of the target lane lines corresponding to the target intersection; Based on the high-precision map data, the exploration path from the starting point to the ending point is determined. The exploration path includes multiple high-precision road segments with interconnected front and rear topologies in the path direction. Each high-precision road segment corresponds to a set of high-precision lane segments. Determine the lane accessibility data between each high-precision lane segment in the first group of high-precision lane segments and each high-precision lane segment in the last group of high-precision lane segments on the exploration path.

5. The method according to claim 4, wherein, The determination of lane accessibility data between each high-precision lane segment in the first group of high-precision lane segments and each high-precision lane segment in the last group of high-precision lane segments on the exploration path includes: Based on the target lane line, determine the lateral accessibility data between adjacent high-precision lane segments in each group of high-precision lane segments on the exploration path; Based on the target lane line, determine the longitudinally accessible data between adjacent high-precision lane segments from the first group to the last group on the exploration path in the path direction of the exploration path; Based on the lateral accessibility data and the longitudinal accessibility data, the lane accessibility data is determined.

6. The method according to claim 4 or 5, wherein, The determination of the route from the starting point to the ending point based on the high-precision map data includes: The high-precision lane segment group on the high-precision road section where the starting point is located is identified as the first high-precision lane segment group; If the target intersection is a split intersection, then the high-precision lane segment group on the exit road section associated with the starting point and the ending point is determined as the last high-precision lane segment group; If the target intersection is not a separated intersection, then the next longitudinal connecting lane of the high-precision road segment where the endpoint is located will be determined as the last high-precision lane segment. The path from the first group of high-precision lane sections to the last group of high-precision lane sections is determined as the exploration path.

7. A navigation method, wherein, include: Obtain navigation and route planning; In response to the navigation planning path including a preset precision path, it is determined whether the recommended lane at the preset precision path matches the associated lane information of the preset precision path; the preset precision path and the associated lane information of the preset precision path are obtained based on the method of any one of claims 1-6; If the recommended lane matches the associated lane information, a prompt message will be output before the navigable object is guided to the preset precision path; The prompt information includes a first prompt information about the existence of a target lane line, and a second prompt information about the associated lane information affected by the target lane line.

8. A path and lane association device, wherein, include: The first determining module is configured to determine the target lane line that affects vehicle lane changes; The second determining module is configured to determine the target intersection involving the target lane line from high-precision map data; The third determining module is configured to determine, based on the high-precision map data, the high-precision target path before the target intersection affected by the target lane line, and the affected lane segments on the high-precision target path; The mapping module is configured to map the high-precision target path to the standard-precision path based on the mapping relationship between the high-precision map data and the standard-precision map data, and then establish the association between the standard-precision path and the lane information of the affected lane segment.

9. A navigation device, wherein, include: The acquisition module is configured to acquire the navigation planning path; The fourth determining module is configured to, in response to the navigation planning path containing a preset precision path, determine whether the recommended lane at the preset precision path matches the associated lane information of the preset precision path; the preset precision path and the associated lane information of the preset precision path are obtained based on the apparatus of claim 8; The output module is configured to output a prompt message before guiding the navigable object to the preset precision path if the recommended lane matches the associated lane information; the prompt message includes a first prompt message indicating the existence of a target lane line, and a second prompt message indicating the associated lane information affected by the target lane line.

10. An electronic device, wherein, The method includes a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the method of any one of claims 1-7.

11. A computer-readable storage medium having computer instructions stored thereon, wherein, When executed by a processor, the computer instructions implement the method described in any one of claims 1-7.

12. An application software for navigation, comprising computer instructions, wherein, When the computer instruction is executed by the processor, it implements the method of claim 7.

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