Path planning method and device

Abstract

The embodiment of the invention provides a path planning method and device, and the method comprises the steps: determining a driving path according to an initial address and a target address of a target vehicle; dividing the driving path into at least one sub-path according to the driving mode and the corresponding use frequency of the driving path on each road section; determining a sub-driving evaluation attribute of the sub-path according to the driving mode of the sub-path, the first distance and the function; determining a driving evaluation attribute corresponding to the driving path according to the sub-driving evaluation attribute corresponding to the sub-path; and determining a target driving path of the target vehicle according to the driving evaluation attribute corresponding to the driving path, so that the target vehicle drives according to the target driving path. According to the technical scheme provided by the embodiment of the invention, the target driving path is determined according to the driving mode adopted by the driving path on each road section and the corresponding use frequency, so that the experience and satisfaction of the target user to the automatic auxiliary navigation driving mode are guaranteed, and the effect of improving the driving efficiency is achieved.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the field of intelligent driving technology, and in particular to a path planning method and device. Background Art

[0002] With the continuous development of smart car technology, in-vehicle navigation systems can quickly plan a driving route with the best distance and time based on the starting and ending points set by the user.

[0003] However, navigation systems typically rely on static map data and real-time traffic information, failing to fully consider complex road conditions and driving environments, resulting in low safety. Furthermore, drivers are often behind the wheel throughout the entire journey, leading to low comfort and driving efficiency. Summary of the Invention

[0004] The disclosed embodiments provide a path planning method and device to ensure the target user's experience and satisfaction with the automatic assisted navigation driving mode, thereby improving driving efficiency.

[0005] In a first aspect, an embodiment of the present disclosure provides a path planning method, the method comprising:

[0006] Determine at least one driving route based on the starting address and the destination address of the target vehicle;

[0007] For the at least one driving route, dividing the driving route into at least one sub-route based on a driving mode adopted on each road segment of the driving route and a corresponding usage frequency; wherein the driving mode includes an automatic assisted navigation driving mode or a manual takeover driving mode;

[0008] determining a sub-travel evaluation attribute of the sub-path according to the driving mode of the sub-path, the first distance of the sub-path, and a sub-travel evaluation attribute determination function;

[0009] Determining a driving evaluation attribute corresponding to the driving path according to the sub-driving evaluation attribute corresponding to the at least one sub-path;

[0010] A target driving path of the target vehicle is determined according to the driving evaluation attribute corresponding to the at least one driving path, so that the target vehicle drives according to the target driving path.

[0011] In a second aspect, an embodiment of the present invention further provides a path planning device, the device comprising:

[0012] A driving route determination module, configured to determine at least one driving route based on a starting address and a destination address of a target vehicle;

[0013] a sub-path division module, configured to divide the at least one driving path into at least one sub-path based on a driving mode and a corresponding usage frequency adopted on each road segment of the driving path; wherein the driving mode includes an automatic assisted navigation driving mode or a manual takeover driving mode;

[0014] a sub-travel evaluation attribute determination module, configured to determine the sub-travel evaluation attribute of the sub-path according to the driving mode of the sub-path, the first distance of the sub-path, and a sub-travel evaluation attribute determination function;

[0015] a driving evaluation attribute determination module, configured to determine a driving evaluation attribute corresponding to the driving path based on the sub-driving evaluation attribute corresponding to the at least one sub-path;

[0016] The target driving path determination module is used to determine the target driving path of the target vehicle according to the driving evaluation attribute corresponding to the at least one driving path, so that the target vehicle travels according to the target driving path.

[0017] In a third aspect, an embodiment of the present invention further provides an electronic device, comprising:

[0018] one or more processors;

[0019] a storage device for storing one or more programs,

[0020] When the one or more programs are executed by the one or more processors, the one or more processors implement the path planning method as described in any one of the embodiments of the present invention.

[0021] In a fourth aspect, an embodiment of the present invention further provides a storage medium comprising computer-executable instructions, which, when executed by a computer processor, are used to execute the path planning method as described in any one of the embodiments of the present invention.

[0022] In a fifth aspect, an embodiment of the present invention further provides a computer program product, comprising a computer program, characterized in that when the computer program is executed by a processor, the computer program implements the path planning method as described in any one of the embodiments of the present invention.

[0023] The technical solution of the disclosed embodiment determines at least one driving route based on the starting address and destination address of a target vehicle. Then, for the at least one driving route, the driving route is divided into at least one sub-route based on the driving mode and corresponding usage frequency employed on each road segment. Then, a sub-driving evaluation attribute of the sub-route is determined based on the driving mode of the sub-route, the first distance of the sub-route, and a sub-driving evaluation attribute determination function. Furthermore, a driving evaluation attribute corresponding to the driving route is determined based on the sub-driving evaluation attribute corresponding to the at least one sub-route. Finally, a target driving route for the target vehicle is determined based on the driving evaluation attribute corresponding to the at least one driving route, so that the target vehicle travels according to the target driving route. This solves the problem of low safety when using an in-vehicle navigation system to quickly plan a driving route with optimal distance and time, but fails to fully consider complex road conditions and driving environments. It also solves the problem of low comfort and driving efficiency during the entire driving process. The embodiment of the present invention determines the target driving route based on the driving mode and corresponding usage frequency employed on each road segment, ensuring the target user's experience and satisfaction with the automatic assisted navigation driving mode, thereby improving driving efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings introduced here only illustrate some of the embodiments to be described by the present invention, and are not exhaustive. A person skilled in the art can derive other drawings based on these drawings without inventive effort.

[0025] Figure 1 is a flow chart of a path planning method provided by an embodiment of the present disclosure;

[0026] Figure 2 is a schematic diagram of a path planning method provided by an embodiment of the present disclosure;

[0027] Figure 3 is a schematic diagram of a takeover strategy prompt provided by an embodiment of the present disclosure;

[0028] Figure 4 1 is a schematic structural diagram of a path planning device provided by an embodiment of the present invention;

[0029] Figure 5 It is a structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0030] The present invention will be further described in detail below with reference to the accompanying drawings and examples. It will be understood that the specific embodiments described herein are intended only to illustrate the present invention and are not intended to limit the present invention. It should also be noted that, for ease of description, the accompanying drawings only illustrate portions relevant to the present invention, not all structures.

[0031] Before introducing the technical solutions provided by the embodiments of the present disclosure, an example application scenario may be first described.

[0032] It should be noted that the automatic assisted navigation driving mode is an advanced driving assistance function designed to help the target vehicle achieve automatic assisted navigation driving on highways or urban expressways. The automatic assisted navigation driving mode uses high-precision maps, sensor fusion, such as cameras, radars, and ultrasonic sensors, as well as related algorithms, to enable the target vehicle to automatically complete operations such as lane changing, overtaking, and entering and exiting ramps according to the navigation route, thereby reducing the driver's burden and improving driving convenience and safety. The manual takeover driving mode refers to an operating mode in which the target vehicle is in the automatic assisted navigation driving state and when the system detects that the driver, i.e., the target user, needs to intervene or the target user actively intervenes, the control of the target vehicle is transferred from the automatic assisted navigation driving mode to the target user. The manual takeover driving mode is an important design to ensure safety in autonomous driving technology, ensuring that the target user can take over the target vehicle in a timely manner in the event of insufficient system capabilities or emergencies. The technical solution provided in the embodiments of the present disclosure can be applied to scenarios where path planning is performed for vehicles equipped with automatic assisted navigation driving. Based on the technical solution of the embodiment of the present disclosure, the target driving route is determined according to the driving mode adopted on each road section and the corresponding frequency of use, ensuring the target user's experience and satisfaction with the automatic assisted navigation driving mode, thereby achieving the effect of improving driving efficiency.

[0033] Example 1

[0034] Figure 1 This is a flow chart of a path planning method provided by an embodiment of the present disclosure. The embodiment of the present disclosure is applicable to the situation where path planning is performed on a vehicle equipped with automatic assisted navigation driving. The method can be executed by a path planning device, which can be implemented in the form of software and / or hardware. The hardware can be a mobile electronic device that can execute the path planning method provided by this technical solution.

[0035] like Figure 1 As shown, the method includes:

[0036] S110: Determine at least one driving route based on the starting address and the target address of the target vehicle.

[0037] The target vehicle refers to the vehicle for which route planning is required. When determining the route, the system considers characteristics such as the target vehicle's type, size, and load capacity to ensure the planned route meets the target vehicle's actual driving capabilities. The starting address refers to the target vehicle's current location or upcoming departure location. The target address refers to the target vehicle's planned destination. During the route determination process, the system may convert the starting and target addresses into geographic coordinates to facilitate route calculation.

[0038] It should be noted that to determine at least one driving route, the system collects map data, including road networks, traffic regulations, speed limit information, and real-time traffic conditions. The system then preprocesses the map data, such as constructing road topology and calculating road distances and estimated travel times. Furthermore, based on the selected route planning algorithm and the starting and destination addresses, the system searches the map data for at least one optimal or feasible driving route.

[0039] Specifically, the system determines at least one driving route from the starting address and the target address of the target vehicle according to the input starting address and the target address, based on the collected map data and the selected path planning algorithm.

[0040] S120 : For at least one driving route, divide the driving route into at least one sub-route based on the driving mode adopted on each road section of the driving route and the corresponding usage frequency.

[0041] Among them, the driving mode includes automatic assisted navigation driving mode or manual takeover driving mode.

[0042] It should be noted that the corresponding usage frequency refers to the proportion of the number of times the automatic assisted navigation driving mode or manual takeover driving mode was adopted on each road section to the total number of times it was driven. Based on the historical driving records of vehicles on each road section within a preset time, the proportion of the number of times the automatic assisted navigation driving mode or manual takeover driving mode was adopted on each road section to the total number of times it was driven can be determined. For example, if a historical vehicle drove on a certain road section a total of 10 times within a preset time, and the automatic assisted navigation driving mode was used on that road section 8 times, then the usage frequency of the automatic assisted navigation driving mode on that road section is 80%.

[0043] It's also important to note that within a driving route, a sub-route refers to a collection of continuous road segments divided according to driving mode and corresponding frequency of use. A sub-route consists of one or more continuous, geographically connected road segments. Within each sub-route, the same driving mode is used, either exclusively in Autopilot or Manual Takeover.

[0044] Optionally, for each road section, a first road section and a second road section are determined based on the driving mode adopted on the road section, the corresponding usage frequency and the frequency threshold; and at least one sub-path is determined based on the first road section and the second road section.

[0045] The driving mode corresponding to the first road section is the automatic assisted navigation driving mode, and the driving mode corresponding to the second road section is the manual takeover driving mode. The frequency threshold refers to the critical frequency value used to divide the first road section and the second road section.

[0046] It should be noted that each road segment is analyzed sequentially, starting from the starting address and ending at the target address. For each road segment, if the frequency of use of the automatic assisted navigation driving mode on the road segment exceeds the frequency threshold, the road segment is considered to be primarily used in the automatic assisted navigation driving mode and is determined to be the first road segment. If the frequency of use of the manual takeover driving mode on the road segment exceeds the frequency threshold, the road segment is considered to be primarily used in the manual takeover driving mode and is determined to be the second road segment.

[0047] It should also be noted that a subpath consists of consecutive sections of the same driving mode. That is, the first section of the road continuously in Autopilot mode is combined into one subpath, and the second section of the road continuously in Manual Takeover mode is combined into another subpath. Within a subpath, the frequency of use of either Autopilot or Manual Takeover exceeds a frequency threshold. Subpath boundaries are demarcated when the driving mode type changes.

[0048] For example, assume a driving route includes sections A, B, C, D, and E. The usage frequency of the automatic assisted navigation driving mode on sections A and B is 80% and 75% respectively, exceeding the threshold of 60%. Therefore, A and B are the first sections and are merged into sub-route 1. The usage frequency of both driving modes on section C is 50%, which does not exceed the threshold. According to the default rule, it is classified as manual takeover driving mode and is the second section, which is separately divided into sub-route 2. The usage frequency of the manual takeover driving mode on sections D and E is 85% and 90% respectively, exceeding the threshold of 60%. Therefore, D and E are the second sections and are merged into sub-route 3.

[0049] In this embodiment, after determining the second road section, road information of the second road section is obtained; for at least one second road section, the second road section is divided into at least one sub-second road section based on the road information of the second road section; and at least one sub-path is determined based on the at least one sub-second road section.

[0050] The road information includes road type information, road route information and road condition information.

[0051] It should be noted that road type information includes at least first road type information and second road type information. The first road type information includes at least expressways. Expressways typically have higher design speeds, fewer intersections, and higher traffic capacity, making them suitable for the target vehicle to navigate in auto-assisted navigation mode. The second road type information includes at least roundabouts. Roundabouts are a special type of road intersection that the target vehicle must navigate according to certain rules, requiring high driver skill and attention, and are therefore suitable for the target vehicle to navigate in manual mode. Road route information includes at least first road route information and second road route information. The first road route information includes at least the existence of a road route. The existence of a road route indicates that the road section has a clear road direction and connections, allowing the target vehicle to travel along the established route and is suitable for the target vehicle to navigate in auto-assisted navigation mode. The second road route information includes at least the absence of a road route. The absence of a road route may refer to a road section that is temporarily closed, under construction, or unopened, making it impassable for the target vehicle or requiring a detour, making it suitable for the target vehicle to navigate in manual mode. Road condition information includes at least first road condition information and second road condition information. The first road condition information includes at least unobstructed roads. An unobstructed road means that the traffic conditions on that road are good, the target vehicle can travel smoothly, and there is no congestion or construction. This makes it suitable for the target vehicle to drive in automatic assisted navigation mode. The second road condition information includes at least road congestion and road construction. Road congestion means that vehicles are moving slowly or stagnant on that road. Road construction means that the road is under repair or renovation. Road congestion and road construction may affect the target vehicle's passage, making it suitable for the target vehicle to drive in manual takeover mode.

[0052] It should also be noted that the sub-second road segments refer to the multiple sub-segments into which the second road segment is divided based on a comprehensive consideration of road type information, road route information, and road condition information. Each sub-second road segment has consistent road type information, road route information, and road condition information. If adjacent sub-second road segments have the same road type information, road route information, and road condition information, they can be merged into a single sub-path.

[0053] Optionally, for at least one second road section, if the road type information corresponding to at least one sub-second road section in the second road section is the first road type, the road route information is the first road route, and the road condition information is the first road condition, the driving mode corresponding to the sub-second road section is determined to be the automatic assisted navigation driving mode; if not, the driving mode corresponding to the sub-second road section is determined to be the manual takeover driving mode; based on the driving mode of the sub-second road section, at least one switching position corresponding to when the driving mode switches between the automatic assisted navigation driving mode and the manual takeover driving mode is determined; based on the at least one switching position, the second road section is divided into at least one sub-second road section.

[0054] It should be noted that if a sub-second road segment satisfies at least one of the following conditions: the corresponding road type information is the second road type, the road route information is the second road route, or the road condition information is the second road condition, then the driving mode for that sub-second road segment is determined to be the manual takeover driving mode. The switching position refers to the point where the driving mode switches from the automatic assisted navigation driving mode to the manual takeover driving mode, or vice versa. The second road segment is divided into multiple new sub-second road segments based on the driving mode switching position, and each new sub-second road segment has a consistent driving mode.

[0055] Exemplarily, assume that there is a second road section, which includes the following sub-second road sections. Sub-second road section one is an expressway, with a clear route and smooth traffic, and the driving mode corresponding to sub-second road section one is the automatic assisted navigation driving mode. Sub-second road section two is a roundabout, with a clear route, but due to heavy traffic, there is partial congestion, and the driving mode corresponding to sub-second road section two is the manual takeover driving mode. Sub-second road section three is an expressway, with no clear route and smooth traffic, and the driving mode corresponding to sub-second road section three is the manual takeover driving mode. A switching position is identified between sub-second road section one and sub-second road section two. The original second road section is divided into two new sub-second road sections, one is the automatic assisted navigation driving mode, corresponding to sub-second road section one, and the other is the manual takeover driving mode, including sub-second road section two and sub-second road section three.

[0056] Specifically, for each driving route, the driving mode and corresponding usage frequency of each road segment are statistically calculated based on the historical vehicle driving records on each road segment within a preset time period. The driving route is then divided into at least one sub-route based on the driving mode and corresponding usage frequency of each road segment.

[0057] S130 : Determine the sub-travel evaluation attribute of the sub-path according to the driving mode of the sub-path, the first distance of the sub-path, and the sub-travel evaluation attribute determination function.

[0058] The first distance of a sub-path refers to the physical length of the sub-path, typically measured in kilometers or miles. The sub-travel assessment attribute is a comprehensive score that reflects the driving quality or convenience of the sub-path. The sub-travel assessment attribute can be determined based on the sub-path's driving mode, the sub-path's first distance, and a sub-travel assessment attribute determination function. The sub-travel assessment attribute determination function is used to calculate the sub-travel assessment attribute of a sub-path, and its input parameters are at least the driving mode and the first distance.

[0059] Specifically, for each driving path, after determining each sub-path, for each sub-path, a function can be determined based on the driving mode of each sub-path, the first distance of each sub-path, and the sub-driving evaluation attribute to determine the sub-driving evaluation attribute of each sub-path.

[0060] For example, let's define the sub-driving evaluation attribute as driving-score, which is determined by the driving mode and the first distance. A weight is used to adjust the influence of the driving mode and the first distance on the sub-driving evaluation attribute. The function for determining the sub-driving evaluation attribute is:

[0061] driving-score=(mode_score*weight_mode)+(distence_score*weight_distence);

[0062] Among them, mode_score refers to the evaluation attribute of the automatic assisted navigation driving mode or the manual takeover driving mode; weight_mode Refers to the weight of the driving mode; distence_score Refers to the evaluation attribute of the first distance; weight_distence Refers to the weight of the first distance. Assume that the evaluation attribute of the automatic assisted navigation driving mode is 8, and the evaluation attribute of the manual takeover driving mode is 5. The automatic assisted navigation driving mode is more convenient than the manual takeover driving mode, so it is given a higher evaluation attribute. Suppose the evaluation attribute of the first distance decreases linearly as the first distance increases, from 10 points at 0 kilometers to 0 points at 50 kilometers. The evaluation attribute of the first distance is:

[0063]

[0064] Where distance_km is the first distance. Suppose the weight of driving mode is 0.6 and the weight of first distance is 0.4.

[0065] Assume there is a sub-path whose driving mode is automatic assisted navigation driving mode and whose length is 10 kilometers. driving-score=(8*0.6)+(8*0.4)=8.

[0066] S140: Determine a driving evaluation attribute corresponding to the driving path based on the sub-driving evaluation attribute corresponding to at least one sub-path.

[0067] The driving evaluation attribute is the sum of the sub-driving evaluation attributes of all sub-paths corresponding to the driving path.

[0068] Specifically, a function is determined based on the driving mode of each sub-path, the first distance of each sub-path, and the sub-driving evaluation attribute. After determining the sub-driving evaluation attribute of each sub-path, the sub-driving evaluation attributes of all sub-paths corresponding to the driving path are added together to obtain the driving evaluation attribute corresponding to the driving path.

[0069] S150: Determine a target driving path for the target vehicle based on the driving evaluation attribute corresponding to the at least one driving path, so that the target vehicle drives according to the target driving path.

[0070] The target driving path refers to the driving path with the highest driving evaluation attribute. After determining the target driving path of the target vehicle, the target vehicle is caused to drive according to the target driving path.

[0071] Optional, see Figure 2 When the driving mode corresponding to the target driving path of the target vehicle is single mode, the navigation mileage information of the target driving path is displayed to the target user; when the driving mode corresponding to the target driving path is non-single mode, the navigation mileage information, the number of manual takeovers and the manual takeover distance are displayed to the target user.

[0072] The navigation mileage information includes at least remaining mileage information, traveled mileage information, mileage and time association information, mileage and road condition association information, and mileage and points of interest association information.

[0073] It should be noted that "single mode" means that the driving mode of all sub-routes corresponding to the target driving path is the automatic assisted navigation driving mode, or the driving mode of all sub-routes corresponding to the target driving path is the manual takeover driving mode. "Non-single mode" means that the driving mode of all sub-routes corresponding to the target driving path includes both the automatic assisted navigation driving mode and the manual takeover driving mode.

[0074] It should be noted that in single mode, remaining mileage information refers to the distance remaining from the current location to the destination. In single mode, due to the consistent driving pattern, remaining mileage information can more accurately reflect the distance the user still needs to travel. Mileage traveled information refers to the distance already traveled from the starting address to the current location. Mileage traveled information helps users understand their driving progress. Mileage-to-time information displays the estimated time remaining to travel or the time taken to travel the distance already traveled. In single mode, due to the stable driving pattern, time predictions may be more accurate. Mileage-to-road condition information provides mileage-related road condition information based on current or predicted road conditions, such as congestion or smooth traffic. In single mode, the impact of road conditions on travel time may be more consistent. Mileage-to-points of interest information indicates mileage-related points of interest, such as gas stations, restaurants, and attractions, along the route, allowing users to choose to stop or detour as needed.

[0075] It should also be noted that in non-single mode, remaining range information also refers to the distance remaining from the current location to the destination, but this information takes into account differences in driving efficiency under different driving modes. Mileage traveled refers to the distance traveled from the starting address to the current location, also taking into account driving mode variations. Range-time information displays the estimated time required to reach the remaining range, but this time estimate may be more complex because it takes into account driving speed variations under different driving modes. Range-road condition information provides road condition information related to range, taking into account current or projected road conditions. In non-single mode, road conditions may affect different driving modes differently. Range-points of interest information indicates points of interest associated with range along the route, but users may need to adjust their plans for stops or detours based on changes in driving mode. Number of manual overrides refers to the number of times the user switched from Navigate on Autopilot to manual override along the route. The number of manual overrides helps users understand how often manual intervention was required during driving. Manual override distance refers to the total distance along the route for which the user required manual override. The manual takeover distance can help target users assess the burden and difficulty of manual driving, and plan corresponding breaks or adjust driving strategies.

[0076] In this embodiment, see Figure 3 When the driving mode corresponding to the target driving path is not a single mode, before the driving mode is switched from the automatic assisted navigation driving mode to the manual takeover driving mode, a takeover prompt message is sent to the target user based on the target time threshold or the target distance threshold.

[0077] Among them, the takeover prompt information is used to represent the prompt information for the target user when the automatic assisted navigation driving mode is changed to the manual takeover driving mode.

[0078] It should be noted that the target duration threshold refers to a time limit set by the system when the driving mode is about to switch from Autopilot to Manual Takeover on the target driving route. This time limit is used to determine the time before the switchover that a takeover prompt is sent to the target user. The target distance threshold refers to a distance limit set by the system when the driving mode is about to switch from Autopilot to Manual Takeover on the target driving route. This distance limit is used to determine the distance from the switchover point that a takeover prompt is sent to the target user.

[0079] Optionally, the average speed of the target vehicle in the previous automatic assisted navigation driving mode is obtained; when the average speed meets a first preset speed range, a first distance threshold is determined based on the first preset speed range and a first duration threshold corresponding to the first preset speed range; a target duration threshold is determined based on the first duration threshold, and a target distance threshold is determined based on the first distance threshold; when the average speed meets a second preset speed range, a second distance threshold is determined based on the second preset speed range and a second duration threshold corresponding to the second preset speed range; a target duration threshold is determined based on the second duration threshold, and a target distance threshold is determined based on the second distance threshold. When the average speed meets a third preset speed range, a third distance threshold is determined based on the third preset speed range and a third duration threshold corresponding to the third preset speed range; a target duration threshold is determined based on the third duration threshold, and a target distance threshold is determined based on the third distance threshold. A first duration before switching to manual takeover driving mode is determined in real time based on the target vehicle's real-time speed and remaining distance; when the first duration meets the target duration threshold or the remaining distance meets the target distance threshold, a takeover prompt message is sent to the target user.

[0080] The average speed refers to the ratio of the total distance traveled by the target vehicle in the previous Autopilot driving mode to the total time. The average speed reflects the target vehicle's overall driving speed in Autopilot driving mode. The first preset speed range refers to a specific speed interval used to determine whether the target vehicle's average speed falls within this range. For example, the first preset speed range may be greater than 70 km / h. The first duration threshold refers to a time limit set by the system when the target vehicle's average speed meets the first preset speed range. The first duration threshold determines the time before switching to manual takeover mode to issue a takeover prompt message to the target user. For example, when the first preset speed range is greater than 70 km / h, the first duration threshold corresponding to the first preset speed range may be 2 minutes. The first distance threshold refers to a distance limit calculated by the system based on the first preset speed range and the first duration threshold when the target vehicle's average speed meets the first preset speed range. This distance limit determines the distance from the switching point before issuing a takeover prompt message to the target user. For example, when the first preset speed range is greater than 70 km / h, the first distance threshold may be average speed times 2 minutes. When the average speed satisfies the first preset speed range, the first duration threshold is determined as the target duration threshold, and the first distance threshold is determined as the target distance threshold.

[0081] It should be noted that the second preset speed range refers to another specific speed interval, different from the first preset speed range, and is used to determine whether the vehicle's average speed in the previous Autopilot driving mode falls within this range. For example, the second preset speed range may be greater than 40 and less than or equal to 70 km / h. The second duration threshold refers to a time limit set by the system when the target vehicle's average speed in the previous Autopilot driving mode meets the second preset speed range. For example, when the second preset speed range is greater than 40 and less than or equal to 70 km / h, the second duration threshold corresponding to the second preset speed range may be 1.5 minutes. The second distance threshold refers to a distance limit calculated by the system based on the second preset speed range and the second duration threshold when the target vehicle's average speed in the previous Autopilot driving mode meets the second preset speed range. For example, when the second preset speed range is greater than 40 and less than or equal to 70 km / h, the second distance threshold may be average speed multiplied by 1.5 minutes. When the average speed meets the second preset speed range, the second duration threshold is determined as the target duration threshold, and the second distance threshold is determined as the target distance threshold. The third preset speed range is another specific speed interval, different from the first two preset speed ranges, used to determine whether the target vehicle's average speed in the previous Autopilot driving mode falls within this range. For example, the third preset speed range may be 40 km / h or less. The third duration threshold is a time limit set by the system when the target vehicle's average speed in the previous Autopilot driving mode meets the third preset speed range. For example, when the third preset speed range is 40 km / h or less, the third duration threshold corresponding to the third preset speed range may be 1 minute. The third distance threshold is a distance limit calculated by the system based on the third preset speed range and the third duration threshold when the target vehicle's average speed in the previous Autopilot driving mode meets the third preset speed range. For example, when the third preset speed range is 40 km / h or less, the third distance threshold may be average speed times 1 minute. When the average speed meets the third preset speed range, the third duration threshold is determined as the target duration threshold, and the third distance threshold is determined as the target distance threshold.

[0082] It should also be noted that the real-time speed refers to the speed of the target vehicle during its current driving process. The remaining distance refers to the remaining driving distance of the target vehicle when it is driving in the current sub-section in the automatic assisted navigation driving mode. The first duration refers to the time required for the system to switch from the current position to the manual takeover driving mode, calculated based on the real-time speed and remaining distance of the target vehicle. The calculation of the first duration can be based on the relationship between speed and time, such as dividing the remaining distance by the real-time speed. The first duration can also be determined based on the remaining distance and real-time speed, taking into account factors such as road conditions and traffic regulations. When the first duration meets the target duration threshold or the remaining distance meets the target distance threshold, a takeover prompt message is sent to the target user to remind the target user to prepare to take over the target vehicle.

[0083] Specifically, after determining the driving evaluation attributes corresponding to each driving path, the target driving path of the target vehicle is determined according to the order of the driving evaluation attributes corresponding to each driving path, and the target driving path is displayed to the target user so that the target vehicle drives according to the target driving path.

[0084] The technical solution of the disclosed embodiment determines at least one driving route based on the starting address and destination address of a target vehicle. Then, for the at least one driving route, the driving route is divided into at least one sub-route based on the driving mode and corresponding usage frequency employed on each road segment. Then, a sub-driving evaluation attribute of the sub-route is determined based on the driving mode of the sub-route, the first distance of the sub-route, and a sub-driving evaluation attribute determination function. Furthermore, a driving evaluation attribute corresponding to the driving route is determined based on the sub-driving evaluation attribute corresponding to the at least one sub-route. Finally, a target driving route for the target vehicle is determined based on the driving evaluation attribute corresponding to the at least one driving route, so that the target vehicle travels according to the target driving route. This solves the problem of low safety when using an in-vehicle navigation system to quickly plan a driving route with optimal distance and time, but fails to fully consider complex road conditions and driving environments. It also solves the problem of low comfort and driving efficiency during the entire driving process. The embodiment of the present invention determines the target driving route based on the driving mode and corresponding usage frequency employed on each road segment, ensuring the target user's experience and satisfaction with the automatic assisted navigation driving mode, thereby improving driving efficiency.

[0085] Example 2

[0086] As an optional embodiment of the above embodiment, this technical solution is introduced below using an example.

[0087] It should be noted that some autonomous vehicles are equipped with a navigation assistance function, which can realize point-to-point driving functions. Moreover, the navigation assistance function at this stage is divided into L2.9 and L3. For L2.9, the first responsible party is the driver. The L2.9 navigation assistance function is generally regarded as an advanced version of the L2 autonomous driving. The L2.9 navigation assistance function integrates more sensors and algorithms, and can provide a higher level of driving assistance, such as adaptive cruise control, lane keeping, automatic lane changing, etc.; while for L3, the first responsible party is the car manufacturer. The L3 autonomous driving function allows the vehicle to drive completely autonomously under specific conditions, such as highways and traffic congestion. The driver does not need to continuously monitor the status of the target vehicle, but needs to take over control in time when the system requests it. The technical solution of the embodiment of the present disclosure is applicable to both L2.9 and L3. See Figure 2 ,When the driving mode corresponding to the target driving path is non-single mode, not only the navigation mileage information, the number of manual takeovers, and the manual takeover distance are displayed to the target user, but also the takeover path prompt is displayed to the target user.

[0088] Takeover path prompts refer to information displayed to the target driver via the navigation interface using specific methods, such as color, icons, and text, regarding the takeover path when the system predicts a transition to manual takeover is imminent while the target vehicle is operating in Autopilot mode. These prompts are designed to help the target driver quickly identify the takeover location, understand the route after takeover, and prepare accordingly. Autopilot paths can be indicated by a single color, such as green, to clearly indicate that the driver is currently in autonomous driving mode and no manual control is required. For manual takeover paths, sections of the path where manual takeover is about to occur can be highlighted in another color, such as red or orange, to draw the driver's attention. This color distinction helps the driver quickly identify the takeover point and prepare in advance. For takeover transition zones, the transition between Autopilot and manual takeover modes can be indicated using gradient colors or specific patterns to alert the target driver to the mode switch. A prominent takeover icon, such as a steering wheel icon, can be placed at the starting point or key locations of the takeover path to visually indicate the need for manual takeover. Text instructions can be added near the takeover path or elsewhere on the navigation interface, such as "Manual takeover ahead, XX meters," or "Manual takeover section," to further clarify the takeover information. Takeover path prompts can also use flashing effects and sound prompts to enhance visual impact and ensure timely identification by the target personnel.

[0089] See also Figure 3When a target user is driving in Navigate on Autopilot mode, the system can use sensors to monitor the target user's status. This primarily involves detecting the target user's presence and ability to take control of the target vehicle. Target user presence detection verifies that the target user is in the driver's seat and is ready to take control of the target vehicle at any time. Seatbelt detection can be achieved using seatbelt sensors within the target vehicle. When the target user fastens their seatbelt, the sensor sends a signal to the system, indicating that the target user is in position. If the system detects an unfastened seatbelt, it may use audible, visual, or on-screen prompts to remind the target user to fasten their seatbelt and recommend switching to manual takeover until the target user fastens their seatbelt. Seat occupancy sensors, typically installed under the target user's seat, detect weight on the seat to determine if the target user is seated. If the seat occupancy sensor detects the target user is not seated, the system recommends switching to manual takeover to ensure the safety of the target vehicle. The system may also issue a prompt to remind the target user to return to the driver's seat. Ability to take control is designed to assess the target user's status and ensure they can quickly and accurately take control of the target vehicle when needed. Execution detection is typically performed by analyzing the target person's fatigue state or level of distraction. Fatigue detection is typically achieved by analyzing physiological characteristics such as facial expressions, blinking frequency, and head posture. The system may use a camera to capture facial images of the target person and analyze these characteristics using image processing algorithms. If the system detects signs of fatigue in the target person, it may use sound, light, or screen prompts to remind the target person to rest and recommend switching to manual driving mode. Distraction detection can also be achieved by analyzing the target person's facial expressions and gaze direction. The system may use a camera to capture the driver's gaze and determine whether the driver is focused on the road ahead. If the system detects that the target person is distracted, such as looking down at a phone for a long time or talking to someone else, it may prompt the driver to focus and recommend switching to manual driving mode.

[0090] See also Figure 3, the system can design an operational domain (ODD), which defines the specific conditions and environments within which the autonomous driving system is designed to operate safely. The ODD covers various factors that enable the normal operation of the autonomous driving system, including but not limited to weather conditions. ODD events refer to events that occur within these design operational domains and may affect the normal operation of the autonomous driving system. ODD events are mainly divided into planned events and unplanned events. Unplanned events refer to those events that are not pre-considered or difficult to predict within the design operational domain and usually pose a challenge to the normal operation of the autonomous driving system. Extreme weather is a major representative of unplanned events, including but not limited to heavy rain, heavy snow, heavy fog, strong winds, etc. Extreme weather conditions can significantly affect the performance of cameras, radars, and lidars, resulting in a decrease in perception capabilities and an increased risk of misjudgment and missed judgments. In extreme weather conditions, the autonomous driving system may automatically exit due to inability to ensure safety, downgrade to a lower driving mode, or recommend switching to manual takeover driving mode. Specifically, sensors and meteorological monitoring equipment on the target vehicle monitor weather conditions in real time, setting thresholds for weather conditions such as rainfall, snowfall, and wind speed. When actual weather conditions exceed these thresholds, they are determined to be unplanned events. Based on the determination, the autonomous driving system takes appropriate measures, such as downgrading to a lower driving mode or recommending a switch to manual takeover. Planned events are those that are pre-considered and planned within the design operating domain and are usually related to road infrastructure and traffic regulations. For example, driving modes are determined based on road type information, road route information, and road condition information.

[0091] The technical solution of the embodiment of the present invention, when the driving mode is not single, displays the takeover path prompts through the navigation interface, including color differentiation, icon identification, text description, flashing effects, sound prompts, etc., to help the target person prepare in advance, help reduce the target person's operational errors during the takeover process, and improve driving safety. During driving, sensors are used to detect the target person's on-site status and execution ability to ensure that the driver can quickly and accurately take over control of the target vehicle when needed, further ensuring driving safety. In addition, for unplanned events, the system can monitor and determine in real time and take corresponding measures to ensure the safety and reliability of the automatic driving system in complex environments.

[0092] Example 3

[0093] Figure 4 is a schematic structural diagram of a path planning device provided by an embodiment of the present disclosure, such as Figure 4As shown, the apparatus includes: a driving path determination module 210 , a sub-path division module 220 , a sub-driving evaluation attribute determination module 230 , a driving evaluation attribute determination module 240 and a target driving path determination module 250 .

[0094] A driving path determination module is used to determine at least one driving path based on the starting address and target address of the target vehicle; a sub-path division module is used to divide the at least one driving path into at least one sub-path based on the driving mode adopted by the driving path on each road section and the corresponding usage frequency; wherein the driving mode includes an automatic assisted navigation driving mode or a manual takeover driving mode; a sub-driving evaluation attribute determination module is used to determine the sub-driving evaluation attribute of the sub-path based on the driving mode of the sub-path, the first distance of the sub-path and the sub-driving evaluation attribute determination function; a driving evaluation attribute determination module is used to determine the driving evaluation attribute corresponding to the driving path based on the sub-driving evaluation attribute corresponding to the at least one sub-path; a target driving path determination module is used to determine the target driving path of the target vehicle based on the driving evaluation attribute corresponding to the at least one driving path, so that the target vehicle travels according to the target driving path.

[0095] The technical solution of the disclosed embodiment determines at least one driving route based on the starting address and destination address of a target vehicle. Then, for the at least one driving route, the driving route is divided into at least one sub-route based on the driving mode and corresponding usage frequency employed on each road segment. Then, a sub-driving evaluation attribute of the sub-route is determined based on the driving mode of the sub-route, the first distance of the sub-route, and a sub-driving evaluation attribute determination function. Furthermore, a driving evaluation attribute corresponding to the driving route is determined based on the sub-driving evaluation attribute corresponding to the at least one sub-route. Finally, a target driving route for the target vehicle is determined based on the driving evaluation attribute corresponding to the at least one driving route, so that the target vehicle travels according to the target driving route. This solves the problem of low safety when using an in-vehicle navigation system to quickly plan a driving route with optimal distance and time, but fails to fully consider complex road conditions and driving environments. It also solves the problem of low comfort and driving efficiency during the entire driving process. The embodiment of the present invention determines the target driving route based on the driving mode and corresponding usage frequency employed on each road segment, ensuring the target user's experience and satisfaction with the automatic assisted navigation driving mode, thereby improving driving efficiency.

[0096] Based on the above technical solutions, the sub-path division module 220 includes: a road segment determination sub-module and a sub-path determination sub-module.

[0097] a road segment determination submodule, configured to determine, for each road segment, a first road segment and a second road segment based on the driving mode used on the road segment, the corresponding usage frequency, and the frequency threshold; wherein the driving mode corresponding to the first road segment is the automatic assisted navigation driving mode, and the driving mode corresponding to the second road segment is the manual takeover driving mode;

[0098] The sub-path determination sub-module is configured to determine the at least one sub-path according to the first road section and the second road section.

[0099] On the basis of the above technical solutions, the device further includes: a road information acquisition submodule, a sub-second road section division submodule, and a sub-path determination submodule.

[0100] A road information acquisition submodule, configured to acquire road information of the second road section; wherein the road information includes road type information, road route information, and road condition information;

[0101] a sub-second road segment division submodule, configured to divide at least one second road segment into at least one sub-second road segment according to road information of the second road segment;

[0102] The sub-path determining sub-module is configured to determine at least one sub-path according to the at least one sub-second road segment.

[0103] On the basis of the above technical solutions, the sub-second road section division submodule includes: an automatic assisted navigation driving mode determination unit, a manual takeover driving mode determination unit, a switching position determination unit and a sub-second road section division unit.

[0104] an automatic assisted navigation driving mode determining unit, configured to, for at least one second road segment, determine that the driving mode corresponding to at least one sub-second road segment in the second road segment is the automatic assisted navigation driving mode if the road type information corresponding to at least one sub-second road segment in the second road segment is the first road type, the road route information is the first road route, and the road condition information is the first road condition;

[0105] a manual takeover driving mode determining unit, configured to, if no, determine that the driving mode corresponding to the sub-second road section is the manual takeover driving mode;

[0106] a switching position determining unit, configured to determine, based on the driving mode of the second sub-road section, at least one switching position corresponding to the switching between the automatic assisted navigation driving mode and the manual takeover driving mode;

[0107] The sub-second section dividing unit is configured to divide the second section into at least one sub-second section according to the at least one switching position.

[0108] On the basis of the above technical solutions, the device further includes: a single mode display module and a non-single mode display module.

[0109] a single mode display module, configured to display navigation mileage information of the target driving route to a target user when the driving mode corresponding to the target driving route of the target vehicle is the single mode; wherein the navigation mileage information includes at least remaining mileage information, traveled mileage information, mileage-time association information, mileage-road condition association information, and mileage-point of interest association information;

[0110] The non-single mode display module is used to display the navigation mileage information, the number of manual takeovers, and the manual takeover distance to the target user when the driving mode corresponding to the target driving path is a non-single mode.

[0111] Based on the above technical solutions, the non-single mode display module also includes a takeover prompt information issuing sub-module, which is used to issue a takeover prompt information to the target user based on the target time threshold or the target distance threshold before the driving mode is switched from the automatic assisted navigation driving mode to the manual takeover driving mode; wherein, the takeover prompt information is used to represent the prompt information to the target user when the automatic assisted navigation driving mode is switched to the manual takeover driving mode.

[0112] Based on the above technical solutions, the takeover prompt information issuing sub-module also includes: an average speed acquisition unit, a first distance threshold determination unit, a first target distance threshold determination unit, a second distance threshold determination unit, a second target distance threshold determination unit, a third distance threshold determination unit, a third target distance threshold determination unit, a judgment switching unit and a takeover prompt information issuing unit.

[0113] an average speed obtaining unit, configured to obtain an average speed of the target vehicle in a previous automatic assisted navigation driving mode;

[0114] a first distance threshold determining unit, configured to determine a first distance threshold according to a first preset speed range and a first time threshold corresponding to the first preset speed range when the average speed satisfies a first preset speed range;

[0115] a first target distance threshold determination unit, configured to determine the target duration threshold according to the first duration threshold, and determine the target distance threshold according to the first distance threshold;

[0116] a second distance threshold determining unit, configured to determine a second distance threshold according to the second preset speed range and a second time threshold corresponding to the second preset speed range when the average speed satisfies a second preset speed range;

[0117] a second target distance threshold determination unit, configured to determine the target duration threshold according to the second duration threshold, and determine the target distance threshold according to the second distance threshold;

[0118] a third distance threshold determining unit, configured to determine a third distance threshold according to the third preset speed range and a third time threshold corresponding to the third preset speed range when the average speed satisfies a third preset speed range;

[0119] a third target distance threshold determination unit, configured to determine the target duration threshold according to the third duration threshold, and determine the target distance threshold according to the third distance threshold;

[0120] a judgment switching unit, configured to determine in real time a first time duration before switching to a manual takeover driving mode based on the real-time speed and remaining distance of the target vehicle;

[0121] The takeover prompt information issuing unit is used to issue a takeover prompt information to the target user when the first duration meets the target duration threshold or the remaining distance meets the target distance threshold.

[0122] The path planning device provided in the embodiments of the present disclosure can execute the path planning method provided in any embodiment of the present disclosure, and has the corresponding functional modules and beneficial effects of the execution method.

[0123] It is worth noting that the various units and modules included in the above-mentioned device are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the protection scope of the embodiments of the present disclosure.

[0124] Example 4

[0125] Figure 5 This is a schematic diagram of the structure of an electronic device provided by an embodiment of the present disclosure. Figure 5 , which shows an electronic device (eg Figure 5 The terminal device in the embodiments of the present disclosure may include, but is not limited to, a mobile terminal such as a mobile phone, a laptop computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), an in-vehicle terminal (such as an in-vehicle navigation terminal), and the like. Figure 5 The electronic device shown is only an example and should not limit the functions and scope of use of the embodiments of the present disclosure.

[0126] like Figure 5As shown, the electronic device 500 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage device 508 into a random access memory (RAM) 503. Various programs and data required for the operation of the electronic device 500 are also stored in the RAM 503. The processing device 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An edit / output (I / O) interface 505 is also connected to the bus 504.

[0127] Typically, the following devices may be connected to the I / O interface 505: an input device 506 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 507 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 508 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 509. The communication device 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 5 The electronic device 500 is shown with various devices, but it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed instead.

[0128] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device 509, or installed from the storage device 508, or installed from the ROM 502. When the computer program is executed by the processing device 501, the above-mentioned functions defined in the method of the embodiment of the present disclosure are performed.

[0129] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0130] The electronic device provided in the embodiment of the present disclosure and the path planning method provided in the above embodiment belong to the same inventive concept. For technical details not fully described in this embodiment, please refer to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0131] Example 5

[0132] An embodiment of the present disclosure provides a computer storage medium having a computer program stored thereon. When the program is executed by a processor, the path planning method provided in the above embodiment is implemented.

[0133] It should be noted that the computer-readable medium mentioned above in the present disclosure may be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, device, or component. In the present disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to wires, optical cables, RF (radio frequency), etc., or any suitable combination thereof.

[0134] In some embodiments, the server can communicate using any currently known or later developed network protocol, such as HTTP (HyperText Transfer Protocol), and can be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or later developed network.

[0135] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0136] The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device:

[0137] Determine at least one driving route based on the starting address and the destination address of the target vehicle;

[0138] For the at least one driving route, dividing the driving route into at least one sub-route based on a driving mode adopted on each road segment of the driving route and a corresponding usage frequency; wherein the driving mode includes an automatic assisted navigation driving mode or a manual takeover driving mode;

[0139] determining a sub-travel evaluation attribute of the sub-path according to the driving mode of the sub-path, the first distance of the sub-path, and a sub-travel evaluation attribute determination function;

[0140] Determining a driving evaluation attribute corresponding to the driving path according to the sub-driving evaluation attribute corresponding to the at least one sub-path;

[0141] A target driving path of the target vehicle is determined according to the driving evaluation attribute corresponding to the at least one driving path, so that the target vehicle drives according to the target driving path.

[0142] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages, or a combination thereof, including, but not limited to, object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on the remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0143] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the module, program segment, or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0144] The units involved in the embodiments described in this disclosure may be implemented in software or hardware, wherein the name of a unit does not necessarily limit the unit itself.

[0145] The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, and without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chip (SOCs), complex programmable logic devices (CPLDs), and the like.

[0146] In the context of the present disclosure, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in conjunction with an instruction execution system, device or equipment. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium can include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0147] The above description is merely a preferred embodiment of the present disclosure and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but also includes other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the above-mentioned disclosed concepts. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions disclosed in this disclosure.

[0148] In addition, although each operation is described in a specific order, this should not be understood as requiring these operations to be performed in the specific order shown or in a sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Similarly, although some specific implementation details have been included in the above discussion, these should not be interpreted as limiting the scope of the present disclosure. Some features described in the context of a separate embodiment can also be implemented in a single embodiment in combination. On the contrary, the various features described in the context of a single embodiment can also be implemented in multiple embodiments individually or in any suitable sub-combination mode.

[0149] Although the subject matter has been described in language specific to structural features and / or methodological logical acts, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are merely example forms of implementing the claims.

Claims

1. A path planning method, characterized in that: include: Determine at least one driving route based on the starting address and the destination address of the target vehicle; For the at least one driving route, dividing the driving route into at least one sub-route based on a driving mode adopted on each road segment of the driving route and a corresponding usage frequency; wherein the driving mode includes an automatic assisted navigation driving mode or a manual takeover driving mode; determining a sub-travel evaluation attribute of the sub-path according to the driving mode of the sub-path, the first distance of the sub-path, and a sub-travel evaluation attribute determination function; Determining a driving evaluation attribute corresponding to the driving path according to the sub-driving evaluation attribute corresponding to the at least one sub-path; A target driving path of the target vehicle is determined according to the driving evaluation attribute corresponding to the at least one driving path, so that the target vehicle drives according to the target driving path.

2. The method according to claim 1, characterized in that The driving path is divided into at least one sub-path according to the driving mode and the corresponding usage frequency adopted on each road section of the driving path, including: For each road segment, determining a first road segment and a second road segment based on the driving mode used on the road segment, the corresponding usage frequency, and the frequency threshold; wherein the driving mode corresponding to the first road segment is the automatic assisted navigation driving mode, and the driving mode corresponding to the second road segment is the manual takeover driving mode; The at least one sub-path is determined according to the first road section and the second road section.

3. The method according to claim 2, characterized in that After determining the second road section, the method further includes: Acquire road information of the second road section; wherein the road information includes road type information, road route information, and road condition information; For at least one second road segment, dividing the second road segment into at least one second sub-road segment according to road information of the second road segment; At least one sub-path is determined according to the at least one sub-second road segment.

4. The method according to claim 3, characterized in that The step of dividing the at least one second road section into at least one second sub-road section according to road information of the second road section includes: For at least one second road segment, if the road type information corresponding to at least one sub-second road segment in the second road segment is the first road type, the road route information is the first road route, and the road condition information is the first road condition, determining that the driving mode corresponding to the sub-second road segment is the automatic assisted navigation driving mode; If not, determining that the driving mode corresponding to the second road section is the manual takeover driving mode; determining, based on the driving mode of the second sub-section, at least one switching position corresponding to when the driving mode switches between an automatic assisted navigation driving mode and a manual takeover driving mode; The second section is divided into at least one second sub-section according to the at least one switching position.

5. The method according to claim 1, wherein After determining the target driving path of the target vehicle, the method further includes: When the driving mode corresponding to the target driving path of the target vehicle is a single mode, the navigation mileage information of the target driving path is displayed to the target user; wherein the navigation mileage information includes at least remaining mileage information, traveled mileage information, mileage and time association information, mileage and road condition association information, and mileage and point of interest association information; When the driving mode corresponding to the target driving path is not a single mode, the navigation mileage information, the number of manual takeovers, and the manual takeover distance are displayed to the target user.

6. The method according to claim 5, characterized in that When the driving mode corresponding to the target driving path is a non-single mode, the method further includes: Before the driving mode is switched from the automatic assisted navigation driving mode to the manual takeover driving mode, a takeover prompt message is sent to the target user based on a target time threshold or a target distance threshold; wherein, the takeover prompt message is used to represent the prompt information to the target user when the automatic assisted navigation driving mode is switched to the manual takeover driving mode.

7. The method according to claim 6, characterized in that The sending of a takeover prompt message to the target user according to the target duration threshold or the target distance threshold includes: Obtaining an average speed of the target vehicle in a previous automatic assisted navigation driving mode; When the average speed satisfies a first preset speed range, determining a first distance threshold according to the first preset speed range and a first time threshold corresponding to the first preset speed range; Determine the target duration threshold according to the first duration threshold, and determine the target distance threshold according to the first distance threshold; Determine in real time the first duration before switching to manual takeover of the driving mode based on the real-time speed and remaining distance of the target vehicle; When the first duration meets the target duration threshold or the remaining distance meets the target distance threshold, a takeover prompt message is sent to the target user.

8. The method according to claim 7, characterized in that The method further comprises: When the average speed satisfies a second preset speed range, determining a second distance threshold according to the second preset speed range and a second time threshold corresponding to the second preset speed range; The target duration threshold is determined according to the second duration threshold, and the target distance threshold is determined according to the second distance threshold.

9. The method according to claim 7, characterized in that The method further comprises: When the average speed satisfies a third preset speed range, determining a third distance threshold according to the third preset speed range and a third time threshold corresponding to the third preset speed range; The target duration threshold is determined according to the third duration threshold, and the target distance threshold is determined according to the third distance threshold.

10. A path planning device, characterized in that: include: A driving route determination module, configured to determine at least one driving route based on a starting address and a destination address of a target vehicle; a sub-path division module, configured to divide the at least one driving path into at least one sub-path based on a driving mode and a corresponding usage frequency adopted on each road segment of the driving path; wherein the driving mode includes an automatic assisted navigation driving mode or a manual takeover driving mode; a sub-travel evaluation attribute determination module, configured to determine the sub-travel evaluation attribute of the sub-path according to the driving mode of the sub-path, the first distance of the sub-path, and a sub-travel evaluation attribute determination function; a driving evaluation attribute determination module, configured to determine a driving evaluation attribute corresponding to the driving path based on the sub-driving evaluation attribute corresponding to the at least one sub-path; The target driving path determination module is used to determine the target driving path of the target vehicle according to the driving evaluation attribute corresponding to the at least one driving path, so that the target vehicle travels according to the target driving path.

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