Method and device for controlling vehicle driving, storage medium and vehicle

Abstract

The invention relates to a method and device for controlling vehicle driving, a storage medium and a vehicle, and the method comprises the steps: determining a to-be-passed target road section of the vehicle according to a predetermined planned path; obtaining experience driving information corresponding to the target road section; the experience driving information is determined according to historical driving information of a specified vehicle on the target road section; determining target driving information according to the experience driving information; and controlling the vehicle to run on the target road section according to the target driving information. According to the technical scheme, the vehicle can have better riding experience when running on the target road section.

Description

Technical Field

[0001] The present disclosure relates to the field of vehicle technology, and in particular to a method, device, storage medium and vehicle for controlling vehicle driving. Background Art

[0002] In the related art, during the driving process of a vehicle, it is usually controlled to travel along the center line of the lane. However, in some cases, traveling along the center line of the lane may cause the vehicle to roll, resulting in safety problems.

[0003] For example, when a vehicle passes through a traffic intersection or a ramp, the shape of the road may change significantly. The driving path planned based on the center line of the lane may cause the vehicle to tilt when it continues to travel along the center line of the lane at the original speed due to the significant change in the shape of the road. Summary of the invention

[0004] In order to overcome the problems existing in the related art, the present disclosure provides a method, device, storage medium and vehicle for controlling vehicle driving.

[0005] According to a first aspect of an embodiment of the present disclosure, there is provided a method for controlling vehicle driving, comprising:

[0006] Determine the target road section that the vehicle is to pass through according to the pre-determined planned path;

[0007] Acquire the experience driving information corresponding to the target road section; the experience driving information is determined according to the historical driving information of the specified vehicle on the target road section;

[0008] determining target driving information according to the empirical driving information;

[0009] The vehicle is controlled to travel on the target road section according to the target driving information.

[0010] Optionally, the experience driving information corresponding to the target road section is obtained in the following manner:

[0011] When the historical driving information corresponding to the target road section of the designated vehicle is obtained, the empirical driving information corresponding to the target road section is determined from a plurality of historical driving information of the designated vehicle on the target road section.

[0012] Optionally, the historical driving information includes a historical driving route; and determining the empirical driving information corresponding to the target road section from a plurality of historical driving information of the designated vehicle on the target road section includes:

[0013] Determine a probability distribution interval of a plurality of historical driving information of a specified vehicle on a target road section according to the historical driving path of the historical driving information;

[0014] The historical driving information of the target probability interval in the probability distribution interval is used as the experience driving information corresponding to the target road section.

[0015] Optionally, the historical driving information includes a historical driving path and a driving speed at each designated trajectory point on the historical driving path;

[0016] Determining the experience driving information corresponding to the target road section from a plurality of historical driving information of the designated vehicle on the target road section includes:

[0017] For multiple historical driving information with the same driving path, determine the probability distribution interval of multiple historical driving information with the same driving path of the specified vehicle on the target road section according to the driving speed of each designated trajectory point on the historical driving path of the historical driving information;

[0018] The historical driving information of the target probability interval in the probability distribution interval is used as the experience driving information corresponding to the target road section.

[0019] Optionally, the experience driving information corresponding to the target road section is obtained in the following manner:

[0020] When the historical driving information of the designated vehicle on the target road section is obtained, the high-precision map is updated according to the historical driving information of the designated vehicle on the target road section;

[0021] According to the updated high-precision map, the empirical driving information corresponding to the target road section is determined.

[0022] Optionally, the experience driving information corresponding to the target road section is obtained in the following manner:

[0023] In the case where the historical driving information corresponding to the target road section of the designated vehicle is not obtained, determining, according to the road information of the target road section, a reference road section whose road similarity with the road information of the target road section is greater than a first preset similarity;

[0024] Obtain historical driving information of a specified vehicle on the reference road section;

[0025] Determine the experience driving information corresponding to the target road section from the historical driving information of the specified vehicle.

[0026] Optionally, the experience driving information corresponding to the target road section is obtained in the following manner:

[0027] In the case where the historical driving information corresponding to the target road section of the designated vehicle is not obtained, determining, based on the road information of the target road section, a reference road section whose road similarity with the road information of the road section is greater than a first preset similarity;

[0028] Get the historical driving information of the specified vehicle on the reference road section;

[0029] Update the high-precision map based on the historical driving information of the specified vehicle on the reference road section;

[0030] According to the updated high-precision map, the empirical driving information corresponding to the target road section is determined.

[0031] Optionally, the experience driving information includes an experience driving path, and the target driving information includes a target driving path; and determining the target driving information according to the experience driving information includes:

[0032] respectively determining the path similarities between a plurality of experience driving paths;

[0033] The target driving path in the target driving information is determined from the experienced driving paths whose path similarity is greater than the second preset similarity.

[0034] Optionally, the experience driving information includes an experience driving path, and the target driving information includes a target driving path; and determining the target driving information according to the experience driving information includes:

[0035] respectively determining whether a plurality of experienced driving paths are in an occupied state, wherein the occupied state indicates that a vehicle other than the vehicle is traveling on the experienced driving path;

[0036] A target driving path in the target driving information is determined from an experience driving path that is not in an occupied state.

[0037] Optionally, the target driving information includes a target driving path and a driving speed of each designated trajectory point on the target driving path;

[0038] The controlling the vehicle to travel on the target road section according to the target travel information comprises:

[0039] According to the driving speed of each designated trajectory point on the target driving path, the vehicle is controlled to travel on the target road section according to the target driving path.

[0040] Optionally, controlling the vehicle to travel on the target road section according to the target driving path according to the driving speed of each designated trajectory point on the target driving path includes:

[0041] For each designated trajectory point, when the vehicle travels to a target position, the driving speed of the vehicle is adjusted so that the vehicle passes through the designated trajectory point at a driving speed corresponding to the designated trajectory point, and the target position is a position at a preset distance from the designated trajectory point in the opposite direction of the vehicle's driving direction.

[0042] According to a second aspect of an embodiment of the present disclosure, there is provided a device for controlling vehicle travel, comprising:

[0043] A first determination module is configured to determine a target road section to be passed by the vehicle according to a predetermined planned path;

[0044] An acquisition module is configured to acquire the experience driving information corresponding to the target road section; the experience driving information is determined according to the historical driving information of the specified vehicle on the target road section;

[0045] A second determination module is configured to determine target driving information according to the empirical driving information;

[0046] The control module is configured to control the vehicle to travel on the target road section according to the target driving information.

[0047] According to a third aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided, on which computer program instructions are stored. When the program instructions are executed by a processor, the steps of the method for controlling vehicle driving provided in the first aspect of the present disclosure are implemented.

[0048] According to the fourth aspect of an embodiment of the present disclosure, a vehicle is provided, comprising: a processor; and a memory for storing processor executable instructions; wherein the processor is configured to implement the steps of the method for controlling vehicle driving provided in the first aspect of the present disclosure when calling the executable instructions stored on the memory.

[0049] The technical solution provided by the embodiments of the present disclosure may include the following beneficial effects: the empirical driving information corresponding to the target section is determined based on the historical driving information of the designated vehicle on the target section, and the historical driving information of the designated vehicle on the target section matches the actual situation of the target section. Therefore, the target driving information is determined based on the empirical driving information, and the vehicle is controlled to travel on the target section according to the target driving information, so that the vehicle has a better riding experience.

[0050] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0052] Figure 1 is a flow chart of a method for controlling vehicle driving according to an exemplary embodiment;

[0053] Figure 2is a block diagram of a device for controlling vehicle driving according to an exemplary embodiment;

[0054] Figure 3 is a block diagram of another device for controlling vehicle driving according to an exemplary embodiment;

[0055] Figure 4 is a block diagram of another device for controlling vehicle driving according to an exemplary embodiment;

[0056] Figure 5 It is a schematic diagram of a functional block diagram of a vehicle according to an exemplary embodiment. DETAILED DESCRIPTION

[0057] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0058] Figure 1 is a flow chart of a method for controlling vehicle driving according to an exemplary embodiment. Figure 1 As shown, the following steps are included.

[0059] In step S11, a target road section to be passed by the vehicle is determined according to a predetermined planned path.

[0060] For example, a vehicle travels from a starting point A to a destination B. By pre-planning the path from A to B as a whole, the pre-planned path includes at least one road section that the vehicle is going to pass through. For example, the planned path is: starting from A, go straight along road M for 2 km, turn right at intersection N to enter road P, go straight along road P for 1 km and arrive at the destination B; in the pre-planned path, the 2 km section on road M, intersection N, and the 1 km section on road P are all sections that the vehicle is going to pass through.

[0061] In step S12, the empirical driving information corresponding to the target road section is obtained, and the empirical driving information is determined based on the historical driving information of the designated vehicle on the target road section.

[0062] By acquiring the experience driving information corresponding to the target road section, at least one of the driving path of the vehicle on the target road section and the speed of each track point on the driving path can be optimized. For example, the vehicle drives along the pre-planned driving path of the target road section, and the driving speed of each track point on the driving path of the target road section is determined to avoid the vehicle from rolling or emergency braking.

[0063] For another example, the original driving speed is maintained unchanged, and the driving path of the vehicle on the target road section is changed to avoid the vehicle making sharp turns or turning in different directions multiple times in a short period of time. For another example, the driving path of the vehicle on the target road section is changed, and the driving speed of the vehicle on the target road section is changed to improve the riding experience of the vehicle.

[0064] The empirical driving information corresponding to the target section is obtained, and the empirical driving information is determined based on the historical driving information of the designated vehicle on the target section. In this way, since the historical driving information of the designated vehicle on the target section has a reference value for driving, the empirical driving information corresponding to the target section obtained helps to improve the vehicle's riding experience at the target section.

[0065] For example, the empirical driving information of the target section can be bound to the lane information in the high-precision map. When the vehicle is driving under the guidance of the high-precision map, if the corresponding lane information of the target section that the vehicle is about to visit in the high-precision map is bound with the empirical driving information, the empirical driving information corresponding to the target section can be obtained to determine the target driving information of the vehicle on the target section.

[0066] In step S13, target driving information is determined based on the empirical driving information.

[0067] The number of acquired experience driving information may be one or more. When the number of acquired experience driving information is more than one, the server or the vehicle-mounted terminal may select any one of the multiple experience driving information of the target road section as the target driving information of the vehicle.

[0068] In one embodiment, the experience driving information includes an experience driving path, and the target driving information includes a target driving path; determining the target driving information based on the experience driving information includes: respectively determining the path similarities between multiple experience driving paths; and determining the target driving path in the target driving information from the experience driving paths whose path similarity is greater than a second preset similarity.

[0069] If the path similarity of the experienced driving path is greater than the second preset similarity, it means that there are other similar driving paths among the multiple experienced driving paths. The specified vehicle drives along the experienced driving path with a path similarity greater than the second preset similarity for multiple times when driving at the target intersection. The experienced driving path with a path similarity greater than the second preset similarity has a higher reference value for the vehicle's driving on the target section. Therefore, determining the target driving path in the target driving information from the experienced driving paths with a path similarity greater than the second preset similarity helps the vehicle to obtain a better riding experience when driving on the target section. The second preset similarity can be 0.75, for example.

[0070] In another embodiment, the experienced driving information includes an experienced driving path, and the target driving information includes a target driving path; determining the target driving information based on the experienced driving information includes: separately determining whether multiple experienced driving paths are in an occupied state, the occupied state indicating that there are vehicles other than the vehicle traveling on the experienced driving path; determining the target driving path in the target driving information from an experienced driving path that is not in an occupied state.

[0071] In this way, by separately determining whether multiple experienced driving paths are in an occupied state, and determining the target driving path in the target driving information from the experienced driving paths that are not in an occupied state, when one of the experienced driving paths is occupied by other vehicles, the vehicle can choose to travel along the unoccupied experienced driving path, avoiding waiting for other vehicles occupying the experienced driving path, thereby shortening the time required for the vehicle to pass the target section.

[0072] In step S14, the vehicle is controlled to travel on the target road section according to the target driving information.

[0073] When the target driving information of the vehicle on the target section is determined, the vehicle can be controlled to travel on the target section according to the target driving information. For example, the server can send the target driving information of the vehicle on the target section to the vehicle-mounted terminal, and the vehicle-mounted terminal can control the vehicle to travel on the target section after receiving the target driving information of the target section.

[0074] In one embodiment, the target driving information includes a target driving path and a driving speed at each designated trajectory point on the target driving path; controlling the vehicle to drive on the target road section according to the target driving information includes: controlling the vehicle to drive on the target road section according to the target driving path based on the driving speed of each designated trajectory point on the target driving path.

[0075] The designated trajectory point may be a key trajectory point on the target driving path, for example, a point on the target driving path where the change in magnitude of the driving speed within a preset time period is greater than a preset speed threshold, or a point on the target driving path where the change in direction of the driving speed within a preset time period is greater than a preset angle threshold.

[0076] In this way, compared with obtaining the driving speed of each trajectory point on the target driving trajectory, using the driving speed of the key trajectory points on the target driving path can reduce the storage and calculation of the driving speed; using the driving speed of the key trajectory points to control the driving process on the target driving path can avoid excessive concentration of designated trajectory points causing frequent acceleration or deceleration of the vehicle, which helps the vehicle pass the target section at a more continuous speed, thereby improving the vehicle's riding experience on the target section.

[0077] In one embodiment, according to the driving speed of each designated trajectory point on the target driving path, controlling the vehicle to travel on the target road section according to the target driving path includes: for each designated trajectory point, when the vehicle travels to the target position, adjusting the vehicle's driving speed so that the vehicle passes through the designated trajectory point at the driving speed corresponding to the designated trajectory point, and the target position is a position at a preset distance from the designated trajectory point in the opposite direction of the vehicle's driving direction.

[0078] For example, when a vehicle is traveling along a target path, it will reach the next designated trajectory point in 50 meters. Within this 50-meter range, the vehicle's driving speed can be adjusted by accelerating or decelerating so that the vehicle passes the next designated trajectory point at a driving speed corresponding to the next designated trajectory point.

[0079] In this way, according to the driving speed of each designated trajectory point on the target driving path, the vehicle's driving process on the target section according to the target driving path is effectively controlled, so that the vehicle travels on the target section according to the target driving information, thereby improving the vehicle's riding experience at the target section.

[0080] Through the method for controlling vehicle driving provided by the present invention, the empirical driving information corresponding to the target section is determined based on the historical driving information of the designated vehicle on the target section, and the historical driving information of the designated vehicle on the target section matches the actual situation of the target section. Therefore, the target driving information is determined based on the empirical driving information, and the vehicle is controlled to drive on the target section according to the target driving information, so that the vehicle can have a better riding experience.

[0081] In one embodiment, historical driving information of a designated vehicle on a target section may be obtained, and based on the historical driving information of the designated vehicle on the target section, empirical driving information corresponding to the target section may be determined; wherein the designated vehicle may, for example, be a vehicle that has a driving record on the target section, and the designated vehicle may be the vehicle itself that has a driving record on the target section, or may be other vehicles other than the vehicle itself that has a driving record on the target section, or may include both the vehicle itself that has a driving record on the target section and other vehicles other than the vehicle itself that has a driving record on the target section.

[0082] In one embodiment, the empirical driving information corresponding to the target section can be obtained in the following manner: when the historical driving information corresponding to the specified vehicle on the target section is obtained, the empirical driving information corresponding to the target section is determined from multiple historical driving information of the specified vehicle on the target section.

[0083] The historical driving information of the designated vehicle on the target section may include the historical driving path of the designated vehicle on the target section; by recording the real-time position information of the designated vehicle and based on different positions of the designated vehicle on the target section, the historical driving path of the designated vehicle on the target section may be generated to determine the empirical driving information of the vehicle on the target section.

[0084] Even if the vehicles are traveling at the same speed, the riding experience may be different when the vehicles are traveling along different paths; for example, when the radius of curvature of the path traveled by the vehicle is small, or when the vehicle turns right after turning left a short time later, the vehicle may tilt, causing a decrease in the riding experience and even affecting passenger safety.

[0085] In one embodiment, historical driving information includes historical driving paths; determining the empirical driving information corresponding to the target section from multiple historical driving information of a specified vehicle on a target section includes: determining the probability distribution interval of multiple historical driving information of the specified vehicle on the target section based on the historical driving paths of the empirical driving information; and using the historical driving information of a target probability interval in the probability distribution interval as the empirical driving information corresponding to the target section.

[0086] For example, according to the historical driving paths of the historical driving information, the probability distribution of multiple historical driving information of a specified vehicle on the target road section may present a normal distribution, and the target probability interval may be the probability interval corresponding to the top 5 frequencies. For another example, according to the historical driving paths of the empirical driving information, 25% of the vehicles choose the C driving path when turning right at the target road section, 20% of the vehicles choose the D driving path when turning right at the target road section, 15% of the vehicles choose the E driving path when turning right at the target road section, and 10% of the vehicles choose the F driving path when turning right at the target road section. Then, when turning right at the target road section, the C, D, E, and F paths may be used as the empirical driving paths in the empirical driving information.

[0087] The probability of the historical driving path appearing at the target section is high, for example, the probability of the historical driving path appearing is greater than or equal to the preset probability. The historical driving paths with probabilities greater than or equal to the preset probability constitute the driving options of the designated vehicle at the target section in most cases, which can avoid sharp turns and the like, so that the vehicle can obtain a better riding experience when driving on the target section; and when the probability of the historical driving path appearing at the target section is low, for example, when the probability of the historical driving path appearing is 0.1%, the historical driving path with a probability of 0.1% is more likely to not conform to the riding habits of most people.

[0088] In another embodiment, the historical driving information includes the historical driving path and the driving speed at each designated trajectory point on the historical driving path; determining the experience driving information corresponding to the target section from multiple historical driving information of the specified vehicle on the target section includes: for multiple historical driving information with the same driving path, according to the driving speed of each designated trajectory point on the historical driving path of the historical driving information, determining the probability distribution interval of multiple historical driving information with the same driving path of the specified vehicle on the target section; and using the historical driving information of the target probability interval in the probability distribution interval as the experience driving information corresponding to the target section.

[0089] By recording the real-time position information and real-time speed information of the designated vehicle and according to the speed information at different positions of the designated vehicle on the target road section and at different positions, the historical driving information of the designated vehicle on the target road section can be determined.

[0090] Even if the vehicle is traveling along the same driving path, the riding experience of the vehicle may be different if the vehicle's driving speed at different trajectory points on the driving path is different; for example, when controlling the vehicle to turn, if the vehicle's driving speed at the turn is high, the vehicle may roll or skid, thereby affecting the riding experience of the driver or passengers in the vehicle.

[0091] According to the driving speed of each designated trajectory point on the historical driving path of the historical driving information, the probability distribution interval of multiple historical driving information of the designated vehicle with the same driving path on the target section is determined, and the historical driving information of the target probability interval in the probability distribution interval is used as the experience driving information corresponding to the target section. This can avoid historical driving information with a low probability such as frequent acceleration or frequent deceleration, so that the obtained experience driving information has a better riding experience.

[0092] In another embodiment, the empirical driving information corresponding to the target section is obtained in the following manner: when the historical driving information corresponding to the specified vehicle on the target section is obtained, the high-precision map is updated according to the historical driving information of the specified vehicle on the target section; based on the updated high-precision map, the empirical driving information corresponding to the target section is determined.

[0093] For example, when the historical driving information corresponding to the specified vehicle on the target section is obtained, the shape of the reference line required for driving on the target section in the high-precision map is adjusted according to the historical driving information of the specified vehicle on the target section to obtain an updated high-precision map; using the updated high-precision map, the vehicle can be guided to obtain a better riding experience when driving on the target section.

[0094] In another embodiment, the empirical driving information corresponding to the target section can be obtained in the following manner: in the case where the historical driving information corresponding to the specified vehicle on the target section is not obtained, based on the road information of the target section, determine a reference section whose road similarity with the road information of the target section is greater than a first preset similarity; obtain the historical driving information of the specified vehicle on the reference section; and determine the empirical driving information corresponding to the target section from the historical driving information of the specified vehicle, where the first preset similarity may be, for example, 0.9.

[0095] Among them, the designated vehicle, for example, may be a vehicle that has a driving record on the reference road section. The designated vehicle may be the vehicle itself that has a driving record on the reference road section, or other vehicles other than the vehicle itself that has a driving record on the reference road section, or may include both the vehicle itself that has a driving record on the reference road section and other vehicles other than the vehicle itself that has a driving record on the reference road section.

[0096] Some target sections may not have a sufficient amount of historical driving information as a reference. For example, the target section has less traffic volume, or the target section is a newly built section and the accumulated traffic volume of the newly built target section is temporarily less, making it possible that the target section has not obtained the historical driving information corresponding to the specified vehicle on the target section.

[0097] In the case that the historical driving information corresponding to the specified vehicle on the target section is not obtained, based on the road information of the target section, and determining a reference section whose road similarity with the road information of the target section is greater than a first preset similarity, the historical driving information of the reference section can be used as a driving reference for the target section, so that the vehicle can obtain a good riding experience at the target section.

[0098] Among them, the road similarity of the road information can be determined based on the number of lanes, lane width, road length, etc. For example, without considering the road traffic conditions, two straight sections with a length of 50 meters, a lane width of 3.5 meters, and four lanes in both directions can be regarded as two sections with the same road conditions.

[0099] In another embodiment, the empirical driving information corresponding to the target section can be obtained in the following manner: in the case where the historical driving information corresponding to the specified vehicle on the target section is not obtained, based on the road information of the target section, determine a reference section whose road similarity with the road information of the section is greater than a first preset similarity; obtain the historical driving information of the specified vehicle on the reference section; update the high-precision map based on the historical driving information of the specified vehicle on the reference section; and determine the empirical driving information corresponding to the target section based on the updated high-precision map.

[0100] The road similarity between the road information of the reference section and the target section is greater than the first preset similarity, indicating that the road conditions of the reference section and the target section are similar, and the historical driving information of the specified vehicle on the reference section has a high reference value for the part corresponding to the target section in the high-precision map.

[0101] For example, based on the historical driving information of a specified vehicle on a reference section, the shape of the reference line required for driving on a target section in a high-precision map can be adjusted to obtain an updated high-precision map; using the updated high-precision map, the vehicle can be guided to obtain a better riding experience when driving on the target section.

[0102] Figure 2 is a block diagram of a device for controlling vehicle travel according to an exemplary embodiment. Figure 2 The device 120 includes a first determination module 121, an acquisition module 122, a second determination module 123 and a control module 124.

[0103] The first determination module 121 is configured to determine a target road section to be passed by the vehicle according to a predetermined planned path;

[0104] The acquisition module 122 is configured to acquire the experience driving information corresponding to the target road section; the experience driving information is determined according to the historical driving information of the specified vehicle on the target road section;

[0105] The second determination module 123 is configured to determine target driving information according to the empirical driving information;

[0106] The control module 124 is configured to control the vehicle to travel on the target road section according to the target driving information.

[0107] In one embodiment, the acquisition module 122 is further configured to determine the empirical driving information corresponding to the target section from a plurality of historical driving information of the designated vehicle on the target section upon acquiring the historical driving information corresponding to the designated vehicle on the target section.

[0108] In one embodiment, the acquisition module 122 is also configured to determine the probability distribution interval of multiple historical driving information of a specified vehicle on a target section based on the historical driving path of the historical driving information; and use the historical driving information of the target probability interval in the probability distribution interval as the experience driving information corresponding to the target section.

[0109] In one embodiment, the historical driving information includes a historical driving path and a driving speed at each designated trajectory point on the historical driving path. The acquisition module 122 is also configured to determine, for multiple historical driving information with the same driving path, a probability distribution interval of multiple historical driving information with the same driving path of the specified vehicle on a target road section based on the driving speed of each designated trajectory point on the historical driving path of the historical driving information; and use the historical driving information of the target probability interval in the probability distribution interval as the experience driving information corresponding to the target road section.

[0110] In one embodiment, the acquisition module 122 is also configured to update the high-precision map based on the historical driving information of the specified vehicle on the target section when the historical driving information corresponding to the specified vehicle on the target section is acquired; and determine the empirical driving information corresponding to the target section based on the updated high-precision map.

[0111] In one embodiment, the acquisition module 122 is also configured to determine, based on the road information of the target road section, a reference road section whose road similarity with the road information of the target road section is greater than a first preset similarity when the historical driving information corresponding to the specified vehicle on the target road section is not obtained; obtain the historical driving information of the specified vehicle on the reference road section; and determine the empirical driving information corresponding to the target road section from the historical driving information of the specified vehicle.

[0112] In one embodiment, the acquisition module 122 is also configured to determine, based on the road information of the target road section, a reference road section whose road similarity with the road information of the road section is greater than a first preset similarity when the historical driving information corresponding to the specified vehicle on the target road section is not obtained; obtain the historical driving information of the specified vehicle on the reference road section; update the high-precision map based on the historical driving information of the specified vehicle on the reference road section; and determine the empirical driving information corresponding to the target road section based on the updated high-precision map.

[0113] In one embodiment, the experienced driving information includes an experienced driving path, the target driving information includes a target driving path, and the second determination module 123 is further configured to respectively determine the path similarities between multiple experienced driving paths; and determine the target driving path in the target driving information from the experienced driving paths whose path similarity is greater than the second preset similarity.

[0114] In one embodiment, the experienced driving information includes an experienced driving path, and the target driving information includes a target driving path. The second determination module 123 is also configured to respectively determine whether multiple experienced driving paths are in an occupied state, and the occupied state indicates that there are other vehicles other than the vehicle traveling on the experienced driving path; and determine the target driving path in the target driving information from the experienced driving path that is not in an occupied state.

[0115] In one embodiment, the target driving information includes a target driving path and a driving speed at each designated trajectory point on the target driving path. The control module 124 is also configured to control the vehicle to travel on the target road section according to the target driving path based on the driving speed of each designated trajectory point on the target driving path.

[0116] In one embodiment, the control module 124 is also configured to adjust the driving speed of the vehicle for each designated trajectory point when the vehicle travels to a target position so that the vehicle passes through the designated trajectory point at a driving speed corresponding to the designated trajectory point, and the target position is a position at a preset distance from the designated trajectory point in the opposite direction of the vehicle's driving direction.

[0117] Through the device for controlling vehicle driving provided by the present invention, the empirical driving information corresponding to the target section is determined based on the historical driving information of the designated vehicle on the target section, and the historical driving information of the designated vehicle on the target section matches the actual situation of the target section. Therefore, the target driving information is determined based on the empirical driving information, and the vehicle is controlled to travel on the target section according to the target driving information, so that the vehicle can have a better riding experience.

[0118] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0119] Figure 3 8 is a block diagram of a device 800 for controlling vehicle travel according to an exemplary embodiment. For example, the device 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0120] Reference Figure 3 , the device 800 may include one or more of the following components: a processing component 802 , a memory 804 , a power component 806 , a multimedia component 808 , an audio component 810 , an input / output interface 812 , a sensor component 814 , and a communication component 816 .

[0121] The processing component 802 generally controls the overall operation of the device 800, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the above-mentioned method for controlling vehicle travel. In addition, the processing component 802 may include one or more modules to facilitate the interaction between the processing component 802 and other components. For example, the processing component 802 may include a multimedia module to facilitate the interaction between the multimedia component 808 and the processing component 802.

[0122] The memory 804 is configured to store various types of data to support operations on the device 800. Examples of such data include instructions for any application or method operating on the device 800, contact data, phone book data, messages, pictures, videos, etc. The memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0123] The power supply component 806 provides power to the various components of the device 800. The power supply component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the device 800.

[0124] The multimedia component 808 includes a screen that provides an output interface between the device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front camera and / or a rear camera. When the device 800 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0125] The audio component 810 is configured to output and / or input audio signals. For example, the audio component 810 includes a microphone (MIC), and when the device 800 is in an operating mode, such as a call mode, a recording mode, and a speech recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 804 or sent via the communication component 816. In some embodiments, the audio component 810 also includes a speaker for outputting audio signals.

[0126] The input / output interface 812 provides an interface between the processing component 802 and the peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: a home button, a volume button, a start button, and a lock button.

[0127] The sensor assembly 814 includes one or more sensors for providing various aspects of the status assessment of the device 800. For example, the sensor assembly 814 can detect the open / closed state of the device 800, the relative positioning of components, such as the display and keypad of the device 800, and the sensor assembly 814 can also detect the position change of the device 800 or a component of the device 800, the presence or absence of user contact with the device 800, the orientation or acceleration / deceleration of the device 800, and the temperature change of the device 800. The sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an accelerometer, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0128] The communication component 816 is configured to facilitate wired or wireless communication between the device 800 and other devices. The device 800 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0129] In an exemplary embodiment, the device 800 can be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components to execute the above-mentioned method of controlling vehicle driving.

[0130] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 804 including instructions, and the instructions can be executed by the processor 820 of the device 800 to complete the above-mentioned method of controlling the driving of the vehicle. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0131] In addition to being an independent electronic device, the above-mentioned device can also be a part of an independent electronic device. For example, in one embodiment, the device can be an integrated circuit (IC) or a chip, wherein the integrated circuit can be an IC or a collection of multiple ICs; the chip can include but is not limited to the following types: GPU (Graphics Processing Unit), CPU (Central Processing Unit), FPGA (Field Programmable Gate Array), DSP (Digital Signal Processor), ASIC (Application Specific Integrated Circuit), SOC (System on Chip, SoC), etc. The above-mentioned integrated circuit or chip can be used to execute executable instructions (or codes) to implement the above-mentioned method of controlling vehicle driving. The executable instructions can be stored in the integrated circuit or chip, or can be obtained from other devices or equipment, such as the integrated circuit or chip including a processor, a memory, and an interface for communicating with other devices. The executable instruction can be stored in the memory, and when the executable instruction is executed by the processor, the above-mentioned method of controlling the vehicle's driving can be implemented; alternatively, the integrated circuit or chip can receive the executable instruction through the interface and transmit it to the processor for execution, so as to implement the above-mentioned method of controlling the vehicle's driving.

[0132] In another exemplary embodiment, a computer program product is also provided. The computer program product includes a computer program executable by a programmable device. The computer program has a code portion for executing the above-mentioned method for controlling vehicle driving when executed by the programmable device.

[0133] Figure 4 1 is a block diagram of a device 1900 for controlling vehicle driving according to an exemplary embodiment. For example, the device 1900 may be provided as a server. Figure 4 The device 1900 includes a processing component 1922, which further includes one or more processors, and a memory resource represented by a memory 1932 for storing instructions that can be executed by the processing component 1922, such as an application. The application stored in the memory 1932 may include one or more modules, each corresponding to a set of instructions. In addition, the processing component 1922 is configured to execute instructions to perform the above-mentioned method of controlling vehicle travel.

[0134] The device 1900 may also include a power supply component 1926 configured to perform power management of the device 1900, a wired or wireless network interface 1950 configured to connect the device 1900 to a network, and an input / output interface 1958. The device 1900 may operate based on an operating system stored in the memory 1932, such as Windows Server 2000. TM , Mac OS X TM , Unix TM , Linux TM , FreeBSD TM or similar.

[0135] Figure 5 is a block diagram of a vehicle 300 according to an exemplary embodiment. For example, the vehicle 300 may be a hybrid vehicle, a non-hybrid vehicle, an electric vehicle, a fuel cell vehicle, or other types of vehicles. The vehicle 300 may be an autonomous vehicle, a semi-autonomous vehicle, or a non-autonomous vehicle.

[0136] Reference Figure 5 , the vehicle 300 may include various subsystems, for example, an infotainment system 310, a perception system 320, a decision control system 330, a drive system 340, and a computing platform 350. The vehicle 300 may also include more or fewer subsystems, and each subsystem may include multiple components. In addition, each subsystem and each component of the vehicle 300 may be interconnected by wire or wireless means.

[0137] In some embodiments, the infotainment system 310 may include a communication system, an entertainment system, and a navigation system, among others.

[0138] The perception system 320 may include several sensors for sensing information about the environment around the vehicle 300. For example, the perception system 320 may include a global positioning system (the global positioning system may be a GPS system, or a Beidou system or other positioning systems), an inertial measurement unit (IMU), a laser radar, a millimeter wave radar, an ultrasonic radar, and a camera.

[0139] The decision control system 330 may include a computing system, a vehicle controller, a steering system, a throttle, and a braking system.

[0140] The drive system 340 may include components that provide power movement for the vehicle 300. In one embodiment, the drive system 340 may include an engine, an energy source, a transmission system, and wheels. The engine may be one or a combination of an internal combustion engine, an electric motor, and an air compression engine. The engine is capable of converting energy provided by the energy source into mechanical energy.

[0141] Some or all functions of the vehicle 300 are controlled by a computing platform 350. The computing platform 350 may include at least one processor 351 and a memory 352, and the processor 351 may execute instructions 353 stored in the memory 352.

[0142] The processor 351 may be any conventional processor, such as a commercially available CPU. The processor may also include a graphics processor (Graphic Process Unit, GPU), a field programmable gate array (Field Programmable Gate Array, FPGA), a system on chip (System on Chip, SOC), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC) or a combination thereof.

[0143] The memory 352 may be implemented by any type of volatile or nonvolatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0144] In addition to instructions 353 , memory 352 may also store data, such as road maps, route information, vehicle location, direction, speed, etc. The data stored in memory 352 may be used by computing platform 350 .

[0145] In the embodiment of the present disclosure, the processor 351 can execute the instruction 353 to complete all or part of the steps of the above-mentioned method for controlling vehicle driving.

[0146] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the present disclosure. The present disclosure is intended to cover any variations, uses or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are to be considered as exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0147] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for controlling vehicle driving, characterized in that, it includes: Determine the target road section that the vehicle is to pass through according to a pre-determined planned path; Obtain the empirical driving information corresponding to the target road section; The empirical driving information is determined according to the historical driving information of a specified vehicle on the target road section; Determine the target driving information according to the empirical driving information; Control the vehicle to drive on the target road section according to the target driving information.

2. The method according to claim 1, characterized in that, The empirical driving information corresponding to the target road section is obtained in the following way: When the historical driving information of the specified vehicle corresponding to the target road section is obtained, determine the empirical driving information corresponding to the target road section from multiple historical driving information of the specified vehicle on the target road section.

3. The method according to claim 2, characterized in that, The historical driving information includes the historical driving path; determining the empirical driving information corresponding to the target road section from multiple historical driving information of the specified vehicle on the target road section includes: According to the historical driving path of the historical driving information, determine the probability distribution interval of multiple historical driving information of the specified vehicle on the target road section; Use the historical driving information in the target probability interval in the probability distribution interval as the empirical driving information corresponding to the target road section.

4. The method according to claim 2, characterized in that, The historical driving information includes the historical driving path and the driving speed at each specified trajectory point on the historical driving path; Determining the empirical driving information corresponding to the target road section from multiple historical driving information of the specified vehicle on the target road section includes: For multiple historical driving information with the same driving path, according to the driving speed at each specified trajectory point on the historical driving path of the historical driving information, determine the probability distribution interval of multiple historical driving information of the specified vehicle with the same driving path on the target road section; Use the historical driving information in the target probability interval in the probability distribution interval as the empirical driving information corresponding to the target road section.

5. The method according to claim 1, characterized in that, The empirical driving information corresponding to the target road section is obtained in the following way: When the historical driving information of the specified vehicle corresponding to the target road section is obtained, update the high-precision map according to the historical driving information of the specified vehicle on the target road section; Determine the empirical driving information corresponding to the target road section according to the updated high-precision map.

6. The method according to claim 1, characterized in that, The empirical driving information corresponding to the target road section is obtained in the following way: When the historical driving information of the specified vehicle corresponding to the target road section is not obtained, determine a reference road section whose road similarity to the road information of the target road section is greater than a first preset similarity according to the road information of the target road section; Obtain the historical driving information of the specified vehicle on the reference road section; Determine the empirical driving information corresponding to the target road section from the historical driving information of the specified vehicle.

7. The method according to claim 1, characterized in that, The empirical driving information corresponding to the target road section is obtained in the following way: In the case where the historical driving information corresponding to the specified vehicle on the target road section is not obtained, according to the road information of the target road section, determine a reference road section whose road similarity to the road information of the road section is greater than a first preset similarity; Obtain the historical driving information of the specified vehicle on the reference road section; Update the high-precision map according to the historical driving information of the specified vehicle on the reference road section; Determine the empirical driving information corresponding to the target road section according to the updated high-precision map.

8. The method according to claim 1, wherein, the empirical driving information includes an empirical driving path, and the target driving information includes a target driving path; the determining the target driving information according to the empirical driving information includes: Determine the path similarity between multiple empirical driving paths respectively; Determine the target driving path in the target driving information from the empirical driving paths whose path similarity is greater than a second preset similarity.

9. The method according to claim 1, wherein, the empirical driving information includes an empirical driving path, and the target driving information includes a target driving path; the determining the target driving information according to the empirical driving information includes: Determine whether multiple empirical driving paths are in an occupied state respectively, where the occupied state indicates that there are other vehicles other than the vehicle driving on the empirical driving path; Determine the target driving path in the target driving information from the empirical driving paths that have never been in an occupied state.

10. The method according to any one of claims 1-9, wherein, the target driving information includes a target driving path and the driving speed at each specified trajectory point on the target driving path; The controlling the vehicle to drive on the target road section according to the target driving information includes: According to the driving speed at each specified trajectory point on the target driving path, control the vehicle to drive on the target road section according to the target driving path.

11. The method according to claim 10, wherein, the controlling the vehicle to drive on the target road section according to the driving speed at each specified trajectory point on the target driving path includes: For each specified trajectory point, when the vehicle travels to the target position, adjust the driving speed of the vehicle so that the vehicle passes through the specified trajectory point according to the driving speed corresponding to the specified trajectory point, where the target position is a position at a preset distance from the specified trajectory point in the opposite direction of the driving direction of the vehicle.

12. A device for controlling vehicle driving, wherein, comprises: A first determination module configured to determine a target road section to be passed by the vehicle according to a pre-determined planned path; An acquisition module configured to acquire the empirical driving information corresponding to the target road section; The empirical driving information is determined according to the historical driving information of the specified vehicle on the target road section; A second determination module configured to determine target driving information according to the empirical driving information; A control module configured to control the vehicle to drive on the target road section according to the target driving information.

13. A computer-readable storage medium having computer program instructions stored thereon, wherein, when the program instructions are executed by a processor, the steps of the method according to any one of claims 1-11 are implemented.

14. A vehicle, wherein, comprising: a processor; a memory for storing executable instructions executable by the processor; wherein the processor is configured to implement the steps of the method according to any one of claims 1 to 11 when calling the executable instructions stored on the memory.

Images