Method and device for determining driving path based on material composition analysis and vehicle

Abstract

The invention relates to the technical field of vehicle control, in particular to a method and device for determining a driving path based on material composition analysis and a vehicle. The method comprises the following steps: performing material component scanning on a preset scanning space range taking a current vehicle as a sphere center, and obtaining material component data of at least one position point in the preset scanning space range; based on the material component data of the at least one position point, determining a material attribute of each position point according to a preset material attribute data set; and according to the material attribute of each position point, determining a material distribution condition in a preset scanning space range, determining a drivable space area of the current vehicle based on the material distribution condition, and determining a driving path of the current vehicle based on the drivable space area. Therefore, the problem that in the prior art, in road material recognition, due to visual illusion, road surface objects are wrongly recognized or not recognized, and then driving strategies are wrong is solved, the object recognition probability is improved, and meanwhile driving safety is improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle control technology, and in particular to a method, device, and vehicle for determining a driving path based on material composition analysis. Background Art

[0002] The rapid development of the Internet of Things (IoT) and its integration with autonomous driving are revolutionizing intelligent traffic management. By connecting various sensors, devices, and machines to the internet, the IoT enables real-time data collection, exchange, and analysis, providing new possibilities for route planning for intelligent vehicles.

[0003] In related technologies, when performing path planning, object recognition is mainly performed through images captured by a camera, or by combining a camera with a millimeter-wave radar or a lidar.

[0004] However, this method is essentially the recognition of the shape composed of object pixels, which is a visual solution. However, in the actual environment, due to various complex light and shadows, or limited by the performance of the sensor, it is easy to misidentify or fail to recognize road objects due to visual illusions, which in turn leads to incorrect driving strategies. This problem needs to be solved urgently. Summary of the Invention

[0005] The present application provides a method, device and vehicle for determining a driving path based on material composition analysis, so as to solve the problem of the prior art in road material identification that road objects are misidentified or not identified due to visual illusions, thereby causing driving strategy errors, thereby improving the probability of object recognition and improving driving safety.

[0006] To achieve the above objectives, a first embodiment of the present application proposes a method for determining a driving path based on material composition analysis, comprising the following steps:

[0007] Performing a material composition scan on a preset scanning space range with the current vehicle as the center, and obtaining material composition data of at least one position point in the preset scanning space range;

[0008] Determining the material properties of each location point based on the material composition data of the at least one location point and according to a preset material property data set;

[0009] According to the material properties of each location point, the material distribution within the preset scanning space range is determined, and based on the material distribution, the drivable space area of ​​the current vehicle is determined, and the driving path of the current vehicle is determined based on the drivable space area.

[0010] According to one embodiment of the present application, determining the drivable space area of ​​the current vehicle based on the material distribution includes:

[0011] Based on the substance distribution, determining whether the gas space constitutes a preset continuous channel;

[0012] In the case where the gas space constitutes the preset continuous channel, a target continuous channel that meets the preset driving requirements is screened out from the preset continuous channels based on the size information of the preset continuous channel and the size information of the current vehicle, and the target continuous channel is used as the drivable space area of ​​the current vehicle.

[0013] According to one embodiment of the present application, determining the target driving path of the current vehicle based on the drivable space area includes:

[0014] Get traffic rules set and current navigation information;

[0015] Based on the current navigation information, a preset path planning algorithm is used to plan a set of driving paths for the current vehicle according to the drivable space area;

[0016] Based on the traffic rule set, each driving path in the driving path set is verified, and according to the verification result, a driving path in the driving path set that meets the preset traffic rules is determined as the target driving path.

[0017] According to one embodiment of the present application, after obtaining material composition data of at least one position point in the preset scanning space range, the method further includes:

[0018] Storing the material composition data of the at least one location point in a preset data buffer, and determining whether new material composition data enters the preset data buffer;

[0019] In the case where the new material composition data enters the preset data buffer, determining whether the accumulated amount of the new material composition data is greater than or equal to a preset threshold;

[0020] When the accumulated amount of the new material composition data is greater than or equal to the preset threshold, a preset update algorithm is triggered, and the material composition data in the local material composition database is updated based on the preset update algorithm.

[0021] According to an embodiment of the present application, the material composition data includes elemental composition and ratio of elemental composition.

[0022] According to the method for determining a driving path based on material composition analysis proposed in an embodiment of the present application, by performing a material composition scan on a preset scanning space range with the current vehicle as the center, material composition data for at least one location point within the preset scanning space range can be obtained; based on the material composition data of at least one location point, the material properties of each location point can be determined according to a preset material property data set; based on the material properties of each location point, the material distribution within the preset scanning space range is determined, and based on the material distribution, the drivable space area of ​​the current vehicle is determined, and the driving path of the current vehicle is determined based on the drivable space area. This solves the problem of the prior art in road material recognition, where visual illusions lead to misidentification or non-recognition of road objects, which in turn leads to incorrect driving strategies, thereby improving the probability of object recognition and driving safety.

[0023] To achieve the above-mentioned objectives, a second embodiment of the present application provides a device for determining a driving path based on material composition analysis, comprising:

[0024] an acquisition module, configured to perform a material composition scan on a preset scanning space range with the current vehicle as the center, and acquire material composition data of at least one position point in the preset scanning space range;

[0025] A first determining module, configured to determine the material properties of each location point based on the material composition data of the at least one location point and a preset material property data set;

[0026] The second determination module is used to determine the material distribution within the preset scanning space range according to the material properties of each location point, and based on the material distribution, determine the drivable space area of ​​the current vehicle, and determine the driving path of the current vehicle based on the drivable space area.

[0027] According to one embodiment of the present application, the second determining module is specifically configured to:

[0028] Based on the substance distribution, determining whether the gas space constitutes a preset continuous channel;

[0029] In the case where the gas space constitutes the preset continuous channel, a target continuous channel that meets the preset driving requirements is screened out from the preset continuous channels based on the size information of the preset continuous channel and the size information of the current vehicle, and the target continuous channel is used as the drivable space area of ​​the current vehicle.

[0030] According to one embodiment of the present application, the second determining module is specifically configured to:

[0031] Get traffic rules set and current navigation information;

[0032] Based on the current navigation information, a preset path planning algorithm is used to plan a set of driving paths for the current vehicle according to the drivable space area;

[0033] Based on the traffic rule set, each driving path in the driving path set is verified, and according to the verification result, a driving path in the driving path set that meets the preset traffic rules is determined as the target driving path.

[0034] According to one embodiment of the present application, after acquiring material composition data of at least one position point in the preset scanning space range, the acquisition module is further configured to:

[0035] Storing the material composition data of the at least one location point in a preset data buffer, and determining whether new material composition data enters the preset data buffer;

[0036] In the case where the new material composition data enters the preset data buffer, determining whether the accumulated amount of the new material composition data is greater than or equal to a preset threshold;

[0037] When the accumulated amount of the new material composition data is greater than or equal to the preset threshold, a preset update algorithm is triggered, and the material composition data in the local material composition database is updated based on the preset update algorithm.

[0038] According to an embodiment of the present application, the material composition data includes elemental composition and ratio of elemental composition.

[0039] According to the device for determining a driving path based on material composition analysis proposed in an embodiment of the present application, by performing a material composition scan on a preset scanning space range with the current vehicle as the center, material composition data for at least one location point within the preset scanning space range can be obtained; based on the material composition data of at least one location point, the material properties of each location point can be determined according to a preset material property data set; based on the material properties of each location point, the material distribution within the preset scanning space range is determined, and based on the material distribution, the drivable space area of ​​the current vehicle is determined, and the driving path of the current vehicle is determined based on the drivable space area. This solves the problem of the prior art in road material recognition, where visual illusions lead to misidentification or non-recognition of road objects, which in turn leads to incorrect driving strategies, thereby improving the probability of object recognition and driving safety.

[0040] To achieve the above-mentioned objectives, the third aspect embodiment of the present application proposes a vehicle, comprising: a memory, a processor, and a computer program stored on the memory and runnable on the processor, wherein the processor executes the program to implement the method for determining the driving path based on material composition analysis as described in the above embodiment.

[0041] To achieve the above-mentioned objectives, the fourth embodiment of the present application proposes a computer-readable storage medium on which a computer program is stored, and the program is executed by a processor to implement the method for determining a driving path based on material composition analysis as described in the above embodiment.

[0042] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0044] Figure 1 A flowchart of a method for determining a driving path based on material composition analysis according to an embodiment of the present application;

[0045] Figure 2 Schematic diagram of a preset scanning space range (1) according to one embodiment of the present application;

[0046] Figure 3 is a schematic diagram of a scanning result (1) according to an embodiment of the present application;

[0047] Figure 4 Schematic diagram of spatial material distribution (I) according to one embodiment of the present application;

[0048] Figure 5 Schematic diagram of a drivable space area result (1) according to one embodiment of the present application;

[0049] Figure 6 Schematic diagram of a preset scanning space range (II) according to one embodiment of the present application;

[0050] Figure 7 Schematic diagram of scanning result (2) according to one embodiment of the present application;

[0051] Figure 8 Schematic diagram of spatial material distribution (II) according to one embodiment of the present application;

[0052] Figure 9 Schematic diagram of the drivable space area result (II) according to one embodiment of the present application;

[0053] Figure 10 Schematic diagram of a preset scanning space range (III) according to one embodiment of the present application;

[0054] Figure 11Schematic diagram of scanning result (3) according to one embodiment of the present application;

[0055] Figure 12 Schematic diagram of spatial material distribution (III) according to one embodiment of the present application;

[0056] Figure 13 Schematic diagram of the drivable space area result (3) according to one embodiment of the present application;

[0057] Figure 14 A block diagram of an apparatus for determining a driving path based on material composition analysis according to an embodiment of the present application;

[0058] Figure 15 A schematic structural diagram of a vehicle provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0059] The following describes in detail embodiments of the present application. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0060] The following describes a method, device, and vehicle for determining a driving path based on material composition analysis according to an embodiment of the present application with reference to the accompanying drawings.

[0061] Figure 1 This is a flowchart of a method for determining a driving path based on material composition analysis according to an embodiment of the present application.

[0062] Before introducing the method for determining a driving path based on material composition analysis proposed in an embodiment of the present application, a brief introduction to the relevant technical background is first given.

[0063] Related technologies, whether identifying objects through camera images or by combining cameras with millimeter-wave radar or lidar, essentially rely on the recognition of shapes composed of pixels. However, in real-world environments, due to complex lighting conditions or limited sensor performance, object recognition errors can occur.

[0064] For example, (1) a purely visual solution that uses camera footage for object recognition has a high probability of failing to recognize objects in low-light conditions, such as at night. (2) In brighter light conditions, such as during the day, there is a high probability of misidentifying objects. For example, sunlight shining through gaps in an overpass onto the ground can be mistaken for lane markings by a vehicle, causing it to collide with a guardrail. A white truck can also be mistaken for the sky, causing it to collide with the truck.

[0065] Furthermore, current assisted driving solutions, without map support, cannot perceive conditions below the road surface, such as ditches, steps, or ponds. This limitation can cause the vehicle to misjudge these situations. For example, the automatic parking function of some vehicles may not function properly on roadside steps.

[0066] It is precisely based on the above problems that the embodiment of the present application proposes a method for determining the driving path based on material composition analysis. The spatial material distribution within a certain range with the vehicle as the center is analyzed, and the object properties and the distance and size of the corresponding material are obtained according to the composition and proportion of the material elements, thereby confirming the space in which the vehicle can drive and plan the driving route. This method can accurately identify the shape and properties of objects regardless of how the light and shadow change, and thus infer the nature of the object targets in front of and around the vehicle and below the horizontal line of the road. It solves the problem of the existing technology in road material recognition that the road objects are misidentified or not recognized due to visual illusions, which in turn causes driving strategy errors, improves the probability of object recognition, and improves driving safety at the same time.

[0067] like Figure 1 As shown, the method for determining a driving path based on material composition analysis includes the following steps:

[0068] In step S101 , a material composition scan is performed on a preset scanning space range with the current vehicle as the center, and material composition data of at least one position point in the preset scanning space range is obtained.

[0069] It is understood that the preset scanning range can be a pre-defined three-dimensional spatial area to be scanned. The size and shape of this range can be adjusted based on actual needs, typically to cover all relevant information about the target area. Material composition data refers to the composition of the material within the target area obtained through scanning technology, such as the elements contained and their proportions. This data can be used to determine the physical or chemical properties of the area.

[0070] Specifically, with the current vehicle as the center point (called the "sphere center"), a preset scanning space range (such as a spherical three-dimensional area) is set. Then, spectral analysis (such as atomic absorption spectroscopy, atomic emission spectroscopy, X-ray fluorescence spectroscopy, etc.) or other material composition detection methods are used to scan different locations within the preset scanning space to ensure that the area within a certain distance around the current vehicle is covered. Through this scanning process, detailed material composition data can be obtained for at least one location within the preset scanning space range. This data is crucial for understanding the material composition of the current vehicle's surrounding environment.

[0071] Optionally, in some embodiments, the material composition data includes elemental composition and ratios of elemental composition.

[0072] In other words, material composition data covers both the elemental composition and the proportional relationships between these elements. This data not only provides basic information about the material makeup of the vehicle's immediate surroundings, but also, through the proportional relationships of the elemental composition, can further analyze the physical or chemical properties of the area, such as the presence of potholes, hazardous chemicals, or the type of material on the road surface. This information is crucial for autonomous vehicles, as they need to make driving decisions based on the varying characteristics of their surroundings. For example, if a pothole is detected on the road ahead, the vehicle may choose to slow down or take a detour to avoid the potential risk of skidding. Therefore, the acquisition and analysis of material composition data is a key step in enabling autonomous vehicles to make safe and efficient driving decisions.

[0073] In step S102 , based on the material composition data of at least one location point and according to a preset material property data set, the material property of each location point is determined.

[0074] The pre-set material property dataset refers to a pre-set database containing the elemental composition and ratios of various currently known substances. By comparing the actual material composition data collected with this dataset, the specific properties of the substance can be inferred. Material properties refer to the state of a substance (solid, liquid, gas), as well as its properties such as hardness, density, conductivity, and corrosiveness.

[0075] Specifically, after obtaining the material composition data of at least one position point within the preset scanning space range, the material composition data of each position point can be compared with the preset material property data set to determine the material properties of each position point, that is, determine what the substance is.

[0076] Understandably, in autonomous driving scenarios, identifying material properties is crucial to vehicle safety. For example, if the road surface is solid and hard, the vehicle can determine that it is relatively smooth and suitable for high-speed driving. However, identifying the presence of liquid on the road surface may indicate the presence of accumulated water or oil, requiring slowing down to prevent slipping. If a large amount of gas is detected ahead, it may indicate a dangerous gas leak, requiring the vehicle to reroute as quickly as possible. Therefore, accurately identifying material properties is a crucial basis for autonomous vehicles to make reasonable driving decisions.

[0077] In step S103, the material distribution within the preset scanning space is determined according to the material properties of each location point, and the drivable space area of ​​the current vehicle is determined based on the material distribution, and the driving path of the current vehicle is determined based on the drivable space area.

[0078] Among them, material distribution refers to the position, size, shape of solid and liquid substances and the continuity of gas space.

[0079] Specifically, the material properties of each specific location can be used to precisely determine the distribution of materials within a pre-defined scanning volume. By analyzing these distributions, the vehicle's drivable area within that volume can be determined—that is, the direction in which it can travel without a collision. Based on this detailed information about the drivable area, at least one optimal driving path can be developed to ensure safe and efficient vehicle operation.

[0080] As a possible implementation method, in some embodiments, the drivable space area of ​​the current vehicle is determined based on the material distribution, including: judging whether the gas space constitutes a preset continuous channel based on the material distribution; in the case that the gas space constitutes a preset continuous channel, based on the size information of the preset continuous channel and the size information of the current vehicle, screening out a target continuous channel that meets the preset driving requirements from the preset continuous channels, and using the target continuous channel as the drivable space area of ​​the current vehicle.

[0081] Specifically, after analyzing the specific distribution of the material, it can be determined based on the material distribution whether the gas space has formed a preset continuous channel (i.e., a continuous channel for the current vehicle to normally travel). Once the gas space can form a preset continuous channel, further analysis can be performed based on the dimensions of the preset continuous channel and the dimensions of the current vehicle. Through this analysis, target continuous channels that meet the preset travel requirements (i.e., the current vehicle can successfully pass through the preset travel requirements) can be screened from the numerous preset continuous channels. Ultimately, these selected target continuous channels will be determined as the current vehicle's drivable space area.

[0082] As a possible implementation method, in some embodiments, the target driving path of the current vehicle is determined based on the drivable space area, including: obtaining a traffic rule set and current navigation information; based on the current navigation information, using a preset path planning algorithm to plan a driving path set of the current vehicle according to the drivable space area; based on the traffic rule set, verifying each driving path in the driving path set, and determining the driving path in the driving path set that meets the preset traffic rules as the target driving path based on the verification result.

[0083] Specifically, in the process of determining the target driving path of the current vehicle based on the drivable space area, a complete set of traffic rules and real-time navigation information can be obtained; next, the preset path planning algorithm is used, combined with the current navigation information (traffic information such as road signs and various warning lights), to plan the driving path of the current vehicle to ensure that these paths are based on the drivable space area. After planning a series of possible driving paths, these paths can be verified according to the traffic rule set. Through this verification process, those driving paths that comply with traffic rules can be screened out. Finally, at least one driving path is determined from these verified paths as the target driving path. The target driving path can ensure that the current vehicle arrives at the destination safely and efficiently while complying with traffic rules.

[0084] Furthermore, in some embodiments, after obtaining the material composition data of at least one position point in a preset scanning space range, it also includes: storing the material composition data of at least one position point in a preset data buffer, and determining whether there is new material composition data entering the preset data buffer; in the case where there is new material composition data entering the preset data buffer, determining whether the cumulative amount of the new material composition data is greater than or equal to a preset threshold; in the case where the cumulative amount of the new material composition data is greater than or equal to the preset threshold, triggering a preset update algorithm, and updating the material composition data in the local material composition database based on the preset update algorithm.

[0085] Specifically, the embodiment of the present application can also set a data buffer (i.e., a preset data buffer) locally in the vehicle to temporarily store the latest material composition data collected by the sensor. When new material composition data enters the preset data buffer and the cumulative amount of the new material composition data is greater than or equal to the preset threshold, the system can use a preset update algorithm (fast update algorithm) to update the local material composition database. For example, for the material composition data of the road area in front of the vehicle, when the spectrometer detects a change in the material composition (such as a change from a normal road surface to an oily road surface, and an increase in the proportion of hydrocarbons in the material composition), the data will accumulate to a certain amount in the buffer, triggering the preset update algorithm to immediately update the material composition information of the corresponding position in the local database, thereby ensuring the accuracy and timeliness of the data.

[0086] To facilitate those skilled in the art to further understand the method for determining a driving path based on material composition analysis proposed in the embodiment of the present application, further explanation is provided below in conjunction with specific implementation scenarios.

[0087] Specifically, scenario 1: material composition scanning is performed within a preset scanning space range with the current vehicle (ego vehicle) as the center of the sphere, such as Figure 2 As shown, Figure 21, 2, 3, 4, and 5 are all vehicles traveling on the road. ① and ② together constitute the scanning space range with the current vehicle (the vehicle) as the center of the sphere. The size of this range can be set according to the performance of the scanning device. Figure 2 It can be concluded that Figure 3 The schematic results show that the scanned materials can be divided into two categories: materials above the road surface (including: visible solid obstacles on the road surface (such as other vehicles, pedestrians, roadblocks, isolation belts, etc.), irregularly shaped objects around the road surface (such as green belts, billboards, temporary construction facilities, etc.), and suspended matter that may pose a collision risk (such as floating garbage, falling objects, etc.)); the road surface and roadbed below the road surface (including: road pavement layer (asphalt / cement, etc.), roadbed structure (base layer such as gravel and soil), road depressions or underground facilities (such as manhole covers, drainage channels, etc.)).

[0088] Further, based on Figure 2 The material distribution obtained after material scanning can be shown as follows Figure 4 shown. Figure 4 The substances represented by the numbers in the table have the following meanings:

[0089] Space 1: Through spectral analysis or other means of detecting material composition, it is determined that the composition of space 1 is oxygen atoms, nitrogen atoms, and hydrogen atoms. Based on their proportions, space 1 can be determined to be air.

[0090] Space 2: Through spectral analysis or other means of detecting material composition, it is determined that the components of space 2 are iron, aluminum, carbon, etc. Based on the composition and their proportions, it can be determined that space 2 is a solid substance;

[0091] Space 3: Through spectral analysis or other means of detecting material composition, it is determined that the components of space 3 are iron, aluminum, carbon, etc. Based on the composition and their proportions, it can be determined that space 3 is a solid substance;

[0092] Space 4: Through spectral analysis or other means of detecting material composition, it is determined that the composition of space 4 is oxygen atoms, nitrogen atoms, and hydrogen atoms. Based on their proportions, space 4 can be determined to be air.

[0093] Space 5: Through spectral analysis or other means of detecting material composition, it is determined that the components of space 5 are iron, aluminum, carbon, etc. Based on the composition and their proportions, it can be determined that space 5 is a solid substance;

[0094] Space 6: Through spectral analysis or other means of detecting material composition, it can be determined that the components of space 6 are iron, aluminum, carbon, etc. Based on the composition and their proportions, it can be determined that space 6 is a solid substance;

[0095] Space 7: Through spectral analysis or other means of detecting material composition, it is determined that the composition of space 7 is oxygen atoms, nitrogen atoms, and hydrogen atoms. Based on their proportions, space 7 can be determined to be air.

[0096] Space 8: Through spectral analysis or other means of detecting material composition, it is determined that the components of space 8 are iron, aluminum, carbon, etc. Based on the composition and their proportions, it can be determined that space 8 is a solid substance;

[0097] Space 9: Through spectral analysis or other means of detecting material composition, it is determined that the components within the space range of 9 are mainly silicon elements, etc. Based on the composition and its proportion, it is determined that space 9 is a road surface and roadbed.

[0098] Depend on Figure 4 It can be seen that Space 1, Space 4, and Space 7 are spaces that the current vehicle (self-vehicle) can travel through, that is, the current vehicle (self-vehicle) can move horizontally and vertically in the continuous space formed by Space 1, Space 4, and Space 7.

[0099] according to Figure 4 The analysis results can be concluded as follows Figure 5 As shown in the driving path results, the current vehicle (the ego vehicle) has drivable spaces within routes ①, ②, and ③. However, route ① encounters a solid line (supplemented by navigation or visual solutions). Due to traffic regulations, route ① is deemed infeasible. Therefore, the current vehicle (the ego vehicle) has routes ② and ③. During driving, the powertrain and chassis coordination of the current vehicle (the ego vehicle) can be determined based on routes ② and ③.

[0100] Scenario 2: Scan the material composition within the preset scanning space with the current vehicle (self-vehicle) as the center of the sphere, such as Figure 6 As shown, Figure 6 1, 2, 3, 4, and 5 are all vehicles traveling on the road. ① and ② together constitute the scanning space range with the current vehicle (the vehicle) as the center of the sphere. The size of this range can be set according to the performance of the scanning device. Figure 6 It can be concluded that Figure 7 The schematic results show that the scanned materials can be divided into two categories: materials above the pavement level; and pavement and roadbed below the pavement level.

[0101] Further, based on Figure 6 The material distribution obtained after material scanning can be shown as follows Figure 8 shown. Figure 8 The substances represented by the numbers in the table have the following meanings:

[0102] Space 1: Through spectral analysis or other means of detecting material composition, it is determined that the composition of space 1 is oxygen atoms, nitrogen atoms, and hydrogen atoms. Based on their proportions, space 1 can be determined to be air.

[0103] Space 2: Through spectral analysis or other means of detecting material composition, it is determined that the components of space 2 are iron, aluminum, carbon, etc. Based on the composition and their proportions, it can be determined that space 2 is a solid substance;

[0104] Space 3: Through spectral analysis or other means of detecting material composition, it is determined that the components of space 3 are iron, aluminum, carbon, etc. Based on the composition and their proportions, it can be determined that space 3 is a solid substance;

[0105] Space 4: Through spectral analysis or other means of detecting material composition, it is determined that the composition of space 4 is oxygen atoms, nitrogen atoms, and hydrogen atoms. Based on their proportions, space 4 can be determined to be air.

[0106] Space 5: Through spectral analysis or other means of detecting material composition, it is determined that the components of space 5 are iron, aluminum, carbon, etc. Based on the composition and their proportions, it can be determined that space 5 is a solid substance;

[0107] Space 6: Through spectral analysis or other means of detecting material composition, it can be determined that the components of space 6 are iron, aluminum, carbon, etc. Based on the composition and their proportions, it can be determined that space 6 is a solid substance;

[0108] Space 7: Through spectral analysis or other means of detecting material composition, it is determined that the composition of space 7 is oxygen atoms, nitrogen atoms, and hydrogen atoms. Based on their proportions, space 7 can be determined to be air.

[0109] Space 8: Through spectral analysis or other means of detecting material composition, it is determined that the components of space 8 are iron, aluminum, carbon, etc. Based on the composition and their proportions, it can be determined that space 8 is a solid substance;

[0110] Space 9: Through spectral analysis or other means of detecting material composition, it is determined that the components within the space 9 are mainly silicon and the like. Based on the components and their proportions, it is determined that space 9 is a road surface and roadbed.

[0111] Space 10: Through spectral analysis or other means of detecting material composition, it is determined that the components within the range of space 10 are mainly oxygen atoms, nitrogen atoms, hydrogen atoms or water molecules. Based on the composition and their proportions, as well as the width, length, and height of the space being a certain distance below the road surface, it can be determined that space 10 is a pothole or a large amount of water.

[0112] Depend on Figure 8It can be seen that Space 1, Space 4, and Space 7 are spaces that the current vehicle (self-vehicle) can travel through, that is, the current vehicle (self-vehicle) can move horizontally and vertically in the continuous space formed by Space 1, Space 4, and Space 7.

[0113] according to Figure 8 The analysis results can be concluded as follows Figure 9 As shown in the driving path results, the current vehicle (the ego vehicle) has drivable spaces along routes ①, ②, ③, and ④. However, route ① faces a solid line (supplemented by navigation or visual solutions). Due to traffic regulations, route ① is deemed infeasible. Therefore, the current vehicle (the ego vehicle) has routes ② and ③. During driving, the vehicle's power and chassis coordination can be determined based on routes ② and ③. However, after changing lanes along route ②, if route ④ is desired, it is not feasible.

[0114] Scenario 3: Scan the material composition within the preset scanning space with the current vehicle (self-vehicle) as the center of the sphere, such as Figure 10 As shown, Figure 10 1, 2, 3, 4, and 5 are all vehicles traveling on the road. ① and ② together constitute the scanning space range with the current vehicle (the vehicle) as the center of the sphere. The size of this range can be set according to the performance of the scanning device. Figure 10 It can be concluded that Figure 11 The schematic results show that the scanned materials can be divided into two categories: materials above the pavement level; and pavement and roadbed below the pavement level.

[0115] Further, based on Figure 11 The material distribution obtained after material scanning can be shown as follows Figure 12 shown. Figure 12 The substances represented by the numbers in the table have the following meanings:

[0116] Space 1: Through spectral analysis or other means of detecting material composition, it is determined that the composition of space 1 is oxygen atoms, nitrogen atoms, and hydrogen atoms. Based on their proportions, space 1 can be determined to be air.

[0117] Space 2: Through spectral analysis or other means of detecting material composition, it is determined that the components of space 2 are iron, aluminum, carbon, etc. Based on the composition and their proportions, it can be determined that space 2 is a solid substance;

[0118] Space 3: Through spectral analysis or other means of detecting material composition, it is determined that the components of space 3 are iron, aluminum, carbon, etc. Based on the composition and their proportions, it can be determined that space 3 is a solid substance with an irregular shape.

[0119] Space 4: Through spectral analysis or other means of detecting material composition, it is determined that the composition of space 4 is oxygen atoms, nitrogen atoms, and hydrogen atoms. Based on their proportions, space 4 can be determined to be air.

[0120] Space 5: Through spectral analysis or other means of detecting material composition, it is determined that the components of space 5 are iron, aluminum, carbon, etc. Based on the composition and their proportions, it can be determined that space 5 is a solid substance;

[0121] Space 6: Through spectral analysis or other means of detecting material composition, it can be determined that the components of space 6 are iron, aluminum, carbon, etc. Based on the composition and their proportions, it can be determined that space 6 is a solid substance;

[0122] Space 7: Through spectral analysis or other means of detecting material composition, it is determined that the composition of space 7 is oxygen atoms, nitrogen atoms, and hydrogen atoms. Based on their proportions, space 7 can be determined to be air.

[0123] Space 8: Through spectral analysis or other means of detecting material composition, it is determined that the components of space 8 are iron, aluminum, carbon, etc. Based on the composition and their proportions, it can be determined that space 8 is a solid substance;

[0124] Space 9: Through spectral analysis or other means of detecting material composition, it is determined that the components within the space 9 are mainly silicon and the like. Based on the components and their proportions, it is determined that space 9 is a road surface and roadbed.

[0125] Space 10: Through spectral analysis or other means of detecting material composition, the oxygen atoms, nitrogen atoms, and hydrogen atoms in the space range of 10 can be determined. According to their proportions, space 7 can be determined to be air.

[0126] Depend on Figure 12 It can be seen that Space 1, Space 4, and Space 7 are spaces that the current vehicle (self-vehicle) can travel through, that is, the current vehicle (self-vehicle) can move horizontally and vertically in the continuous space formed by Space 1, Space 4, and Space 7.

[0127] according to Figure 12 The analysis results can be concluded as follows Figure 13 As shown in the driving path results, the current vehicle (the ego vehicle) has drivable spaces along routes ①, ②, ③, and ④. However, route ① faces a solid line (supplemented by navigation or visual solutions). Due to traffic regulations, route ① is deemed infeasible. Therefore, the current vehicle (the ego vehicle) has routes ②, ③, and ④. During driving, the powertrain and chassis coordination of the current vehicle (the ego vehicle) can be determined based on routes ② and ③.

[0128] According to the method for determining a driving path based on material composition analysis proposed in an embodiment of the present application, by performing a material composition scan on a preset scanning space range with the current vehicle as the center, material composition data for at least one location point within the preset scanning space range can be obtained; based on the material composition data of at least one location point, the material properties of each location point can be determined according to a preset material property data set; based on the material properties of each location point, the material distribution within the preset scanning space range is determined, and based on the material distribution, the drivable space area of ​​the current vehicle is determined, and the driving path of the current vehicle is determined based on the drivable space area. This solves the problem of the prior art in road material recognition, where visual illusions lead to misidentification or non-recognition of road objects, which in turn leads to incorrect driving strategies, thereby improving the probability of object recognition and driving safety.

[0129] Next, a device for determining a driving path based on material composition analysis according to an embodiment of the present application will be described with reference to the accompanying drawings.

[0130] Figure 14 It is a block diagram of an apparatus for determining a driving path based on material composition analysis according to an embodiment of the present application.

[0131] like Figure 14 As shown, the device 10 for determining a driving path based on material composition analysis includes: an acquisition module 100 , a first determination module 200 and a second determination module 300 .

[0132] The acquisition module 100 is configured to perform a material composition scan on a preset scanning space with the current vehicle as the center, and acquire material composition data of at least one position point in the preset scanning space;

[0133] A first determination module 200 is configured to determine the material properties of each location point based on the material composition data of at least one location point and a preset material property data set;

[0134] The second determination module 300 is used to determine the material distribution within the preset scanning space range according to the material properties of each location point, and based on the material distribution, determine the drivable space area of ​​the current vehicle, and determine the driving path of the current vehicle based on the drivable space area.

[0135] Optionally, in some embodiments, the second determining module 300 is specifically configured to:

[0136] Based on the material distribution, determine whether the gas space constitutes a preset continuous channel;

[0137] In the case where the gas space constitutes a preset continuous channel, a target continuous channel that meets the preset driving requirements is screened out from the preset continuous channels based on the size information of the preset continuous channel and the size information of the current vehicle, and the target continuous channel is used as the drivable space area of ​​the current vehicle.

[0138] Optionally, in some embodiments, the second determining module 300 is specifically configured to:

[0139] Get traffic rules set and current navigation information;

[0140] Based on the current navigation information, the preset path planning algorithm is used to plan the current vehicle's driving path set according to the drivable space area;

[0141] Based on the traffic rule set, each driving path in the driving path set is verified, and according to the verification result, a driving path in the driving path set that meets the preset traffic rules is determined as a target driving path.

[0142] Optionally, in some embodiments, after acquiring material composition data of at least one position point in a preset scanning space range, the acquisition module 100 is further configured to:

[0143] Storing material composition data of at least one location point in a preset data buffer, and determining whether new material composition data enters the preset data buffer;

[0144] When new material composition data enters the preset data buffer, determining whether the accumulated amount of the new material composition data is greater than or equal to a preset threshold;

[0145] When the accumulated amount of new material composition data is greater than or equal to a preset threshold, a preset update algorithm is triggered, and the material composition data in the local material composition database is updated based on the preset update algorithm.

[0146] Optionally, in some embodiments, the material composition data includes elemental composition and ratios of elemental composition.

[0147] It should be noted that the above explanation of the embodiment of the method for determining a driving path based on material composition analysis is also applicable to the device for determining a driving path based on material composition analysis in this embodiment, and will not be repeated here.

[0148] According to the device for determining a driving path based on material composition analysis proposed in an embodiment of the present application, by performing a material composition scan on a preset scanning space range with the current vehicle as the center, material composition data for at least one location point within the preset scanning space range can be obtained; based on the material composition data of at least one location point, the material properties of each location point can be determined according to a preset material property data set; based on the material properties of each location point, the material distribution within the preset scanning space range is determined, and based on the material distribution, the drivable space area of ​​the current vehicle is determined, and the driving path of the current vehicle is determined based on the drivable space area. This solves the problem of the prior art in road material recognition, where visual illusions lead to misidentification or non-recognition of road objects, which in turn leads to incorrect driving strategies, thereby improving the probability of object recognition and driving safety.

[0149] Figure 15 A schematic diagram of the structure of a vehicle provided in an embodiment of the present application. The vehicle may include:

[0150] Memory 1501 , processor 1502 , and computer programs stored in the memory 1501 and executable on the processor 1502 .

[0151] When the processor 1502 executes the program, the method for determining the driving path based on material composition analysis provided in the above embodiment is implemented.

[0152] Furthermore, the vehicle further comprises:

[0153] The communication interface 1503 is used for communication between the memory 1501 and the processor 1502 .

[0154] The memory 1501 is used to store computer programs that can be run on the processor 1502 .

[0155] The memory 1501 may include a high-speed RAM (Random Access Memory) memory, and may also include a non-volatile memory, such as at least one disk memory.

[0156] If the memory 1501, the processor 1502, and the communication interface 1503 are implemented independently, the communication interface 1503, the memory 1501, and the processor 1502 can be connected to each other via a bus and communicate with each other. The bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 15 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0157] Optionally, in a specific implementation, if the memory 1501, the processor 1502 and the communication interface 1503 are integrated on a chip, the memory 1501, the processor 1502 and the communication interface 1503 can communicate with each other through an internal interface.

[0158] The processor 1502 may be a CPU (Central Processing Unit), or an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present application.

[0159] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for determining a driving path based on material composition analysis.

[0160] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of such features. Throughout the description of this application, "plurality" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0161] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0162] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for determining a driving path based on material composition analysis, characterized in that: The following steps are involved: Performing a material composition scan on a preset scanning space range with the current vehicle as the center, and obtaining material composition data of at least one position point in the preset scanning space range; Determining the material properties of each location point based on the material composition data of the at least one location point and according to a preset material property data set; According to the material properties of each location point, the material distribution within the preset scanning space range is determined, and based on the material distribution, the drivable space area of ​​the current vehicle is determined, and the driving path of the current vehicle is determined based on the drivable space area.

2. The method according to claim 1, characterized in that The determining of the drivable space area of ​​the current vehicle based on the material distribution includes: Based on the substance distribution, determining whether the gas space constitutes a preset continuous channel; In the case where the gas space constitutes the preset continuous channel, a target continuous channel that meets the preset driving requirements is screened out from the preset continuous channels based on the size information of the preset continuous channel and the size information of the current vehicle, and the target continuous channel is used as the drivable space area of ​​the current vehicle.

3. The method according to claim 2, characterized in that The determining of the target driving path of the current vehicle based on the drivable space area includes: Get traffic rules set and current navigation information; Based on the current navigation information, a preset path planning algorithm is used to plan a set of driving paths for the current vehicle according to the drivable space area; Based on the traffic rule set, each driving path in the driving path set is verified, and according to the verification result, a driving path in the driving path set that meets the preset traffic rules is determined as the target driving path.

4. The method according to claim 1, wherein After obtaining material composition data of at least one position point in the preset scanning space range, the method further includes: Storing the material composition data of the at least one location point in a preset data buffer, and determining whether new material composition data enters the preset data buffer; In the case where the new material composition data enters the preset data buffer, determining whether the accumulated amount of the new material composition data is greater than or equal to a preset threshold; When the accumulated amount of the new material composition data is greater than or equal to the preset threshold, a preset update algorithm is triggered, and the material composition data in the local material composition database is updated based on the preset update algorithm.

5. The method according to claim 1, wherein The material composition data includes elemental composition and ratio of elemental composition.

6. A device for determining a driving path based on material composition analysis, characterized in that: include: an acquisition module, configured to perform a material composition scan on a preset scanning space range with the current vehicle as the center, and acquire material composition data of at least one position point in the preset scanning space range; A first determining module, configured to determine the material properties of each location point based on the material composition data of the at least one location point and a preset material property data set; The second determination module is used to determine the material distribution within the preset scanning space range according to the material properties of each location point, and based on the material distribution, determine the drivable space area of ​​the current vehicle, and determine the driving path of the current vehicle based on the drivable space area.

7. The device according to claim 6, characterized in that The second determining module is specifically configured to: Based on the substance distribution, determining whether the gas space constitutes a preset continuous channel; In the case where the gas space constitutes the preset continuous channel, a target continuous channel that meets the preset driving requirements is screened out from the preset continuous channels based on the size information of the preset continuous channel and the size information of the current vehicle, and the target continuous channel is used as the drivable space area of ​​the current vehicle.

8. The device according to claim 7, characterized in that The second determining module is specifically configured to: Get traffic rules set and current navigation information; Based on the current navigation information, a preset path planning algorithm is used to plan a set of driving paths for the current vehicle according to the drivable space area; Based on the traffic rule set, each driving path in the driving path set is verified, and according to the verification result, a driving path in the driving path set that meets the preset traffic rules is determined as the target driving path.

9. A vehicle, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for determining a driving path based on material composition analysis as described in any one of claims 1 to 5.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the method for determining a driving path based on material composition analysis as described in any one of claims 1 to 5.

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