Vehicle positioning method, electronic equipment and storage medium

Abstract

The invention discloses a vehicle positioning method, electronic equipment and a storage medium. The method comprises the steps that first sensing information sent by a vehicle and second sensing information sent by road end equipment are acquired, and the road end equipment is located on a road where the vehicle runs; based on the first acquisition time of the first sensing information and the second acquisition time of the second sensing information, performing space-time alignment on the first sensing information and the second sensing information to obtain aligned first sensing information and aligned second sensing information; and positioning the vehicle based on the aligned first sensing information and the aligned second sensing information to obtain a positioning result of the vehicle. According to the invention, the technical problem of low vehicle positioning accuracy in the prior art is solved.

Description

Technical Field

[0001] The present application relates to the field of intelligent network connection technology, and more specifically, to a vehicle positioning method, an electronic device and a storage medium. Background Art

[0002] With the rapid development of intelligent network technology, the practical application of autonomous vehicles is gradually expanding. Traditional vehicle positioning methods usually rely on the Global Positioning System (GPS), but in complex environments, GPS signals are easily interfered and blocked, resulting in low vehicle positioning accuracy.

[0003] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0004] The embodiments of the present application provide a vehicle positioning method, an electronic device, and a storage medium to at least solve the technical problem of low vehicle positioning accuracy in the related art.

[0005] According to one aspect of an embodiment of the present application, a vehicle positioning method is provided, including: acquiring first perception information sent by the vehicle, and second perception information sent by a road-side device, wherein the road-side device is located on a road on which the vehicle is traveling; based on a first acquisition time of the first perception information and a second acquisition time of the second perception information, performing spatiotemporal alignment on the first perception information and the second perception information to obtain aligned first perception information and aligned second perception information; based on the aligned first perception information and the aligned second perception information, performing positioning on the vehicle to obtain a positioning result of the vehicle.

[0006] According to another aspect of an embodiment of the present application, a vehicle positioning method is also provided, including: acquiring a first perception feature sent by the vehicle and a second perception feature sent by a road-side device, wherein the road-side device is located on the road where the vehicle is traveling, the first perception feature is a feature obtained by extracting features from first perception information collected by the vehicle, and the second perception feature is a feature obtained by extracting features from second perception information collected by the road-side device; based on a first collection time of the first perception information and a second collection time of the second perception information, performing spatiotemporal alignment on the first perception feature and the second perception feature to obtain an aligned first perception feature and an aligned second perception feature; based on the aligned first perception feature and the aligned second perception feature, positioning the vehicle to obtain a positioning result of the vehicle.

[0007] According to another aspect of an embodiment of the present application, another vehicle positioning method is provided, including: responding to an input instruction acting on an operation interface, displaying first perception information sent by the vehicle and second perception information sent by a road-side device on the operation interface, wherein the road-side device is located on the road on which the vehicle is traveling; responding to a vehicle instruction acting on the operation interface, displaying a positioning result of the vehicle on the operation interface, wherein the positioning result is a result of positioning the vehicle based on the aligned first perception information and the aligned second perception information, and the aligned first perception information and the aligned second perception information are obtained by spatiotemporally aligning the first perception information and the second perception information based on a first acquisition time of the first perception information and a second acquisition time of the second perception information.

[0008] According to another aspect of an embodiment of the present application, another vehicle positioning method is provided, including: obtaining first perception information and second perception information by calling a first interface, wherein the first interface includes a first parameter, and the parameter value of the first parameter is the first perception information and the second perception information, and the road end equipment is located on the road where the vehicle is traveling; based on the first acquisition time of the first perception information and the second acquisition time of the second perception information, the first perception information and the second perception information are temporally and spatially aligned to obtain the aligned first perception information and the aligned second perception information; based on the aligned first perception information and the aligned second perception information, the vehicle is positioned to obtain a positioning result of the vehicle; and the positioning result of the vehicle is output by calling a second interface, wherein the second interface includes a second parameter, and the parameter value of the second parameter is the positioning result of the vehicle.

[0009] According to another aspect of an embodiment of the present application, an electronic device is further provided, including: a memory storing an executable program; and a processor for running the program, wherein any one of the above methods is executed when the program is running.

[0010] According to another aspect of an embodiment of the present application, a computer-readable storage medium is further provided, which includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute any one of the above methods.

[0011] In the embodiment of the present application, the first perception information sent by the vehicle and the second perception information sent by the roadside device are obtained; based on the first acquisition time of the first perception information and the second acquisition time of the second perception information, the first perception information and the second perception information are temporally and spatially aligned to obtain the aligned first perception information and the aligned second perception information; based on the aligned first perception information and the aligned second perception information, the vehicle is positioned to obtain the positioning result of the vehicle. It is easy to notice that the first perception information and the second perception information can be temporally and spatially aligned, and the aligned first perception information and the aligned second perception information can be used to position the vehicle, thereby compensating for the communication delay, so that in the process of collaborative positioning using the first perception information collected by the vehicle and the second perception information collected by the roadside device, a more accurate positioning result can be obtained, thereby improving the positioning accuracy of the vehicle, and further solving the technical problem of low positioning accuracy of the vehicle in the related art.

[0012] It is easy to notice that the above general description and the following detailed description are only for the purpose of exemplifying and explaining the present application, and do not constitute a limitation of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0014] Figure 1 is a schematic diagram of an application scenario of a vehicle positioning method according to an embodiment of the present application;

[0015] Figure 2 is a flow chart of a vehicle positioning method according to Embodiment 1 of the present application;

[0016] Figure 3 is a schematic diagram of vehicle positioning according to an embodiment of the present application;

[0017] Figure 4 is a flow chart of a vehicle positioning method according to Embodiment 2 of the present application;

[0018] Figure 5 is a flow chart of a vehicle positioning method according to Embodiment 3 of the present application;

[0019] Figure 6 is a flow chart of a vehicle positioning method according to Embodiment 4 of the present application;

[0020] Figure 7 is a schematic diagram of a vehicle positioning device according to Embodiment 1 of the present application;

[0021] Figure 8is a schematic diagram of a vehicle positioning device according to Embodiment 2 of the present application;

[0022] Fig. 9 is a schematic diagram of a vehicle positioning device according to Embodiment 3 of the present application;

[0023] Fig.10 is a schematic diagram of a vehicle positioning device according to Embodiment 4 of the present application;

[0024] Fig.11 It is a structural block diagram of a computer terminal according to an embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this application.

[0026] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] First, some nouns or terms that appear in the description of the embodiments of the present application are subject to the following explanations:

[0028] Road-end equipment: It can be sensors on the intelligent connected road section where the vehicle is currently traveling, for example, cameras, lidar and other equipment on the road section where the vehicle is currently traveling.

[0029] Deep neural network: a machine learning technology with a network structure composed of multiple layers of neurons, which is used to process and analyze large amounts of data and can perform tasks such as feature extraction, classification, and prediction.

[0030] Feature extraction: It can be to extract representative features from raw data to facilitate machine learning algorithms to analyze and process the data.

[0031] Feature fusion: It can be the merging of feature information from different sources, types or forms to obtain a more complete and accurate feature representation.

[0032] RTK (Real Time Kinematic, carrier phase differential technology) positioning: a technology that can use the carrier phase information provided by the global satellite navigation system to perform high-precision positioning.

[0033] Transformer model: It can be a deep learning network based on the self-attention mechanism, which is often used in natural language processing and computer vision tasks.

[0034] Caffe (Convolutional Architecture For Fast Feature Embedding, convolutional neural network framework): can be a commonly used deep learning framework.

[0035] PyTorch: It can be an open source python machine learning library based on Torch, which can be used for natural language processing. Torch is a data structure containing multi-dimensional tensors and python is a language.

[0036] Tensorflow: It can be an artificial intelligence learning system, which is applied to many machine learning and deep learning fields such as speech recognition and image recognition.

[0037] Spatiotemporal alignment: It can refer to predicting feature information at the same timestamp based on perception information at different timestamps.

[0038] Example 1

[0039] According to an embodiment of the present application, a method embodiment of a vehicle positioning method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0040] In an optional embodiment, the above vehicle positioning method can be applied to Figure 1 The application scenarios shown are not limited to these. Figure 1 is a schematic diagram of an application scenario of a vehicle positioning method according to an embodiment of the present application. Figure 1In the application scenario shown, the vehicle 10 and the roadside device 20 can communicate with the server 40 through the network 30. The vehicle 10 may include but is not limited to a variety of different types of sensors, such as cameras, laser radars, RTK positioning sensors and communication devices, and the roadside device 20 may include but is not limited to a single type of sensor and communication device. The server 40 may perform the following steps in the vehicle positioning method: obtaining the first perception information sent by the vehicle and the second perception information sent by the roadside device, wherein the roadside device is located on the road where the vehicle is traveling; based on the first acquisition time of the first perception information and the second acquisition time of the second perception information, the first perception information and the second perception information are spatiotemporally aligned to obtain the aligned first perception information and the aligned second perception information; based on the aligned first perception information and the aligned second perception information, the vehicle is positioned to obtain the positioning result of the vehicle.

[0041] Under the above operating environment, this application provides Figure 2 The vehicle positioning method shown. Figure 2 is a flow chart of a vehicle positioning method according to Embodiment 1 of the present application, such as Figure 2 As shown, the method comprises the following steps:

[0042] Step S202: Acquire first perception information sent by the vehicle and second perception information sent by a road-side device, wherein the road-side device is located on the road on which the vehicle is traveling.

[0043] The above-mentioned first perception information may be information perceived by the vehicle. Optionally, environmental information around the vehicle may be acquired through sensors on the vehicle, wherein the sensors on the vehicle may include cameras, lidars, RTK positioning and other sensors, wherein the environmental information around the vehicle may include information such as the position, speed, shape and the like of other vehicles around the vehicle, as well as information such as the position, speed, posture and the like of the vehicle itself.

[0044] The above-mentioned second perception information may be the perception information collected by the road-side equipment. Specifically, it may include environmental information within the road section where the vehicle is currently traveling, such as lane lines, traffic signs, road conditions, etc., as well as information such as the position, speed and behavior of other vehicles and pedestrians on the road section.

[0045] In an optional embodiment, the position, speed, shape of other vehicles around the vehicle, as well as the position, speed, posture and other information of the vehicle itself can be obtained by various sensors such as cameras, lidars, RTK positioning, etc. on the vehicle, that is, the first perception information. And through the cameras, lidars and other sensors on the intelligent networked section where the vehicle is located, the lane lines, traffic signs, road conditions and other information in the intelligent networked section where the vehicle is located, as well as the position, speed and behavior of other vehicles and pedestrians on the section, that is, the second perception information, can be obtained. Furthermore, the first perception information obtained and the second perception information obtained can be uploaded to the cloud, and the data can be processed in the cloud, so that the vehicle can be accurately positioned.

[0046] Step S204: based on the first collection time of the first perception information and the second collection time of the second perception information, the first perception information and the second perception information are temporally and spatially aligned to obtain aligned first perception information and aligned second perception information.

[0047] The first acquisition time mentioned above may be the time when the vehicle perceives the first perception information. In order to facilitate uploading the first acquisition time to the cloud, the first acquisition time may be used as the timestamp of the first perception information. Similarly, the second acquisition time may be used as the timestamp of the second perception information.

[0048] In an optional embodiment, the Transformer architecture, or a spatiotemporal prediction deep model of an architecture such as caffe, PyTorch, or Tensorflow can be used to take the first perception information and the timestamp corresponding to the first perception information, and the second perception information and the timestamp corresponding to the second perception information as input, so that the first perception information and the second perception information aligned to the same timestamp can be output, that is, the aligned first perception information and the aligned second perception information. Optionally, the above method helps to compensate for communication delays, so that more accurate results can be obtained in the collaborative positioning process using the first perception information collected by the vehicle and the second perception information collected by the roadside device.

[0049] Step S206: Based on the aligned first perception information and the aligned second perception information, the vehicle is positioned to obtain a positioning result of the vehicle.

[0050] In an optional embodiment, after obtaining the aligned first perception information and the aligned second perception information, the aligned first perception information and the aligned second perception information can be fused, and the fused result can be converted into accurate positioning information of the vehicle in the intelligent connected road section, thereby realizing collaborative positioning using the vehicle side and the road side, and improving the accuracy of vehicle positioning, thereby improving the safety and efficiency of autonomous driving vehicles in application scenarios such as path planning and control strategies of vehicle autonomous driving systems.

[0051] In the embodiment of the present application, the first perception information sent by the vehicle and the second perception information sent by the roadside device are obtained; based on the first acquisition time of the first perception information and the second acquisition time of the second perception information, the first perception information and the second perception information are temporally and spatially aligned to obtain the aligned first perception information and the aligned second perception information; based on the aligned first perception information and the aligned second perception information, the vehicle is positioned to obtain the positioning result of the vehicle. It is easy to notice that the first perception information and the second perception information can be temporally and spatially aligned, and the aligned first perception information and the aligned second perception information can be used to position the vehicle, thereby compensating for the communication delay, so that in the process of collaborative positioning using the first perception information collected by the vehicle and the second perception information collected by the roadside device, a more accurate positioning result can be obtained, thereby improving the positioning accuracy of the vehicle, and further solving the technical problem of low positioning accuracy of the vehicle in the related art.

[0052] In the above embodiment of the present application, based on the first acquisition time of the first perception information and the second acquisition time of the second perception information, the first perception information and the second perception information are temporally and spatially aligned to obtain the aligned first perception information and the aligned second perception information, including: respectively extracting the first perception information and the second perception information to obtain the first perception feature of the first perception information and the second perception feature of the perception information; respectively encoding the first acquisition time and the second acquisition time to obtain the first time feature of the first acquisition time and the second time feature of the second acquisition time; performing temporal and spatial alignment based on the first perception feature, the second perception feature, the first time feature and the second time feature to obtain the aligned first perception feature and the aligned second perception feature; determining the aligned first perception information based on the aligned first perception feature, and determining the aligned second perception information based on the aligned second perception feature.

[0053] In an optional embodiment, after the first perception information and the second perception information are obtained, a deep neural network, such as a convolutional neural network, a point cloud processing network, etc., can be used to extract features from the first perception information and the second perception information. Optionally, the extracted features may include features such as edges, textures, shapes, key points, etc. Optionally, the first perception features and the second perception features can be uploaded to the cloud via vehicle-road communication, thereby achieving spatiotemporal alignment and feature fusion.

[0054] Furthermore, the first acquisition time and the second acquisition time can be encoded respectively to obtain the first time feature of the first acquisition time and the second time feature of the second acquisition time. Therefore, in the process of using the spatiotemporal prediction deep model to perform spatiotemporal alignment operations, not only the first perception information collected by the vehicle side and the second perception information collected by the road side equipment are considered, but also the first acquisition time corresponding to the first perception information and the second acquisition time corresponding to the second perception information are considered, thereby realizing compensation for communication delays and improving the accuracy of vehicle positioning.

[0055] In the above embodiment of the present application, spatiotemporal alignment is performed based on the first perceptual feature, the second perceptual feature, the first time feature, and the second time feature to obtain the aligned first perceptual feature and the aligned second perceptual feature, including: splicing the first perceptual feature, the second perceptual feature, the first time feature, and the second time feature to obtain a spliced ​​feature; based on the spliced ​​feature, predicting the aligned first perceptual feature and the aligned second perceptual feature, wherein the aligned first perceptual feature and the aligned second perceptual feature correspond to the same acquisition time.

[0056] In an optional embodiment, after obtaining the first perception feature, the second perception feature, the first time feature, and the second time feature, the first perception feature and the first time feature, the second time feature and the second perception feature can be spliced, or the first perception feature and the second time feature, the second time feature and the first perception feature can be spliced ​​to generate a corresponding time series, and the time series is determined as a spliced ​​feature. Furthermore, the aligned first perception feature and the aligned second perception feature can be predicted based on the time feature, thereby compensating for the communication delay and improving the accuracy of vehicle positioning.

[0057] In the above embodiments of the present application, the vehicle is positioned based on the aligned first perception information and the aligned second perception information to obtain a positioning result of the vehicle, including: fusing the aligned first perception information and the aligned second perception information to obtain fused information; and positioning the vehicle based on the fused information to obtain a positioning result of the vehicle.

[0058] The above-mentioned fusion information may be the first perception information and the second perception information after time alignment.

[0059] The above positioning result may be the current location of the vehicle.

[0060] In an optional embodiment, the aligned first perception information and the aligned second perception information can be spliced ​​through a related multimodal deep learning model, and the spliced ​​results can be fused to obtain fused information, thereby enhancing the perception capability of the vehicle positioning system, optimizing the positioning results, and improving the accuracy of the positioning results. The multimodal deep learning model here can be a model provided in the relevant technology, and this application does not specifically limit this.

[0061] In the above embodiment of the present application, the aligned first perception information and the aligned second perception information are fused to obtain fused information, including: determining the point cloud data and visual data in the aligned first perception information and the aligned second perception information; fusing the point cloud data and the visual data to obtain fused information.

[0062] The above-mentioned point cloud data can be the perception information collected by the laser radar on the vehicle in the first perception information after alignment, and the perception information collected by the laser radar on the intelligent connected road section where the vehicle is located in the second perception information after alignment.

[0063] The above-mentioned visual data can be the perception information collected by the camera on the vehicle in the first perception information after alignment, and the perception information collected by the camera on the intelligent connected road section where the vehicle is located in the second perception information after alignment.

[0064] In an optional embodiment, when the aligned first perception information and the aligned second perception information are fused, the point cloud data collected by the laser radar on the vehicle and the visual data collected by the camera on the vehicle can be determined from the aligned first perception information, and the point cloud data collected by the laser radar on the intelligent connected road section where the vehicle is located and the visual data collected by the camera on the intelligent connected road section where the vehicle is located can be determined from the aligned second perception information, so that the point cloud data and visual data collected by different devices can be fused, and ultimately the accuracy of the positioning results can be improved.

[0065] In the above embodiments of the present application, point cloud data and visual data are fused to obtain fusion information, including: converting the point cloud data to a preset space to obtain point cloud features, and converting the visual data to a preset space to obtain visual features; encoding the point cloud features and the visual features to obtain fusion features; and determining the fusion information based on the fusion features.

[0066] The above-mentioned preset space may be a BEV (Bird's Eye View) feature layer.

[0067] In an optional embodiment, the point cloud data and visual data can be converted to the BEV feature layer through a relevant multimodal deep learning model to obtain point cloud features and visual features. Furthermore, the BEV feature layer can be used to encode the point cloud features and visual features to obtain fusion features. Optionally, after obtaining the fusion features, corresponding fusion information can be determined based on the fusion features, that is, the first perception information and the second perception information after time alignment are obtained, so that the fusion information can be used to determine the positioning result of the vehicle.

[0068] In the above-mentioned embodiment of the present application, based on the first acquisition time of the first perception information and the second acquisition time of the second perception information, the first perception information and the second perception information are temporally and spatially aligned to obtain the aligned first perception information and the aligned second perception information, including: preprocessing the first perception information and the second perception information to obtain the first preprocessing information and the second preprocessing information; based on the first acquisition time of the first perception information and the second acquisition time of the second perception information, the first preprocessing information and the second preprocessing information are temporally and spatially aligned to obtain the aligned first perception information and the aligned second perception information.

[0069] The above-mentioned preprocessing can be used to eliminate interference factors such as noise, illumination change, motion blur, etc. in the first perception information and the second perception information. By performing preprocessing, more accurate data can be obtained.

[0070] In an optional embodiment, before the first perception information and the second perception information are spatiotemporally aligned, the first perception information and the second perception information may be preprocessed by using techniques such as image enhancement, filtering, and denoising, so as to remove interference factors such as noise, illumination change, and motion blur in the first perception information and the second perception information, and obtain the first preprocessed information and the second preprocessed information. Furthermore, the first preprocessed information and the second preprocessed information may be spatiotemporally aligned based on the first acquisition time of the first perception information and the second acquisition time of the second perception information.

[0071] In the above embodiment of the present application, obtaining the first perception information sent by the vehicle includes: determining at least one vehicle traveling within a preset range of the vehicle; obtaining the perception information sent by at least one vehicle to obtain the first perception information.

[0072] The above-mentioned preset range can be set by those skilled in the art according to their needs, and the size of the preset range is not specifically limited in this application.

[0073] In an optional embodiment, a preset range can be determined first, and then at least one vehicle can be determined within the preset range, and perception information collected by the laser radar and camera on the vehicle can be obtained, and the perception information collected by the laser radar and camera on the vehicle can be determined as the first perception information.

[0074] In the above embodiment of the present application, after positioning the vehicle based on the aligned first perception information and the aligned second perception information to obtain the positioning result of the vehicle, the method also includes: generating control information or a driving path of the vehicle based on the positioning result of the vehicle; and controlling the vehicle based on the control information or the driving path.

[0075] The above control information can be used to indicate the vehicle's forward direction during driving.

[0076] The above-mentioned driving route can represent the travel information of the vehicle.

[0077] In an optional embodiment, after obtaining the positioning result of the vehicle, corresponding control information and driving path can be generated according to the positioning result, so as to improve the safety and efficiency of the autonomous driving vehicle in application scenarios such as path planning and control strategy of the autonomous driving system.

[0078] Figure 3 is a schematic diagram of vehicle positioning according to an embodiment of the present application, such as Figure 3 As shown, the first perception information of the vehicle side and the second perception information of the road side can be collected. After the first perception information and the second perception information are collected, the first perception information and the second perception information can be preprocessed respectively. Furthermore, feature extraction can be performed on the preprocessed first perception information and the preprocessed second perception information respectively, and the results obtained after feature extraction can be used to align the space and time of the vehicle-side data and the road-side data, and finally feature fusion can be performed to obtain a fusion result.

[0079] By adopting the embodiments of the present application, the communication delay can be compensated by aligning the first perception information and the second perception information in time and space; in the vehicle positioning process, the positioning accuracy and robustness are improved by fusing the vehicle's own perception information and the perception information of the road-side equipment, so that the positioning error can be reduced in complex scenes and dynamic environments; by effectively fusing laser point cloud data and visual data at the feature level, the perception ability of the positioning system is improved, the positioning results are further optimized, and the adaptability of the positioning system in different scenes and environmental conditions is enhanced.

[0080] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0081] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0082] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, disk, CD), including several instructions for enabling a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0083] Example 2

[0084] According to an embodiment of the present application, a vehicle positioning method is also provided. Figure 4 is a flow chart of a vehicle positioning method according to Embodiment 2 of the present application, such as Figure 4 As shown, the method comprises the following steps:

[0085] Step S402: Acquire a first perception feature sent by the vehicle and a second perception feature sent by a road-side device, wherein the road-side device is located on the road on which the vehicle is traveling, the first perception feature is a feature extracted from first perception information collected by the vehicle, and the second perception feature is a feature extracted from second perception information collected by the road-side device.

[0086] Step S404: based on the first acquisition time of the first perception information and the second acquisition time of the second perception information, the first perception feature and the second perception feature are temporally and spatially aligned to obtain the aligned first perception feature and the aligned second perception feature.

[0087] Step S406: Positioning the vehicle based on the aligned first perception features and the aligned second perception features to obtain a positioning result of the vehicle.

[0088] In an optional embodiment, after the vehicle collects the first perception information, the first perception information may be first extracted, and the first perception feature obtained after the feature extraction may be uploaded to the cloud. Alternatively, the vehicle may first upload the collected first perception information to the cloud, and then extract the first perception information in the cloud to obtain the first perception feature. At the same time, after the road-side device collects the second perception information, the second perception information may be first extracted, and the second perception feature obtained after the feature extraction may be uploaded to the cloud. Alternatively, the road-side device may first upload the collected second perception information to the cloud, and then extract the second perception information in the cloud to obtain the second perception feature.

[0089] Furthermore, after acquiring the first perception feature and the second perception feature, the first perception feature and the second perception feature can be aligned in time and space to obtain the aligned first perception feature and the aligned second perception feature, and the aligned first perception feature and the aligned second perception feature can be used to locate the vehicle, thereby compensating for the communication delay and improving the accuracy of vehicle positioning.

[0090] It should be noted that the preferred implementation scheme involved in the above embodiments of the present application is the same as the scheme provided in Example 1, as well as the application scenario and implementation process, but is not limited to the scheme provided in Example 1.

[0091] Example 3

[0092] According to an embodiment of the present application, another vehicle positioning method is also provided. Figure 5 is a flow chart of a vehicle positioning method according to Embodiment 3 of the present application, such as Figure 5 As shown, the method comprises the following steps:

[0093] Step S502: In response to an input instruction on the operation interface, first perception information sent by the vehicle and second perception information sent by a road-side device are displayed on the operation interface, wherein the road-side device is located on the road on which the vehicle is traveling.

[0094] The above-mentioned operation interface can be a display interface of a computer terminal, a display interface of a mobile terminal, or a central control display screen on a vehicle. Optionally, the type of operation interface is not specifically limited in this application.

[0095] The above-mentioned input instructions can be used to instruct the operation interface to display the first perception information sent by the vehicle and the second perception information sent by the road-side device. Optionally, the above-mentioned input instructions can be expressed in the form of text display or in the form of voice. This application does not impose specific restrictions on the representation method of the input instructions.

[0096] Step S504: In response to the vehicle command on the operation interface, the positioning result of the vehicle is displayed on the operation interface, wherein the positioning result is a result of positioning the vehicle based on the aligned first perception information and the aligned second perception information, and the aligned first perception information and the aligned second perception information are obtained by spatiotemporally aligning the first perception information and the second perception information based on the first acquisition time of the first perception information and the second acquisition time of the second perception information.

[0097] The above-mentioned vehicle instructions can be used to instruct the operation interface to display the vehicle positioning results. Optionally, the above-mentioned vehicle instructions can be expressed in the form of text display or in the form of voice. The present application does not impose specific restrictions on the representation method of the vehicle instructions.

[0098] In an optional embodiment, when the operation interface receives an input command, the first perception information sent by the vehicle and the second perception information sent by the roadside device can be displayed on the operation interface. Furthermore, the first perception information and the second perception information can be spatiotemporally aligned by using the first acquisition time of the first perception information and the second acquisition time of the second perception information, thereby obtaining the aligned first perception information and the aligned second perception information, and determining the positioning result of the vehicle based on the aligned first perception information and the aligned second perception information. Optionally, when the operation interface receives a vehicle command, the positioning result can be displayed on the operation interface.

[0099] It should be noted that the preferred implementation scheme involved in the above embodiments of the present application is the same as the scheme provided in Example 1, as well as the application scenario and implementation process, but is not limited to the scheme provided in Example 1.

[0100] Example 4

[0101] According to an embodiment of the present application, another vehicle positioning method is provided. Figure 6 is a flow chart of a vehicle positioning method according to Embodiment 4 of the present application, such as Figure 6 As shown, the method comprises the following steps:

[0102] Step S602: Acquire the first perception information and the second perception information by calling the first interface, wherein the first interface includes a first parameter, a parameter value of the first parameter is the first perception information and the second perception information, and the road end device is located on the road on which the vehicle is traveling.

[0103] The first interface may be a Universal Serial Bus (USB) interface, or may be a virtual data transmission interface.

[0104] The above-mentioned first parameter can be used to represent the first perception information and the second perception information.

[0105] Step S604: based on the first acquisition time of the first perception information and the second acquisition time of the second perception information, the first perception information and the second perception information are temporally and spatially aligned to obtain aligned first perception information and aligned second perception information.

[0106] Step S606: Based on the aligned first perception information and the aligned second perception information, the vehicle is positioned to obtain a positioning result of the vehicle.

[0107] Step S608: Output the positioning result of the vehicle by calling the second interface, wherein the second interface includes a second parameter, and the parameter value of the second parameter is the positioning result of the vehicle.

[0108] The second interface mentioned above may be a USB interface, and the first interface mentioned above may also be a virtual data transmission interface.

[0109] The second parameter mentioned above can be used to represent the positioning result of the vehicle.

[0110] In an optional embodiment, the first perception information and the second perception information may be acquired through the first interface by means of data transmission. Optionally, after acquiring the first perception information and the second perception information, the first perception information and the second perception information may be time-space aligned based on the first acquisition time of the first perception information and the second acquisition time of the second perception information, thereby obtaining the aligned first perception information and the aligned second perception information. Furthermore, the vehicle may be positioned using the aligned first perception information and the aligned second perception information, and the positioning result generated by positioning the vehicle may be output through the second interface.

[0111] It should be noted that the preferred implementation scheme involved in the above embodiments of the present application is the same as the scheme provided in Example 1, as well as the application scenario and implementation process, but is not limited to the scheme provided in Example 1.

[0112] Example 5

[0113] According to an embodiment of the present application, a device for implementing the above vehicle positioning method is also provided. Figure 7 is a schematic diagram of a vehicle positioning device according to Example 1 of the present application, such as Figure 7As shown, the device includes: an acquisition module 702 , a processing module 704 and a positioning module 706 .

[0114] The acquisition module 702 is used to acquire the first perception information sent by the vehicle and the second perception information sent by the roadside device, wherein the roadside device is located on the road on which the vehicle is traveling. The processing module 704 is used to perform spatiotemporal alignment on the first perception information and the second perception information based on the first acquisition time of the first perception information and the second acquisition time of the second perception information to obtain the aligned first perception information and the aligned second perception information. The positioning module 706 is used to locate the vehicle based on the aligned first perception information and the aligned second perception information to obtain the positioning result of the vehicle.

[0115] It should be noted that the acquisition module 702, the processing module 704 and the positioning module 706 correspond to steps S202 to S206 in Example 1, and the examples and application scenarios implemented by the two modules and the corresponding steps are the same, but are not limited to the contents disclosed in the above-mentioned Example 1. It should be noted that the above-mentioned modules or units can be hardware components or software components stored in a memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n), and the above-mentioned modules can also be run in the computer terminal 10 provided in Example 1 as part of the device.

[0116] In the above embodiment of the present application, the processing module 704 includes: an extraction unit, which is used to extract the first perceptual information and the second perceptual information respectively, to obtain a first perceptual feature of the first perceptual information and a second perceptual feature of the perceptual information; an encoding unit, which is used to encode the first acquisition time and the second acquisition time respectively, to obtain a first time feature of the first acquisition time and a second time feature of the second acquisition time; a processing unit, which is used to perform spatiotemporal alignment based on the first perceptual feature, the second perceptual feature, the first time feature, and the second time feature to obtain an aligned first perceptual feature and an aligned second perceptual feature; a first determination unit, which is used to determine the aligned first perceptual information based on the aligned first perceptual feature, and to determine the aligned second perceptual information based on the aligned second perceptual feature.

[0117] In the above embodiment of the present application, the processing unit includes: a splicing subunit, which is used to splice the first perceptual feature, the second perceptual feature, the first time feature and the second time feature to obtain a splicing feature; a prediction subunit, which is used to predict the aligned first perceptual feature and the aligned second perceptual feature based on the splicing feature, wherein the aligned first perceptual feature and the aligned second perceptual feature correspond to the same acquisition time.

[0118] In the above embodiment of the present application, the positioning module 706 includes: a fusion unit, used to fuse the aligned first perception information and the aligned second perception information to obtain fusion information; a positioning unit, used to locate the vehicle based on the fusion information to obtain a positioning result of the vehicle.

[0119] In the above embodiment of the present application, the fusion unit includes: a determination subunit, used to determine the point cloud data and visual data in the aligned first perception information and the aligned second perception information; a fusion subunit, used to fuse the point cloud data and the visual data to obtain fusion information.

[0120] In the above embodiments of the present application, the fusion subunit is also used to convert point cloud data into a preset space to obtain point cloud features, and convert visual data into a preset space to obtain visual features; encode point cloud features and visual features to obtain fusion features; and determine fusion information based on the fusion features.

[0121] In the above embodiment of the present application, the processing module 704 includes: a preprocessing unit, which is used to preprocess the first perception information and the second perception information to obtain the first preprocessed information and the second preprocessed information; a spatiotemporal alignment unit, which is used to perform spatiotemporal alignment on the first preprocessed information and the second preprocessed information based on the first acquisition time of the first perception information and the second acquisition time of the second perception information to obtain the aligned first perception information and the aligned second perception information.

[0122] In the above embodiment of the present application, the acquisition module 702 includes: a second determination unit, used to determine at least one vehicle traveling within a preset range of the vehicle; and an acquisition unit, used to acquire perception information sent by at least one vehicle to obtain first perception information.

[0123] In the above embodiments of the present application, the device also includes: a generation module for generating control information or a driving path of the vehicle based on the positioning result of the vehicle; and a control module for controlling the vehicle based on the control information or the driving path.

[0124] It should be noted that the preferred implementation scheme involved in the above embodiments of the present application is the same as the scheme provided in Example 1, as well as the application scenario and implementation process, but is not limited to the scheme provided in Example 1.

[0125] Example 6

[0126] According to an embodiment of the present application, a device for implementing the above vehicle positioning method is also provided. Figure 8 is a schematic diagram of a vehicle positioning device according to Example 2 of the present application, such as Figure 8 As shown, the device includes: an acquisition module 802 , a processing module 804 and a positioning module 806 .

[0127] Among them, the above-mentioned acquisition module 802 is used to acquire the first perception feature sent by the vehicle and the second perception feature sent by the road-side equipment, wherein the road-side equipment is located on the road where the vehicle is traveling, and the first perception feature is a feature obtained by extracting the first perception information collected by the vehicle, and the second perception feature is a feature obtained by extracting the second perception information collected by the road-side equipment; the processing module 804 is used to perform spatiotemporal alignment on the first perception feature and the second perception feature based on the first collection time of the first perception information and the second collection time of the second perception information to obtain the aligned first perception feature and the aligned second perception feature; the positioning module 806 is used to locate the vehicle based on the aligned first perception feature and the aligned second perception feature to obtain the positioning result of the vehicle.

[0128] It should be noted here that the above-mentioned acquisition module 802, processing module 804 and positioning module 806 correspond to steps S402 to S406 in Example 2, and the instances and application scenarios implemented by the modules and corresponding steps are the same, but are not limited to the contents disclosed in the above-mentioned Example 2.

[0129] Example 7

[0130] According to an embodiment of the present application, another device for implementing the above vehicle positioning method is also provided. Fig. 9 is a schematic diagram of a vehicle positioning device according to Embodiment 3 of the present application, such as Fig. 9 As shown, the device includes: a sending module 902 and a display module 904.

[0131] Among them, the above-mentioned sending module 902 is used to respond to input instructions acting on the operation interface, and display the first perception information sent by the vehicle and the second perception information sent by the road-side device on the operation interface, wherein the road-side device is located on the road on which the vehicle is traveling; the above-mentioned display module 904 is used to respond to vehicle instructions acting on the operation interface, and display the positioning result of the vehicle on the operation interface, wherein the positioning result is the result of positioning the vehicle based on the aligned first perception information and the aligned second perception information, and the aligned first perception information and the aligned second perception information are based on the first collection time of the first perception information and the second collection time of the second perception information, and are obtained by temporally and spatially aligning the first perception information and the second perception information.

[0132] It should be noted here that the above-mentioned sending module 902 and display module 904 correspond to steps S502 to S504 in Example 3. The instances and application scenarios implemented by the modules and corresponding steps are the same, but are not limited to the contents disclosed in the above-mentioned Example 3.

[0133] Example 8

[0134] According to an embodiment of the present application, another device for implementing the above vehicle positioning method is also provided. Fig.10 is a schematic diagram of a vehicle positioning device according to Embodiment 4 of the present application, such as Fig.10 As shown, the device includes: a first calling module 1002 , a processing module 1004 , a positioning module 1006 , and a second calling module 1008 .

[0135] The first calling module 1002 is used to obtain the first perception information and the second perception information by calling the first interface, wherein the first interface includes a first parameter, and the parameter value of the first parameter is the first perception information and the second perception information, and the road end device is located on the road where the vehicle is traveling; the processing module 1004 is used to perform spatiotemporal alignment on the first perception information and the second perception information based on the first collection time of the first perception information and the second collection time of the second perception information to obtain the aligned first perception information and the aligned second perception information; the positioning module 1006 is used to locate the vehicle based on the aligned first perception information and the aligned second perception information to obtain the positioning result of the vehicle; the second calling module 1008 is used to output the positioning result of the vehicle by calling the second interface, wherein the second interface includes a second parameter, and the parameter value of the second parameter is the positioning result of the vehicle.

[0136] It should be noted here that the above-mentioned first calling module 1002, processing module 1004, positioning module 1006, and second calling module 1008 correspond to steps S602 to S608 in Example 4, and the instances and application scenarios implemented by the modules and corresponding steps are the same, but are not limited to the contents disclosed in the above-mentioned Example 4.

[0137] Example 9

[0138] The embodiment of the present application may provide a computer terminal, which may be any computer terminal device in a computer terminal group. Optionally, in this embodiment, the computer terminal may also be replaced by a terminal device such as a mobile terminal.

[0139] Optionally, in this embodiment, the computer terminal may be located in at least one network device among a plurality of network devices of the computer network.

[0140] In this embodiment, the above-mentioned computer terminal can execute the program code of the following steps in the vehicle positioning method: obtaining first perception information sent by the vehicle and second perception information sent by a road-side device, wherein the road-side device is located on the road on which the vehicle is traveling; based on a first acquisition time of the first perception information and a second acquisition time of the second perception information, performing spatiotemporal alignment on the first perception information and the second perception information to obtain aligned first perception information and aligned second perception information; based on the aligned first perception information and the aligned second perception information, performing positioning on the vehicle to obtain a positioning result of the vehicle.

[0141] Optionally, Fig.11 is a structural block diagram of a computer terminal according to an embodiment of the present application. Fig.11 As shown, the computer terminal A may include: one or more (only one is shown in the figure) processors 1102, a memory 1104, a storage controller, and a peripheral interface, wherein the peripheral interface is connected to a radio frequency module, an audio module, and a display.

[0142] Among them, the memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the vehicle positioning method and device in the embodiment of the present application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, the above-mentioned vehicle positioning method is realized. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory may further include a memory remotely arranged relative to the processor, and these remote memories can be connected to the terminal A via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0143] The processor can call the information and application stored in the memory through the transmission device to perform the following steps: obtain the first perception information sent by the vehicle and the second perception information sent by the road-side equipment, wherein the road-side equipment is located on the road on which the vehicle is traveling; based on the first collection time of the first perception information and the second collection time of the second perception information, align the first perception information and the second perception information in time and space to obtain the aligned first perception information and the aligned second perception information; based on the aligned first perception information and the aligned second perception information, locate the vehicle to obtain the positioning result of the vehicle.

[0144] Optionally, the processor may also execute the program code of the following steps: based on the first acquisition time of the first perception information and the second acquisition time of the second perception information, perform spatiotemporal alignment on the first perception information and the second perception information to obtain the aligned first perception information and the aligned second perception information, including: respectively extracting the first perception information and the second perception information to obtain the first perception feature of the first perception information and the second perception feature of the perception information; respectively encoding the first acquisition time and the second acquisition time to obtain the first time feature of the first acquisition time and the second time feature of the second acquisition time; perform spatiotemporal alignment based on the first perception feature, the second perception feature, the first time feature and the second time feature to obtain the aligned first perception feature and the aligned second perception feature; determine the aligned first perception information based on the aligned first perception feature, and determine the aligned second perception information based on the aligned second perception feature.

[0145] Optionally, the processor may also execute the program code of the following steps: performing spatiotemporal alignment based on the first perceptual feature, the second perceptual feature, the first time feature and the second time feature to obtain an aligned first perceptual feature and an aligned second perceptual feature, including: splicing the first perceptual feature, the second perceptual feature, the first time feature and the second time feature to obtain a spliced ​​feature; based on the spliced ​​feature, predicting the aligned first perceptual feature and the aligned second perceptual feature, wherein the aligned first perceptual feature and the aligned second perceptual feature correspond to the same acquisition time.

[0146] Optionally, the processor may also execute the program code of the following steps: positioning the vehicle based on the aligned first perception information and the aligned second perception information to obtain a positioning result of the vehicle, including: fusing the aligned first perception information and the aligned second perception information to obtain fused information; positioning the vehicle based on the fused information to obtain a positioning result of the vehicle.

[0147] Optionally, the processor may also execute the program code of the following steps: fusing the aligned first perception information and the aligned second perception information to obtain fused information, including: determining the point cloud data and visual data in the aligned first perception information and the aligned second perception information; fusing the point cloud data and the visual data to obtain fused information.

[0148] Optionally, the processor may also execute program code for the following steps: fusing point cloud data and visual data to obtain fusion information, including: converting point cloud data to a preset space to obtain point cloud features, and converting visual data to a preset space to obtain visual features; encoding point cloud features and visual features to obtain fusion features; and determining fusion information based on the fusion features.

[0149] Optionally, the processor may also execute the program code of the following steps: based on the first acquisition time of the first perception information and the second acquisition time of the second perception information, spatiotemporally aligning the first perception information and the second perception information to obtain aligned first perception information and aligned second perception information, including: preprocessing the first perception information and the second perception information to obtain first preprocessing information and second preprocessing information; based on the first acquisition time of the first perception information and the second acquisition time of the second perception information, spatiotemporally aligning the first preprocessing information and the second preprocessing information to obtain aligned first perception information and aligned second perception information.

[0150] Optionally, the processor may also execute program code of the following steps: obtaining first perception information sent by a vehicle includes: determining at least one vehicle traveling within a preset range of the vehicle; obtaining perception information sent by at least one vehicle to obtain first perception information.

[0151] Optionally, the processor may also execute program code for the following steps: after positioning the vehicle based on the aligned first perception information and the aligned second perception information and obtaining the positioning result of the vehicle, the method further includes: generating control information or a driving path of the vehicle based on the positioning result of the vehicle; and controlling the vehicle based on the control information or the driving path.

[0152] In the embodiment of the present application, the first perception information sent by the vehicle and the second perception information sent by the roadside device are obtained; based on the first acquisition time of the first perception information and the second acquisition time of the second perception information, the first perception information and the second perception information are temporally and spatially aligned to obtain the aligned first perception information and the aligned second perception information; based on the aligned first perception information and the aligned second perception information, the vehicle is positioned to obtain the positioning result of the vehicle. It is easy to notice that the first perception information and the second perception information can be temporally and spatially aligned, and the aligned first perception information and the aligned second perception information can be used to position the vehicle, thereby compensating for the communication delay, so that in the process of collaborative positioning using the first perception information collected by the vehicle and the second perception information collected by the roadside device, a more accurate positioning result can be obtained, thereby improving the positioning accuracy of the vehicle, and further solving the technical problem of low positioning accuracy of the vehicle in the related art.

[0153] Those skilled in the art will appreciate that the structure shown in the figure is for illustration only, and the computer terminal may also be a smart phone (such as an Android phone, an iOS phone, etc.), a tablet computer, a PDA, a mobile Internet device (MID), a PAD, or other terminal devices. Fig.11It does not limit the structure of the above electronic device. For example, the computer terminal A may also include Fig.11 More or fewer components (such as network interfaces, display devices, etc.) shown in, or having Fig.11 Different configurations shown.

[0154] A person of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing the hardware related to the terminal device through a program, and the program can be stored in a computer-readable storage medium, and the storage medium may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0155] Example 10

[0156] The embodiment of the present application further provides a storage medium. Optionally, in this embodiment, the storage medium can be used to store the program code executed by the vehicle positioning method provided in the first embodiment.

[0157] Optionally, in this embodiment, the above storage medium may be located in any computer terminal in a computer terminal group in a computer network, or in any mobile terminal in a mobile terminal group.

[0158] Optionally, in this embodiment, the storage medium is configured to store program codes for executing the following steps: obtaining first perception information sent by the vehicle and second perception information sent by a road-side device, wherein the road-side device is located on the road on which the vehicle is traveling; based on a first acquisition time of the first perception information and a second acquisition time of the second perception information, performing spatiotemporal alignment on the first perception information and the second perception information to obtain aligned first perception information and aligned second perception information; based on the aligned first perception information and the aligned second perception information, performing positioning on the vehicle to obtain a positioning result for the vehicle.

[0159] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0160] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0161] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0162] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0163] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0164] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0165] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A vehicle positioning method, characterized in that: include: Acquire first perception information sent by a vehicle and second perception information sent by a road-side device, wherein the road-side device is located on a road on which the vehicle is traveling; Based on a first collection time of the first perception information and a second collection time of the second perception information, the first perception information and the second perception information are temporally and spatially aligned to obtain aligned first perception information and aligned second perception information; Based on the aligned first perception information and the aligned second perception information, the vehicle is positioned to obtain a positioning result of the vehicle.

2. The method according to claim 1, characterized in that Based on a first acquisition time of the first perception information and a second acquisition time of the second perception information, the first perception information and the second perception information are temporally and spatially aligned to obtain aligned first perception information and aligned second perception information, including: Extracting features from the first perception information and the second perception information respectively to obtain a first perception feature of the first perception information and a second perception feature of the perception information; Encode the first acquisition time and the second acquisition time respectively to obtain a first time feature of the first acquisition time and a second time feature of the second acquisition time; Performing spatiotemporal alignment based on the first perceptual feature, the second perceptual feature, the first time feature, and the second time feature to obtain an aligned first perceptual feature and an aligned second perceptual feature; The aligned first perceptual information is determined based on the aligned first perceptual feature, and the aligned second perceptual information is determined based on the aligned second perceptual feature.

3. The method according to claim 2, characterized in that Performing spatiotemporal alignment based on the first perceptual feature, the second perceptual feature, the first time feature, and the second time feature to obtain an aligned first perceptual feature and an aligned second perceptual feature includes: splicing the first perception feature, the second perception feature, the first time feature, and the second time feature to obtain a spliced ​​feature; Based on the splicing feature, the aligned first perceptual feature and the aligned second perceptual feature are predicted, wherein the aligned first perceptual feature and the aligned second perceptual feature correspond to the same acquisition time.

4. The method according to claim 1, characterized in that Based on the aligned first perception information and the aligned second perception information, the vehicle is positioned to obtain a positioning result of the vehicle, including: fusing the aligned first perception information and the aligned second perception information to obtain fused information; The vehicle is positioned based on the fusion information to obtain a positioning result of the vehicle.

5. The method according to claim 4, characterized in that Fusing the aligned first perception information and the aligned second perception information to obtain fused information includes: Determining point cloud data and visual data in the aligned first perception information and the aligned second perception information; The point cloud data and the visual data are fused to obtain the fusion information.

6. The method according to claim 5, characterized in that Fusing the point cloud data and the visual data to obtain the fusion information includes: Converting the point cloud data to a preset space to obtain point cloud features, and converting the visual data to the preset space to obtain visual features; Encoding the point cloud features and the visual features to obtain fusion features; The fusion information is determined based on the fusion feature.

7. The method according to claim 1, characterized in that Based on a first acquisition time of the first perception information and a second acquisition time of the second perception information, the first perception information and the second perception information are temporally and spatially aligned to obtain aligned first perception information and aligned second perception information, including: Preprocessing the first perception information and the second perception information to obtain first preprocessing information and second preprocessing information; Based on a first acquisition time of the first perception information and a second acquisition time of the second perception information, the first preprocessing information and the second preprocessing information are temporally and spatially aligned to obtain the aligned first perception information and the aligned second perception information.

8. The method according to claim 1, characterized in that Get the first perception information sent by the vehicle, including: determining at least one vehicle traveling within a preset range of the vehicle; Acquire the perception information sent by the at least one vehicle to obtain the first perception information.

9. The method according to claim 1, characterized in that: After positioning the vehicle based on the aligned first perception information and the aligned second perception information to obtain a positioning result of the vehicle, the method further includes: Based on the positioning result of the vehicle, generating control information or a driving path of the vehicle; The vehicle is controlled based on the control information or the driving path.

10. A vehicle positioning method, characterized in that: include: Acquire a first perception feature sent by a vehicle and a second perception feature sent by a roadside device, wherein the roadside device is located on a road on which the vehicle is traveling, the first perception feature is a feature obtained by extracting first perception information collected by the vehicle, and the second perception feature is a feature obtained by extracting second perception information collected by the roadside device; Based on a first acquisition time of the first perception information and a second acquisition time of the second perception information, the first perception feature and the second perception feature are temporally and spatially aligned to obtain an aligned first perception feature and an aligned second perception feature; The vehicle is positioned based on the aligned first perception feature and the aligned second perception feature to obtain a positioning result of the vehicle.

11. A vehicle positioning method, characterized in that: include: In response to an input instruction acting on an operation interface, displaying on the operation interface first perception information sent by the vehicle and second perception information sent by a road-side device, wherein the road-side device is located on a road on which the vehicle is traveling; In response to a vehicle command applied to the operation interface, a positioning result of the vehicle is displayed on the operation interface, wherein the positioning result is a result of positioning the vehicle based on the aligned first perception information and the aligned second perception information, and the aligned first perception information and the aligned second perception information are obtained by spatiotemporally aligning the first perception information and the second perception information based on a first acquisition time of the first perception information and a second acquisition time of the second perception information.

12. A vehicle positioning method, characterized in that: include: Acquiring first perception information and second perception information by calling a first interface, wherein the first interface includes a first parameter, a parameter value of the first parameter is the first perception information and the second perception information, and a road end device is located on a road where the vehicle is traveling; Based on a first collection time of the first perception information and a second collection time of the second perception information, the first perception information and the second perception information are temporally and spatially aligned to obtain aligned first perception information and aligned second perception information; Positioning the vehicle based on the aligned first perception information and the aligned second perception information to obtain a positioning result of the vehicle; The positioning result of the vehicle is output by calling a second interface, wherein the second interface includes a second parameter, and a parameter value of the second parameter is the positioning result of the vehicle.

13. An electronic device, characterized in that: include: A memory storing an executable program; A processor, configured to run the program, wherein the program executes the method according to any one of claims 1 to 12 when running.

14. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored executable program, wherein when the executable program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 12.

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