Method and device for controlling automatic vehicle moving of a vehicle

Abstract

The application provides a method for controlling automatic vehicle moving, comprising the following steps: acquiring a no-parking time period corresponding to a current parking area of a vehicle, and recording a current parking time of the vehicle; when a preset proximity relationship between the current parking time and a start time of the no-parking time period is met, acquiring potential parking space availability information in a target area around the vehicle, the potential parking space availability information at least comprising a current occupancy state of each parking space in the target area and a parking position and an estimated leaving time of each parked vehicle in the target area; based on the potential parking space availability information, generating an automatic moving strategy for the vehicle, and controlling the vehicle to perform automatic moving operation according to the automatic moving strategy. The application also provides a device for controlling automatic vehicle moving and a computer program product. By predicting which parking space will be vacated at what time in advance, the automatic moving strategy can be more efficiently planned.

Description

Technical Field

[0001] This application relates to a method for controlling the automatic relocation of a vehicle, and also to a device for controlling the automatic relocation of a vehicle and a computer program product. Background Technology

[0002] In some countries or regions, there are temporary no-parking rules on both sides of the road during specific times (such as road cleaning periods). If a vehicle is parked in a designated area during these times, it may face a fine. As a result, drivers often need to return to their vehicles in advance to move them manually. However, during the process of moving the vehicle, they may encounter problems such as insufficient parking spaces nearby or obstructions caused by illegal parking, such as fire hydrants, resulting in considerable inconvenience.

[0003] Currently known automatic parking technologies primarily rely on onboard environmental perception modules to detect the availability of nearby parking spaces and automatically move into an available space. However, when there are no available parking spaces nearby, such technologies cannot provide an effective parking solution and still require driver intervention, making it difficult to meet the needs of automatic parking in complex road environments.

[0004] Therefore, existing automatic vehicle relocation solutions for no-parking scenarios still have many shortcomings. Summary of the Invention

[0005] The purpose of this application is to provide a method for controlling the automatic relocation of a vehicle, a device for controlling the automatic relocation of a vehicle, and a computer program product, so as to at least solve some of the problems in the prior art.

[0006] According to a first aspect of this application, a method for controlling the automatic relocation of a vehicle is provided, wherein the method includes the following steps: Step S1: Obtain the no-parking period corresponding to the current parking area of ​​this vehicle, and record the current parking time of this vehicle; Step S2: When the current parking time and the start time of the no-parking period satisfy a preset proximity relationship, obtain the availability information of potential parking spaces in the target area around the vehicle that is not subject to no-parking restrictions. The potential parking space availability information includes at least: the current occupancy status of each parking space in the target area, and the parking location of each parked vehicle in the target area and its expected departure time; and Step S3: Based on the potential parking space availability information, generate an automatic relocation strategy for the vehicle and control the vehicle to perform automatic relocation operations according to the automatic relocation strategy.

[0007] This application specifically includes the following technical concept: By acquiring the occupancy status of parking spaces within a target area and the estimated departure time of parked vehicles in real time, the system can predict which parking spaces will become available and when. This allows for advance planning of an automatic vehicle relocation strategy, rationally arranging the vehicle to enter soon-to-be-vacated spaces and avoiding aimless cruising or ineffective waiting. This process requires no driver intervention, reducing the user's operational burden and significantly improving overall vehicle relocation efficiency. Therefore, efficient and orderly automatic vehicle relocation can be achieved, effectively avoiding the risk of violations due to overstaying parking.

[0008] In an exemplary embodiment, in step S2, the estimated departure time of the parked vehicle is obtained through at least one of the following methods: obtaining shared information through a communication network with parked vehicles in the target area, and determining the estimated departure time based on the shared information. Specifically, the communication network adopts a dual-architecture communication mode of V2V and V2I, and automatically switches to the other communication link within a preset time threshold when one communication link is interrupted; and / or, collecting multi-dimensional departure features in the target area and / or obtaining historical departure behavior data of the target area through an environmental perception module, and predicting the estimated departure time based on the multi-dimensional departure features and / or the historical departure behavior data. Specifically, the multi-dimensional departure features include at least one of the following: the door open / closed status of the parked vehicle; the engine start status; the charging gun connection status; the in-vehicle Bluetooth and / or CarPlay connection status; the activity trajectory of surrounding personnel; and / or, vehicle body vibration characteristics.

[0009] In an exemplary embodiment, the potential parking space availability information further includes: the accuracy of the estimated departure time of each parked vehicle in the target area; the accuracy is determined by a machine learning model based on at least one of the following information: the arrival time of each parked vehicle, the distance to the vehicle, the multi-dimensional departure features collected by the environmental perception module, and the historical departure behavior data of the target area.

[0010] In an exemplary embodiment, step S3 includes: sorting each parking space in the target area by a first priority according to the potential parking space availability information; wherein, vacant parking spaces are assigned a higher priority than occupied parking spaces; for occupied parking spaces, the earlier the expected departure time of the parked vehicle is, the higher the assigned priority; based on the first priority sorting, determining a target parking space for the vehicle, and controlling the vehicle to automatically move to the target parking space.

[0011] In an exemplary embodiment, the method further includes: obtaining vehicle status information of other vehicles to be moved that are in the same parking area as the vehicle through a communication network, the vehicle status information including: arrival time of each vehicle to be moved, emergency vehicle relocation request and / or expected parking duration; in step S3, additionally generating the automatic vehicle relocation strategy based on the vehicle status information.

[0012] In an exemplary embodiment, step S3, generating an automatic vehicle relocation strategy further includes: sorting each vehicle to be relocated by a second priority based on the vehicle status information, wherein the vehicle to be relocated with an earlier arrival time, an emergency relocation need, and a longer expected parking time is assigned a higher priority; and determining a target parking space for the vehicle based on the first priority sort and the second priority sort, wherein each vehicle to be relocated in the second priority sort from high to low is sequentially matched to the corresponding parking space in the first priority sort from high to low to determine the target parking space for the vehicle.

[0013] In an exemplary embodiment, the automatic vehicle relocation strategy generated in step S3 further includes: if a target parking space is determined for the vehicle in the target area based on the potential parking space availability information, then the vehicle is controlled to first drive into a temporary parking area to wait, and when the target parking space is about to become available, the vehicle is controlled to drive from the temporary parking area into the target parking space; a warning threshold is set for the vehicle to wait for the target parking space to become available, and if the waiting time exceeds the warning threshold and the target parking space is still not available, the vehicle is controlled to give up waiting and execute the departure and parking space search strategy.

[0014] In an exemplary embodiment, step S3 further includes: if a target parking space is determined for the vehicle in the target area based on the potential parking space availability information, then after controlling the vehicle to automatically move to the target parking space, the vehicle's parking location, arrival time and / or expected departure time in the target area are synchronized to the communication network through encrypted communication.

[0015] According to a second aspect of this application, an apparatus for controlling the automatic relocation of a vehicle is provided. The apparatus includes a memory and a processor. The memory stores computer program instructions, and when the computer program instructions are executed by the processor, the processor is capable of performing the method described according to the first aspect of this application.

[0016] According to a third aspect of this application, a computer program product is provided, comprising computer program instructions, wherein, when executed by a processor, the computer program instructions enable the processor to perform the method according to a first aspect of this application. Attached Figure Description

[0017] The principles, features, and advantages of this application will be better understood below with reference to the accompanying drawings. The drawings include: Figure 1 A flowchart is shown for a method of controlling the automatic relocation of the vehicle according to an exemplary embodiment of this application; Figure 2 It shows Figure 1 The flowchart for step S2 is shown below; Figure 3 It shows Figure 1 The flowchart for step S3 is shown below; Figure 4 It shows Figure 1 Another flowchart of step S3 shown; Figure 5 A flowchart is shown for a method of controlling the automatic relocation of the vehicle according to another exemplary embodiment of this application; Figure 6 A schematic diagram illustrating the use of the method according to this application in an exemplary application scenario is shown; Figure 7 A schematic diagram illustrating the use of the method according to this application in another exemplary application scenario is shown; and Figure 8 A block diagram of an apparatus for controlling the automatic relocation of a vehicle according to an exemplary embodiment of this application is shown. Detailed Implementation

[0018] To make the technical problems to be solved, the technical solutions, and the beneficial technical effects of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and several exemplary embodiments. It should be understood that the specific embodiments described herein are only for explaining this application and are not intended to limit the scope of protection of this application.

[0019] Figure 1 A flowchart of a method for controlling the automatic relocation of the vehicle according to an exemplary embodiment of this application is shown.

[0020] In step S1, the no-parking period corresponding to the current parking area of ​​the vehicle is obtained, and the current parking time of the vehicle is recorded.

[0021] The no-parking periods can be understood, for example, as follows: some roadside parking areas are not open for parking all day, but rather parking is prohibited during designated times. If a vehicle is parked in a no-parking area during those times, it may face fines or violation records. For instance, the no-parking rule may apply to one side of the road and is only effective during specific times.

[0022] In one embodiment, when the vehicle enters a street area, the onboard sensing module can identify no-parking signs placed along the roadside, which may indicate the no-parking hours and applicable area. For example, the vehicle sensors may identify the words "No Parking on Fridays, 7:00 AM to 11:00 AM" to obtain and store the no-parking hours. In another embodiment, the no-parking hours information can also be read from map data.

[0023] In one embodiment, the current parking time of the vehicle can be obtained from the vehicle's infotainment system time, or the local time can be obtained via the network.

[0024] In step S2, when the current parking time of the vehicle and the start time of the no-parking period meet a preset proximity relationship, the availability information of potential parking spaces in the target area around the vehicle that is not subject to no-parking restrictions is obtained. The availability information of potential parking spaces includes, for example, at least: the current occupancy status of each parking space in the target area, and the parking location of each parked vehicle in the target area and its expected departure time.

[0025] In one embodiment, the target area refers, for example, a legal and compliant parking area within a predetermined distance (e.g., 50 meters) around the vehicle that is not subject to no-parking periods. For instance, this target area is the preferred ideal parking location for the vehicle user if they manually move the vehicle, such as an alternative parking area located on the same road segment as the original parking location, close to it, and convenient for the user to find the vehicle later. For instance, if the no-parking period affects parking areas on the left side of the road, the target area could be parking areas on the right side of the road.

[0026] In one embodiment, the potential parking space availability information may include, in addition to the current occupancy status, parking location, and expected departure time, the accuracy of the expected departure time to indicate its reliability. For example, it may be determined based on the owner's settings, historical behavior, or perception information, and represented in the form of percentage or confidence level.

[0027] In addition, potential parking space availability information may also include: charging type (such as free or charged), parking space size (such as standard parking space or large parking space), surrounding traffic conditions (such as congestion level), distance from the vehicle, and the remaining time that the parking space is available for temporary use, in order to support more accurate parking space matching and vehicle relocation decisions.

[0028] In one embodiment, the potential parking space availability information can be obtained through a communication network. For example, the vehicle can establish vehicle-to-vehicle (V2V) communication with parked vehicles in the target area via an onboard communication unit (TCU), and / or establish vehicle-to-infrastructure (V2I) communication with a roadside communication unit, forming a vehicle-road cooperative communication network. Through this network, the vehicle can obtain information such as parking location, estimated parking duration, and estimated departure time reported by parked vehicles in the target area. Optionally, the communication network can use national cryptographic algorithms (such as SM4) to encrypt the transmitted data to ensure the security and tamper-proof capability of information transmission.

[0029] In one embodiment, the potential parking space availability information can also be obtained based on environmental perception. For example, the vehicle can use an onboard environmental perception module to collect environmental information within the target area. This onboard environmental perception module may include, for example, a camera, millimeter-wave radar, lidar, ultrasonic sensors, etc. By processing the environmental perception information through image recognition, target detection and tracking, point cloud analysis, etc., multi-dimensional information such as the occupancy status of each parking space within the target area, the location of parked vehicles, vehicle type, door open / close status, and personnel activity trajectories can be identified in real time.

[0030] In one embodiment, updates to potential parking space availability information can also be obtained in real time. For example, when a vehicle enters an empty parking space, the occupancy status of the corresponding parking space is immediately updated to "occupied," and the vehicle's parking location and estimated departure time are recorded. When a parked vehicle leaves, the status of the corresponding parking space is updated to "empty." Furthermore, if the estimated departure time of a parked vehicle changes (e.g., the driver temporarily adjusts their travel plans), the updated information can be obtained in real time through a communication network.

[0031] In step S3, based on the potential parking space availability information, an automatic relocation strategy is generated for the vehicle, and the vehicle is controlled to perform automatic relocation operations according to the automatic relocation strategy.

[0032] In this context, a target parking space refers to an alternative parking space identified for the vehicle to park long-term after leaving the current no-parking zone. This target parking space can be a currently vacant space within the target area, or a space that is currently occupied but is expected to become available before the start of the no-parking period.

[0033] In one embodiment, if a target parking space is identified for the vehicle within the target area based on potential parking space availability information, and the target parking space is currently vacant, the vehicle can be directly controlled to automatically drive into the target parking space.

[0034] In one embodiment, if the target parking space is currently occupied but is expected to become available shortly after the start of the no-parking period, the vehicle can be controlled to first drive into the temporary parking area to wait, and when the target parking space is expected to become available, the vehicle can be controlled to drive from the temporary parking area into the target parking space.

[0035] In one embodiment, if a target parking space cannot be determined for the vehicle within the target area based on potential parking space availability information, the vehicle can be controlled to leave the area currently affected by the no-parking period, and the vehicle can continue to search for a parking space.

[0036] In one embodiment, if there are multiple vehicles to be moved, the status information of each vehicle to be moved and the status of each parking space in the target area can be combined to uniformly allocate target parking spaces to each vehicle to be moved, and control each vehicle to perform automatic vehicle moving operations according to the allocation results and a predetermined priority order.

[0037] In one embodiment, the automatic vehicle relocation strategy can also be dynamically adjusted over time. For example, if a target parking space cannot be initially determined for the vehicle, it can be controlled to drive into a nearby temporary parking area to wait, and continuously reassessed based on updated network information. If a vacant parking space becomes available in the target area or the expected departure time is updated, a new target parking space can be determined for the vehicle, and it can be controlled to drive into the newly matched target parking space.

[0038] In one embodiment, before performing the automatic vehicle relocation operation, a notification can be sent to the vehicle owner's mobile terminal, such as via an in-vehicle app, SMS, or WeChat push notification: "Your vehicle is about to enter a no-parking period. Automatic vehicle relocation has been initiated, and a temporary parking area has been matched with a municipal free parking area 300 meters away. The vehicle is expected to be moved by 7:30." If the vehicle owner confirms, the automatic vehicle relocation operation will begin.

[0039] Figure 2 It shows Figure 1 The flowchart for step S2 is shown. In this embodiment, Figure 1 Step S2 further includes sub-steps S21 to S23.

[0040] In sub-step S21, if there are connected vehicles (i.e., vehicles equipped with TCUs and connected to the communication network) parked in the target area, this vehicle obtains shared information through communication networking with the connected vehicles, and determines its expected departure time and corresponding accuracy based on the shared information.

[0041] In one embodiment, the shared information may directly include the estimated departure time of each parked vehicle, which is reported by the vehicle itself at its parking location. For example, the vehicle reports its planned departure time immediately after parking.

[0042] In another embodiment, the shared information may include the parking location (such as parking space number or coordinates), arrival time (i.e., parking start time), planned parking duration, and multi-source auxiliary information (such as calendar schedule, remaining charging time, etc.) reported by each parked vehicle, and the estimated departure time is estimated accordingly. The accuracy can be determined based on the reliability of the information source. For example, calendar schedules have high accuracy (e.g., 95%), remaining charging time sources have medium accuracy (e.g., 85%), and estimations based solely on arrival time and historical statistics have low accuracy (e.g., 70%).

[0043] In one embodiment, the shared information is transmitted in an encrypted manner, such as using the national cryptographic algorithm SM4, to ensure information security.

[0044] In one embodiment, the communication network adopts a dual-architecture communication mode of V2V (vehicle-to-vehicle) and V2I (vehicle-to-infrastructure). Vehicles can form local networks through direct vehicle-to-vehicle communication, while roadside equipment can also participate in the network to synchronize and record parking space status and expected departure time information. When one communication link is interrupted, it automatically switches to the other communication link within a preset time threshold, thereby ensuring the continuity and reliability of information acquisition.

[0045] In sub-step S22, for non-networked vehicles parked in the target area (e.g., vehicles without TCU, not connected to the communication network, or with communication function failure), the vehicle's environmental perception capability can be used to collect multi-dimensional departure characteristics in the target area and / or obtain historical departure behavior data of the target area, and based on this, predict their expected departure time and corresponding accuracy.

[0046] In one embodiment, the vehicle's onboard perception module can be used to obtain multi-dimensional status information of parked vehicles within the target area through methods such as image capture, point cloud scanning, and signal detection.

[0047] The aforementioned multi-dimensional departure features refer to typical characteristics that can reflect the intention or signs that a vehicle may be about to leave. By detecting these features, the accuracy of judging the probability and timing of vehicle departure can be improved.

[0048] In one embodiment, the multidimensional departure feature includes at least one of the following: - Door opening / closing status: If a door opening / closing action is detected and there are continuous opening and closing actions, it may indicate that the driver is about to get into the vehicle and is preparing to drive away; - Engine started status: After the engine is started, the vehicle usually drives away within a short period of time; - Charging gun connection status: The charging gun is disconnected, indicating that the vehicle may be about to finish charging and is ready to leave; - In-vehicle Bluetooth and / or CarPlay connection status: The phone has established a connection with the vehicle's infotainment system, which usually indicates that the driver has entered the vehicle and is ready to depart; - Activity patterns of people in the vicinity: Someone approached the driver's side door and entered the vehicle, indicating that the vehicle was about to leave; - Vehicle vibration characteristics: Vibrations generated by engine starting or passengers getting in and out of the vehicle can help determine changes in vehicle condition; and / or - Wheel steering status: Wheel steering is detected, indicating that the vehicle may be about to leave the parking space.

[0049] In one embodiment, historical departure behavior data can be obtained in various ways, such as long-term collection through roadside equipment, collection through communication networks, or acquisition from the cloud. This data may include average parking duration over different time periods, departure probability distribution, holiday patterns, and parking habits of different vehicle types.

[0050] In one embodiment, when determining the expected departure time or probability of departure based on historical departure behavior data, machine learning models, preset rules, or table lookup methods can be used. For example, information such as the current time, season, morning / afternoon, and real-time traffic flow can be input into the model to output the prediction result, or it can be calculated according to a predetermined rule (such as "average parking time of 45 minutes during weekday morning rush hour"), or the corresponding value can be directly read from a historical statistics table.

[0051] For example, if historical departure behavior data shows that the frequency of vehicles leaving the target area is high between 7:30 and 9:30 am on weekdays, then for an unconnected vehicle for which no obvious departure characteristics have been collected, if the current time is 9:00 am, the accuracy of its departure within half an hour can be set to 70%; if the current time is 5:00 pm, and the historical departure frequency is low during this period, then the accuracy of its departure within half an hour can be set to 30% accordingly.

[0052] In sub-step S23, the estimated departure times and their corresponding accuracy for all parked vehicles within the target area are summarized. Then, a machine learning model can be used to further refine or verify the estimated departure times and accuracy. For example, the following information can be input into the trained machine learning model: the arrival time of each parked vehicle, the distance to the vehicle, multi-dimensional departure features collected by the environmental perception module, and / or historical departure behavior data of the target area.

[0053] In one embodiment, the machine learning model used may be lightweight, such as CNN or LSTM, to reduce computational overhead while ensuring prediction accuracy, making it easier to deploy and run in real time on in-vehicle terminals.

[0054] For example, vehicle D parked in the target area is a connected vehicle. This vehicle obtains its shared information through the communication network and determines its estimated departure time to be 7:30, with an initial accuracy of 85%. In sub-step S23, if the machine learning model detects features of vehicle D such as door opening and closing, people approaching the driver's seat and connecting Bluetooth and CarPlay, the machine learning model can improve its accuracy to 88% based on these features.

[0055] For example, vehicle E parked in the target area is a non-networked vehicle. Initially, based on historical departure behavior data, its estimated departure time is predicted to be 9:00 (within half an hour), with an initial accuracy of 60%. In sub-step S23, the machine learning model, based on detected multi-dimensional departure features (such as charging gun disconnection, engine start, vehicle vibration, etc.), can, for example, correct its estimated departure time to 8:45 (within 15 minutes), improving the accuracy to 80%.

[0056] Figure 3 It shows Figure 1 The flowchart for step S3 is shown. In this embodiment, Figure 1 Step S3 further includes sub-steps S31 to S34.

[0057] In sub-step S31, each parking space is sorted by first priority based on its current occupancy status and the expected departure time of the parked vehicle within the target area.

[0058] In one embodiment, vacant parking spaces are assigned the highest priority, and for occupied parking spaces, the earlier the expected departure time of the parked vehicle, the higher the priority of that parking space.

[0059] In one embodiment, accuracy may also be considered as an additional factor. For example, when multiple parking spaces have the same expected departure time, those with higher accuracy are ranked higher.

[0060] For example, there are five parking spaces in the target area: Parking Space A (vacant), Parking Space B (leaving at 6:50, accuracy 95%), Parking Space C (leaving at 7:30, accuracy 85%), Parking Space D (leaving at 9:00, accuracy 60%), and Parking Space E (no specific time, accuracy < 50%). Taking into account the vacancy status of the parking spaces, the expected departure time of the parked vehicles, and the accuracy, the following first priority order (from high to low) can be determined, for example: Parking Space A, Parking Space B, Parking Space C, Parking Space D, Parking Space E.

[0061] In one embodiment, before or after the first priority ranking, the legality and / or compliance of each parking space in the target area may also be verified, for example, to confirm that there are no temporary traffic controls or parking restrictions.

[0062] In one embodiment, the first priority ranking can also be dynamically updated. For example, if the expected departure time of a vehicle parked in parking space B is postponed from 6:50 to 7:50, its ranking in the first priority ranking may be downgraded from second to third. Similarly, if a new car enters an empty parking space, or a vehicle that originally had no definite departure time suddenly leaves, the ranking can be adjusted accordingly to reflect the latest parking space status.

[0063] In one embodiment, the accuracy can also be graded, for example, into levels such as greater than 90%, 70%-90%, 50%-70%, and less than 50%. This simplifies computational overhead and improves processing efficiency during sorting.

[0064] In sub-step S32, the vehicle status information of other vehicles waiting to be moved within the same parking area as this vehicle is obtained through a communication network, and each vehicle is ranked according to a second priority based on the vehicle status information. An automatic vehicle relocation strategy can also be subsequently generated based on this vehicle status information.

[0065] In one embodiment, the vehicle status information includes: the arrival time of each vehicle to be moved (referring to the order of arrival at the no-parking zone), the emergency relocation request (e.g., whether it is an ambulance, fire truck, or other temporary emergency high-priority request), and the expected parking duration (reflecting the expected parking duration).

[0066] In one embodiment, the earlier the arrival time, the greater the need for emergency relocation, and the longer the expected parking time, the higher the priority assigned to the vehicle and the higher its ranking in the second priority sorting.

[0067] For example, there are five vehicles waiting to be moved within the same no-parking zone: vehicle M (this vehicle, entering at 5:50), vehicle N (entering at 6:00), vehicle O (entering at 6:10), vehicle P (entering at 6:20), and vehicle Q (entering at 6:30), where vehicle Q is an ambulance. The estimated parking times for each vehicle are 5 hours, 4 hours, 3 hours, 1 hour, and 1 hour, respectively. Taking into account arrival time, emergency vehicle relocation needs, and estimated parking times, a second priority order (from high to low) can be determined, for example, as follows: vehicle Q, vehicle M, vehicle N, vehicle O, and vehicle P.

[0068] In sub-step S33, parking spaces within the target area are matched for all vehicles to be moved, based on the first priority sorting and the second priority sorting.

[0069] In one embodiment, each vehicle to be moved in the second priority sort, from highest to lowest, is sequentially matched to the corresponding parking space in the first priority sort, from highest to lowest.

[0070] For example, matching is performed in the following order: -Car Q (second priority, first position):Car A (first priority, first position); - Car M (second priority, second position): Parking space B (first priority, second position); -Car N (second priority, third position): Parking space C (first priority, third position); -Car O (4th in the second priority sort):Car D (4th in the first priority sort); -Car P (5th in the second priority sort): Because parking space E became available too late, it is temporarily unable to match an available parking space in the target area, for example, the departure search strategy is executed.

[0071] In sub-step S34, the target parking space for this vehicle is determined based on the matching result of sub-step S33. For example, in the matching result shown above, this vehicle (vehicle M) is matched to parking space B, then parking space B is the target parking space for this vehicle.

[0072] It should be noted that, although in Figure 3 Neutron steps S31 and S32 are shown to be performed sequentially, but this application is not limited to this. In practical applications, they can also be performed in parallel, or alternately based on continuously dynamically updated information.

[0073] Figure 4 It shows Figure 1 Another flowchart of step S3 is shown. In this embodiment, Figure 1 Step S3 further includes sub-steps S301 to S306.

[0074] In sub-step S301, if a target parking space is determined for the vehicle within the target area based on the potential parking space availability information, a temporary parking area can also be allocated to the vehicle. This temporary parking area can be understood as not being the optimal alternative compared to the target area, for example, it may be slightly farther away or have limited availability time, but its availability time may be earlier than the target parking space. Therefore, it can serve as a transition area for the vehicle to briefly stop before the target parking space becomes available.

[0075] In one embodiment, attribute information of nearby temporary parking areas is obtained, including, for example, the distance from the vehicle's current location, available vacancy time, surrounding congestion level, charging type, and / or parking space size. A multi-dimensional matching algorithm is used to match temporary parking areas for the vehicle. During matching, the attribute information of each temporary parking area, the estimated vacancy time of the target parking space, the vehicle's size, and charging acceptance are comprehensively considered to select the temporary parking area with the highest matching degree.

[0076] In another embodiment, a database of temporary parking areas surrounding the no-parking zone can be constructed and prioritized according to their attribute information. Then, each vehicle to be moved within the no-parking zone is sequentially matched to the corresponding temporary parking area in the database to determine the temporary parking area for that vehicle.

[0077] For example, the temporary parking area information determined for each vehicle to be moved is as follows: Vehicle M (this vehicle): Temporary parking area 1 (a compliant waiting area on the edge of the road on the no-parking side, free of charge, with available time matched). Car N: Temporary parking area 2 (a free municipal parking area 300 meters away, with a 95% match rate for available time, matching parking space size, and a 30% congestion rate in the surrounding area). Car O: Temporary parking area 3 (free parking area at a distance of 450 meters, with a 92% match rate for available time, matching parking space size, and a 25% match rate for surrounding congestion). Car P: Temporary parking area 4 (paid parking lot 200 meters away, billed by the hour, standard parking space size, congestion level 15%).

[0078] In sub-step S302, the vehicle is controlled to drive into the temporary parking area to wait. In sub-step S303, when the target parking space determined for the vehicle is expected to become available, the vehicle is controlled to return from the temporary parking area to the vicinity of the target parking space to wait.

[0079] For example, if target parking space B is expected to become available at 6:50, the vehicle can be controlled to drive to the compliant waiting area on the edge of the no-parking side of the road, return to the vicinity of target parking space B at 6:40 and wait for it to become available. After the vehicle in target parking space B leaves at 6:50, the vehicle can then be controlled to drive into target parking space B.

[0080] In sub-step S304, a warning threshold can be set for the vehicle to wait for the target parking space to become available. If the waiting time exceeds the warning threshold and the target parking space is still not available, the vehicle can be controlled to give up waiting and execute the departure parking space search strategy in sub-step S305.

[0081] For example, the warning threshold can be set to 7:00. If the target parking space is still not available by then, the vehicle will abandon the wait and proceed with the search for a new space. If the target parking space becomes available before the threshold is reached (for example, at 6:55), the vehicle can be controlled to drive into the target parking space in sub-step S306.

[0082] Figure 5 A flowchart of a method for controlling the automatic relocation of the vehicle according to another exemplary embodiment of this application is shown.

[0083] In this embodiment, Figure 1The method shown includes an additional optional step S4 after step S3. If a target parking space has been determined for the vehicle in the target area based on the potential parking space availability information in step S3, then in step S4, after controlling the vehicle to automatically move to the target parking space, the vehicle's parking location, arrival time and / or expected departure time in the target area can also be synchronized to the communication network via encrypted communication.

[0084] In one embodiment, the encrypted communication adopts a dual-link architecture, including vehicle-to-vehicle (V2V) communication and vehicle-to-infrastructure (V2I) communication, which serve as backups for each other to ensure the reliability of information synchronization.

[0085] In one embodiment, after the vehicle leaves the target parking space, the corresponding status information can also be updated to the communication network so that other vehicles waiting to be moved can be informed of the change in the parking space occupancy status in the target area in a timely manner.

[0086] Figure 6 A schematic diagram illustrating the use of the method described in this application in an exemplary application scenario is shown.

[0087] In this exemplary application scenario, a row of vehicles (e.g., vehicles M, N, O, P, and Q) are parked on the right side of the road and are waiting to be moved. A no-parking sign is posted on this side of the road, indicating that parking is prohibited from 7:00 AM to 11:00 AM on Fridays. The current time is 6:45 AM, which is close to the start time of the no-parking period. Therefore, the automatic vehicle relocation program needs to be activated for vehicle M.

[0088] In this embodiment, the no-parking zone is on the right side of the road. Therefore, the parking area on the left side of the road, which is opposite to it and not affected by the no-parking zone, is set as the target area. This area is close to the original parking location, making it easier for the car owner to find their vehicle later.

[0089] First, for example, assign parking spaces A, B, C, D, and E within the target area 60 on the left to all vehicles M, N, O, P, and Q that need to be moved on the right. For example... Figure 6 As shown, there are five parking spaces on the left side of the road: A, B, C, D, and E, including vacant space A. Based on the aforementioned... Figure 4 The description method can prioritize parking spaces on the left based on their availability, estimated departure time of parked vehicles, and accuracy. The ranking results from high to low are as follows: Parking space A (vacant), Parking space B (departing at 6:50, accuracy 95%), Parking space C (departing at 7:30, accuracy 85%), Parking space D (departing at 9:00, accuracy 60%), Parking space E (no specific time, accuracy <50%).

[0090] Then, based on vehicle status information such as arrival time, emergency needs, and expected parking time, the vehicles M, N, O, P, and Q waiting to be moved on the right side of the road are sorted by a second priority. The sorting results from high to low are, for example, vehicle Q (ambulance, arriving at 6:30), vehicle M (this vehicle, arriving at 5:50), vehicle N (arriving at 6:00), vehicle O (arriving at 6:10), and vehicle P (arriving at 6:20).

[0091] Based on the above sorting results, the vehicles to be moved in the second priority sort are sequentially matched to the corresponding parking spaces in the first priority sort. An example matching result is as follows: Car Q (second highest priority) is matched with parking space A (first highest priority). Car M (second priority, second in sorting) is matched with parking space B (first priority, second in sorting). Car N (second priority, third in sorting) is matched with parking space C (first priority, third in sorting). Car O (second priority, fourth in sorting) is matched with parking space D (first priority, fourth in sorting). Car P (second priority, fifth in order of priority) has no available parking space because parking space E became available too late, so it will execute the leave-to-find-a-parking-space strategy.

[0092] exist Figure 6 In the diagram, the matching results are schematically marked by connecting lines.

[0093] Figure 7 A schematic diagram illustrating the use of the method described in this application in another exemplary application scenario is shown.

[0094] In this embodiment, before the no-parking period begins, the vehicle M is first controlled to drive into the temporary waiting area 71 on the edge of the no-parking side of the road (this area is close to the original parking location, free of charge, and its vacancy time matches the expected vacancy time of the target parking space B). After the vehicle parked in the target parking space B leaves, the vehicle M is then controlled to drive from the temporary waiting area 71 into the target parking space B.

[0095] Similarly, vehicle N can be controlled to enter temporary parking area 72 and wait (a municipal free parking area 200 meters away, with an vacancy time matching the target parking space C's vacancy time by 95%, matching parking space size, and a surrounding congestion level of 30%). Vehicle O can be controlled to enter temporary parking area 73 and wait (a municipal free parking area 300 meters away, with an vacancy time matching by 92%, matching parking space size, and a surrounding congestion level of 25%). After their respective matched target parking spaces C and D become available, vehicles N and O can then be controlled to enter their corresponding target parking spaces C and D from the temporary parking areas, respectively.

[0096] In an embodiment not shown, if the originally assigned temporary parking area is closed or unavailable, another temporary parking area can be immediately reassigned to ensure the smooth relocation process.

[0097] Figure 8 A block diagram of an apparatus for controlling the automatic relocation of a vehicle according to an exemplary embodiment of this application is shown.

[0098] In one embodiment, device 10 may be deployed locally on the vehicle, with each vehicle to be moved executing independently and following the same decision-making logic, thereby ensuring that their final allocation results tend to be consistent. In another embodiment, device 10 may also be deployed in the cloud, centrally receiving information on the availability of potential parking spaces for vehicles to be moved and the target area, and uniformly allocating parking spaces.

[0099] Device 10 includes a processor 11 and a memory 12. The memory 12 may include a computer-readable storage medium such as a hard disk, RAM, or flash memory, and stores computer program instructions. The processor 11 may be a central processing unit (CPU), microcontroller unit (MCU), graphics processing unit (GPU), neural network processing unit (NPU), digital signal processor (DSP), or other general-purpose or special-purpose processor. When the processor 11 executes the computer program instructions in the memory 12, it can perform the method described above for controlling the automatic relocation of the vehicle.

[0100] It should be noted that the specific process of the automatic vehicle relocation method involved in this embodiment is described in a simplified manner. The relevant technical details have been elaborated in detail in the foregoing method embodiments, and can be directly referred to in the description of the corresponding parts. They will not be repeated here.

[0101] Although specific embodiments of this application are described in detail herein, they are given for illustrative purposes only and should not be construed as limiting the scope of this application. Various substitutions, modifications, and alterations can be conceived without departing from the spirit and scope of this application.

Claims

1. A method for controlling the automatic relocation of the vehicle, wherein, The method includes the following steps: Step S1: Obtain the no-parking period corresponding to the current parking area of ​​this vehicle, and record the current parking time of this vehicle; Step S2: When the current parking time and the start time of the no-parking period satisfy a preset proximity relationship, obtain the availability information of potential parking spaces in the target area around the vehicle that is not subject to no-parking restrictions. The potential parking space availability information includes at least: the current occupancy status of each parking space in the target area, and the parking location of each parked vehicle in the target area and its expected departure time; and Step S3: Based on the potential parking space availability information, generate an automatic relocation strategy for the vehicle and control the vehicle to perform automatic relocation operations according to the automatic relocation strategy.

2. The method according to claim 1, wherein, In step S2, the estimated departure time of the parked vehicle is obtained by at least one of the following methods: Shared information is obtained through a communication network with parked vehicles within the target area, and the estimated departure time is determined based on this shared information. Specifically, the communication network employs a dual-architecture communication mode of V2V and V2I. When one communication link is interrupted, it automatically switches to the other communication link within a preset time threshold; and / or The estimated departure time is predicted by acquiring multi-dimensional departure features and / or historical departure behavior data of the target area through an environmental perception module. Specifically, the multi-dimensional departure features include at least one of the following: The door open / closed status of parked vehicles; Engine is running; Charging gun connection status; In-vehicle Bluetooth and / or CarPlay connection status; The activity trajectory of people in the surrounding area; and / or Vehicle body vibration characteristics.

3. The method according to claim 1 or 2, wherein, The potential parking space availability information also includes: the accuracy of the estimated departure time of each parked vehicle in the target area; The accuracy is determined using a machine learning model based on at least one of the following: the arrival time of each parked vehicle, the distance to the vehicle, multi-dimensional departure features collected by the environmental perception module, and / or historical departure behavior data of the target area.

4. The method according to any one of claims 1 to 3, wherein, Step S3 includes: Based on the potential parking space availability information, each parking space in the target area is sorted by first priority. Vacant parking spaces are assigned a higher priority than occupied parking spaces. For occupied parking spaces, the earlier the expected departure time of the parked vehicle, the higher the assigned priority. Based on the first priority ranking, a target parking space is determined for this vehicle, and the vehicle is controlled to automatically move to the target parking space.

5. The method according to any one of claims 1 to 4, wherein, The method further includes: The vehicle status information of other vehicles waiting to be moved in the same parking area as this vehicle is obtained through the communication network. The vehicle status information includes: the arrival time of each vehicle waiting to be moved, the emergency vehicle moving requirement and / or the expected parking duration. In step S3, the automatic vehicle relocation strategy is additionally generated based on the vehicle status information.

6. The method according to claim 5, wherein, In step S3, generating the automatic vehicle relocation strategy also includes: Based on the vehicle status information, each vehicle to be moved is sorted by a second priority. The earlier the arrival time, the more urgent the need for moving the vehicle, and the longer the expected parking time, the higher the priority is assigned to the vehicle to be moved. Based on the first priority sorting and the second priority sorting, a target parking space is determined for this vehicle. Specifically, each vehicle to be moved in the second priority sorting from high to low is sequentially matched to the corresponding parking space in the first priority sorting from high to low, so as to determine the target parking space for this vehicle.

7. The method according to any one of claims 1 to 6, wherein, Step S3, generating the automatic vehicle relocation strategy, also includes: If a target parking space is identified for this vehicle within the target area based on the potential parking space availability information, then the vehicle is controlled to first drive into the temporary parking area to wait, and when the target parking space is about to become available, the vehicle is controlled to drive from the temporary parking area into the target parking space. A warning threshold is set for vehicles waiting for a target parking space to become available. If the waiting time exceeds the warning threshold and the target parking space is still not available, the vehicle is controlled to abandon the wait and execute a departure parking space search strategy.

8. The method according to any one of claims 1 to 7, wherein, Step S3 also includes: If a target parking space is determined for the vehicle within the target area based on the potential parking space availability information, then after controlling the vehicle to automatically move to the target parking space, the vehicle's parking location, arrival time, and / or expected departure time within the target area are synchronized to the communication network via encrypted communication.

9. An apparatus for controlling the automatic movement of a vehicle, the apparatus comprising a memory and a processor, the memory storing computer program instructions, wherein when the computer program instructions are executed by the processor, the processor is capable of performing the method according to any one of claims 1 to 8.

10. A computer program product comprising computer program instructions, wherein, When executed by a processor, the computer program instructions enable the processor to perform the method according to any one of claims 1 to 8.

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