Patent Description:
In order to solve the parking requirement of the last kilometer in an open scenario, a memory parking function has been proposed. A user only needs to complete the learning for a route map according to a system prompt, and thus, a vehicle can automatically travel to a target parking space or can be called to automatically leave a garage, according to a learned route in the subsequent use. Memory Parking only uses a sensor around the body of the vehicle to construct a scenario map through a simultaneous localization and mapping (SLAM) technology, and can achieve high-precision positioning without relying on a high-precision map.

However, due to the cost, most of the current memory parking systems use a sensor scheme in which a low-cost vision sensor dominates and an ultrasonic radar assists. Due to the limitations of the arrangement of the visual sensor and an environmental factor such as light, it is difficult for the memory parking systems to cope with all working conditions during parking, which limits the application of the memory parking systems.

<CIT> describes a process comprising determining risk levels for vehicles adjacent to a vacant parking space based on vehicle data, visual and non-visual factors, and determining a recommended parking position based on the determined risk levels. <CIT> discloses in particular a method for parking a vehicle, comprising:.

<CIT> discloses a vehicle self-protection method including: obtaining the ambient environment information of the vehicle and the historical information of the vehicle, and determining a level of a risk faced by the vehicle based on the ambient environment information of the vehicle and the historical information of the vehicle; and performing a corresponding operation to avoid a vehicle risk and reduce a property loss and personal safety risks.

According to example embodiments of the present invention, a technical solution in which a vehicle is adaptively parked is provided.

According to a first aspect of the present invention, a method for parking a vehicle according to claim <NUM> is provided.

According to a second aspect of the present invention an apparatus for parking a vehicle according to claim <NUM> is provided.

According to a third aspect of the present invention, an electronic device according to claim <NUM> is provided.

According to a fourth aspect of the present invention, a non-transitory computer readable storage medium according to claim <NUM> is provided, storing computer instruction, wherein the computer instruction is used to cause a computer to perform the method according to the first aspect of the present invention.

According to a fifth aspect of the present invention, a computer program product according to claim <NUM> is provided, including a computer program, wherein the computer program, when executed by a processor, implements the method according to the first aspect of the present invention.

Through the technical solution of the present invention, the usage mode of the parking can be adaptively controlled for a different risk level of the parking environment, thereby widening the application scenarios of the parking technology.

It should be understood that the content described in this part is not intended to define key or important features of the embodiments of the present invention, and is not used to limit the scope of the present invention. Other features of the present invention will be easily understood through the following description.

The above and other features, advantages and aspects of various embodiments of the present invention will become more apparent in combination with the accompanying drawings and with reference to the following detailed description. In the accompanying drawings, the same or similar reference number refers to the same or similar element.

The embodiments of the present invention will be described below in more detail with reference to the accompanying drawings. Although certain embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention may be embodied in various forms, and should not be construed as being limited to the embodiments set forth herein. Rather, these embodiments are provided in order to make a more thorough and complete understanding for the present invention. It should be understood that the accompanying drawings and embodiments in the present invention are for illustrative purposes only, and are not used to limit the scope of protection of the present invention.

In the description for the embodiments of the present invention, the term "comprising" and its analogous terms should be understood as openly-inclusive (i.e., "including, but not limited to"). The term "based on" should be understood as "at least partially based on". The term "an embodiment" or "the embodiment" should be understood as "at least one embodiment". The terms such as "first" and "second" may refer to different or identical objects. Other explicit and implicit definitions may further be included in the following description.

The current autonomous driving field mainly includes the following parking modes: an automatic parking assist (APA) mode, a remote parking mode (Remote Parking Assist (RPA) mode), a memory parking mode (Home Autonomous Valet Parking (HAVP) mode), and a valet parking mode (Public Autonomous Valet Parking (PAVP) mode). Each parking mode supports pulling the vehicle out a parking position and parking the vehicle into the parking position.

The automatic parking assist APA automatically searches for a parking space when the vehicle is cruising at a low speed. After the parking space is searched, a corresponding parking space is selected. When the brake is released, the vehicle may automatically enter into the parking space. During the automatic parking, the user needs to sit in the vehicle. The automatic parking is used in the vicinity of the target parking space. At the same time, it is required to pay attention to the brake, the gear position, the steering wheel, and the like in the whole course. Accordingly, the automatic parking has a high safety guarantee, but has a big use limitation.

The remote parking mode RPA mode refers to that a remote control portion is added on the basis of the APA. Generally, in the remote parking, a mobile device application (APP) or a remote control key is used as a remote control apparatus. The remote control key communicates with the entire vehicle by radio frequency, and the mobile device APP communicates with the vehicle by Bluetooth. The remote parking mainly includes remote straight-in, remote parking-in and remote pulling-out. The remotely controllable range of the remote parking requires the user to be within a short range (e.g., <NUM> meters) of the target parking space or vehicle.

For the memory parking (HAVP), also known as self-learning parking, the vehicle needs to learn a specific parking route. At the starting point of the parking route, the user turns on the "parking route learning" function, and then parks the vehicle into a fixed parking position. Accordingly, the vehicle learns the driving and parking routes autonomously and record the routes in the "memory" of the vehicle. Upon completion of the learning of the parking route, the vehicle can implement the automatic parking-in and pulling-out by imitating the previously learned parking route. This approach liberates the user to a great extent, brings convenience to the user, but requires a high safety level, and has high requirements on the vehicle performance and the environmental condition.

For the autonomous parking (PAVP), after the passenger disembarks at a specific position at a parking lot entrance, the vehicle determines a parking route according to the information obtained by a vehicle terminal or according to the information from a parking lot side, and autonomously parks into an available parking position in the parking lot. The autonomous parking depends on a high-precision map, and the use scenario of the autonomous parking is limited to a public garage of a large-scale shopping mall, etc. A high-precision device such as a laser radar is generally used for the collecting for the map, and at the same time, a large amount of manual labeling is required, resulting a high cost and a limited application range.

As described above, each parking mode has its limitation, which often makes the application of the parking technology limited, and thus, the user cannot select the appropriate parking technology according to the conditions of the vehicle and the parking environment.

The present invention provides a method and an apparatus for parking a vehicle, an electronic device and a medium. According to the method, parking environment data of a parking environment of a vehicle and historical parking data of the vehicle in the parking environment are acquired, thus determining the risk of the parking environment. The method further includes: selecting a corresponding constraint set from a plurality of constraint sets. The plurality of constraint sets reflect a corresponding parking risk. Then, the vehicle is controlled to park according to the selected constraint set. Here, the constraint set defines a usage mode of the parking technology. If it is determined that the risk of the current parking environment is high, a more secure constraint set may be selected, and if it is determined that the risk is low, a more convenient constraint set may be selected. Accordingly, the usage mode of the parking technology can be flexibly adjusted, and the application range of the parking technology can be widened, which brings convenience to the user while the safety is guaranteed.

The embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

<FIG> is a schematic diagram of an example environment <NUM> in which an embodiment of the present invention may be implemented. The example environment <NUM> is suitable, for example, for a parking application scenario. For example, a user <NUM> drives a vehicle <NUM> into a parking environment, and it is desired that the vehicle can be parked into a target parking space without the manual driving of the user. Herein, the parking environment may be a geographic area (e.g., a parking lot) or may be one or more road sections within the geographic area. For example, the vehicle may pass through a plurality of different road sections (each of which may be referred to as a parking environment), while traveling to a parking space in the parking lot. In addition, herein, the parking includes a process of parking into the parking space and a process of pulling out the parking space, and specifically includes a process in which the vehicle travels to the vicinity of the parking space and a process in which the vehicle travels into the parking space from the vicinity of the parking space, as well as a process in which the vehicle travels to the vicinity of the user from the parking space.

As shown in <FIG>, the vehicle <NUM> may already learn or remember a route <NUM>, and the user <NUM> expects the vehicle <NUM> to park at the target parking space <NUM> after passing through the route <NUM>. In some embodiments, the vehicle <NUM> may autonomously travel to the parking space <NUM> without requiring the user <NUM> to perform a supervision in the vehicle and control and take over, if necessary, the vehicle <NUM>. In some embodiments, the user <NUM> is required to stay in the vehicle for supervision and to control and take over the vehicle <NUM> if necessary. Although <FIG> shows that the parking is performed in the situation where the user <NUM> is outside the vehicle <NUM>, it should be understood that the user <NUM> may also stay in the vehicle <NUM>.

To achieve the parking that does not require the manual driving of the user, the vehicle <NUM> may include various types of sensors, for example, a vision sensor (including a wide angle camera and a surround view camera), an ultrasonic radar (including UPAs in the front and rear of the vehicle and an APA in the side of the vehicle) and an inertial sensor. With these sensors, the vehicle <NUM> can sense and identify a stationary or moving object in the parking environment and construct a map of the parking environment. For clarity, <FIG> only schematically shows the radar <NUM> in the side of the vehicle <NUM>.

The vehicle <NUM> may be connected to a server <NUM> through, for example, a cellular network (e.g., a <NUM> network and a <NUM> network), and transmit travelling data (e.g., image data, position data and travelling data (e.g., braking, a vehicle speed and a direction) that are sensed by the sensors) to the server <NUM>.

In some embodiments, the user <NUM> may interact <NUM> with the vehicle <NUM> through a vehicle-machine interaction (the user is in the vehicle), or through a remote key or a mobile device (the user is outside the vehicle) via a cellular (e.g., <NUM> and <NUM>) and/or Bluetooth communication, For example, the user <NUM> may control the vehicle <NUM> to move forward and backward, and control the braking, vehicle speed, gear position, direction, etc., of the vehicle <NUM>. The interaction information of the user <NUM> and the vehicle <NUM> may also be transmitted and stored to the server <NUM>.

Embodiments of the present invention are described above with reference to a scenario where the vehicle <NUM> is parked into the parking space <NUM>. However, it should be appreciated by those skilled in the art that the embodiments of the present invention are also applicable to an application scenario where the vehicle is pulled out the parking space.

<FIG> is a schematic block diagram of a parking system <NUM> according to an embodiment of the present invention. The parking system <NUM> includes a vehicle <NUM>, a user-controlled mobile device <NUM>, and a server <NUM> located in the cloud.

The vehicle <NUM> may include a Bluetooth module <NUM>. The vehicle <NUM> may communicate with the mobile device <NUM> via the Bluetooth module <NUM>. For example, a vehicle control signal is received from the mobile device <NUM>, so as to remotely control the vehicle <NUM> to park. In some embodiments, in order to ensure a good quality of the Bluetooth communication between the mobile device <NUM> and the vehicle <NUM>, the mobile device <NUM> and the vehicle <NUM> are maintained within a distance (e.g., <NUM> to <NUM> meters). In some embodiments, the quality (e.g., stability and speed) of communication between the Bluetooth module <NUM> and the mobile device <NUM> may be detected, to be used to determine whether it is permitted to use the Bluetooth module <NUM> to receive an instruction from the user during parking.

The vehicle <NUM> further includes a cellular module <NUM>. The vehicle <NUM> may communicate with the server <NUM> via the cellular module <NUM>. For example, the vehicle <NUM> may transmit sensor data, travelling data, position data, etc., to the server, and receive static environment information (e.g., map data) and dynamic environment information (e.g., weather data) of a parking environment from the server <NUM>. In some embodiments, the vehicle <NUM> may further communicate with the mobile device <NUM> via the cellular module <NUM>. In the case of good cellular communication quality, the mobile device <NUM> and the vehicle <NUM> can communicate with each other even if the mobile device <NUM> and the vehicle <NUM> are separated by a relatively long distance. In some embodiments, the quality (e.g., stability and speed) of communication between the cellular module <NUM> and the server <NUM> may be detected, to be used to determine whether it is permitted to use the cellular module <NUM> to receive an instruction from the user during parking.

The vehicle <NUM> includes a positioning module <NUM>, for example, a GPS module. The positioning module <NUM> is used to determine a geographical position of the vehicle <NUM>, for example, to determine whether the vehicle <NUM> is in a predetermined parking environment (e.g., a parking lot) based on longitude and latitude information. When it is determined that the vehicle <NUM> is in the predetermined parking environment, the vehicle <NUM> may acquire associated parking environment data and historical parking data generated within the parking environment from the server <NUM> via the cellular module <NUM>. Here, the historical parking data refers to a behavior that the user <NUM> or an other user controls a vehicle in the parking environment, for example, braking or taking over the vehicle.

The vehicle <NUM> further includes a sensor <NUM> disposed on the body of the vehicle. As described above, the sensor <NUM> may include, but not limited to, a vision sensor, an ultrasonic radar, an inertial sensor, and the like. The vision sensor includes a surround view camera disposed around the periphery of the vehicle to provide a <NUM>-degree image and a wide angle camera disposed in the front of the vehicle. The ultrasonic radar includes a plurality of ultrasonic radars (referred to as "UPAs") disposed in the front and rear of the vehicle to be used to measure obstacles before and behind the vehicle, and an ultrasonic radar (referred to as "APA") disposed in the side of the vehicle to be used to measure obstacles on the side of the vehicle. Through the sensor <NUM>, a map of the parking environment of the vehicle can be constructed. Through these sensors <NUM>, dynamic environment information in the parking environment of the vehicle may further be detected, for example, a lighting condition and an occurrence frequency of obstacles.

A parking management engine <NUM> is used to determine a corresponding parking mode according to the parking environment. To this end, the parking management engine <NUM> may acquire the static environment information of the parking environment that is pre-stored or received via the cellular module <NUM>, for example, a road width, a complexity and a parking space size. The parking management engine <NUM> may further acquire the dynamic environment information of the parking environment. For example, the parking management engine <NUM> may acquire the dynamic environment information of the parking environment via the sensor <NUM>, such as weather and a current traffic flow. The parking management engine <NUM> may further acquire the communication quality related to the Bluetooth module <NUM> and the cellular module <NUM>, for example, the speed and stability of a network. Using these information, the parking management engine <NUM> may determine the risk level of the current parking environment.

In some embodiments, the parking management engine <NUM> may further acquire historical parking data of the parking environment via the cellular module <NUM>. The historical parking data includes statistical data of a historical behavior (e.g., a user takeover behavior and a braking behavior) in the parking environment. The historical parking data reflects a risk of the parking environment. If there are many braking or takeover behaviors in the parking environment, indicating a high risk or a risk higher than expected, a higher risk level can be determined accordingly.

The parking management engine <NUM> may manage the parking environment, mark the parking environment with a corresponding risk level, and configure at least one corresponding parking constraint for each risk level. The constraint includes requiring the user to be in the vehicle or permitting the user to be outside the vehicle, limiting an interaction medium of the user and the vehicle <NUM>, a vehicle speed, a distance between the user and the vehicle and a supervision responsibility, and the like. Parking constraints may be grouped into a constraint set, and the parking management engine <NUM> maps the determined risk level to a corresponding constraint set.

An interaction module <NUM> provides an interaction between the user and the vehicle <NUM>. The interaction may include a vehicle-machine interaction in the vehicle, an interaction between the mobile device <NUM> and the vehicle <NUM>, an interaction between the user and the body of the vehicle, and the like. For example, the user may input an instruction to the vehicle <NUM> via a touch screen or an other input/output apparatus to provide control for the vehicle, and the vehicle <NUM> provides a state alert, a takeover alert, an exception alert and other prompt information for the user.

A travel control module <NUM> is used to control the vehicle <NUM> to travel toward the target parking space and park at the target parking space. During this time, the vehicle <NUM> needs to satisfy the constraint set determined by the parking management engine <NUM>, otherwise a reminder may be issued to the user through the interaction module <NUM>, requiring the user to operate to satisfy the constraint on parking. The constraint set will be described in detail below with reference to <FIG>.

The mobile device <NUM> may communicate with the vehicle <NUM> and the server <NUM> via a Bluetooth or cellular communication. For example, via an application (APP) of the mobile device <NUM>, an instruction to control the vehicle <NUM> is sent, and the state alert, the takeover alert and the exception alert related to the vehicle <NUM> are received.

The server <NUM> may store the parking environment data and the historical parking data, and may send the parking environment data and the historical parking data to vehicle <NUM>. The server <NUM> may update the parking environment data and the historical parking data according to the sensing data from the vehicle <NUM> and a user behavior. In some embodiments, the parking management engine <NUM> may alternatively be deployed at the server <NUM>. In this case, the server <NUM> may determine the risk level and corresponding constraint set of the parking environment in response to a parking request from the vehicle <NUM>, for controlling the vehicle <NUM> to park into or pull out the parking space.

<FIG> is a schematic flow diagram of a method <NUM> for parking a vehicle according to an embodiment of the present invention. The method <NUM> may be performed at, for example, the vehicles <NUM> and <NUM>.

At block <NUM>, the vehicle acquires parking environment data of a parking environment related to a vehicle and historical parking data in the parking environment. When it is determined through the positioning module <NUM> that the vehicle enters a preset geographical area and is ready to park, the vehicle acquires the information related to the parking environment to determine how to park.

In some embodiments, the parking environment data includes static environment information of the parking environment. The static environment information represents environmental information that does not change or changes slowly over time, including, but not limited to, information related to a road condition and a parking space condition. For example, the static environment information may include a road width, a curvature, a slope, a number of lanes, a shape of an intersection on a route (e.g., a cross-shaped intersection, a Y-shaped intersection, a special-shaped intersection, a ring-shaped intersection and a U-turn intersection) of a plurality of road sections through which the vehicle travels to a target parking space along a pre-remembered route. The static environment information may further include a visual condition of the parking space, a size of the parking space, and a size of the surrounding space of the parking space. The static environment information may be acquired from the server <NUM> in advance and stored locally in the vehicle, or may be sensed by the vehicle through the sensor <NUM>.

In some embodiments, the parking environment data further includes dynamic environment information of the parking environment. The dynamic environment information represents environmental information that changes rapidly over time, including, but not limited to, traffic information, weather information, positioning reference information, and the like. For example, the traffic information may include a traffic participant on the road, e.g., a large/special-shaped vehicle, a non-motor vehicle, a pedestrian and a motor vehicle. The traffic information may further include a degree of mixing of the non-motor vehicle and the pedestrian, a congestion situation of the motor vehicle, a road occupancy situation by construction, etc. in a current parking environment. The weather situation may include light and weather information. The positioning reference information may include a change situation of a fixed reference along the parking route and a change situation of a semantic element. The dynamic environment information may be acquired from the server <NUM> in advance and stored locally in the vehicle, or may be sensed by the vehicle through the sensor <NUM>.

In some embodiments, the dynamic environment information may further include communication condition information. The communication condition information may include, but not limited to, the communication quality of the Bluetooth module <NUM> and the cellular module <NUM>, for example, the stability and transmission speed of each of the Bluetooth module <NUM> and the cellular module <NUM>. The communication condition information may be obtained from the actual measurement of the vehicle.

As described above, the vehicle further acquires the historical parking data in the parking environment. The historical parking data records statistical data (e.g., a number of times, a frequency or a proportion) of historical behaviors generated by users in the current parking environment for a period of time (e.g., a day, a week, a month). The historical behaviors include a takeover behavior and braking behavior generated by a current user and an other users. It should be appreciated that the more frequent the user behavior is, the higher the risk of the parking environment is than expected. The user behavior may be made by the user in response to the prompt information of the vehicle, or may be made by the user after the user himself observes the environment and senses a risk. The user behavior may be recorded locally and may be uploaded to the server <NUM>. Therefore, the historical parking data may be acquired by accessing the server <NUM>.

At block <NUM>, the vehicle selects, according to the parking environment data and the historical parking data, a constraint set for parking the vehicle from a plurality of constraint sets. Here, the plurality of constraint sets correspond to a corresponding parking risk level. The parking environment data and the historical parking data give a risk prompt of the current parking environment. Thus, rating management may be performed on different parking environments through the parking management engine <NUM>. As an example, three risk levels are given.

A low risk level satisfies the following conditions: a good weather environment, stable light, a spacious road, a simple road structure, a single type and low occurrence frequency of an obstacle, most of users having no takeover or braking on a current road, and a good network condition.

A medium risk level satisfies the following conditions: a normal weather environment, stable light, a moderately spacious road, there being a certain curve and a certain intersection, various types of obstacles, a medium occurrence frequency of the obstacles, most of users having a certain takeover on a current road, and a normal network condition.

A high risk level satisfies the following conditions: a bad weather environment, unstable light, a narrow road, there being many curves and many intersections, various types of obstacles, a high occurrence frequency of the obstacles, most of users having frequent takeovers on a current road, and a bad network condition.

Only three exemplary risk levels are shown above. It should be understood that the risk level is not limited to the three levels and may include more or fewer risk levels. In some embodiments, the risk level may be determined through any model (e.g., a neural network model) known or developed in future. Specifically, the model may be trained, and used to infer the risk level of the parking environment from the acquired parking environment data and historical parking data. Alternatively, each piece of data in the parking environment data and the historical parking data may be categorized according to experience, so as to determine the risk level of the parking environment with reference to a preset rule.

According to the invention, different usage constraints applicable to the current parking environment are determined based on the risk level, wherein a constraint refers to a permission or restriction condition related to the autonomous parking of the vehicle.

In some embodiments, the constraint may include a position of the user relative to the vehicle. For example, the user is required to remain in the vehicle during the parking, or the user is allowed to be outside the vehicle. The constraint may further include a type of an interaction between the user and the vehicle. For example, an interaction is performed through a vehicle-machine interaction (e.g., a touch screen or an other controller) in the vehicle, the user uses a mobile device to interact with the vehicle via a Bluetooth communication, the user uses a mobile device to interact with the vehicle via a cellular communication, and the user uses a remote key to interact with the vehicle. In addition, the constraint may further include an interactive manner, for example, a single click or a long press. In some cases, the user is required to hold a long press to park, or to make a single click to park, without requiring the user to keep the interactive state at all times.

The constraint may include a distance between the user and the vehicle. For example, the distance is <NUM> (i.e., the user is in the vehicle), <NUM>-<NUM> meters, <NUM>-<NUM> meters, or unlimited. It should be appreciated that the type of the interaction and the distance should be compatible with each other, that is, the distance conforms to the limitation of the type of the interaction. For example, when the constraint refers to the Bluetooth communication, the distance should generally not exceed <NUM> meters. The cellular communication may not limit the distance.

The constraint may further include a limitation to a vehicle speed. The vehicle speed may be expressed as a range of the vehicle speed, that is, a range of the permitted moving speed of the vehicle during parking.

The constraint may further include a requirement for the user to supervise the vehicle, including requiring the user to supervise the vehicle, or permitting the user not to supervise the vehicle. The supervision means that a state in which the user may interact with the vehicle and may randomly control the vehicle is required to be maintained. For example, when the user is in the vehicle, the user is required to hold the steering wheel by hand, and when the user is outside the vehicle, the mobile device APP is required to be in an active state.

Constraints are grouped into a constraint set, and the constraint set includes one or more constraints. In some embodiments, the parking management engine <NUM> may maintain the corresponding relationship between the plurality of constraint sets and the risk level, and may select, according to the determined risk level, one constraint set from the plurality of constraint sets for use in the current parking environment. As an example, four constraint sets are given, as shown in Table <NUM>.

Only four exemplary constraint sets are shown above. It should be understood that the constraint sets are not limited to the four sets, and may include more or fewer constraint sets. Furthermore, the number of risk levels and the number of constraint sets may be the same or different.

In some embodiments, the constraint set may be inferred directly from the parking environment data and the historical parking data. The constraint set may be determined by any model (e.g., a neural network model) known or developed in future. Specifically, the model may be trained, and used to infer the constraint set applicable to the parking environment from the acquired parking environment data and historical parking data. Alternatively, each piece of data in the parking environment data and the historical parking data may be categorized according to experience, so as to select the constraint set with reference to a preset rule.

Further referring to <FIG>, at block <NUM>, the vehicle is controlled to park according to the selected constraint set. The vehicle travels along the parking route to the parking space until the parking is completed. In this process, the parking route may be divided into a plurality of parking environments. Thus, in a first parking environment (e.g., a first road section), the vehicle may be parked according to a first constraint set, in a second parking environment (e.g., a second road section), the vehicle may be parked according to a second constraint set, and so on. In addition, in an N-th parking environment, for example, the last stage in which the vehicle enters the parking space from the vicinity of the parking space, the vehicle may be parked according to an N-th constraint set. It should appreciated that, for each parking environment described above, the corresponding risk level and/or constraint set may be determined, and for the each parking environment, the corresponding parking environment data and historical parking data may further be maintained.

In some embodiments, a takeover behavior and braking behavior of the user of the vehicle in a process of controlling the vehicle to park may be acquired. The generation time and positions of these behaviors may be associated and stored, and used to update the corresponding historical parking data. In some embodiments, sensing data detected by a sensor of the vehicle in the process of controlling the vehicle to park may further be acquired, and the parking environment data is updated according to the sensing data. The takeover behavior, the braking behavior and the sensing data detected by the sensor of the vehicle may be stored in the local parking data of the vehicle, and uploaded to the server at the appropriate time. Therefore, it is possible to iterate, according to the risk of multiple use by users, feed back and road repair, an algorithm model through scenario data accumulated many times to improve the scenario adaptability, thereby dynamically adjusting usage permissions of different parking environments. Accordingly, more and more roads can be used outside the vehicle, thereby improving the stability and adaptability of the system.

It should be appreciated that, in addition to being performed at the vehicle, the method <NUM> may be performed at the server <NUM>. In this situation, the server <NUM> determines and selects a risk level and a corresponding constraint set of the parking environment, and may transmit the selected constraint set to the vehicle, for controlling the vehicle to park.

The above describes an adaptive parking solution according to the embodiment of the present invention. According to this solution, if it is determined that the risk of the current parking environment is high, a more secure constraint set may be selected, and if it is determined that the risk is low, a more convenient constraint set may be selected. Accordingly, the usage mode of the parking technology can be flexibly adjusted, and the application range of the parking technology can be widened, which brings convenience to the user while the safety is guaranteed.

<FIG> is a schematic diagram of a user interface <NUM> for parking a vehicle according to an embodiment of the present invention. The user interface <NUM> may be presented on a user interaction interface in a vehicle or on a mobile device of a user.

As shown in the drawing, the route starting from the time of looking for a parking space to the time of the completion of parking is divided into a safe road section <NUM> and a risky road section <NUM>. According to an embodiment of the present invention, in the safe road section <NUM>, the vehicle may use an easy constraint set to liberate the user from a driving task. However, once it is detected that the vehicle enters the risky road section <NUM>, a prompt message (e.g., "you have entered a risky road section, the speed has dropped to <NUM>/h, please monitor the environment, and take over in time if there is any danger") may be displayed on the interface <NUM>. In some embodiments, the user may further be prompted by voice or an alarm tone that the user has entered the parking environment having a high risk.

As shown in the drawing, when the vehicle enters a parking environment having a higher risk, the constraint of the parking varies. For example, the travel speed of the vehicle is automatically reduced to <NUM>/hour. In other scenarios, the vehicle may further prompt the user to hold the steering wheel (when the user is in the vehicle), or to turn on the mobile device to supervise the vehicle (e.g., watch a video) on the mobile device. That is, the requirement for the user to supervise the vehicle is increased.

It can be seen that the adaptive parking solution according to the present invention is capable of dynamically determining the risk level and constraint of the parking environment, thereby increasing the adaptability of the parking technology and ensuring the driving safety.

The embodiments of the present invention further provide a corresponding apparatus for implementing the above method or process. <FIG> is a schematic block diagram of an apparatus <NUM> for parking a vehicle according to an embodiment of the present invention. The apparatus <NUM> is disposed in the parking management engine <NUM> of the vehicle <NUM> as shown in <FIG>. Alternatively, the device <NUM> may also be disposed in the server <NUM>.

The apparatus <NUM> includes an acquiring unit <NUM>, a constraint set selecting unit <NUM> and a parking controlling unit <NUM>. The acquiring unit <NUM> is configured to acquire parking environment data of a parking environment related to a vehicle and historical parking data in the parking environment. The constraint set selecting unit <NUM> is configured to select, according to the parking environment data and the historical parking data, a constraint set for parking the vehicle from a plurality of constraint sets, the plurality of constraint sets corresponding to a corresponding parking risk level. The parking controlling unit <NUM> is configured to control the vehicle to park according to the selected constraint set.

In some embodiments, the acquiring unit <NUM> may be further configured to acquire static environment information of the parking environment. The acquiring unit <NUM> may be further configured to acquire dynamic environment information of the parking environment. The acquiring unit <NUM> may be further configured to acquire communication condition information of the parking environment.

In some embodiments, the static environment information may include a road condition and/or parking space condition on a parking route. The dynamic environment information may include traffic information, weather information and/or positioning reference information on the parking route. The communication condition information may include a network condition of a cellular communication and/or a network condition of a Bluetooth communication. The network condition may include the stability and speed of a network.

In some embodiments, the historical parking data may include statistical data of a historical behavior of a user of the vehicle or an other user of the vehicle in the parking environment. The historical behavior may include a user takeover behavior and a braking behavior.

In some embodiments, a constraint set in the plurality of constraint sets may include a constraint for a position of the user relative to the vehicle, a constraint for a type of an interaction between the user and the vehicle, a constraint for a distance between the user and the vehicle; a constraint for a speed at which the vehicle is parked; and a constraint for a requirement for the user to supervise the vehicle.

In some embodiments, the apparatus <NUM> may further include an updating unit. The updating unit may be configured to: record a takeover behavior and braking behavior of the user of the vehicle in a process of controlling the vehicle to park; and update the historical parking data according to the takeover behavior and the braking behavior.

In some embodiments, the updating unit may be further configured to: acquire sensing data detected by a sensor of the vehicle in the process of controlling the vehicle to park; and update the parking environment data according to the sensing data.

In the technical solution of the present invention, the acquisition, storage, application, etc. of the personal information of a user all comply with the provisions of the relevant laws and regulations, and do not violate public order and good customs.

It should be understood that the each described unit in the apparatus <NUM> corresponds to each step in the method <NUM> described with reference to <FIG>. Moreover, the operations and features of the apparatus <NUM> and the units included therein all correspond to the above operations and features described in combination with <FIG> and have the same effects, and thus, the specific details will not be repeated.

The units included in the apparatus <NUM> may be implemented by various means, including software, hardware, firmware, or any combination thereof. In some embodiments, one or more units may be implemented by means of software and/or firmware, for example, a machine-executable instruction stored on a storage medium. In addition to or as an alternative to the machine-executable instruction, some or all of the units in the apparatus <NUM> may be implemented, at least in part, by one or more hardware logic components. As an example rather than a limitation, exemplary types of hardware logic components that may be used include a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), an application specific standard product (ASSP), a system on chip (SOC), a complex programmable logic device (CPLD), etc..

Some or all of the units shown in <FIG> may be implemented as hardware modules, software modules, firmware modules, or any combination thereof. In particular, in some embodiments, the procedures, methods or processes described above may be implemented by means of hardware in a storage system or a host corresponding to the storage system or an other computing device independent of the storage system.

<FIG> is a schematic block diagram of an exemplary computing device <NUM> that may be used to implement the embodiments of the present invention. The device <NUM> may be implemented in the vehicle <NUM> and server <NUM> shown in <FIG>. As shown in the drawing, the device <NUM> includes a central processing unit (CPU) <NUM>, which may execute various appropriate actions and processes in accordance with a computer program instruction stored in a read-only memory (ROM) <NUM> or a computer program instruction loaded into a random access memory (RAM) <NUM> from a storage unit <NUM>. The RAM <NUM> further stores various programs and data required by operations of the device <NUM>. The CPU <NUM>, the ROM <NUM> and the RAM <NUM> are connected to each other through a bus <NUM>. An input/output (I/O) interface <NUM> is also connected to the bus <NUM>.

A plurality of components in the device <NUM> are coupled to the I/O interface <NUM>, including: an input unit <NUM>, such as a keyboard or a mouse; an output unit <NUM>, such as various types of displays, or speakers; the storage unit <NUM>, such as a disk or an optical disk; and a communication unit <NUM> such as a network card, a modem, or a wireless communication transceiver. The communication unit <NUM> allows the device <NUM> to exchange information/data with other devices over a computer network such as the Internet and/or various telecommunication networks.

The CPU <NUM> performs the various methods and processes described above, such as the method <NUM>. For example, in some embodiments, the method described above may be implemented as a computer software program, which is tangibly included in a machine readable medium, such as the storage unit <NUM>. In some embodiments, part or all of the computer program may be loaded and/or installed on the device <NUM> via the ROM <NUM> and/or the communication unit <NUM>. When the computer program is loaded into the RAM <NUM> and executed by the CPU <NUM>, one or more steps of any of the methods described above may be performed. Alternatively, in other embodiments, the CPU <NUM> may be configured to perform any of the methods described above by any other appropriate means (for example, by means of firmware).

Program codes for implementing the method of the present invention may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer or other programmable data processing apparatus such that the program codes, when executed by the processor or controller, enables the functions/operations specified in the flowcharts and/or block diagrams being implemented. The program codes may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on the remote machine, or entirely on the remote machine or server.

In the context of the present invention, the machine readable medium may be a tangible medium that may contain or store programs for use by or in connection with an instruction execution system, apparatus, or device. The machine readable medium may be a machine readable signal medium or a machine readable storage medium. The machine readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the machine readable storage medium may include an electrical connection based on one or more wires, portable computer disk, hard disk, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, portable compact disk read only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the foregoing.

Claim 1:
A method for parking a vehicle, comprising:
acquiring (<NUM>) parking environment data of a parking environment related to a vehicle and historical parking data in the parking environment, thereby determining a parking risk level of the parking environment;
selecting (<NUM>), according to the parking environment data and the historical parking data, a constraint set for parking the vehicle from a plurality of constraint sets, wherein each constraint set of the plurality of constraint sets corresponds to a corresponding parking risk level; and
controlling (<NUM>) the vehicle to park according to the selected constraint set, wherein each constraint set of the plurality of constraint sets comprises one or more constraints, wherein each constraint refers to a permission or restriction condition related to the parking of the vehicle, and each constraint set including at least one of the following constraints:
a position of the user relative to the vehicle;
a type of an interaction between the user and the vehicle;
a distance between the user and the vehicle;
a speed at which the vehicle is parked; and
a requirement for the user to supervise the vehicle.