Optimize parking space

Abstract

A system for selecting an optimized parking location for a vehicle includes a data processor, a plurality of sensors within the vehicle, and a user model based on historical data of parking events for the vehicle; the data processor is adapted to collect parking preferences of a driver of the vehicle, identify a destination of the vehicle, identify a current location of the vehicle, collect data from the plurality of sensors within the vehicle, collect data from external sources and create a list of potential parking spaces, access the user model, rank the potential parking spaces based on the driver's parking preferences, the data from the external sources, and the user model, and provide an output based on the parking preferences of the driver of the vehicle and the user model.

Description

Technical Field

[0001] The present disclosure relates to systems and methods for selecting an optimized parking space based on a driver's preferences. Background Art

[0002] In-vehicle information systems are commonly used in vehicles such as cars, trucks, and sport utility vehicles. Information systems typically provide navigation information, entertainment information (e.g., information associated with a radio, CD player, DVD player, etc.), and other vehicle information. In some cases, information systems can be used to configure user preferences. For example, an information system presents options to a user, and the user indicates their preferences by selecting one or more options.

[0003] Due to the lack of information about possible vacant spaces available to the driver of the vehicle, the driver of the vehicle may feel anxious and uncertain when searching for the optimal parking location, which may better meet their own preferences regarding parking complexity and time to destination. Some parking facilities provide customers with guidance on where parking locations are available. These may include signs indicating the number of spots available throughout the facility or on each floor. They may also have lights or other indicators near each parking space, visible from a distance, indicating whether the parking space is available. Current autonomous driving systems do not include the ability to search for and select parking locations that are adapted to the driver's preferences. Furthermore, current autonomous driving systems do not explain their choices.

[0004] Therefore, while current systems and methods achieve their intended purposes, a need exists for new and improved systems and methods for selecting an optimal parking space by adapting parking space selection to the driver's preferences and contextual information, interacting with the driver regarding the parking space selection, and explaining the reasons behind the parking space selection. Summary of the Invention

[0005] According to several aspects of the present disclosure, a method for selecting an optimized parking location for a vehicle includes: collecting parking preferences of a driver of the vehicle using a data processor; identifying a destination of the vehicle using the data processor; identifying a current location of the vehicle using the data processor; collecting data from a plurality of sensors within the vehicle using the data processor; collecting data from an external source using the data processor; and creating a list of potential parking spaces; accessing a user model using the data processor based on historical data of parking events for the vehicle; sorting the potential parking spaces using the data processor based on the driver's parking preferences, data from the external source, and the user model; and providing an output using the data processor based on the parking preferences of the driver of the vehicle and the user model.

[0006] According to another aspect, collecting, with the data processor, parking preferences of a driver of the vehicle further comprises collecting, with the data processor, via a driver interface, one of a first selection preference, a second selection preference, and a third selection preference.

[0007] According to another aspect, providing an output using a data processor based on the parking preferences and user model of the driver of the vehicle further includes: using the data processor to send an instruction to a vehicle controller to automatically park the vehicle in a highest ranked potential parking space when the driver of the vehicle has selected a first selection preference via the driver interface.

[0008] According to another aspect, providing an output using a data processor based on the parking preferences and user model of a driver of the vehicle further includes: displaying, using the data processor, a plurality of ranked potential parking spaces via the driver interface; collecting, using the data processor, a selection of one of the ranked potential parking spaces and a selection of one of automatic parking and manual parking by the driver via the driver interface; and sending, using the data processor, an instruction to the vehicle controller to automatically park the vehicle in the selected one of the plurality of ranked potential parking spaces when the driver of the vehicle has selected a second selection preference and automatic parking via the driver interface.

[0009] According to another aspect, providing an output, using the data processor, based on the parking preferences of the driver of the vehicle and the user model further includes: sending, using the data processor, an instruction to a vehicle controller to allow the driver of the vehicle to manually park the vehicle in one of the selected ones of the plurality of sorted potential parking spaces when the driver has selected a second selection preference and manual parking via the driver interface.

[0010] According to another aspect, providing an output, using a data processor, based on the parking preferences of a driver of the vehicle and a user model further includes displaying, using the data processor, via the driver interface, the plurality of sorted potential parking spaces when the driver of the vehicle has selected a third selection preference via the driver interface.

[0011] According to another aspect, displaying, with the data processor, via the driver interface, a plurality of ranked potential parking spaces further includes displaying, with the data processor, via the driver interface, an explanation of the ranking of the plurality of ranked potential parking spaces.

[0012] According to another aspect, displaying, with the data processor, via the driver interface, an interpretation of the ranking of the plurality of potential parking spaces further comprises displaying, with the data processor, via the driver interface, a comparison of parking characteristics of each of the plurality of potential parking spaces to the user preferences based on the parking preferences of the driver of the vehicle, data from an external source, and the user model.

[0013] According to another aspect, the method further includes updating the user model using the data processor via the driver interface and ultimately selecting which of the plurality of potential parking spaces based on input collected by the data processor.

[0014] According to another aspect, the method further includes creating, using a data processor, a list of potential parking spaces at predetermined intervals and ranking the potential parking spaces based on the driver's parking preferences and the user model as the vehicle moves toward the destination.

[0015] According to another aspect, ranking the potential parking spaces with the data processor based on the driver's parking preferences, data from an external source, and the user model further includes assigning a value to each of the potential parking spaces based on how well each of the potential parking spaces satisfies the driver's parking preferences.

[0016] According to another aspect, ranking the potential parking spaces with the data processor based on the driver's parking preferences, data from external sources, and the user model further includes calculating a probability that each of the potential parking spaces will be empty when the vehicle arrives.

[0017] According to several aspects of the present disclosure, a system for selecting an optimized parking location for a vehicle includes a data processor, multiple sensors within the vehicle, and a user model based on historical data of parking events for the vehicle; the data processor is adapted to collect parking preferences of a driver of the vehicle, identify a destination of the vehicle, identify a current location of the vehicle, collect data from multiple sensors within the vehicle, collect data from external sources and create a list of potential parking spaces, access the user model, rank the potential parking spaces based on the driver's parking preferences, the data from the external sources, and the user model, and provide an output based on the parking preferences of the driver of the vehicle and the user model.

[0018] According to another aspect, the system further includes a driver interface, wherein the data processor is adapted to collect a parking preference of a driver of the vehicle via the driver interface, the parking preference being one of a first selection preference, a second selection preference, and a third selection preference.

[0019] According to another aspect, the system further includes a vehicle controller, wherein when the driver of the vehicle selects the first selection preference, the output provided by the data processor includes instructions sent to the vehicle controller to automatically park the vehicle in the highest ranked potential parking space.

[0020] According to another aspect, the data processor is further adapted to display a plurality of sorted potential parking spaces via the driver interface and to collect, via the driver interface, a selection of one of the sorted potential parking spaces and a selection of one of automatic parking and manual parking by the driver, wherein, when the driver of the vehicle selects a second selection preference and automatic parking, the output provided by the data processor includes sending an instruction to the vehicle controller to automatically park the vehicle in the selected one of the plurality of sorted potential parking spaces when the driver of the vehicle has selected the second selection preference and manual parking, the output provided by the data processor includes sending an instruction to the vehicle controller to allow the driver of the vehicle to manually park the vehicle in the selected one of the plurality of sorted potential parking spaces, and when the driver of the vehicle selects a third selection preference, the output provided by the data processor includes displaying the plurality of sorted potential parking spaces via the driver interface.

[0021] According to another aspect, the data processor is further adapted to display an interpretation of the ranking of the plurality of ranked potential parking spaces by displaying, via the driver interface, a comparison of parking characteristics of each of the plurality of potential parking spaces to the user preferences based on the parking preferences of the driver of the vehicle, data from the external source, and the user model.

[0022] According to another aspect, the data processor is adapted to update the user model based on input collected by the data processor via the driver interface and which of the plurality of potential parking spaces is ultimately selected.

[0023] According to another aspect, the data processor is adapted to repeatedly create the list of potential parking spaces and to sort the potential parking spaces at predetermined intervals as the vehicle moves toward the destination.

[0024] According to another aspect, the data processor is adapted to rank the potential parking spaces based on the driver's parking preferences, data from an external source, and a user model by assigning a value to each of the potential parking spaces based on the extent to which each of the potential parking spaces satisfies the driver's parking preferences, and calculating a probability that each of the potential parking spaces will be empty when the vehicle will arrive at such a parking space.

[0025] Further areas of applicability will become apparent from the description provided herein.It should be understood that the description and specific examples are intended for purposes of illustration only and are not intended to limit the scope of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The drawings described herein are for illustration purposes only and are not intended to limit the scope of the present disclosure in any way.

[0027] Figure 1 is a schematic diagram of a system according to an exemplary embodiment of the present disclosure;

[0028] Figure 2 is an example of a display on a driver interface that allows the driver to select between a first selection preference, a second selection preference, and a third selection preference;

[0029] Figure 3 is an example of a display presenting a ranked list of parking spaces to a driver on a driver interface; and

[0030] Figure 4 The operation is illustrated Figure 1 Flowchart of a method of a system. DETAILED DESCRIPTION

[0031] The following description is merely exemplary in nature and is not intended to limit the present disclosure, application, or uses.

[0032] refer to Figure 1 The system 10 for selecting an optimized parking location for a vehicle includes a data processor 12, a plurality of sensors 14 within the vehicle, and a user model 16. The data processor 12 is a non-general purpose electronic control device or CPU having a pre-programmed digital computer or processor, a memory or non-transitory computer-readable medium for storing data such as control logic, software applications, instructions, computer code, data, lookup tables, etc., and a transceiver and input / output ports. Computer-readable media includes any type of media that can be accessed by a computer, such as read-only memory (ROM), random access memory (RAM), a hard drive, a compact disk (CD), a digital video disk (DVD), or any other type of memory. "Non-transitory" computer-readable media does not include wired, wireless, optical, or other communication links that transmit temporary electrical or other signals. Non-transitory computer-readable media includes media in which data can be permanently stored and media in which data can be stored and later rewritten, such as rewritable optical disks or erasable storage devices. Computer code includes any type of program code, including source code, object code, and executable code. Thus, the term "data processor" as used herein is not literally limited to a single CPU. Furthermore, data processor 12 itself may comprise a network of one or more computers, such as any other device referred to herein as a "computer."

[0033] The plurality of sensors 14 collects inputs of various vehicle conditions and data from one or more vehicle systems. Such data may include system mode failures, operating limits of individual vehicle system components, and reconfiguration parameters associated with the vehicle systems to allow for user interfaces. The plurality of sensors 14 also collects environmental inputs. The plurality of sensors 14 may include temperature sensors, traffic sensors, road type (e.g., highway, city) sensors, weather (e.g., rain) sensors, occupancy sensors, exterior cameras, interior cameras, lidar / radar, brake sensors, steering sensors, throttle sensors, speed sensors, vehicle switches, personal devices, HMI interactions, microphones, and the like.

[0034] As provided, the sensors 14 can measure any of a variety of phenomena or characteristics. As further examples, the sensors can measure the vehicle's ignition position or state, whether the vehicle is being turned off or on, whether the vehicle is within a certain distance of a location or to what extent, weather type (e.g., rain), weather level (e.g., amount of rain), outside temperature, outside humidity, outside wind temperature, cabin temperature, vehicle speed, occupancy of seats in the vehicle, weight of occupants of seats in the vehicle (e.g., to identify children and adults), who is in the cabin (e.g., as identified by the presence of user-specific auxiliary devices), vehicle status (e.g., amount of gas in the tank, cabin temperature, fuel level), driver status (e.g., how long the driver has been driving and how he is driving (e.g., erratically), general conditions (e.g., weather, temperature, day, time of day), driving conditions (e.g., road type, traffic), etc.

[0035] The user model 16 is based on historical data from past parking events for the driver, the vehicle, or both. The user model 16 can be based on the vehicle's own historical data from past parking events, or it can be customized for a specific driver. In such cases, the driver-specific user model 16 can be stored in a cloud-based database, where the driver's unique user model 16 is downloaded to the vehicle when the driver uses the specific vehicle. The user model 16 is created by collecting data from past parking events and using past behavior to predict future behavior. The user model 16 contains information about the characteristics of the selected parking space, as well as other factors that contribute to parking space selection. The user model 16 predicts what characteristics are desirable in a parking space given the current conditions. The driver-specific user model 16 can differentiate between the driving patterns of the same user based on the vehicle being driven. For example, the driver-specific user model 16 can differentiate between when a driver uses their vehicle exclusively for work and when they use the vehicle almost exclusively for traveling with their family. The user model 16 is created / updated by the data processor 12 and stored within the data processor 12 in the case of a vehicle-specific user model 16, or in a remote cloud-based database in the case of a driver-specific user model 16. Additionally, the user model 16 may be stored within a mobile application on a device belonging to the driver, where the user model 16 and system 10 may have access to the driver's calendar, which may help the user model predict current preferences, such as when the calendar indicates that the driver is late for a meeting, and therefore prioritize close / easy parking regardless of cost.

[0036] The data processor 12 is adapted to collect the parking preferences of the driver of the vehicle. In an exemplary embodiment, the system 10 includes a driver interface 18. The data processor 12 is adapted to collect the parking preferences of the driver of the vehicle via the driver interface 18. The data processor 12 receives the parking preferences from the driver interface 18 via an input / output port within the data processor 12. In various embodiments, the driver interface 18 may include, but is not limited to, a voice system and / or a display system. It will be appreciated that in various embodiments, other types of driver interfaces 18 that receive information about the driver's preferences from the driver may be implemented within the vehicle, or may be implemented separately from the vehicle and may communicate with the data processor 12 (e.g., a smartphone, tablet computer, remote server, etc.).

[0037] In various embodiments, the voice-based driver interface 18 presents preference options to the driver through a verbal dialogue and receives preference information from the driver in the form of recorded user speech. The data processor 12 manages the verbal dialogue generated by the voice-based driver interface to obtain preference information. The verbal dialogue can be managed based on the context of the dialogue. The current context can be identified based on context information received from the vehicle or other systems associated with the vehicle. The context information can be provided by, for example, other control modules in the vehicle (e.g., body control module, engine control module, transmission control module, infotainment control module, etc.), multiple sensors 14 and / or the vehicle's communication bus or other communication devices. The voice-based driver interface 18 processes the recorded user speech to identify preference information and provides the preference information to the data processor.

[0038] In various embodiments, the driver interface 18 presents preference options to the driver by displaying a graphical user interface on a display and receives driver parking preferences from the driver in the form of input signals received from the driver's interaction with sensors and / or switches of the display. The data processor 12 manages the graphical user interface generated by the driver interface 18 to obtain preference information. The graphical user interface can be managed based on the context of the display. The current context can be identified based on context information received from the vehicle or from other systems associated with the vehicle. The driver interface 18 processes the input signals to identify preference information and provides the preference information to the data processor 12. Alternatively, the driver interface 18 can communicate with the driver's personal device or mobile application, wherein the driver parking preferences can be transmitted to the data processor 12 even when the driver / user of the vehicle is not in the vehicle.

[0039] The data processor 12 is adapted to identify the destination of the vehicle. The data processor 12 accesses information from an onboard system, such as a navigation system, to determine the vehicle's final destination. The data processor 12 is also adapted to identify the vehicle's current location. The data processor 12 receives information from a GPS system 20 to determine the vehicle's current location. The data processor 12 is also adapted to collect data from a plurality of sensors 14 within the vehicle to determine the vehicle and the environmental conditions surrounding the vehicle.

[0040] The data processor 12 is further adapted to collect data from external sources 22 and create a list of potential parking spaces for the vehicle. The data processor 12 collects data from external sources 22, such as sensor / camera data from parking infrastructure and information about nearby parking availability from databases maintained by various parking infrastructure and transportation groups, such as the Department of Transportation (DOT). Furthermore, the external sources 22 may include other vehicles, from which information can be obtained directly via network communications through crowdsourcing. For example, when a vehicle leaves a parking space, it communicates this information to nearby vehicles via a vehicle-to-vehicle network to notify other vehicles of the availability of the recently vacated parking space. The data processor 12 includes a transceiver that allows the data processor 12 to communicate wirelessly with a remote database of external sources 22 via a WLAN, 4G, or 5G network, or the like.

[0041] The data processor 12 is further adapted to access the user model 16 and rank potential parking spaces based on the driver's parking preferences, data from the external source 22 and the user model 16 , and provide an output based on the vehicle's driver's parking preferences and the user model 16 .

[0042] Data processor 12 is adapted to rank potential parking spaces based on the driver's parking preferences, data from external source 22, and user model 16 by assigning a value to each of the potential parking spaces based on how well each space satisfies the driver's parking preferences. For example, according to user model 16, a vehicle parks in covered parking spaces whenever it rains. User model 16 will use this information to predict that the vehicle's driver will prefer covered parking spaces when it rains and will assign a higher value to covered parking spaces whenever it rains. In another example, user model 16 may indicate that on weekdays, when the vehicle's driver is driving alone to work in the mornings, the vehicle typically parks in less expensive parking spaces, but on weekends, when the vehicle's driver is traveling with passengers, the vehicle typically parks closer to the final destination later in the day, regardless of cost. Therefore, if the vehicle's driver is dining with friends on Saturday evening, data processor 12 will assign a higher value to the parking space closest to the final destination.

[0043] When sorting potential parking spots, the system 10 optimizes based on the driver's perspective, taking into account weather, the distance the driver is likely willing to travel, and how long the vehicle will need to be parked there. The system 10 further optimizes based on the vehicle's perspective, taking into account factors such as the distance to the final destination, the distance to the parking spot, the vehicle's speed and maneuverability, and whether the vehicle needs to charge while parked. Finally, the system 10 further optimizes based on the parking spot's perspective, taking into account factors such as the complexity of the parking spot (structure, street, difficulty in getting out, etc.), price, probability of being empty, the time allowed for parking, permitted demand, and the vehicle's possible next mission. For example, the autonomous vehicle may need to autonomously drive to a more distant parking spot, or may need to continue driving to complete a mission, such as taking another passenger to a different location, delivering a package to a different location, etc. These subsequent missions may affect where the vehicle drops off the user and the parking spot ultimately selected.

[0044] The first step in sorting or scoring the list of potential parking spaces involves identifying parking spaces for which information is known, to identify a parking space that meets the priorities established by the user model 16 and is close enough to the vehicle to be selected if it is empty. For example, when calculating the score P for a given parking space, i , calculate the variable:

[0045] P i Position: can be mapped to a value between 0-1, where 1 represents closer parking and smaller numbers represent farther parking;

[0046] P i Price: can be mapped to a value between 0-1, where 1 represents expensive parking and smaller numbers are used for cheaper parking; and

[0047] P i Complexity: Assume a value between 0-1, where 1 represents the most complex parking.

[0048] According to the user model 16, the user's preference for the parking space at P is obtained using the preference for the parking space at the current time and destination. i The probability of stopping is between 0 and 1, then:

[0049] Rating (P i )=User value(P i )*(-(Complexity(P i )+Price(P i ))).

[0050] According to the user model 16, a binary value of 1 is obtained, indicating that the driver wishes to park in the parking space P i , otherwise it gets the value 0, then:

[0051] Score (Pi )=User value(P i )-(Complexity(P i )+Price(P i )).

[0052] The distance to the final destination can also be added here, but is currently considered in conjunction with the time it will take the driver to walk to the final destination.

[0053] Additionally, the second step in ranking or scoring potential parking spaces involves a probabilistic analysis, in which data processor 12 calculates the probability that each potential parking space will be empty when the vehicle arrives at that space. For example, assume that a database of parking options is available to system 10, and an occupancy distribution model has been calculated so that, for any time and date, the probability of finding an empty spot at a particular parking location can be retrieved. Using this data, data processor 12 determines that certain parking structures are typically full or nearly full during specific times, such as during business hours for parking structures near office buildings and during morning and evening hours for parking structures near restaurant areas. When ranking potential parking spaces, data processor 12 calculates the probability that a parking space within a particular parking structure will be available at the estimated arrival time. If the data indicates that such a space has a low probability of availability, data processor 12 assigns it a lower score. Alternatively, system 10 can communicate with the parking facility to reserve parking spaces, thereby eliminating the probabilistic element in ranking / scoring potential parking spaces and allowing system 10 to guarantee that such a space will be empty when the vehicle arrives.

[0054] At least some of the parking preference options presented to the driver via the driver interface 18 are multi-dimensional (i.e., have at least two options related by a condition or have at least one fuzzy value option). In an exemplary embodiment, the driver interface 18 accepts the driver's selection of one of a first selection preference, a second selection preference, and a third selection preference. Figure 2 , shows an example of a display screen 26A for the driver interface 18 including a first touchscreen icon 28A for selecting a first selection preference, a second touchscreen icon 28B for selecting a second selection preference, and a third touchscreen icon 28C for selecting a third selection preference.

[0055] The first selection preference may be categorized as "park only." In an exemplary embodiment, system 10 further includes a vehicle controller 24. When the driver of the vehicle selects the first selection preference, the output provided by data processor 12 includes instructions sent to vehicle controller 24 to automatically park the vehicle in the highest-ranked potential parking space. For example, in an autonomous vehicle, the driver may wish to allow system 10 to select the highest-ranked parking space, and vehicle controller 24 will maintain control of the vehicle until the vehicle is parked in the highest-ranked parking space.

[0056] The second selection preference may be categorized as "Ask me first." In an exemplary embodiment, the data processor 12 is further adapted to display a plurality of ranked potential parking spaces via the driver interface 18 and to collect the driver's selection of one of the ranked potential parking spaces and one of automatic parking and manual parking via the driver interface 18. The data processor 12 displays the ranked parking spaces in descending order. For example, the driver interface 18 displays the three highest ranked parking spaces so that the driver can select one of the three highest ranked parking spaces. If the driver wishes, the driver can scroll down to see additional lower ranked parking spaces. Reference Figure 3 , shows an example of a display screen 26B for the driver interface 18, including a ranked list of potential parking spaces. As shown, the list includes three touchscreen icons 30A, 30B, and 30C, one for each of the three highest ranked parking spaces. Display screen 26B also includes a touchscreen slider 32 to allow the driver to scroll down through the ranked list of parking spaces to view spaces further down in the ranking.

[0057] When the driver of the vehicle has selected the second selection preference and automatic parking, the output provided by the data processor 12 includes sending instructions to the vehicle controller 24 to automatically park the vehicle in a selected one of the plurality of ranked potential parking spaces. When the driver of the vehicle has selected the second selection preference and manual parking, the output provided by the data processor 12 includes sending instructions to the vehicle controller 24 to allow the driver of the vehicle to manually park the vehicle in the selected one of the plurality of ranked potential parking spaces. For example, in an autonomous vehicle, the vehicle controller 24 will disengage autonomous driving, allowing the driver of the vehicle to take control of the vehicle and manually park the vehicle in the selected parking space.

[0058] The third selection preference may be categorized as "Let Me Park." When the driver of the vehicle selects the third selection preference, the output provided by data processor 12 includes displaying a plurality of ranked potential parking spaces via driver interface 18. No selection of a parking space is required. The driver of the vehicle simply uses the ranked list of parking spaces as a reference to decide where to park the vehicle.

[0059] In an exemplary embodiment, the data processor 12 is further adapted to display, via the driver interface 18, an explanation of the ranking of the plurality of ranked potential parking spaces by displaying a comparison of the parking characteristics of each of the plurality of potential parking spaces with the parking preferences of the driver of the vehicle based on the data from the external source 22 and the user preferences of the user model 16.

[0060] For example, Figure 3 As shown, the data processor 12 may provide an explanation that the highest-ranked parking space in the sorted parking space list is ranked #1 because it is raining and the particular parking space is in a covered parking structure and is closest to the destination. In another example, the data processor may provide an explanation that the highest-ranked parking space in the sorted parking space list is ranked #1 because the weather outside is sunny, and even though other spaces in the list are closer, the #1 sorted parking space has the lowest cost. The reason and explanation for the ranking may be based on the user model 16, where past parking events have created a pattern of vehicles parking in less expensive parking spaces, except in cases of inclement weather.

[0061] In an exemplary embodiment, driver interface 18 is adapted to receive information from the driver regarding more specific parking preferences. For example, data processor 12 may ask the driver, via driver interface 18, a question such as, "You are traveling toward building ABC. Are you in a hurry?" The driver may respond "yes," either verbally or by entering a response into driver interface 18, to which data processor 12 ranks closer parking spaces higher, or "no," to which data processor 12 ranks cheaper or more convenient parking spaces higher, even if the driver may need to travel a certain distance to reach the final destination. In another example, for an autonomous vehicle, data processor 12 may ask the driver, via driver interface 18, a question such as, "Do you wish to be dropped off at the entrance?" If the driver selects this, the vehicle will proceed to the entrance of the final destination and, after the driver has exited the vehicle, automatically proceed to a nearby parking spot. This ranking of parking spots is based on the fact that typical driver preferences, such as distance to the final destination, are less important.

[0062] In an exemplary embodiment, data processor 12 is adapted to update user model 16 based on input collected by data processor 12 via driver interface 18 and the ultimate selection of one of a plurality of potential parking spaces. Each time the vehicle is parked, the selected parking space, its characteristics, data from a plurality of sensors 14 within the vehicle, and data from external sources 22 are collected by data processor 12 and used to update user model 16. Such updates continually improve the predictions made by user model 16 and allow user model 16 to evolve as the driver's habits and preferences may change over time.

[0063] In an exemplary embodiment, data processor 12 is adapted to repeatedly create and rank the list of potential parking spaces at predetermined intervals as the vehicle moves toward its destination. As the vehicle approaches its final destination, data processor 12 continuously collects data from external source 22 and updates the ranked list of parking spaces. For example, a database for a parking structure may be updated to indicate that the availability of parking spaces in that structure has changed, and data processor 12 may update the ranked list of parking spaces to include recently vacated spaces or remove recently occupied spaces. Additionally, weather conditions or traffic conditions may change, thereby affecting the ranking of potential parking spaces. By continuously updating the ranked list of parking spaces, data processor 12 ensures that accurate information is relayed to the driver of the vehicle as the vehicle approaches its final destination.

[0064] refer to Figure 4 , a flow chart illustrating a method 100 for selecting an optimized parking location for a vehicle is shown. Beginning at block 102, the method includes collecting parking preferences of a driver of the vehicle using the data processor 12. Moving to block 104, the method 100 also includes identifying a destination of the vehicle using the data processor 12. Moving to block 106, the method 100 also includes identifying a current location of the vehicle using the data processor 12. Moving to block 108, the method 100 also includes collecting data from a plurality of sensors 14 within the vehicle using the data processor 12, and, moving to block 110, collecting data from external sources 22 using the data processor 12, and then, moving to block 112, creating a list of potential parking spaces.

[0065] Moving to block 114 , the method 100 further includes accessing, using the data processor 12 , the user model 16 based on historical data of parking events for the vehicle, and, moving to block 116 , ranking, using the data processor 12 , the potential parking spaces based on the driver's parking preferences, data from the external source 22 , and the user model 16 , and, moving to block 118 , providing, using the data processor 12 , an output based on the parking preferences of the driver of the vehicle and the user model 16 .

[0066] In an exemplary embodiment, collecting the parking preferences of the driver of the vehicle with the data processor 12 at block 102 further includes collecting, with the data processor 12 via the driver interface 18 , one of a first selection preference, a second selection preference, and a third selection preference.

[0067] Within box 118, moving to box 120, providing an output using the data processor 12 based on the parking preferences of the driver of the vehicle and the user model 16 also includes: using the data processor 12 to send instructions to the vehicle controller 24 to automatically park the vehicle in the highest ranked potential parking space when the driver of the vehicle has selected the first selection preference via the driver interface 18.

[0068] Within box 118, moving to box 122, providing an output using the data processor 12 based on the parking preferences of the driver of the vehicle and the user model 16 also includes: displaying, using the data processor 12 via the driver interface 18, a plurality of ranked potential parking spaces; and moving to box 124, collecting, using the data processor 12 via the driver interface 18, a selection of one of the ranked potential parking spaces and a selection of one of automatic parking and manual parking by the driver.

[0069] Moving from frame 124 to frame 126 , the method 100 includes sending, with the data processor 12 , instructions to the vehicle controller 24 to automatically park the vehicle in a selected one of the plurality of sorted potential parking spaces when the driver of the vehicle has selected the second selection preference and automatic parking via the driver interface 18 .

[0070] Moving from frame 124 to frame 128 , the method 100 includes sending, with the data processor 12 , an instruction to the vehicle controller 24 to allow the driver of the vehicle to manually park the vehicle in a selected one of the plurality of sorted potential parking spaces when the driver has selected the second selection preference and manual parking via the driver interface 18 .

[0071] Within box 118 , moving to box 130 , providing an output using the data processor 12 based on the parking preferences of the driver of the vehicle and the user model 16 further includes: displaying, using the data processor 12 , via the driver interface 18 , a plurality of ranked potential parking spaces when the driver of the vehicle has selected a third selection preference via the driver interface 18 .

[0072] In an exemplary embodiment, displaying the plurality of ranked potential parking spaces via the driver interface with data processor 12 at blocks 122 and 130 further includes displaying an explanation of the ranking of the plurality of ranked potential parking spaces via driver interface 18 with data processor 12 .

[0073] In another exemplary embodiment, displaying, via the driver interface 18, the explanation of the ranking of the plurality of potential parking spaces using the data processor 12 at blocks 122 and 130 further includes displaying, via the driver interface 18, using the data processor 12, a comparison of parking characteristics of each of the plurality of potential parking spaces to the user preferences based on the parking preferences of the driver of the vehicle, data from the external source 22, and the user model 16.

[0074] Moving to box 132 , the method 100 also includes updating the user model 16 via the driver interface 18 using the data processor 12 based on the input collected by the data processor 12 and which of the plurality of potential parking spaces is ultimately selected.

[0075] In an exemplary embodiment, the method 100 further includes, as the vehicle moves toward the destination, Figure 4 As shown by arrow 134 in FIG, the list of potential parking spaces is repeatedly created at box 112 and sorted at box 116 by the data processor 12 at predetermined intervals based on the driver's parking preferences and the user model 16.

[0076] In another exemplary embodiment, at box 116, ranking the potential parking spaces using the data processor 12 based on the driver's parking preferences, data from the external source 22, and the user model 16 also includes: assigning a value to each of the potential parking spaces based on the degree to which each of the potential parking spaces satisfies the driver's parking preferences.

[0077] In yet another exemplary embodiment, at box 116, ranking the potential parking spaces using the data processor 12 based on the driver's parking preferences, data from the external source 22, and the user model 16 also includes calculating a probability that each of the potential parking spaces will be empty when the vehicle will arrive at the parking space.

[0078] The system 10 and method 100 of the present disclosure provide the following advantages: selecting an optimal parking space by adapting the parking space selection to the driver's preferences and contextual information, interacting with the driver regarding the parking space selection, and explaining the reasoning behind the parking space selection. This allows for better driver satisfaction when such a vehicle system selects a parking space, particularly for an autonomous vehicle.

[0079] The description of the present disclosure is merely exemplary in nature, and variations that do not depart from the gist of the present disclosure are intended to be within the scope of the present disclosure. Such variations are not to be regarded as a departure from the spirit and scope of the present disclosure.

Claims

1. A method for selecting an optimized parking location for a vehicle, comprising: collecting, using a data processor, parking preferences of a driver of the vehicle; identifying a destination of the vehicle using the data processor; identifying, using the data processor, a current location of the vehicle; collecting data from a plurality of sensors within the vehicle using the data processor; utilizing the data processor to collect data from external sources and create a list of potential parking spaces; accessing, with the data processor, a user model based on historical data of parking events for the vehicle; ranking the potential parking spaces using the data processor based on the driver's parking preferences, data from an external source, and the user profile; as well as providing an output with the data processor based on the parking preferences of the driver of the vehicle and the user model; wherein collecting, using the data processor, parking preferences of a driver of the vehicle further comprises collecting, using the data processor via a driver interface, one of a first selection preference, a second selection preference, and a third selection preference; Wherein, providing an output using the data processor based on the parking preference of the driver of the vehicle and the user model comprises: displaying, using the data processor, via the driver interface, a plurality of ranked potential parking spaces; collecting, with the data processor, via the driver interface, a selection by the driver of one of the sorted potential parking spaces and a selection of one of automatic parking and manual parking; and sending, with the data processor, instructions to a vehicle controller to automatically park the vehicle in a selected one of the plurality of sorted potential parking spaces when a driver of the vehicle has selected the second selection preference and automatic parking via the driver interface; wherein displaying, with the data processor, via the driver interface, the plurality of ranked potential parking spaces comprises displaying, with the data processor, via the driver interface, an explanation of the ranking of the plurality of ranked potential parking spaces; wherein displaying, using the data processor, via the driver interface, an interpretation of the ranking of the plurality of potential parking spaces comprises displaying, using the data processor, via the driver interface, a comparison of parking characteristics of each of the plurality of potential parking spaces with the user preferences based on the parking preferences of the driver of the vehicle, data from an external source, and the user model.

2. The method according to claim 1, wherein Providing an output using the data processor based on the parking preferences of the driver of the vehicle and the user model also includes: using the data processor to send instructions to the vehicle controller to automatically park the vehicle in the highest ranked potential parking space when the driver of the vehicle has selected the first selection preference via the driver interface.

3. The method according to claim 1, wherein Providing an output, using the data processor, based on the parking preferences of the driver of the vehicle and the user model further includes sending, using the data processor, an instruction to the vehicle controller to allow the driver of the vehicle to manually park the vehicle in one of the selected ones of the plurality of sorted potential parking spaces when the driver of the vehicle has selected the second selection preference and manual parking via the driver interface.

4. The method according to claim 3, wherein: Providing an output, using the data processor, based on the parking preferences of the driver of the vehicle and the user model further includes displaying, using the data processor, via the driver interface, the plurality of ranked potential parking spaces when the driver of the vehicle has selected the third selection preference via the driver interface.

5. The method according to claim 1, further comprising: The user model is updated via the driver interface using the data processor based on input collected by the data processor and ultimately selecting which of the plurality of potential parking spaces is selected.

6. The method according to claim 5, further comprising: As the vehicle moves toward the destination, the list of potential parking spaces and the ranking of the potential parking spaces are repeatedly created and ranked by the data processor at predetermined intervals based on the driver's parking preferences and the user profile.

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