Utilizing transition times to intelligently select transition locations for autonomous vehicles - Patents.com

Abstract

This disclosure describes an AV transition location system that can utilize a computer-implemented model to analyze updates from provider and requester devices, determine transition times for various locations within various geographic areas, and intelligently select transition locations for an autonomous vehicle or other provider device based on the transition times. In particular, in one or more embodiments, the disclosed system utilizes geohash mapping combined with provider device telematic data to establish pickup metrics that meet transition time characteristics in a given geographic area. Depending on the specific characteristics required by the provider device, the disclosed system can provide a subset of preferred pickup locations to accurately and efficiently navigate the autonomous device.

Description

[Background technology]

[0001] [CROSS-REFERENCE TO RELATED APPLICATIONS] This application claims the benefit of and priority to U.S. Patent Application No. 18 / 163,562, filed February 2, 2023. The entire contents of the aforementioned patent application are incorporated herein by reference.

[0002] Recent years have seen significant developments in on-demand transportation systems that utilize mobile devices to interface across computer networks. Indeed, the proliferation of web and mobile applications has enabled requesting devices to utilize on-demand ride selection systems to interface across computer networks, thereby initiating transportation from one geographic location to another and coordinating appropriate pickup or drop-off locations between provider and requester devices. For example, traditional transportation network systems can determine the geographic locations of provider and requester devices, generate digital matches between provider and requester devices, and further track, analyze, and manage pickup, transportation, and drop-off routines through digital transmissions across computer networks. However, despite these recent advances, traditional transportation network systems continue to exhibit many shortcomings and deficiencies, particularly with respect to implementation for autonomous vehicle (or "AV") provider devices.

[0003] For example, conventional systems and computing device implementations suffer from significant performance and accuracy issues when determining pickup or drop-off locations in a particular geographic area. For example, intersections, event venues, or otherwise congested areas often contain few AV-accessible pickup or drop-off locations within the nearby geographic area. Moreover, autonomous vehicles often have limited access to certain areas, introducing ambiguity regarding suitable pickup or drop-off locations and the proximity of requester devices to the suitable locations. These complexities render many conventional approaches for locating, identifying, and matching autonomous vehicle provider devices and requester devices with pickup or drop-off locations ineffective. For example, conventional systems often assign provider devices to inaccessible pickup or drop-off locations or to incompatible roads due to inaccuracies in location and identification techniques.

[0004] These technical issues also reduce the flexibility and functional capabilities of conventional systems. For example, in addition to the difficulty of identifying and locating acceptable pickup or drop-off locations, the unique characteristics that identify locations for autonomous vehicles also hinder effective coordination between provider and requester devices. For example, requester devices in congested geographic areas are often located within a general geographic area, such as a building access point that the provider device approaches along an entrance or exit on a designated road. Therefore, conventional systems in congested areas often function under a rigid pickup / drop-off location selection model, relying on the provider and requester to collaborate on a detailed final location selection. Meanwhile, unlike conventional driver systems, autonomous vehicles generally lack the flexibility to effectively coordinate with requester devices in making split-second decisions to deviate from the rigid location selection in response to contextual features. Moreover, conventional systems utilize the same pickup / drop-off location selection approach regardless of the type of provider device, the availability of suitable pickup or drop-off locations, or the special requirements of the autonomous vehicle. However, this rigid approach reduces the flexibility to implement a system that provides more flexible operational control between provider and requester devices. Indeed, conventional systems are also unable to address contextual features about a particular transportation request when selecting pickup and drop-off locations for autonomous vehicles.

[0005] Furthermore, conventional systems suffer from many computational deficiencies. For example, conventional systems that match provider devices with requester devices that are unable to efficiently access nearby pickup or drop-off locations require significant and inefficient communication between the devices over a computer network. For example, as discussed above, conventional systems have difficulty accurately identifying autonomous vehicle-accessible locations and device orientations within congested or heavily trafficked areas. Thus, conventional systems attempting to provide pickup or drop-off locations often generate locations that require significant rerouting instructions and result in duplicate requests from provider and requester devices. Moreover, due at least in part to these difficulties, conventional systems often experience an increase in cancellation requests, resulting in duplicate server matching processes, duplicate instructions to client devices, and duplicate notifications to both provider and requester devices. Thus, conventional systems suffer from inefficient utilization of computing resources (e.g., memory and processing power), excessive bandwidth utilization, and increased latency.

[0006] These, along with additional problems and challenges, exist with respect to conventional transportation network systems. Summary of the Invention

[0007] This disclosure describes one or more embodiments of methods, non-transitory computer-readable media, and systems that intelligently analyze signals from requester and provider devices, determine accurate transition times, and utilize computing models that use the transition times to select more accurate transition locations for autonomous vehicles and other provider devices. In particular, in one or more embodiments, the disclosed system utilizes geohash mapping in combination with provider device telematic data to determine transition times across various geographic regions. The disclosed system can utilize computing models that analyze these transition times and contextual characteristics to select accurate and efficient transition locations for autonomous vehicles. For example, in some implementations, the disclosed system identifies locations that meet a transition time threshold and utilizes the signals to identify more accurate and efficient autonomous vehicle transition locations. In some implementations, the disclosed system further improves accuracy for autonomous vehicles by implementing an autonomous vehicle-accessible location filter that matches selected transition locations to areas accessible to autonomous vehicles. The disclosed system can also utilize other contextual information, such as time, mode of transportation, provider device rating, number / volume of data points, and / or number of routes, to more accurately select transition locations for autonomous vehicles. In this manner, the disclosed system can improve accuracy, versatility, and efficiency in determining transition locations and matching provider and requester devices across various geographic regions. [Brief explanation of the drawings]

[0008] The detailed description refers to the drawings, which are briefly described below.

[0009] [Figure 1] FIG. 1 is a block diagram of an environment for implementing an AV transition location system according to one or more embodiments.

[0010] [Figure 2] FIG. 10 illustrates selecting a subset of preferred pickup locations based on transition times, according to one or more embodiments.

[0011] [Figure 3] FIG. 10 illustrates monitoring updates from requester and / or provider devices to determine transition classifications for a location, according to one or more embodiments.

[0012] [Figure 4] FIG. 1 illustrates determining transition classifications for multiple locations and providing a subset of preferred pickup locations to a vehicle navigation system according to one or more embodiments.

[0013] [Figure 5] FIG. 10 illustrates utilizing a selection model to analyze transition times and select a subset of preferred pickup locations, according to one or more embodiments.

[0014] [Figure 6] FIG. 10 illustrates providing an example set of preferred pickup locations with transition time metrics to a vehicle navigation system according to one or more embodiments.

[0015] [Figure 7] FIG. 1 illustrates an autonomous vehicle utilizing a preferred pickup location within a geographic area that includes multiple potential pickup options, according to one or more embodiments.

[0016] [Figure 8] FIG. 1 illustrates an exemplary sequence of operations for determining a preferred pickup location according to one or more embodiments.

[0017] [Figure 9]FIG. 1 is a block diagram of a computing device for implementing one or more embodiments of the present disclosure.

[0018] [Figure 10] FIG. 1 illustrates an example environment for a transportation matching system according to one or more embodiments. DETAILED DESCRIPTION OF THE INVENTION

[0019] This disclosure describes one or more embodiments of an AV transition location system that utilizes a computing model to analyze updates from provider devices and requester devices, determine transition times for various locations within various geographic areas, and intelligently select transition locations for autonomous vehicles or other provider devices based on the transition times. In one or more embodiments, the AV transition location system analyzes updates from requester devices and / or provider devices at various locations to determine transition times (e.g., the amount of time a provider device is at a particular location). The AV transition location system can aggregate these transition times to establish a threshold length transition pickup measure in a given geographic area. Furthermore, the AV transition location system can compare the threshold length transition pickup measures between locations to select preferred pickup locations for autonomous vehicles operating within the geographic area. Indeed, depending on various characteristics, the AV transition location system can determine a subset of preferred pickup locations and provide them to a vehicle navigation system for navigating the provider device. In this way, the AV transition location system can improve accuracy, versatility, and efficiency in generating preferred pickup locations across geographic locations for autonomous vehicles.

[0020] By way of example, in one or more embodiments, the AV transition location system utilizes geohash mapping to identify multiple pickup locations. Additionally, the AV transition location system receives updates from provider and requester devices, including telematic data and / or global positioning data, to determine transition times at multiple pickup locations. By way of example, the AV transition location system determines an arrival time, monitors updates from requester and / or provider devices, determines a departure time for a transportation request, and determines a transition time for the transportation request. For example, the AV transition location system can monitor provider device location data to determine the length of time a provider will remain near a pickup location.

[0021] Additionally, the AV transition location system can analyze transition times at locations for transportation requests to determine a transition classification. For example, the AV transition location system can compare the transition times for transportation requests to threshold transition times to determine a transition classification (e.g., long pickup / drop-off or short pickup / drop-off).

[0022] As mentioned above, the AV transition location system can aggregate transition classifications for various transportation requests. For example, the AV transition location system can combine transition classifications for multiple transportation requests at a particular location to determine a threshold length transition pickup measure at that location. The AV transition location system can perform similar analyses of transportation requests across multiple locations. Thus, the AV transition location system can determine a threshold length transition pickup measure across different locations based on the transitions at each location.

[0023] As noted, in one or more embodiments, the AV transition location system determines a subset of preferred pickup locations (or preferred transition locations) to provide to the vehicle navigation system. As an example, the AV transition location system compares a measure of threshold-length transition pickup at a particular pickup location with additional measures of threshold-length transition pickup corresponding to additional pickup locations. Based on this comparison, the AV transition location system selects a subset of preferred pickup locations (e.g., transition locations with the highest measures of threshold-length transition pickup).

[0024] In one or more embodiments, the AV transition location system can utilize various methods to select a subset of suitable preferred pickup locations for an autonomous vehicle. By way of example, the AV transition location system can utilize an autonomous vehicle location filter to select a filtered subset of areas accessible to the autonomous vehicle. Moreover, in some implementations, the AV transition location system utilizes other context signals to select preferred transition locations. For example, the AV transition location system can monitor transition times over a particular period (e.g., time of day or time of week) and select preferred transition times specific to the particular period. Similarly, the AV transition location system can monitor provider device ratings, the number of transportation requests at the pickup location, the number of transportation routes, the transportation mode, OMS data, digital images of the location, or vehicle speeds in a geographic area to select preferred locations for the autonomous vehicle. In some implementations, the AV transition location system utilizes a computer-implemented selection model (e.g., an optimization model or a machine learning model) to analyze these various signals and thereby identify preferred transition locations for the autonomous vehicle. Thus, the AV transition location system can select preferred transition locations for the autonomous vehicle based on particular context signals.

[0025] As suggested above, an AV transition location system offers several improvements or advantages over conventional systems. For example, an AV transition location system can improve accuracy and operational performance relative to conventional systems. Indeed, unlike conventional systems that struggle to identify and determine pickup locations at intersections, event venues, or otherwise congested areas, an AV transition location system can utilize transition times and other metrics to identify preferred pickup locations in congested locations. Moreover, in one or more embodiments, the AV transition location system utilizes a selection model to determine a subset of suitable preferred pickup locations for an autonomous vehicle provider device under dynamic conditions. Thus, the AV transition location system can provide accurate preferred pickup locations that consider unique contextual characteristics for an autonomous vehicle at different times or in different situations.

[0026] The AV transition location system also improves versatility over conventional systems. In particular, rather than relying on the same pickup location selection approach regardless of context or provider device, the AV transition location system generates a subset of preferred pickup locations that considers the unique demand and context characteristics of autonomous vehicles. The AV transition location system can also provide preferred pickup locations that are more efficient and more accessible to both provider and requester devices, taking into account the difficulties in determining pickup locations in congested geographic areas. In effect, the AV transition location system generates a subset of preferred pickup locations that can better accommodate autonomous vehicle provider devices or other devices with special requirements.

[0027] Additionally, the AV transition location system improves computing efficiency over conventional systems. For example, by utilizing a selection model to provide a subset of preferred pickup locations, the AV transition location system provides pickup locations that require fewer rerouting instructions for autonomous vehicles and reduced requests from provider and requester devices. Indeed, because the AV transition location system can provide pickup locations based on transition time and other transportation / ride-sharing metrics, the AV transition location system results in a significant reduction in cancellation requests, routing instructions, duplicate matching processes, or duplicate notifications. Therefore, the AV transition location system can reduce utilization of computing resources (e.g., processing power and / or memory) and improve network bandwidth.

[0028] As indicated by the foregoing discussion, this disclosure utilizes a variety of terms to describe the features and advantages of the AV transition location system. For example, as used herein, the term “provider device” refers to a computing device associated with a transportation provider or driver (e.g., a human driver or an autonomous computer system driver) that operates a transportation vehicle. For example, a provider device may refer to a mobile device, such as a smartphone or tablet, operated by a provider, or a device associated with an autonomous vehicle that travels along a transportation route. As used herein, an autonomous vehicle (or autonomous vehicle provider device) refers to a vehicle that operates autonomously (e.g., without a human driver). Thus, an autonomous vehicle provider device refers to a self-driving vehicle that responds to transportation requests from a requester device and is utilized to provide transportation services.

[0029] As suggested above, the term "requester device" refers to a computing device associated with a requester that submits a transportation request to a transportation matching system (e.g., a rideshare system). For example, a requester device receives an interaction from the requester in the form of a user interaction to submit a transportation request. After the transportation matching system matches the requester (or requester device) with a provider (or provider device), the requester can wait for pickup by the provider at a predetermined pickup location. Upon pickup, the provider transports the requester to a drop-off location specified in the requester's transportation request. Thus, a requester may refer to (i) a person who requests a request or other form of transportation and is still waiting to be picked up, or (ii) a person who has been picked up by a transportation vehicle and is currently aboard the transportation vehicle heading to the drop-off location.

[0030] As used herein, the term "transportation request" refers to a request from a requesting device (i.e., a requester device) for transportation by a transportation vehicle (e.g., a rideshare vehicle). In particular, a transportation request includes a request for a transportation vehicle to transport a requester or group of individuals from one geographic area to another. A transportation request may include information such as a requested pickup location, a destination location (e.g., a location to which the requester wishes to travel), a request location (e.g., a location from which the transportation request was initiated), location profile information, a requester rating, or travel history. As an example of such information, a transportation request may include an address as the destination location and the requester's current location as the requested pickup location. A transportation request may also include a requester device initiating a session through a transportation matching application and transmitting its current location (thereby indicating a desire to receive transportation service from the current location).

[0031] Moreover, as used herein, the term "pickup location" refers to a location where a provider device can pick up a requester device. For example, a pickup location can include a designated curb, streetside, or parking area. Illustratively, a pickup location is often located in an area away from oncoming traffic that is suitable for parking a vehicle (e.g., a rideshare pickup location for picking up a requester / requester device). Moreover, as used herein, the term "transition location" refers to a stopping location for a transportation vehicle (e.g., a rideshare transition location). For example, a transition location can include a pickup location or a drop-off location for a transportation request.

[0032] Additionally, as used herein, the term "autonomous vehicle location filter" refers to a computer-implemented algorithm for selecting transition locations for an autonomous vehicle. An autonomous vehicle destination filter may include a computer-implemented algorithm for filtering transition locations that are incompatible with the autonomous vehicle.

[0033] Additionally, as used herein, the term "transition classification" refers to a category or class of transitions corresponding to a vehicle. As an example, an AV transition location system may determine a transition classification based on the duration of the transition. For example, based on a threshold transition time, a transition taking longer than the threshold may be classified as a "long transition." A transition taking shorter than the threshold may be classified as a "short transition."

[0034] As used herein, the term "transition time" refers to the amount of time a vehicle spends (e.g., stopped) at a transition location. Thus, for example, transition time (e.g., pickup transition time) includes the time a transport vehicle is at a pickup location (e.g., to pick up a requester device) or at a drop-off location (e.g., to drop off a requester device). In particular, transition time (e.g., rideshare transition time) includes the time after a provider device arrives at a pickup location until the provider device successfully executes pickup of the requester device and begins the ride to the destination location. Illustratively, transition time includes the time starting from the arrival of the requester device, the time for coordination between the requester device and the provider device at the pickup location, and the time until the provider device departs from the pickup location. Similarly, transition time can include the time a transport vehicle remains at a drop-off location.

[0035] Moreover, as used herein, the term "pickup transition time" (e.g., rideshare pickup transition time) refers to the amount of time (e.g., transition time) that a transportation vehicle spends (e.g., stopped) at a transition location to pick up a requester device. Similarly, the term "drop-off transition time" refers to the amount of time (e.g., transition time) that a transportation vehicle spends (e.g., stopped) at a transition location to drop off a requester device.

[0036] Additionally, as used herein, the term "threshold length transition pickup measure" refers to a metric that evaluates the number of transition pickups that meet a particular standard or requirement. For example, to calculate this measure, the system may determine the number of transition pickups that meet the transition threshold time. In one or more embodiments, the system divides the number of transition pickups that meet the transition threshold time by the total number of transition pickups (e.g., to determine the percentage of long or short pickup classifications).

[0037] Additionally, as used herein, the term "transportation mode" refers to a mode of operation of a provider device (or a transportation request corresponding to a provider device). Some examples of transportation modes for a transportation vehicle include: single passenger mode (where the provider device is used to transport a single passenger at a time); multi-passenger or shared ride mode (where the provider device is used to transport multiple passengers traveling along a similar route); luxury mode (where the vehicle is limited to transportation requests above a threshold, such as high-value requests); destination mode (where the provider device is limited to transportation requests that direct the provider device toward a specific destination selected by the provider device); or delivery mode (where the provider device is limited to transportation requests to transport goods or packages from one location to another).

[0038] Similarly, as used herein, the term "eligibility-limited transport mode" refers to a transport mode that limits transport requests based on certain eligibility criteria. For example, a luxury mode or a destination mode limits the provider device's eligibility to a particular subset of transport requests (e.g., transport requests above a threshold or transport requests that proceed to a destination selected by the provider).

[0039] Additionally, as used herein, the term "provider device rating" (e.g., rideshare provider rating) is a rating or score for a device provider. A provider device rating can include a combination of scores or ratings from provider devices that use the provider device. The rating may be based on factors such as reliability of pickup and drop-off, timeliness in coordinating pickup and drop-off, and / or satisfaction level indicated by the requester device.

[0040] Moreover, as used herein, the term "selection model" refers to a computer-implemented model for selecting a subset of preferred pickup locations. In particular, a selection model may include a computer-implemented model for selecting multiple preferred pickup locations based on transit time and other transportation or ride-sharing metrics (e.g., threshold transit time, AV location filter, transportation mode, provider device rating, number of requests, number of routes).

[0041] In one or more embodiments, the selection model includes a machine learning model. As used herein, the term "machine learning model" refers to a computer algorithm or a group of computer algorithms that can be trained and / or adjusted based on inputs to approximate an unknown function. As another example, a machine learning model can include a computer algorithm that uses branches, weights, or parameters that change based on training data to improve for a particular task. Thus, a machine learning model can utilize one or more learning techniques to improve in accuracy and / or effectiveness. Exemplary machine learning models include various types of decision trees, support vector machines, Bayesian networks, random forest models, or neural networks (e.g., deep neural networks). For example, an AV transition location system may utilize a convolutional neural network or a recurrent neural network to select a preferred transition location for an autonomous vehicle. In one or more embodiments, the selection model includes an optimization model. As used herein, the term "optimization model" refers to a computer algorithm or a group of computer algorithms that balance factors to achieve a particular goal or result (e.g., an optimal result). In one or more embodiments, the selection model includes a heuristic model. As used herein, the term "heuristic model" refers to a model that utilizes a set of rules or heuristics to select a preferred pickup location. For example, a heuristic model may utilize a transition time threshold to select a preferred pickup location.

[0042] Further details regarding the AV transition location system will now be provided with reference to the figures. In particular, FIG. 1 illustrates a block diagram of a system environment for implementing an AV transition location system 106, according to one or more embodiments. As shown in FIG. 1, the environment includes a server 102 that houses the AV transition location system 106 as part of a transportation matching system 104. The environment of FIG. 1 further includes a provider device 122 and a requester device 112, as well as a network 116. The server 102 may include one or more computing devices to implement the AV transition location system 106. Further details regarding the illustrated computing devices (e.g., the server 102, the provider device 122, and / or the requester device 112) are provided with reference to FIGS. 9-10 below.

[0043] As shown, AV transition location system 106 communicates with provider devices 122 (and other provider devices) and requester devices 112 (and other requester devices) using network 116. Network 116 may include any of the networks described in connection with FIGS. 9-10 . For example, AV transition location system 106 communicates with provider devices 122 (and other provider devices) and requester devices 112 to match transportation requests received from requester devices 112 with provider devices 122 (or other provider devices). In practice, transportation matching system 104 or AV transition location system 106 can receive transportation requests from requester devices 112 and provide request information, such as the requested location (e.g., requested pickup location and / or requested drop-off location), requester identification information (for the requester corresponding to requester device 112), and requested pickup time, to various provider devices. In some embodiments, according to device settings, the transportation matching system 104 or the AV transition location system 106 receives device information from various provider devices and requester devices 112, such as location coordinates (e.g., latitude, longitude, and / or elevation), heading or direction, movement information, and indications of user interactions with various interface elements.

[0044] 1 , provider device 122 includes provider application 110. In many embodiments, transportation matching system 104 or AV transition location system 106 communicates with provider device 122 through provider application 110 to receive and provide information including, for example, location data, movement data, transportation request information (e.g., pickup location and / or drop-off location), and transportation route information for navigating to one or more specified locations.

[0045] Similarly, the transportation matching system 104 or the AV transition location system 106 communicates with the requestor device 112 (e.g., through the requestor application 114) to facilitate connecting the request to a transportation vehicle. In many embodiments, the AV transition location system 106 communicates with the requestor device 112 through the requestor application 114 to receive and provide information including, for example, location data, movement data, transportation request information (e.g., requested location), and navigation information to guide the requestor to the specified location.

[0046] As indicated above, the transportation matching system 104 or the AV transition location system 106 can provide (and / or cause the provider device 122 to display or render) visual elements within graphical user interfaces associated with the provider application 110 and the requester application 114. For example, the transportation matching system 104 or the AV transition location system 106 can provide a digital map for display on the provider device 122 showing a transportation route for navigating to a specified location. The AV transition location system 106 can also provide a transportation request notification for display on the provider device 122 indicating the transportation request. Additionally, the AV transition location system 106 can provide a digital map for display on the requester device 112, where the digital map shows the transportation route.

[0047] The AV transition location system 106 may also provide a preferred pickup location to the third-party system 132. To facilitate connecting the request to a transportation vehicle, in some embodiments, the transportation matching system 104 or the AV transition location system 106 communicates with the third-party system 132. As illustrated by FIG. 1 , the third-party system 132 includes a vehicle navigation system 134. In many embodiments, the transportation matching system 104 or the AV transition location system 106 communicates with the third-party system 132 through the vehicle navigation system 134 to receive and provide information including, for example, location data, movement data, transportation request information (e.g., pickup location and / or drop-off location), and a preferred pickup location.

[0048] 1 depicts vehicle navigation system 134 located on third-party system 132, in some implementations, vehicle navigation system 134 may be implemented by (e.g., located entirely or partially on) one or more components of the environment. For example, vehicle navigation system 134 may be implemented by server 102. For example, provider device 122 may download all or a portion of vehicle navigation system 134 for implementation independent of or in conjunction with server 102. Similarly, while FIG. 1 depicts AV transition location system 106 implemented on server 102, AV transition location system 106 may be implemented in various components of the environment.

[0049] 1 illustrates an environment with a particular number and arrangement of components associated with AV transition location system 106, in some embodiments, the environment may include more or fewer components in a different configuration. For example, in some embodiments, transportation matching system 104 or AV transition location system 106 may communicate directly with provider device 122 and / or requester device 112, bypassing network 116. In these or other embodiments, transportation matching system 104 or AV transition location system 106 may be housed (in whole or in part) on provider device 122 and / or requester device 112. Additionally, transportation matching system 104 or AV transition location system 106 may include or communicate with a database for storing information such as various machine learning models, historical data (e.g., historical provider device and / or requester device patterns), transportation requests, and / or other information described herein.

[0050] As noted, in certain embodiments, the AV transition location system 106 selects a subset of preferred pickup locations for a provider device based on transition times. For example, Figure 2 illustrates selecting a subset of preferred pickup locations (or drop-off locations) according to one or more embodiments.

[0051] 2 illustrates that the AV transition location system 106 performs operation 202 of monitoring updates from provider and requester devices. For example, the AV transition location system 106 can monitor updates including the transmission of a transportation request, cancellation, or approval. Similarly, the AV transition location system 106 monitors provider and requester device telematic data (e.g., location, speed, idle time, acceleration, fuel consumption) and / or utilizes global positioning data to identify provider devices at various locations using global positioning data and motion data. For example, the AV transition location system 106 performs operation 202 by monitoring telematic data and / or global positioning data from provider devices during transportation requests, pickups, and transfers. Illustratively, the AV transition location system 106 identifies telematic data and / or global positioning data indicating provider devices moving in a direction toward the pickup location. Additionally, the AV transition location system 106 utilizes telematic data and / or global positioning data to determine that a provider device has stopped based on these signals.

[0052] Similarly, in one or more embodiments, the AV transition location system 106 monitors provider and requestor devices in particular geographic locations, including areas accessible to particular vehicle types (e.g., autonomous vehicles or large vehicles) or areas accessible to particular transportation or ride-sharing modes (e.g., priority service or multiple occupants). Indeed, in one or more embodiments, the AV transition location system 106 places emphasis on more accurate telematic and / or global positioning data, particularly outside of congested regions or areas.

[0053] As further shown in FIG. 2 , the AV transition location system 106 performs operation 204 by determining a pickup transition time for a provider device by evaluating characteristics of the provider device pickup. For example, the AV transition location system determines an arrival time, monitors the provider device and / or requester device, and determines a departure time for the transportation request to determine a pickup transition time for the transportation request. In practice, the AV transition location system may monitor provider device and / or requester device location data (as described above) to determine the length of time the provider remains near the pickup location, thereby determining the transition time. For example, the AV transition location system 106 determines a time metric representing an average transition time for multiple pickup locations (e.g., a time metric of 99 seconds or 159 seconds). Similarly, the AV transition location system 106 determines a time metric representing a measure of pickups that meet a threshold transition time for multiple pickup locations (e.g., a time metric of 25% or 48%). The time metric may take into account driving conditions, mode of transport (e.g., multi-occupant mode or limited eligibility mode), weather conditions, traffic, accidents, time of day, events or other incidents that affected pickup transition times.

[0054] Additionally, as shown, the AV transition location system 106 performs operation 206 of obtaining multiple pickup locations in a geographic area. The pickup locations may be associated with specific location identifiers (e.g., geohashes) in the geographic locations served by the AV transition location system. A geohash is a unique identifier for a specific area on Earth; for example, this may involve using a geocoding system that includes a hierarchical spatial data structure that can operate to subdivide space into multiple shapes. Geohashes may be of different sizes or resolutions; for example, a geohash-5 versus a geohash-6 can describe geohashes of different sizes. A geohash may be a convenient way to represent a location (anywhere in the world) using a short alphanumeric string, such as a shortened URL, that uniquely identifies a location on Earth.

[0055] For example, the AV transition location system 106 compares telematic data and / or global positioning data with known coordinates of pickup locations to obtain multiple pickup locations. Specifically, in one or more embodiments, the AV transition location system 106 utilizes transportation data to obtain an indicator of possible pickup locations available for pickup within a geographic area. For example, the AV transition location system 106 may evaluate transportation data from previous pickups to obtain an indicator of pickup locations that have been successfully used by other provider devices. In one or more embodiments, the AV transition location system 106 may utilize third-party listings of pickup locations that meet transportation criteria. For example, the AV transition location system 106 may utilize third-party applications to integrate navigation data and mapping, thereby obtaining a listing of pickup locations in a geographic area. As shown in FIG. 2, the AV transition location system 106 also performs operation 208 of selecting a subset of preferred pickup locations. As shown in FIG. 2, in one or more embodiments, the AV transition location system 106 selects the subset of preferred pickup locations based on pickup transition times at pickup locations within the geographic area. For example, the AV transition location system 106 may select a subset of preferred pickup locations from a plurality of pickup locations based on a measure of pickups that meets a transition time threshold. As shown in Figure 2, the AV transition location system 106 may select a subset of preferred pickup locations as locations whose measure of pickups meets a transition time threshold of 25%. Alternatively, in one or more embodiments, although not shown, the AV transition location system 106 may select a subset of preferred pickup locations that have an average pickup transition time that exceeds a certain threshold amount (e.g., 99 seconds).

[0056] 2 (and other figures herein) illustrates selecting a subset of preferred pickup locations, the AV transition location system 106 may also perform the operations described herein with respect to drop-off locations and / or pickup locations. Thus, for example, the AV transition location system 106 may monitor provider and requester devices at pickup and / or drop-off locations, determine drop-off transition times, and select a subset of preferred pickup and / or drop-off locations. Similarly, the AV transition location system 106 may select a subset of preferred drop-off locations from a plurality of drop-off locations based on pickup metrics that meet a transition time threshold.

[0057] As mentioned above, the AV transition location system 106 can determine a transition classification for a pickup transition time associated with a pickup location. In particular, Figure 3 illustrates determining a transition classification associated with a pickup transition time, according to one or more embodiments.

[0058] 3 , the AV transition location system 106 performs operation 302 of determining an arrival time at a pickup location for a provider device. As mentioned, the AV transition location system 106 may utilize telematic data and / or global positioning data from the provider device during the request to establish the provider device's arrival time at the pickup location. In one or more embodiments, the provider device provides notification to the AV transition location system 106 when the provider device arrives at the pickup location. In one or more embodiments, the arrival time may include the amount of time the provider device spends waiting to access the pickup location within a threshold distance from the pickup location.

[0059] 3, the AV transition location system 106 performs operation 304 by monitoring updates from the requester device and the provider device. As shown, the AV transition location system 106 monitors telematic data and / or global positioning data from the provider device and / or the requester device to determine whether the device is located near the pickup location. In effect, the AV transition location system 106 compares the location of the requester device with the location of the provider device to determine when the requester device and the provider device converge at the pickup location. In addition, the AV transition location system 106 monitors telematic data and / or global positioning data from the provider device to determine when the provider device remains near the pickup location.

[0060] 3, the AV transition location system 106 performs operation 306 to determine the departure time of the provider device and / or the requester device from the pickup location. In particular, the AV transition location system 106 monitors telematic data and / or global positioning data from the provider device and / or the requester device to determine when the device moves from the pickup location. In one or more embodiments, the provider device and / or the requester device provides notification to the AV transition location system 106 when the provider device departs from the pickup location.

[0061] 3, the AV transition location system 106 performs operation 308 to determine a transition time (e.g., a pickup transition time or a drop-off transition time) at a pickup location. Utilizing the information collected from operations 302, 304, and 306, the AV transition location system 106 performs operation 308 to determine a transition time. As mentioned, the transition time may include the amount of time the provider device is located at the pickup or drop-off location measured from the arrival time to the departure time.

[0062] 3, the AV transition location system 106 determines a transition classification for a transition time. In particular, the AV transition location system 106 performs a determine transition classification operation 310. The AV transition location system 106 determines the transition classification based on analyzing the transition time and comparing the transition time to one or more thresholds. For example, the AV transition location system 106 may compare the pickup transition time (or drop-off transition time) to a threshold transition time 312 to determine a transition classification (e.g., a long transition classification above the threshold or a short transition classification below the threshold).

[0063] The AV transition location system 106 may determine the threshold transition time 312 based on a variety of factors. For example, the AV transition location system 106 may analyze historical data of known pickup locations (e.g., known AV pickup locations) to determine the threshold transition time 312. Illustratively, the AV transition location system 106 may determine historical transition times for one or more of the known pickup locations and use the historical transition times to determine the threshold transition time 312. In some embodiments, the AV transition location system 106 combines (e.g., averages or averages with a determined deviation) the historical transition times across various known AV pickup locations to determine the threshold transition time 312.

[0064] The AV transition location system 106 can utilize dynamic thresholds that change based on different context characteristics. For example, in some implementations, the AV transition location system 106 utilizes a first threshold for a first time and a second threshold for a second time. Similarly, the AV transition location system 106 can select and utilize different thresholds based on different modes of transportation, provider device ratings, or other transition metrics.

[0065] The AV transition location system 106 may also utilize a different number of thresholds. For example, the AV transition location system 106 may utilize two, three, or four thresholds to determine different transition classifications (e.g., long, medium, and short pickup transition classes).

[0066] Therefore, in one or more embodiments, the AV transition location system 106 determines a transition classification based on various contextual features that affect transition times. For example, the AV transition location system 106 can determine a transportation mode corresponding to a transportation request and determine a transition classification specific to that transportation mode (e.g., long pickup for multi-passenger mode or short pickup for multi-passenger mode). Similarly, the AV transition location system 106 can determine a transportation classification specific to a particular event, time of day, or other contextual feature.

[0067] The AV transition location system 106 may also utilize the transition classification to select and provide a subset of preferred pickup or drop-off locations to the vehicle navigation system. For example, Figure 4 illustrates providing a subset of preferred pickup locations based on a threshold length transition pickup metric, according to one or more embodiments.

[0068] 4 shows that the AV transition location system 106 performs operations 402a-402n to determine transition classifications for multiple pickup locations 404a-404n. As described above with respect to FIG. 3, the AV transition location system 106 determines transition times 1a, 2a, 3a, and 4a corresponding to pickup location 404a. Furthermore, by combining transition times 1a, 2a, 3a, and 4a, the AV transition location system 106 can determine an expected pickup transition time at pickup location 404a.

[0069] As discussed above, the AV transition location system 106 can also determine a transition classification for a pickup corresponding to the transition time for that pickup location. For example, as shown in FIG. 4, the AV transition location system 106 determines multiple transition times for a transportation request corresponding to a pickup location (e.g., pickup locations 404a-404n) and determines transition classifications for the multiple transition times. Illustratively, the AV transition location system 106 can compare transition times 1a, 2a, 3a, and 4a corresponding to pickup location 404a to threshold transition times to determine transition classification 402a for pickup location 404a. Similarly, the AV transition location system 106 can compare transition times 1n, 2n, 3n, and 4n corresponding to pickup location 404n to threshold transition times corresponding to pickup location 404n to determine transition classification 402n for pickup location 404n.

[0070] 4, the AV transition location system 106 performs an operation 406 of determining a threshold length transition pickup measure for a plurality of pickup locations 404a-404n. Specifically, the AV transition location system 106 may determine a measure of instances when the transition classifications 402a-402n satisfy the transition classification requirements of the AV transition location system 106. In one or more embodiments, the threshold length transition pickup measure may be a percentage value of a particular transition classification (e.g., a percentage of long pickup classifications or a percentage of short pickup classifications). By way of example, in one or more embodiments, the AV transition location system 106 may determine the threshold length transition pickup measure for the pickup location 404a by determining a measure of how often the transition time at the pickup location 404a is a long pickup.

[0071] In one or more embodiments, the AV transition location system 106 performs operation 408 of comparing the measure of threshold length transition pickup to a surfacing threshold. For example, the AV transition location system 106 may determine a first measure of threshold length transition pickup for a first location (e.g., 75%) and compare the first measure of threshold length transition pickup to a surfacing threshold (e.g., 50%). If the first measure of threshold length transition pickup meets the surfacing threshold, the AV transition location system 106 selects the transition location to be included in the subset of preferred pickup locations. Similarly, the AV transition location system 106 may determine a second measure of threshold length transition pickup for a second location (e.g., 35%) and compare the second measure of threshold length transition pickup to a surfacing threshold (e.g., 50%). If the second measure of threshold length transition pickup does not meet the surfacing threshold, the AV transition location system 106 does not select the transition location for inclusion in the subset of preferred pickup locations.

[0072] The AV transition location system 106 can select the subset of preferred pickup locations using a variety of different techniques. For example, the AV transition location system 106 can directly compare measures of threshold length transition pickup between locations and select the subset of locations based on this comparison. By way of example, the AV transition location system 106 can select the top few (e.g., top 10) or top percentage (e.g., top 10%) of locations having the highest measures of threshold length transition pickup.

[0073] While Figure 4 illustrates using a threshold length transition pickup measure, the AV transition location system 106 can use a variety of other techniques to select a subset of preferred pickup locations. For example, the AV transition location system 106 can directly compare transition times for various locations. Illustratively, the AV transition location system 106 can select the locations (e.g., a few or a small percentage of locations) with the highest average transition times. Indeed, the AV transition location system 106 can determine a variety of different statistical measures of transition times (e.g., average, mean, median, variance) and compare these statistical measures to select a subset of preferred pickup locations.

[0074] 4, the AV transition location system 106 can perform operation 410 of providing a subset of preferred pickup locations. Specifically, as discussed immediately above, the AV transition location system 106 can compare a threshold long transition pickup measure (or other measure of transition time / transition classification) between pickup locations to generate the subset of preferred pickup locations. Thus, for example, the AV transition location system 106 can provide all pickup locations that have a long pickup classification rate of at least 60%.

[0075] Additionally, the AV transition location system 106 may provide an indication of a measure of transition time (e.g., a measure of threshold length transition pickup) associated with each pickup location of the subset of preferred pickup locations. In particular, as shown in Figure 4, the AV transition location system 106 may provide an indication of the percentage of threshold length transition pickup. By way of example, the AV transition location system 106 may provide an indication of 84% for locations that meet the threshold transition time at an 84% rate.

[0076] In some embodiments, the AV transition location system 106 provides a subset of preferred pickup locations by providing a complete list of pickup locations while specifying a subset of preferred pickup locations. For example, the AV transition location system 106 may provide a list of all pickup locations, but provide a subset of preferred pickup locations by specifying a transition time measure and / or a threshold long transition pickup measure (thereby identifying those with the highest rate of long pickup classification and / or the longest transition time).

[0077] Moreover, the AV transition location system 106 may also select and provide a subset of preferred pickup locations based on the number of requests. Indeed, as shown in FIG. 4, the size of the circle surrounding a pickup location indicates the number of observed transitions corresponding to that location. In some embodiments, the AV transition location system 106 selects a subset of preferred pickup locations based on the number of transportation requests (e.g., the higher the number of transportation requests / transitions, the higher the confidence). For example, the AV transition location system 106 may only provide a pickup location if the pickup location has a threshold number of transportation requests / transitions. Similarly, the AV transition location system 106 may weight or penalize pickup locations based on the number of transitions at the pickup location (e.g., providing a positive weight for a large number of pickups and a negative weight for a small number of pickups).

[0078] 4 illustrates providing a subset of preferred pickup locations, the AV transition location system 106 may also perform the operations enumerated above with respect to drop-off locations and / or pickup locations. Thus, for example, the AV transition location system 106 may determine a transition classification at the pickup and / or drop-off locations, determine a threshold length transition pickup and / or drop-off metric, and provide a subset of preferred pickup and / or drop-off locations. Similarly, the AV transition location system 106 may provide a subset of preferred drop-off locations from a plurality of drop-off locations based on a pickup metric that meets a transition time threshold.

[0079] The AV transition location system 106 can provide a subset of preferred pickup locations based on a variety of factors and utilizing a variety of computer-implemented algorithms. For example, Figure 5 illustrates selecting a subset of preferred pickup locations according to one or more embodiments.

[0080] 5 illustrates that the AV transition location system 106 selects a subset of preferred pickup locations from a plurality of pickup locations using a selection model 520. As shown, the AV transition location system 106 determines transition times 502a-502n for the plurality of pickup locations. The AV transition location system 106 then utilizes the selection model 520 to determine the subset of preferred pickup locations based on the transition times 502a-502n and other possible factors.

[0081] For example, as discussed above, the selection model 520 may utilize a heuristic model to select a subset of preferred pickup locations by applying a threshold transition time 504. Illustratively, in one or more embodiments, the AV transition location system 106 compares the transition times 502a-502n to the threshold transition time 504 to select a subset of preferred pickup locations having transition times that meet the threshold transition time. Indeed, when selecting a subset of preferred pickup locations accessible to an AV provider device, the AV transition location system 106 selects a subset of preferred pickup locations that meet the long pickup transition time threshold requirement.

[0082] In one or more embodiments, the AV transition location system 106 utilizes an AV location filter 506 to select a subset of preferred pickup locations. Illustratively, in one or more embodiments, the AV transition location system 106 selects the subset of preferred pickup locations by comparing locations that satisfy the AV location filter 506 with pickup locations that have transition times 502a-502n. For example, the AV transition location system 106 limits the plurality of pickup locations to those that satisfy the AV location filter 506 and are accessible to the AV provider device. In effect, the AV transition location system 106 selects the subset of preferred pickup locations based on both the transition times 502a-502n and the AV location filter 506.

[0083] In some embodiments, the AV transition location system 106 utilizes a heuristic function (e.g., a rule-based function) or an optimization model (e.g., weighting various factors to optimize or improve a particular objective). For example, as shown in Figure 5, the AV transition location system 106 can generate rules or weights for individual pickup locations based on various additional features, such as AV location filters, transportation modes, provider device ratings, number of requests, and other transition metrics or contextual features.

[0084] To illustrate, the AV transition location system 106 can utilize an autonomous vehicle location filter to select a filtered subset of areas accessible to an autonomous vehicle. To illustrate, the AV transition location system 106 can filter a plurality of pickup locations to include only locations accessible to an autonomous vehicle, taking into account autonomous vehicle mobility constraints in a particular area and under particular road conditions. As another example, the AV transition location system 106 can filter preferred pickup locations to exclude areas with traffic rules or patterns that are prohibitive for autonomous vehicle operation. In addition, the AV transition location system 106 can filter preferred pickup locations based on road signs or available lanes. To illustrate, the AV transition location system 106 can provide preferred pickup locations based on areas determined to be suitable for the autonomous vehicle provider to travel.

[0085] In one or more embodiments, the AV transition location system 106 evaluates transportation modes 508 to select a subset of preferred pickup locations. Illustratively, in one or more embodiments, the AV transition location system 106 compares transition times 502a-502n to transportation modes when weighting transition times for provider devices. For example, the AV transition location system 106 may consider increased transition times that often occur in multi-passenger transportation modes compared to single-passenger transportation modes. Thus, for example, the AV transition location system 106 may weight transition times more heavily for multi-passenger transportation modes (i.e., because multi-passenger transportation modes may skew the results). Similarly, the AV transition location system 106 may weight transition times differently for eligibility-limited transportation modes. As another example, the AV transition location system 106 may consider increased transition times that often occur in AV transportation modes compared to manned vehicle transportation modes. Indeed, the AV transition location system 106 may consider various modes with differences in transition times that are partially related to transportation modes (and not strictly to pickup locations).

[0086] In one or more embodiments, the AV transition location system 106 evaluates provider device ratings 510 to select a subset of preferred pickup locations. Illustratively, in one or more embodiments, the AV transition location system 106 compares transition times 502a-502n to the provider device ratings 510 when weighting the transition times for the provider devices. Indeed, provider device ratings may affect the amount of transition time for a particular location (e.g., a low driver rating may equate to a higher wait time). The AV transition location system 106 can weight the transition times based on the provider device ratings to account for these differences.

[0087] In one or more embodiments, the AV transition location system 106 evaluates the number of requests 512 at pickup locations to select a subset of preferred pickup locations. Illustratively, in one or more embodiments, the AV transition location system 106 compares the transition times 502a-502n to the number of requests 512 when weighting the transition times for provider devices. For example, as mentioned above, the AV transition location system 106 may give a heavier weight to locations with a higher number of transportation requests / transitions. For example, the AV transition location system 106 may determine that a particular location has received a larger number of requests overall, and therefore the AV transition location system 106 has more confidence in the validity of the transition times determined for that location (due to a larger data set). For example, for locations with higher transition times (above a transition threshold) and high volume, the AV transition location system 106 may give a higher reward for selecting the transition location. On the other hand, for locations with lower transition times (below the transition threshold) and higher volumes, the AV transition location system 106 may give a higher penalty (or a smaller reward) for selecting the transition location.

[0088] In one or more embodiments, the AV transition location system 106 evaluates other transition metrics 514 to select a subset of preferred pickup locations. By way of example, in one or more embodiments, the AV transition location system 106 compares the transition times 502a-502n to the transition metrics 514 when weighting the transition times for provider devices. For example, the AV transition location system 106 can measure and consider transition metrics 514 such as requester device wait time, requester device walking distance, availability of parking spots on a road, popularity of bike lanes, use of one-way streets, number or probability of trip cancellations, number of requester or provider devices for a geographic region, trip volume for a geographic region, trip route or segment utilization, vehicle occupancy, vehicle speed, inclement weather, time of day, planned events, vehicle accidents, or street-level imagery of fleet vehicles. In practice, the AV transition location system 106 can evaluate the transition times 502a-502n and the transition metrics 514 to determine whether the transition times 502a-502n provide an accurate representation of typical transition times at the associated pickup location. Based on evaluating the transition times 502a-502n and the transition metrics 514, the AV transition location system 106 can determine a subset of preferred pickup transition times.

[0089] The AV transition location system 106 can also utilize the transition metric 514 as a signal to weight when selecting a preferred pickup location. Indeed, the AV transition location system 106 can weight the transition metric 514 in combination with transition time to select a preferred pickup location. Thus, for example, the AV transition location system 106 can consider transition time along with requester device wait time and requester device walking distance to select a preferred pickup location. The AV transition location system 106 can also analyze street image data, trip cancellations, and street imagery to select a preferred pickup location.

[0090] Additionally, the AV transition location system 106 can provide priorities within a subset of preferred pickup locations within a geographic area. The AV transition location system 106 can determine priorities for types / categories based on a variety of factors. For example, in some embodiments, the AV transition location system 106 selects priorities based on the time or distance of the preferred pickup locations from the requester device. In some embodiments, the AV transition location system 106 selects priorities based on historical data (e.g., historical data indicating which pickup locations result in the most efficient pickup locations). In some embodiments, the AV transition location system 106 selects priorities based on results from the selection model 520. Specifically, the AV transition location system 106 analyzes the subset of preferred pickup locations, the transition time, and the location of the requester device to suggest priorities within the subset of preferred pickup locations.

[0091] As mentioned, the selection model 520 can utilize an optimization model to balance transition times, threshold transition times 504, AV location filters 506, transportation modes 508, provider device ratings 510, number of requests 512, and other transition metrics 514. Specifically, the selection model 520 can define a set of decision variables representing different pickup locations. In addition, the optimization model employs a set of constraints that define restrictions on the decision variables (e.g., constraints on traffic routes, constraints on time windows). In addition, the optimization model employs an objective function that defines what to optimize (e.g., minimum travel distance, minimum transition time). By utilizing the optimization model, the AV transition location system 106 can utilize numerous decision variables and constraints to efficiently provide a subset of preferred pickup transition times. In practice, the AV transition location system 106 can utilize a variety of optimization algorithms, including linear, integer, and constraint programming.

[0092] As mentioned, the selection model 520 may utilize a machine learning model, such as a decision tree or a neural network, to select a preferred pickup location. Specifically, the AV transition location system 106 utilizes a preferred pickup prediction machine learning model to determine or predict a subset of preferred pickup locations from a plurality of pickup locations. For example, the AV transition location system 106 may utilize a preferred pickup prediction machine learning model trained on the input features and ground truth pickup information to select a preferred pickup location.

[0093] To illustrate, the AV transition location system 106 can identify a set of ground truth AV transition locations (e.g., locations commonly used by AVs to pick up or drop off passengers). The AV transition location system 106 can generate or monitor various input signals related to the ground truth AV transition locations. For example, the AV transition location system 106 can analyze transition times, modes, provider device ratings, number of requests / transitions, and other transition metrics discussed above (e.g., wait times, walk times, street-level imagery, etc.). The AV transition location system 106 can analyze these input signals using machine learning models (e.g., decision trees or neural networks) to generate transition predictions.

[0094] For example, the AV transition location system 106 can generate a categorical transition prediction (e.g., a binary classification) indicating that the pickup location is an AV pickup location or a non-AV pickup location. Similarly, the AV transition location system 106 can generate a non-binary prediction (e.g., a probability or transition time) indicating a measure of suitability for the location for the AV transition. The AV transition location system 106 can then compare the generated prediction to ground truth.

[0095] To illustrate, the AV transition location system 106 can utilize a loss function to compare the transition prediction to ground truth. Thus, for example, the AV transition location system 106 can compare a binary prediction to a ground truth indication of whether the location was an AV transition location. Similarly, the AV transition location system 106 can compare a non-binary prediction to ground truth (e.g., the rating of the location or the ground truth transition time for the location). The AV transition location system 106 can utilize a loss function to determine a measure of loss between the ground truth and the prediction. The AV transition location system 106 can then modify the parameters of the machine learning model based on the loss measure. For example, the AV transition location system 106 can utilize gradient descent and / or backpropagation to modify the parameters of the machine learning model, thereby reducing the loss measure. The AV transition location system 106 can iteratively train the machine learning model to improve the accuracy of the predictions.

[0096] At runtime, the AV transition location system 106 can analyze characteristics of a particular location using the trained parameters of the machine learning model. The AV transition location system 106 can generate a transition prediction that indicates the suitability of a particular location for an AV transition. The AV transition location system 106 can use the transition prediction to select a subset of preferred pickup locations. For example, the AV transition location system 106 can select locations that the machine learning model classifies as AV transition locations. Similarly, the AV transition location system 106 can select locations that meet a probability threshold or exceed a predicted transition time. As further shown in FIG. 5 , the AV transition location system 106 can perform an operation 530 of providing a subset of preferred pickup locations. Specifically, the AV transition location system 106 can use the selection model 520 to generate the subset of preferred pickup locations. By way of example, the AV transition location system 106 can provide a subset of recommended pickup locations based on evaluating the transition times 502a-502n and one or more of the other factors shown in FIG. 5 .

[0097] 5 illustrates providing a subset of preferred pickup locations, AV transition location system 106 may also perform the operations enumerated above with respect to drop-off locations and / or pickup locations. Thus, for example, AV transition location system 106 may utilize a selection model using factors such as transition time, threshold transition time, AV location filter, transportation mode, provider device rating, number of requests, and / or transition metric. Similarly, AV transition location system 106 may select a subset of preferred drop-off locations from a plurality of drop-off locations based on factors considered by the selection model.

[0098] As mentioned, in certain embodiments, AV transition location system 106 communicates with a vehicle navigation system. For example, FIG. 6 shows providing transition metrics to vehicle navigation system 634 (e.g., vehicle navigation system 134). As mentioned, vehicle navigation system 634 may be implemented by (e.g., located entirely or partially within) AV transition location system 106. In some embodiments, vehicle navigation system 634 is a third-party system (e.g., a third party that controls navigation of an autonomous vehicle).

[0099] 6, the AV transition location system 106 can provide transition metrics 602 to a vehicle navigation system 634. For example, the AV transition location system 106 can provide a transition time measure for a pickup location, a longitude and latitude, a number of pickups for a preferred pickup location, a number of transition times that meet a threshold, an average idle time at a preferred pickup location, and a maximum idle time at a preferred pickup location.

[0100] 6, the AV transition location system 106 can provide multiple values ​​for the transition metric 602 to account for changes to the transition metric 602. In particular, the AV transition location system can determine multiple subsets of preferred pickup locations corresponding to multiple time periods (e.g., time of day, time of week, time of year) and / or locations. For example, the AV transition location system 106 can adjust the subset of preferred pickup locations based on inclement weather, annual seasons, events, road construction, vehicle accidents, traffic congestion, or tourist seasons. In fact, the AV transition location system can provide multiple subsets of preferred pickup locations to the vehicle navigation system based on these variable conditions.

[0101] As mentioned above, the AV transition location system 106 can generate time-specific values ​​by monitoring times for transportation requests and transitions. Indeed, the AV transition location system 106 can use transportation requests between 12:00 and 1:00 to generate transition times and preferred pickup locations specific to that time period. Additionally, the AV transition location system 106 can use transportation requests between 5:00 and 6:00 to generate a different set of transition times and preferred pickup locations specific to that time period. The AV transition location system 106 can collect and use similar information about recurring events, weather conditions, or other contextual features.

[0102] 6 shows one example of values ​​provided to the vehicle navigation system 634, the AV transition location system 106 can provide a variety of different formats. For example, in some embodiments, the AV transition location system 106 provides a data table with one row per pickup location (e.g., block or OSM segment) and a percentage (e.g., a measure of threshold length transition pickup) for those locations (e.g., geographic point in time + percentage).

[0103] As further shown in FIG. 6, the vehicle navigation system 634 may then communicate with the provider device 636 to provide a subset of preferred pickup locations based on the subset of preferred pickup locations and the transition metric 602 .

[0104] As noted, in certain embodiments, the AV transition location system 106 provides a subset of preferred pickup locations for a provider device based on evaluating transition times and additional factors. For example, Figure 7 illustrates the selection of a preferred pickup location in a busy business location, according to one or more embodiments.

[0105] Specifically, FIG. 7 illustrates a congested location where multiple requester devices 710 are located within a congested area. Selecting an appropriate pickup location in a congested area can be difficult for an AV provider device. In the case of transportation with a human driver, the requester has multiple options for guiding the provider to an alternative pickup location. For example, the requester may wave or call out to the driver in the congested area to attract their attention, or use a visual marker (such as a brightly colored item that is easily visible from a distance) to help the driver find the requester. However, AV provider devices do not have human drivers and do not have the same options for establishing an alternative pickup location. Therefore, conventional systems often select a poor or incompatible location and allow the provider and requester to coordinate or negotiate a different pickup location.

[0106] However, autonomous vehicles do not have human drivers who can easily coordinate alternate pickup locations based on verbal or visual cues to the requester device. Therefore, the AV transition location system 106 addresses this technical deficiency by identifying transition locations for autonomous vehicles. In effect, the AV transition location system 106 selects a transition location that allows the autonomous vehicle to successfully pick up or drop off the provider device based on a transition time that signals that a particular location is suitable for the autonomous vehicle.

[0107] 7 illustrates a geographic region (e.g., an event center or other congested location) with multiple potential transition locations. The AV transition location system 106 can analyze the transition locations within the geographic region and select one or more preferred transition locations for the autonomous vehicle. Illustratively, the AV transition location system 106 can analyze transition times to select a pickup or drop-off location that is less congested, more visible, or easier for the autonomous vehicle to access and requires less human coordination.

[0108] Thus, as shown, the AV transition location system 106 identifies a preferred pickup location 720 for the provider device 730 based on the determined transition time at the preferred pickup location 720, as discussed above. In fact, as shown, the AV transition location system 106 directs the provider device 730 to a preferred pickup location 720 on the side of the road that is most accessible to the requester device and slightly displaced from a congested business access point.

[0109] In one or more embodiments, each of the components of the AV transition location system 106 communicate with one another using any suitable communication technology. In addition, the components of the AV transition location system 106 can communicate with one or more other devices, including one or more client devices described above. Furthermore, although the components in the figures are described in connection with the AV transition location system 106, at least some of the components for performing operations in conjunction with the AV transition location system 106 described herein may be implemented on other devices in the environment.

[0110] Components of the AV transition location system 106 may include software, hardware, or both. For example, components of the AV transition location system 106 may include one or more instructions stored on a computer-readable storage medium and executable by processors of one or more computing devices. When executed by one or more processors, the computer-executable instructions of the AV transition location system 106 can cause the computing devices to perform the methods described herein. Alternatively, components of the AV transition location system 106 may include hardware, such as a dedicated processing device that performs a particular function or group of functions. Additionally or alternatively, components of the AV transition location system 106 may include a combination of computer-executable instructions and hardware.

[0111] Additionally, components of the AV transition location system 106 that perform the functions described herein may be implemented, for example, as part of a standalone application, as a module of an application, as a plug-in for an application, including a content management application, as one or more library functions that can be called by other applications, and / or as a cloud computing model. Thus, components of the AV transition location system 106 may be implemented as part of a standalone application on a personal computing device or a mobile device. Alternatively, or in addition, components of the AV transition location system 106 may be implemented in any application that enables the creation and delivery of marketing content to users, including, but not limited to, various applications.

[0112] 1-7, corresponding text, and examples provide many different systems, methods, and non-transitory computer-readable media for selecting and providing transportation requests to qualified provider devices. In addition to the foregoing, embodiments may also be described in terms of flowcharts that include operations for achieving particular results. For example, FIG. 8 illustrates a flowchart of an exemplary sequence of operations according to one or more embodiments.

[0113] While Figure 8 illustrates operations according to some embodiments, alternative embodiments may omit, add, rearrange, and / or modify any of the operations illustrated in Figure 8. The operations of Figure 8 may be performed as part of a method. Alternatively, a non-transitory computer-readable medium may contain instructions that, when executed by one or more processors, cause a computing device to perform the operations of Figure 8. In still further embodiments, a system may perform the operations of Figure 8. Additionally, operations described herein may be repeated or performed in parallel with each other or with different instances of the same or other similar operations.

[0114] 8 shows an example sequence of operations 800 for determining a subset of preferred pickup locations according to one or more embodiments. As shown, the sequence of operations 800 includes an operation 810 for monitoring provider devices and requester devices to determine pickup transition times. In particular, operation 810 may involve determining pickup transition times for multiple pickup locations by monitoring, via one or more servers, provider devices and requester devices corresponding to transportation requests to determine a provider device arrival time from a provider device to a pickup location corresponding to a transportation request from a requester device; determining a departure time for the transportation request from the provider device or the requester device; and comparing the departure time and the provider device arrival time to determine a pickup transition time.

[0115] Additionally, the series of operations 800 includes an operation of selecting a subset of preferred pickup locations 820. In particular, operation 820 may involve selecting a subset of preferred pickup locations from the plurality of pickup locations based on pickup transit times.

[0116] Additionally, the series of operations 800 includes operation 830 of transmitting the subset of preferred pickup locations to a vehicle navigation system. In particular, operation 830 may involve transmitting, via one or more servers, one or more of the subset of preferred pickup locations to the vehicle navigation system for navigating the provider device to one or more of the subset of preferred pickup locations.

[0117] In some embodiments, the series of operations 800 includes the additional operation where selecting a subset of preferred pickup locations includes selecting a filtered subset utilizing an autonomous vehicle location filter, the autonomous vehicle location filter indicating areas accessible to the autonomous vehicle.

[0118] In some embodiments, the series of operations 800 includes the additional operation of comparing the transition time to a threshold transition time to determine a first transition classification for the transportation request.

[0119] In some embodiments, the series of operations 800 includes additional operations such as determining an additional transition time corresponding to a pickup location for an additional transportation request from an additional requester device; and comparing the additional transition time to a threshold transition time to determine a second transition classification for the additional transportation request; and determining a threshold length transition pickup measure for the pickup location based on the first transition classification and the second transition classification.

[0120] In some embodiments, the series of operations 800 includes an additional operation of selecting a subset of preferred pickup locations by comparing a measure of threshold length transition pickup corresponding to the pickup locations with additional measures of threshold length transition pickup corresponding to the additional pickup locations.

[0121] In some embodiments, the series of operations 800 includes an additional operation where the pickup transition times correspond to a first time period, and selecting a subset of preferred pickup locations includes selecting a first subset of preferred pickup locations for the first time period, and further includes determining an additional plurality of pickup transition times corresponding to a second time period; and selecting a second subset of preferred pickup locations corresponding to the second time period.

[0122] In some embodiments, the series of operations 800 includes additional operations such as determining a transportation mode corresponding to the transportation request, where the transportation mode includes at least one of a multi-occupant mode or an eligibility-limited transportation mode; and selecting a subset of preferred pickup locations based on the pickup transition time and the transportation mode.

[0123] In some embodiments, the series of operations 800 includes additional operations such as determining provider device ratings associated with the provider devices; and selecting a subset of preferred pickup locations from the plurality of pickup locations based on the pickup transition times and the provider device ratings.

[0124] In some embodiments, the series of operations 800 includes additional operations such as determining the number of transportation requests at the pickup locations; and selecting a subset of preferred pickup locations based on the number of transportation requests at the pickup locations and the pickup transit times.

[0125] Embodiments of the present disclosure may include or utilize special purpose or general purpose computers including computer hardware such as, for example, one or more processors and system memory, as discussed in more detail below. Embodiments within the scope of the present disclosure also include physical and other computer-readable media for carrying or storing computer-executable instructions and / or data structures. In particular, one or more of the processes described herein may be implemented at least in part as instructions embodied in a non-transitory computer-readable medium and executable by one or more computing devices (e.g., any of the media content access devices described herein). In general, a processor (e.g., a microprocessor) receives instructions from a non-transitory computer-readable medium (e.g., memory, etc.) and executes those instructions, thereby performing one or more processes, including one or more of the processes described herein.

[0126] Computer-readable media may be any available media that can be accessed by a general-purpose or special-purpose computer system, including one or more servers. Computer-readable media that store computer-executable instructions are non-transitory computer-readable storage media (devices). Computer-readable media that carry computer-executable instructions are transmission media. Thus, by way of example, and not limitation, embodiments of the present disclosure may include at least two separate and distinct types of computer-readable media: non-transitory computer-readable storage media (devices) and transmission media.

[0127] Non-transitory computer-readable storage media (devices) include RAM, ROM, EEPROM, CD-ROM, solid state drives (“SSD”) (e.g., RAM-based), flash memory, phase-change memory (“PCM”), other types of memory, other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store desired program code means in the form of computer-executable instructions or data structures and that can be accessed by a general-purpose or special-purpose computer.

[0128] Furthermore, upon reaching various computer system components, program code means in the form of computer-executable instructions or data structures may be automatically transferred from transmission media to non-transitory computer-readable storage media (devices) (or vice versa). For example, computer-executable instructions or data structures received over a network or data link may be buffered in RAM within a network interface module (e.g., a "NIC") and then ultimately transferred to computer system RAM and / or to less volatile computer storage media (devices) within the computer system. It should therefore be understood that non-transitory computer-readable storage media (devices) may be included in computer system components that also (or even primarily) utilize transmission media.

[0129] Computer-executable instructions include, for example, instructions and data that, when executed on a processor, cause a general-purpose computer, a special-purpose computer, or a special-purpose processing device to perform a particular function or group of functions. In some embodiments, computer-executable instructions are executed on a general-purpose computer to turn the general-purpose computer into a special-purpose computer that implements elements of the present disclosure. Computer-executable instructions may be, for example, binaries, intermediate format instructions such as assembler language, or even source code. Although the subject matter has been described in language specific to structural features and / or method operations, the subject matter defined in the appended claims is not necessarily limited to the described features or operations described above. Rather, the described features and operations are disclosed as example forms of implementing the claims.

[0130] Those skilled in the art will appreciate that the present disclosure may be implemented in a networked computing environment having many types of computer system configurations, including virtual reality devices, personal computers, desktop computers, laptop computers, message processors, handheld devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, mobile phones, PDAs, tablets, pagers, routers, switches, and the like. The present disclosure may also be implemented in a distributed system environment where tasks are performed by both local and remote computer systems that are linked through a network (either by hardwired data links, wireless data links, or a combination of hardwired and wireless data links). In a distributed system environment, program modules may be located in both local and remote memory storage devices.

[0131] Embodiments of the present disclosure can also be implemented in a cloud computing environment. For the purposes of this description, "cloud computing" is defined as a model for enabling on-demand network access to a shared pool of configurable computing resources. For example, cloud computing can be adopted in the market to offer ubiquitous and convenient on-demand access to a shared pool of configurable computing resources that can be rapidly provisioned through virtualization, released with low management effort or service provider interaction, and then scaled accordingly.

[0132] Cloud computing models can consist of various characteristics such as, for example, on-demand self-service, pervasive network access, resource pooling, rapid elasticity, metered service, etc. Cloud computing models can also expose various service models such as, for example, Software as a Service ("SaaS"), Platform as a Service ("PaaS"), and Infrastructure as a Service ("IaaS"). Cloud computing models can also be deployed using different deployment models such as private cloud, community cloud, public cloud, hybrid cloud, etc. In this description and in the claims, a "cloud computing environment" is an environment in which cloud computing is employed.

[0133] 9 illustrates, in block diagram form, an exemplary computing device 900 (e.g., provider device 122, requester device 112, or server 102) that may be configured to perform one or more of the processes described above. It will be understood that the AV transition location system 106 can include implementations of the computing device 900 including, but not limited to, the provider device 122, the third-party system 132, and / or the server 102. As illustrated by FIG. 9 , the computing device may include a processor 902, a memory 904, a storage device 906, an I / O interface 908, and a communication interface 910. In particular embodiments, the computing device 900 may include fewer or more components than those shown in FIG. 9 . The components of the computing device 900 shown in FIG. 9 will now be described in further detail.

[0134] In particular embodiments, processor 902 includes hardware for executing instructions, such as those making up a computer program. By way of example, and not limitation, to execute instructions, processor 902 may retrieve (or fetch) the instructions from an internal register, an internal cache, memory 904, or storage device 906, decode them, and execute them.

[0135] The computing device 900 includes a memory 904 coupled to the processor 902. The memory 904 may be used to store data, metadata, and programs for execution by the processor. The memory 904 may include one or more of volatile and non-volatile memory, such as random access memory ("RAM"), read only memory ("ROM"), solid-state disk ("SSD"), flash, phase change memory ("PCM"), or other types of data storage. The memory 904 may be internal or distributed memory.

[0136] Computing device 900 includes a storage device 906 that includes storage for storing data or instructions. By way of example and not limitation, storage device 906 can include the non-transitory storage media described above. Storage device 906 may include a hard disk drive ("HDD"), flash memory, a Universal Serial Bus ("USB") drive, or a combination of these or other storage devices.

[0137] Computing device 900 also includes one or more input or output interfaces 908 (or "I / O interfaces 908") provided to enable a user (e.g., a requester or a provider) to provide input (such as user strokes) to, receive output from, and otherwise transfer data to, computing device 900. These I / O interfaces 908 may include a mouse, a keypad or keyboard, a touchscreen, a camera, an optical scanner, a network interface, a modem, other known I / O devices, or a combination of such I / O interfaces 908. A touchscreen may be activated using a stylus or a finger.

[0138] I / O interface 908 may include one or more devices for presenting output to a user, including, but not limited to, a graphics engine, a display (e.g., a display screen), one or more output providers (e.g., display providers), one or more audio speakers, and one or more audio providers. In particular embodiments, interface 908 is configured to provide graphical data to a display for presentation to a user. The graphical data may represent one or more graphical user interfaces and / or any other graphical content as may be useful in a particular implementation.

[0139] The computing device 900 may further include a communications interface 910. The communications interface 910 may include hardware, software, or both. The communications interface 910 may provide one or more interfaces for communications (e.g., packet-based communications, etc.) between the computing device and one or more other computing devices 900 or one or more networks. By way of example and not limitation, the communications interface 910 may include a network interface controller (“NIC”) or network adapter for communicating with an Ethernet or other wire-based network, or a wireless NIC (“WNIC”) or wireless adapter for communicating with a wireless network such as WI-FI. The computing device 900 may further include a bus 912. The bus 912 may include hardware, software, or both that connect the components of the computing device 900 to one another.

[0140] 10 illustrates an example network environment 1000 of a transportation matching system 104. The network environment 1000 includes a client device 1006 (e.g., a provider device 122 or a requester device 112), a transportation matching system 104, and a third-party system 132 connected to each other by a network 1004. While FIG. 10 illustrates a particular arrangement of the client device 1006, the transportation matching system 104, the vehicle subsystem 1008, and the network 1004, this disclosure contemplates any suitable arrangement of the client device 1006, the transportation matching system 104, the vehicle subsystem 1008, and the network 1004. By way of example and not limitation, two or more of the client device 1006, the transportation matching system 104, and the vehicle subsystem 1008 communicate directly, bypassing the network 1004. As another example, two or more of the client device 1006, the transportation matching system 104, and the vehicle subsystem 1008 may be physically or logically co-located with one another, in whole or in part.

[0141] 10 depicts a particular number of client devices 1006, transportation matching systems 104, vehicle subsystems 1008, and networks 1004, this disclosure contemplates any suitable number of client devices 1006, transportation matching systems 104, vehicle subsystems 1008, and networks 1004. By way of example and not limitation, network environment 1000 may include multiple client devices 1006, transportation matching systems 104, vehicle subsystems 1008, and / or networks 1004.

[0142] This disclosure contemplates any suitable network 1004. By way of example and not limitation, one or more portions of network 1004 may include an ad-hoc network, an intranet, an extranet, a virtual private network (“VPN”), a local area network (“LAN”), a wireless LAN (“WLAN”), a wide area network (“WAN”), a wireless WAN (“WWAN”), a metropolitan area network (“MAN”), a portion of the Internet, a portion of a public switched telephone network (“PSTN”), a cellular telephone network, or a combination of two or more of these. Network 1004 may include one or more networks 1004.

[0143] Links may connect client device 1006, AV transition location system 106, and vehicle subsystem 1008 to network 1004 or to each other. This disclosure contemplates any suitable links. In particular embodiments, one or more links may be one or more wirelines (e.g., Digital Subscriber Line (“DSL”) or Data Over Cable Service Interface Specification (“DOCSIS”), wireless (e.g., Wi-Fi® or Worldwide Interoperability for Microwave Access (“WiMAX®”), or the like), or optical (e.g., Synchronous Optical Network (“SONET”) or Synchronous Digital Hierarchy (“SDH”)). In particular embodiments, one or more links may each comprise an ad-hoc network, an intranet, an extranet, a VPN, a LAN, a WLAN, a WAN, a WWAN, a MAN, a portion of the Internet, a portion of the PSTN, a cellular technology-based network, a satellite communication technology-based network, another link, or a combination of two or more such links. Links need not necessarily be the same throughout network environment 1000. One or more first links may differ in one or more respects from one or more second links.

[0144] In particular embodiments, client device 1006 may be an electronic device that includes hardware, software, or embedded logic components, or a combination of two or more such components, and is capable of performing appropriate functions implemented or supported by client device 1006. By way of example and not limitation, client device 1006 may include any of the computing devices discussed above in connection with FIG. 9. Client device 1006 may enable a network user at client device 1006 to access network 1004. Client device 1006 may enable that user to communicate with other users at other client devices 1006.

[0145] In particular embodiments, the client device 1006 may include a requester application or web browser, such as MICROSOFT INTERNET EXPLORER, GOOGLE CHROME, or MOZILLA FIREFOX, and may have one or more add-ons, plug-ins, or other extensions, such as TOOLBAR or YAHOO TOOLBAR. A user at the client device 1006 may enter a Uniform Resource Locator ("URL") or other address that directs the web browser to a particular server (e.g., a server), and the web browser may generate a HyperText Transfer Protocol ("HTTP") request and communicate the HTTP request to the server. The server may accept the HTTP request and, in response to the HTTP request, communicate one or more HyperText Markup Language ("HTML") files to the client device 1006. The client device 1006 may render a web page for presentation to the user based on the HTML files from the server. This disclosure contemplates any suitable web page file. By way of example and not limitation, a web page may be rendered from an HTML file, an Extensible HyperText Markup Language ("XHTML") file, or an Extensible Markup Language ("XML") file, depending on particular needs. Such pages may execute, for example, without limitation, JAVASCRIPT, JAVA, scripts such as those described in MICROSOFT SILVERLIGHT, combinations of markup languages ​​and scripts such as AJAX (Asynchronous JAVASCRIPT and XML), and the like.As used herein, a reference to a web page encompasses one or more corresponding web page files that a browser may use to render the web page, and vice versa, where appropriate.

[0146] In particular embodiments, the transportation matching system 104 may be a network-addressable computing system capable of hosting a transportation matching network. The transportation matching system 104 may generate, store, receive, and transmit data such as, for example, user profile data, concept profile data, text data, transportation request data, GPS location data, provider data, requester data, vehicle data, or other suitable data related to the transportation matching network. This may include authenticating the identity of providers and / or vehicles authorized to provide transportation services through the transportation matching system 104. Additionally, the transportation matching system 104 may manage the identity of service requesters, such as users / requesters. In particular, the transportation matching system 104 may maintain requester data, such as trip / ride history, personal data, or other user data, in addition to navigation and / or traffic management services or other location services (e.g., GPS services).

[0147] In particular embodiments, transportation matching system 104 may manage a transportation matching service to connect users / requesters with vehicles and / or providers. By managing the transportation matching service, transportation matching system 104 can manage the distribution and allocation of resources from vehicle systems and user resources, such as GPS locations and availability indicators, as described herein.

[0148] The transportation matching system 104 may be accessed by other components of the network environment 1000 either directly or via the network 1004. In certain embodiments, the transportation matching system 104 may include one or more servers. Each server may be a single server or a distributed server spanning multiple computers or multiple data centers. The servers may be of various types, such as, without limitation, a web server, a news server, a mail server, a message server, an advertisement server, a file server, an application server, an exchange server, a database server, a proxy server, another server suitable for performing the functions or processes described herein, or any combination thereof. In certain embodiments, each server may include hardware, software, or embedded logic components, or a combination of two or more such components, to perform the appropriate functions implemented or supported by the server. In certain embodiments, the transportation matching system 104 may include one or more data stores. A data store may be used to store various types of information. In certain embodiments, the information stored in a data store may be organized according to a particular data structure. In particular embodiments, each data store may be a relational, column-oriented, correlational, or other suitable database. While this disclosure describes or illustrates particular types of databases, this disclosure contemplates any suitable type of database. Particular embodiments may provide an interface that allows a client device 1006 or transportation matching system 104 to manage, retrieve, modify, add, or delete information stored in the data stores.

[0149] In particular embodiments, the transportation matching system 104 may provide users with the ability to take actions on various types of items or objects supported by the transportation matching system 104. By way of example and not limitation, the items and objects may include transportation matching networks to which a user of the transportation matching system 104 may belong, vehicles that a user may request, location specifiers, computer-based applications that a user may use, transactions that allow a user to buy or sell items via the service, interactions with advertisements that a user may perform, or other suitable items or objects. A user may interact with anything that can be represented in the transportation matching system 104 or by an external system, such as a third-party system that is separate from the transportation matching system 104 and coupled to the transportation matching system 104 via the network 1004.

[0150] In particular embodiments, the transportation matching system 104 may be capable of linking various entities. By way of example and not limitation, the transportation matching system 104 may allow users to interact with each other or other entities, or may allow users to interact with these entities through an application programming interface (“API”) or other communication channel.

[0151] In particular embodiments, the transportation matching system 104 may include various servers, subsystems, programs, modules, logs, and data stores. In particular embodiments, the transportation matching system 104 may include one or more of the following: a web server, an action logger, an API request server, a relevance and ranking engine, a content object classifier, a notification controller, an action log, a third-party content object publication log, an inference module, an authorization / privacy server, a search module, an advertisement targeting module, a user interface module, a user profile (e.g., provider profile or requester profile) store, a connection store, a third-party content store, or a location store. The transportation matching system 104 may also include suitable components, such as network interfaces, security mechanisms, load balancers, failover servers, an administration and network operation console, other suitable components, or any suitable combination thereof. In particular embodiments, the transportation matching system 104 may include one or more user profile stores for storing user profiles for transportation providers and / or transportation requesters. A user profile may include, for example, biographical information, demographic information, behavioral information, social information, or other types of descriptive information such as interests, preferences, or location.

[0152] The web server may include a mail server or other messaging functionality for receiving and routing messages between the transportation matching system 104 and one or more client devices 1006. An action logger may be used to receive communications from the web server regarding user actions on or off the transportation matching system 104. In combination with the action log, a user-exposed third-party content object log for third-party content objects may be maintained. A notification controller may provide information about content objects to the client device 1006. The information may be pushed to the client device 1006 as a notification, or the information may be pulled from the client device 1006 in response to a request received from the client device 1006. An authorization server may be used to enforce one or more privacy settings of users of the transportation matching system 104. A user's privacy settings determine how certain information associated with the user can be shared. The authorization server may allow users to opt in or out of having their actions logged by or shared with other systems, such as by setting appropriate privacy settings. The third-party content object store may be used to store content objects received from third parties. The location store may be used to store location information received from a client device 1006 associated with a user.

[0153] Additionally, vehicle subsystem 1008 can include a human-operated vehicle or an autonomous vehicle. A provider of a human-operated vehicle can perform operations to pick up, transport, and drop off one or more requesters in accordance with embodiments described herein. In certain embodiments, vehicle subsystem 1008 can include an autonomous vehicle, e.g., a vehicle that does not require a human operator. In these embodiments, vehicle subsystem 1008 can perform operations, communicate, and otherwise function without the assistance of a human provider in accordance with available technology.

[0154] In certain embodiments, vehicle subsystem 1008 may include one or more sensors incorporated therein or associated therewith. For example, sensors may be mounted on or otherwise located within vehicle subsystem 1008. In certain embodiments, sensors may be located in multiple areas at once, e.g., split throughout vehicle subsystem 1008 such that different components of the sensor may be placed in different locations according to the sensor's optimal operation. In these embodiments, sensors may include motion-related components such as an inertial measurement unit (“IMU”) including one or more accelerometers, one or more gyroscopes, and one or more magnetometers. Sensors may additionally or alternatively include a wireless IMU (“WIMU”), one or more cameras, one or more microphones, or other sensors or data input devices capable of receiving and / or recording information regarding navigating a route for picking up, transporting, and / or dropping off a requester.

[0155] In particular embodiments, vehicle subsystems 1008 may include a communication device capable of communicating with client device 1006 and / or AV transition location system 106. For example, vehicle subsystems 1008 may include an on-board computing device communicatively linked to network 1004 for sending and receiving data such as GPS location information, sensor-related information, requester location information, or other relevant information.

[0156] In the foregoing specification, the invention has been described with reference to specific exemplary embodiments thereof. Various embodiments and aspects of the invention are described with reference to the details discussed herein and the accompanying drawings which illustrate various embodiments. The above description and drawings are illustrative of the invention and should not be construed as limiting the invention. Numerous specific details have been set forth to provide a thorough understanding of various embodiments of the invention.

[0157] The present invention may be embodied in other specific forms without departing from its spirit or essential characteristics. The described embodiments are to be considered in all respects only as illustrative and not restrictive. For example, methods described herein may be performed with fewer or more steps / actions, or the steps / actions may be performed in a different order. In addition, steps / actions described herein may be repeated or performed in parallel with each other or with different instances of the same or other similar steps / actions. The scope of the present invention is, therefore, indicated by the appended claims, rather than by the foregoing description. All changes that come within the meaning and range of equivalency of the claims are embraced within their scope.

Claims

1. monitoring, via one or more computing systems, updates from provider devices and requester devices corresponding to the transportation request; determining a time of arrival of a provider device at a pickup location corresponding to a transportation request from a requester device; Determining a departure time for the transportation request from the provider device or the requester device; and Comparing the departure time and the arrival time at the provider device to determine a pickup transition time. determining pickup transition times for a plurality of pickup locations by: selecting a subset of preferred pickup locations from the plurality of pickup locations based on the pickup transition times; and transmitting, via the one or more computing systems, the one or more of the subset of preferred pickup locations to a vehicle navigation system for navigating a provider device to the one or more of the subset of preferred pickup locations. A computer-implemented method comprising:

2. 2. The computer-implemented method of claim 1, wherein selecting the subset of preferred pickup locations comprises selecting the filtered subset utilizing an autonomous vehicle location filter, the autonomous vehicle location filter indicating areas accessible to an autonomous vehicle.

3. The computer-implemented method of claim 1 , further comprising comparing the pickup transition time to a threshold transition time to determine a first transition classification for the transport request.

4. determining additional pickup transit times corresponding to the pickup locations for additional transportation requests from additional requester devices; comparing the additional pickup transition time to the threshold transition time to determine a second transition classification for the additional transport request; and determining a threshold length transition pickup measure for the pickup location based on the first transition classification and the second transition classification; The computer-implemented method of claim 3 further comprising:

5. 5. The computer-implemented method of claim 4, further comprising selecting the subset of preferred pickup locations by comparing the measure of threshold length transition pickup corresponding to the pickup location with additional measures of threshold length transition pickup corresponding to additional pickup locations.

6. the pickup transition time corresponds to a first time period, and selecting the subset of preferred pickup locations comprises selecting a first subset of preferred pickup locations for the first time period, the computer-implemented method comprising: determining an additional plurality of pickup transition times corresponding to the second time period; and selecting a second subset of preferred pickup locations corresponding to the second time period; The computer-implemented method of claim 1 further comprising:

7. determining a transport mode corresponding to the transport request, wherein the transport mode includes at least one of a multi-occupant mode or an entitlement-limited transport mode; and selecting the subset of preferred pickup locations based on the pickup transit time and the transportation mode. The computer-implemented method of claim 1 further comprising:

8. determining a provider device rating associated with the provider device; and selecting the subset of preferred pickup locations from the plurality of pickup locations based on the pickup transition times and the provider device ratings; The computer-implemented method of claim 1 further comprising:

9. determining a number of transportation requests corresponding to the pickup location; and selecting the subset of preferred pickup locations based on the number of transportation requests corresponding to the pickup locations and the pickup transit time; The computer-implemented method of claim 1 , further comprising:

10. 1. A system comprising: at least one processor; and When executed by the at least one processor, the system: monitoring, via one or more servers, updates from provider devices and requester devices corresponding to the transportation request; determining a time of arrival of a provider device at a pickup location corresponding to a transportation request from a requester device; Determining a departure time for the transportation request from the provider device or the requester device; and Comparing the departure time and the arrival time at the provider device to determine a pickup transition time. determining pickup transition times for a plurality of pickup locations by: selecting a subset of preferred pickup locations from the plurality of pickup locations based on the pickup transition times; and transmitting, via the one or more servers, the one or more subset of preferred pickup locations to a vehicle navigation system for navigating a provider device to the one or more subset of preferred pickup locations. A non-transitory computer-readable medium having instructions for causing A system comprising:

11. The instructions may include:

11. The system of claim 10, further comprising the steps of selecting a subset of the preferred pickup locations and selecting the filtered subset utilizing an autonomous vehicle location filter, the autonomous vehicle location filter indicating areas accessible to an autonomous vehicle.

12. The instructions may include: determining additional pickup transit times corresponding to the pickup locations for additional transportation requests from additional requester devices; combining the pickup transition time and the additional pickup transition time to determine an expected pickup transition time at the pickup location; and selecting the subset of preferred pickup locations by comparing the expected pickup transition time with a threshold transition time; The system of claim 10 further comprising:

13. The pickup transition time corresponds to a first time period, and the instructions include: selecting a subset of preferred pickup locations by selecting a first subset of preferred pickup locations for the first time period; determining an additional plurality of pickup transition times corresponding to the second time period; and selecting a second subset of preferred pickup locations corresponding to said second time period; The system of claim 10 further comprising:

14. The instructions may include: determining a transport mode corresponding to the transport request, wherein the transport mode includes at least one of a multi-occupant mode or an entitlement-limited transport mode; and selecting a subset of the preferred pickup locations based on the pickup transit time and the transportation mode; The system of claim 10 further comprising:

15. The instructions may include: determining a provider device rating associated with the provider device; and selecting the subset of preferred pickup locations from the plurality of pickup locations based on the pickup transition times and the provider device ratings; The system of claim 10 further comprising:

16. The instructions may include: determining the number of transportation requests at the pickup location; and selecting the subset of preferred pickup locations based on the number of transportation requests at the pickup locations and the pickup transit time; The system of claim 10 , further comprising:

17. When executed by at least one processor, the method causes the at least one processor to: monitoring, via one or more servers, updates from provider devices and requester devices corresponding to the transportation request; determining a time of arrival of a provider device at a pickup location corresponding to a transportation request from a requester device; Determining a departure time for the transportation request from the provider device or the requester device; and Comparing the departure time and the arrival time at the provider device to determine a pickup transition time. determining pickup transition times for a plurality of pickup locations by: selecting a subset of preferred pickup locations from the plurality of pickup locations based on the pickup transition times; and transmitting, via the one or more servers, the one or more subset of preferred pickup locations to a vehicle navigation system for navigating a provider device to the one or more subset of preferred pickup locations. A computer program having instructions to perform the following:

18. When executed by the at least one processor, the method causes the at least one processor to:

20. The computer program product of claim 17, further comprising instructions for selecting a subset of the preferred pickup locations and selecting the filtered subset utilizing an autonomous vehicle location filter, the autonomous vehicle location filter indicating areas accessible to an autonomous vehicle.

19. When executed by the at least one processor, the method causes the at least one processor to: determining additional pickup transit times corresponding to the pickup locations for additional transportation requests from additional requester devices; combining the pickup transition time and the additional pickup transition time to determine an expected pickup transition time at the pickup location; and selecting the subset of preferred pickup locations by comparing the expected pickup transition time with a threshold transition time; 20. The computer program product of claim 17, further comprising instructions to:

20. When executed by the at least one processor, the method causes the at least one processor to: determining a transport mode corresponding to the transport request, wherein the transport mode includes at least one of a multi-occupant mode or an entitlement-limited transport mode; and selecting a subset of the preferred pickup locations based on the pickup transit time and the transportation mode; 20. A computer program product as claimed in any one of claims 17 to 19, further comprising instructions to:

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