Patent Description:
An autonomous vehicle is a vehicle that is capable of sensing its environment and navigating with minimal or no human input. In particular, an autonomous vehicle can observe its surrounding environment using a variety of sensors and identify an appropriate motion path through such surrounding environment.

<CIT> proposes a vehicle having a plurality of control apparatuses, a user input, a geographic position component, an object detection apparatus, memory, and a display. A processor is also included and is programmed to receive the destination information, identify a route, and determine the current geographic location of the vehicle. The processor is also programmed to identify an object and object type based on object information received from the object detection apparatus and to determine at least one warning characteristic of the identified object based on at least one of: the object type, a detected proximity of the detected object to the vehicle, the location of the detected object relative to predetermined peripheral areas of the vehicle, the current geographic location of the vehicle, and the route. The processor is also configured to select and display on the display an object warning image based on the at least one warning characteristic.

Aspects and advantages of embodiments of the present invention will be set forth in part in the following description, or can be learned from the description, or can be learned through practice of the embodiments.

According to a first aspect of the present invention, there is provided a computer-implemented method as set out in claim <NUM>.

According to a second aspect of the present invention, there is provided a computing system as set out in claim <NUM>.

According to a third aspect of the present invention, there is provided one or more non-transitory computer-readable media as set out in claim <NUM>.

Other aspects of the present invention are directed to various systems, apparatuses, non-transitory computer-readable media, user interfaces, and electronic devices.

These and other features, aspects, and advantages of various embodiments of the present invention will become better understood with reference to the following description and appended claims. The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate example embodiments of the present invention and, together with the description, serve to explain the related principles.

Generally, the present invention is directed to methods and systems for communicating intent of an autonomous vehicle. According to the present invention, an autonomy computing system of an autonomous vehicle determines a motion plan for the autonomous vehicle based on maps and data received from sensors of the autonomous vehicle that describes the environment in which the autonomous vehicle is operating. Such a motion plan includes data that indicates intents of the autonomous vehicle. For example, the autonomous vehicle can plan to stop at an approaching intersection (e.g., based on a stop sign or signal determined from map and/or environmental sensor data). A computing system can receive, from the autonomy computing system of the autonomous vehicle, data indicating the intent of the autonomous vehicle (e.g., that the autonomous vehicle intends to stop at the approaching intersection). Multiple intents of the autonomous vehicle are determined based on the data indicating the intent. For example, the data can indicate that the autonomous vehicle plans to stop at the approaching intersection because there is a red signal light and because pedestrians are currently crossing the path of the autonomous vehicle (e.g., at the intersection). From amongst the determined intents, an intent of the autonomous vehicle is selected. In some implementations, the intent can be selected based on a predetermined hierarchy. For example, an intent indicating that the autonomous vehicle plans to stop at the approaching intersection because there is a red signal light can be selected instead of an intent indicating that the autonomous vehicle plans to stop because pedestrians are currently crossing the path of the autonomous vehicle because a predetermined hierarchy can indicate that intents associated with traffic signals should be selected in lieu of intents associated with pedestrian crossings. A determination is made that the intent of the autonomous vehicle (e.g., planned deceleration associated with the approaching intersection) should be communicated to a passenger of the autonomous vehicle (e.g., operator or non-operator passenger of the autonomous vehicle). For example, a determination can be made that the deceleration associated with the approaching intersection is of sufficient magnitude (e.g., exceeds a predetermined threshold) that a passenger of the autonomous vehicle should be notified.

Responsive to a determination that a passenger of the autonomous vehicle should be notified of the intent of the autonomous vehicle, a graphical interface indicating the intent of the autonomous vehicle is generated and displayed for viewing by the passenger of the autonomous vehicle. For example, a graphical interface indicating that the autonomous vehicle is (or is planning to) decelerate due to the approaching intersection can be generated and displayed to a passenger of the autonomous vehicle.

In some implementations, the graphical interface can include a map of the area surrounding the current location of the autonomous vehicle and can depict the location of the autonomous vehicle (e.g., within the surrounding area). In such implementations, the graphical interface can include a graphic overlay on the map indicating the intent of the autonomous vehicle. In some implementations, generating the graphical interface can include distilling or summarizing complex vehicle intent information into an easily understandable graphical element that quickly conveys to the passenger the intent of the autonomous vehicle. The graphical interface can include (e.g., as part of the graphic overlay) one or more elements depicting an event associated with the intent of the autonomous vehicle. For example, the autonomous vehicle can be stopped for two cars, and the graphic overlay can indicate that the autonomous vehicle is stopped (e.g., via a graphic corresponding to a stop sign) and the graphical interface can indicate that the associated event is waiting for two cars (e.g., via one or more textual elements). Similarly, the autonomous vehicle can be approaching a traffic signal and the graphical overlay can indicate the intent of the autonomous vehicle (e.g., continuing, stopping, stopped, or the like) and the associated event, for example, the status of the traffic signal (e.g., red, yellow, green, or the like). In some implementations, the graphical interface can indicate one or more parameters associated with the event. For example, the autonomous vehicle can be approaching a turn and the graphical interface can indicate a time until completion or execution of the turn. Similarly, the autonomous vehicle can be yielding (e.g., decelerating) in response to another vehicle, a pedestrian, a cyclist, or the like, and the graphical interface can indicate a speed of the vehicle, cyclist, pedestrian, or the like and/or a distance between the autonomous vehicle and the vehicle, cyclist, pedestrian, or the like.

In some implementations, the computing system can determine that the intent of the autonomous vehicle should be communicated to the passenger based on a determination that a frequency in the change of the intent indicated by the data received from the autonomy computing system meets a predetermined threshold. The data received from the autonomy computing system can indicate multiple intents within a short period of time (e.g., the autonomy computing system can frequently alter its planned motion path for the autonomous vehicle based on, for example, changes in data received from sensors of the autonomous vehicle). For example, the data received from the autonomy computing system can indicate that the autonomous vehicle intends to decelerate in order to avoid a pedestrian, however, the data received from the autonomy computing system could subsequently indicate that the autonomous vehicle intends to maintain its current speed (e.g., because data received from sensors of the autonomous vehicle indicates the pedestrian has already cleared the path of the autonomous vehicle). Accordingly, in order to prevent multiple intents (e.g., possibly contradictory intents) from being communicated to the passenger of the autonomous vehicle within a short time period, a determination can be made with regards to the frequency in the change of the intent indicated by the data received from the autonomy computing system, and the intent of the autonomous vehicle can be communicated in response to a determination that the frequency in the change of the intent meets a predetermined threshold (e.g., the intent of the autonomous vehicle has remained constant for a threshold period of time). For example, the intent of the autonomous vehicle can be communicated in response to a determination that the frequency in the change of the intent is less than a predetermined threshold.

Additionally or alternatively, the computing system can determine that the intent of the autonomous vehicle should be communicated to the passenger based on a determination that a degree of confidence of an event associated with the intent indicated by the data received from the autonomy computing system meets a predetermined threshold. The data received from the autonomy computing system can indicate an event associated with the intent of the autonomous vehicle. For example, the data can indicate that the autonomous vehicle intends to decelerate because a pedestrian has entered the path of the autonomous vehicle. In certain scenarios, the autonomous vehicle can determine its intent, but the nature of the associated event can be unclear. For example, the autonomous vehicle can detect an object in its path and determine to decelerate in order to avoid the object, but the autonomous vehicle can be uncertain regarding the nature of the object (e.g., whether the object is a pedestrian, cyclist, or the like). This uncertainty can be indicated by the data received from the autonomy computing system. For example, the data can indicate the nature of the object to a degree of confidence. Because communicating erroneous information about the nature of the event to the passenger could undermine the confidence of the passenger in the autonomous vehicle, a determination can be made about whether to communicate the intent of the autonomous vehicle based on a determination that the degree of confidence meets a predetermined threshold (e.g., the intent can be conveyed when the confidence regarding the event exceeds the predetermined threshold).

The computing system can include a human machine interface device (e.g., a mobile device, tablet computing device, or the like) that can be viewable by a passenger of the autonomous vehicle. The device can include a display (e.g., for viewing by the passenger), one or more processors, and memory. The memory can include instructions that when executed by the processor(s) cause the device to perform one or more of the operations described herein.

The systems and methods described herein can provide a number of technical effects and benefits. For example, the systems and methods described herein can communicate the intent of an autonomous vehicle to its passenger thereby allowing the passenger to anticipate impending changes in force and increasing passenger comfort. Additionally or alternatively, by communicating the intent of an autonomous vehicle to its passenger, the systems and methods described herein can demonstrate environmental understanding and driving competence of the autonomous vehicle to its passenger thereby reassuring the passenger that the autonomous vehicle is correctly interpreting its environment and acting appropriately.

With reference now to the Figures, example embodiments of the present invention will be discussed in further detail.

<FIG> depicts a block diagram of an example computing system according to example embodiments of the present invention. Referring to <FIG>, the example computing system includes autonomous vehicle <NUM>, central computing system <NUM>, and user computing device <NUM> that are communicatively coupled over one or more communication networks <NUM>. Autonomous vehicle <NUM> can include one or more sensors <NUM>, autonomy computing system <NUM>, one or more vehicle controls <NUM>, and human machine interface device <NUM>.

Human machine interface device <NUM> can enable communication, control, and/or other interface actions to occur between autonomous vehicle <NUM> and a human (e.g., a passenger located within autonomous vehicle <NUM>). Human machine interface device <NUM> can be communicatively coupled to autonomy computing system <NUM> to enable exchange of data, instructions, and/or requests between system <NUM> and device <NUM>.

Human machine interface device <NUM> can include or be implemented by one or more computing devices that are operatively connected. Human machine interface device <NUM> can be an embedded computing device or a stand-alone computing device. In one particular example, human machine interface device <NUM> can be a tablet computing device that is positioned within autonomous vehicle <NUM> for viewing by a passenger (e.g., within a rear seat area of autonomous vehicle <NUM>).

Human machine interface device <NUM> can include one or more processors <NUM>, memory <NUM>, event detector <NUM>, display <NUM>, one or more user input components <NUM>, one or more sensors <NUM>, and navigational system <NUM>. Processor(s) <NUM> can be any suitable processing device (e.g., a processor core, a microprocessor, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a controller, a microcontroller, etc.) and can be one processor or a plurality of processors that are operatively connected. Memory <NUM> can include one or more non-transitory computer-readable storage media, such as random-access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), one or more memory devices, flash memory devices, etc., and combinations thereof.

Memory <NUM> can store information that can be accessed by processor(s) <NUM>. For instance, memory <NUM> (e.g., one or more non-transitory computer-readable storage mediums, memory devices) can store data that can be obtained, received, accessed, written, manipulated, created, and/or stored. Memory <NUM> can also store computer-readable instructions that can be executed by processor(s) <NUM>. The instructions can be software written in any suitable programming language or can be implemented in hardware. Additionally, or alternatively, the instructions can be executed in logically and/or virtually separate threads on processor(s) <NUM>. For example, memory <NUM> can store instructions that when executed by processor(s) <NUM> cause processor(s) <NUM> to perform any of the operations and/or functions described herein.

In some implementations, human machine interface device <NUM> can include display device <NUM> (e.g., a touch-sensitive display device) and/or other input/output components <NUM> that provide an interactive user interface. For example, display device <NUM> can be a rear-seat display device that is accessible by a passenger that is located in a rear seat of autonomous vehicle <NUM>.

In some implementations, in addition or alternatively to human machine interface device <NUM>, the systems and methods of the present invention can include or leverage user computing device <NUM> that is associated with the passenger. For example, in some implementations, in addition or alternatively to the display of the user interface by human machine interface device <NUM>, the interactive user interface can be provided on or accessible via a display of user computing device <NUM>. User computing device <NUM> can be communicatively connected to human machine interface device <NUM> via a local area network such as a short range wireless connection (e.g., a Bluetooth, ZigBee, near-field communication (NFC), infrared, etc.) or other forms of connections (e.g., hardwiring). As examples, user computing device <NUM> can be a smartphone, tablet computing device, wearable computing device, portable gaming device, hand-held display screen, or other form of computing device.

In yet further implementations, certain operations described herein can be performed by central computing system <NUM> that is remotely located to autonomous vehicle <NUM> and in communication with autonomous vehicle <NUM> over network(s) <NUM> (e.g., cellular data networks, satellite communication networks, wide area networks, etc.). As an example, central computing system <NUM> can include one or more server computing devices. In the event that plural server computing devices are used, the server computing devices can be arranged according to a parallel computing architecture, a sequential computing architecture, or combinations thereof. In some implementations, central computing system <NUM> can provide control, monitoring, management, and/or other functionality for a fleet of autonomous vehicles including autonomous vehicle <NUM>.

Network(s) <NUM> can be any type of network or combination of networks that allows for communication between devices. In some embodiments, network(s) <NUM> can include one or more of a local area network, wide area network, the Internet, secure network, cellular network, mesh network, peer-to-peer communication link, and/or some combination thereof, and can include any number of wired or wireless links. Communication over network(s) <NUM> can be accomplished, for instance, via a network interface using any type of protocol, protection scheme, encoding, format, packaging, etc..

In accordance with aspects of the invention, a computing system of autonomous vehicle <NUM> can be configured to communicate intent of autonomous vehicle <NUM> to a passenger of autonomous vehicle <NUM> (e.g., an operator and/or non-operator passenger). For example, human machine interface device <NUM> can receive, from autonomy computing system <NUM>, data indicating an intent of autonomous vehicle <NUM> (e.g., intent to perform a driving maneuver) and can determine, based on the data indicating the intent, that the intent of autonomous vehicle <NUM> should be communicated to a passenger of autonomous vehicle <NUM>. Responsive to determining that the intent of autonomous vehicle <NUM> should be communicated to the passenger, human machine interface device <NUM> can generate a graphical interface indicating the intent of autonomous vehicle <NUM> and can provide the graphical interface for display (e.g., via display <NUM>) for viewing by the passenger. In some implementations, human machine interface device <NUM> can generate or otherwise trigger an audible signal for the passenger (e.g., a signal indicating the intent, a signal alerting the passenger to view display <NUM> for information regarding the intent, or the like).

In some implementations, human machine interface device <NUM> can determine multiple intents of autonomous vehicle <NUM> based on the data received from autonomy computing system <NUM>. For example, the data received from autonomy computing system <NUM> can indicate autonomous vehicle <NUM> plans to stop at an approaching intersection because there is a red signal light and because pedestrians are currently crossing the path of autonomous vehicle <NUM> (e.g., at the intersection). In such implementations, human machine interface device <NUM> can select, from amongst the intents, an intent to communicate to the passenger of autonomous vehicle <NUM>. In some implementations, human machine interface device <NUM> can be configured to select the intent to be communicated to the passenger based on a predetermined hierarchy. For example, human machine interface device <NUM> can be configured to select an intent indicating that autonomous vehicle <NUM> plans to stop at the approaching intersection because there is a red signal light instead of an intent indicating that autonomous vehicle <NUM> plans to stop because pedestrians are currently crossing the path of autonomous vehicle <NUM> because a predetermined hierarchy can indicate that intents associated with traffic signals should be selected in lieu of intents associated with pedestrian crossings.

In some implementations, human machine interface device <NUM> can be configured to determine that the intent of autonomous vehicle <NUM> should be communicated to the passenger based on a determination that a frequency in the change of the intent indicated by the data received from autonomy computing system <NUM> meets a predetermined threshold. The data received from autonomy computing system <NUM> can indicate multiple intents within a short period of time (e.g., autonomy computing system <NUM> can frequently alter its planned motion path for autonomous vehicle <NUM> based on, for example, changes in data received from sensor(s) <NUM>). For example, the data received from autonomy computing system <NUM> can indicate that autonomous vehicle <NUM> intends to decelerate in order to avoid a pedestrian, however, the data received from autonomy computing system <NUM> could subsequently indicate that autonomous vehicle <NUM> intends to maintain its current speed (e.g., because data received from sensor(s) <NUM> indicates the pedestrian has already cleared the path of autonomous vehicle <NUM>). Accordingly, in order to prevent multiple intents (e.g., possibly contradictory intents) from being communicated to the passenger of autonomous vehicle <NUM> within a short time period, human machine interface device <NUM> can be configured to make a determination with regards to the frequency in the change of the intent indicated by the data received from autonomy computing system <NUM>, and the intent of autonomous vehicle <NUM> can be communicated in response to a determination that the frequency in the change of the intent meets a predetermined threshold (e.g., the intent of autonomous vehicle <NUM> has remained constant for a threshold period of time). For example, the intent of autonomous vehicle <NUM> can be communicated in response to a determination that the frequency in the change of the intent is less than a predetermined threshold.

Additionally or alternatively, human machine interface device <NUM> can be configured to determine that the intent of autonomous vehicle <NUM> should be communicated to the passenger based on a determination that a degree of confidence of an event associated with the intent indicated by the data received from autonomy computing system <NUM> meets a predetermined threshold. The data received from autonomy computing system <NUM> can indicate an event associated with the intent of autonomous vehicle <NUM>. For example, the data can indicate that autonomous vehicle <NUM> intends to decelerate because a pedestrian has entered the path of autonomous vehicle <NUM>. In certain scenarios, autonomous vehicle <NUM> can determine its intent, but the nature of the associated event can be unclear. For example, autonomous vehicle <NUM> can detect an object in its path and determine to decelerate in order to avoid the object, but autonomous vehicle <NUM> can be uncertain regarding the nature of the object (e.g., whether the object is a pedestrian, cyclist, or the like). This uncertainty can be indicated by the data received from autonomy computing system <NUM>. For example, the data can indicate the nature of the object to a degree of confidence. Because communicating erroneous information about the nature of the event to the passenger could undermine the confidence of the passenger in autonomous vehicle <NUM>, human machine interface device <NUM> can be configured to make a determination about whether to communicate the intent of autonomous vehicle <NUM> based on a determination that the degree of confidence meets a predetermined threshold (e.g., the intent can be conveyed when the confidence regarding the event exceeds the predetermined threshold).

The intent can be an intent to perform a driving maneuver. For example, the intent could be that autonomous vehicle <NUM> intends to change lanes, decelerate (e.g., to yield to and/or stop for a traffic sign or signal, approaching vehicle, pedestrian, cyclist, unclassified object or the like), merge into traffic, pull alongside a curb or roadside, perform a left- or right-hand turn (e.g., a protected or unprotected turn), deviate from a typical pathway within its lane and/or without substantially intruding an adjacent lane in order to avoid an object or obstruction, decelerate or alter its speed based on a context-based speed limit (e.g., a school zone), or other driving maneuver. In some implementations, human machine interface device <NUM> can be configured to distill or summarize complex vehicle intent information such that it is easily understandable by a passenger. For example, as indicated above, human machine interface device <NUM> can be configured to generate a graphical interface indicating the intent of autonomous vehicle <NUM>. The graphical interface can include one or more elements that distill or summarize complex vehicle intent information such that it is easily understandable by a passenger. For example, <FIG> depicts example graphical interface elements for communicating intent of an autonomous vehicle according to example embodiments of the present invention.

Referring to <FIG>, graphics <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and <NUM> include elements that distill or summarize complex vehicle intent information such that it is easily understandable by a passenger. In some implementations, the one or more elements of a graphic indicating intent can include elements depicting an event associated with the intent. For example, graphic <NUM> can depict an intent of autonomous vehicle <NUM> to decelerate in response to a red traffic signal. Similarly, graphic <NUM> can depict an intent of autonomous vehicle <NUM> to remain stopped for a red traffic signal; graphic <NUM> can depict an intent of autonomous vehicle <NUM> to maintain its current velocity in response to a yellow traffic signal; graphic <NUM> can depict an intent of autonomous vehicle <NUM> to maintain its current velocity in response to a green traffic signal; graphics <NUM> and <NUM> can depict an intent of autonomous vehicle <NUM> to perform a left-hand turn; graphics <NUM> and <NUM> can depict an intent of autonomous vehicle <NUM> to perform a right-hand turn; graphic <NUM> can depict an intent of autonomous vehicle <NUM> to remain stopped for two other vehicles; graphic <NUM> can depict an intent of autonomous vehicle <NUM> to remain stopped or decelerate for another vehicle; graphic <NUM> can depict an intent of autonomous vehicle <NUM> to remain stopped or decelerate for a cyclist; and graphic <NUM> can depict an intent of autonomous vehicle <NUM> to remain stopped or decelerate for a pedestrian. In some implementations, the one or more elements of a graphic indicating intent can include elements that provide contextual information associated with the intent and/or associated event. For example, graphics <NUM>, <NUM>, and/or <NUM> can indicate a time until the turn is completed; graphic <NUM> can indicate a margin between autonomous vehicle <NUM> and an approaching vehicle; graphics <NUM> and/or <NUM> can indicate a velocity and/or acceleration status of an approaching vehicle; and graphics <NUM>, <NUM>, and/or <NUM> can indicate a distance to and/or velocity of another vehicle, a cyclist, and/or a pedestrian, respectively.

In some implementations, human machine interface device <NUM> can be configured to generate a graphical interface that includes a map depicting the current location of autonomous vehicle <NUM>. In such implementations, the graphical interface can include a graphic overlay on the map indicating an intent of autonomous vehicle <NUM>. For example, <FIG> depict example graphical interfaces for communicating intent of an autonomous vehicle according to example embodiments of the present invention.

Referring to <FIG>, graphical interface <NUM> can include portion <NUM> and map <NUM>. Portion <NUM> can indicate a status of autonomous vehicle <NUM> on a planned route (e.g., a distance to the next turn on the planned route, or the like). Map <NUM> can include element <NUM>, which can depict the current location of autonomous vehicle <NUM> (e.g., within its surrounding environment). As indicated above, human machine interface device <NUM> can be configured to generate a graphical interface that includes a graphic overlay on the map indicating an intent of autonomous vehicle <NUM>. For example, referring to <FIG>, graphical interface <NUM> can include graphic overlay <NUM> indicating an intent of autonomous vehicle <NUM> to remain stopped and/or decelerate in response to a detected cyclist. Similarly, referring to <FIG>, graphical interface <NUM> can include graphic overlay <NUM> indicating an intent of autonomous vehicle <NUM> to remain stopped and/or decelerate in response to a red traffic signal; referring to <FIG>, graphical interface <NUM> can include graphic overlay <NUM> indicating an intent of autonomous vehicle <NUM> to execute a right-hand turn; referring to <FIG>, graphical interface <NUM> can include graphic overlay <NUM> indicating an intent of autonomous vehicle <NUM> to abort a planned lane change (e.g., in response to the presence of another vehicle in the lane); referring to <FIG>, graphical interface <NUM> can include graphic overlay <NUM> indicating an intent of autonomous vehicle <NUM> to execute a lane change (e.g., in order to pass an approaching vehicle in its current lane); and referring to <FIG>, graphical interface <NUM> can include graphic overlay <NUM> indicating an intent of autonomous vehicle <NUM> to execute a lane change.

<FIG> depicts a flow chart diagram of an example method to communicate intent of an autonomous vehicle according to example embodiments of the present invention. Referring to <FIG>, at (<NUM>), data indicating one or more intents of an autonomous vehicle can be received. For example, human machine interface device <NUM> can receive data indicating one or more intents of autonomous vehicle <NUM> from autonomy computing system <NUM>. At (<NUM>), one or more intents of the autonomous vehicle can be determined. For example, human machine interface device <NUM> can determine, based on the data received from autonomy computing system <NUM>, one or more intents of autonomous vehicle <NUM>. At (<NUM>), an intent of the autonomous vehicle is selected. For example, human machine interface device <NUM> can select, from amongst the determined intent(s) (e.g., based on a predetermined hierarchy), an intent to communicate to a passenger of autonomous vehicle <NUM>. At (<NUM>), a determination that the intent should be communicated to a passenger of the autonomous vehicle is made. For example, human machine interface device <NUM> can determine to communicate the selected intent of autonomous vehicle <NUM> to a passenger of autonomous vehicle <NUM> (e.g., based on a determination that a frequency in the change of the intent meets a predetermined threshold, a determination that a degree of confidence of an event associated with the intent meets a predetermined threshold, or the like). At (<NUM>), a graphical interface indicating the intent of the autonomous vehicle is generated. For example, human machine interface device <NUM> can generate a graphical interface similar to graphical interfaces <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and/or <NUM>. At (<NUM>), the graphical interface indicating the intent of the autonomous vehicle is provided for display for viewing by the passenger of the autonomous vehicle. For example, human machine interface device <NUM> can provide a graphical interface similar to graphical interfaces <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and/or <NUM> (e.g., via display <NUM>) for viewing by a passenger of autonomous vehicle <NUM>.

Claim 1:
A computer-implemented method comprising:
determining, by a computing system comprising one or more computing devices, a motion plan for an autonomous vehicle based on maps and data received from sensors of the autonomous vehicle;
determining (<NUM>), by the computing system and based at least in part on the motion plan for the autonomous vehicle, a plurality of intents of the autonomous vehicle;
selecting (<NUM>), by the computing system, from amongst the plurality of intents, an intent of the autonomous vehicle;
characterized in that it further comprises:
determining (<NUM>), by the computing system, that the intent of the autonomous vehicle should be communicated to a passenger of the autonomous vehicle; and
responsive to determining that the intent of the autonomous vehicle should be communicated to the passenger, providing (<NUM>), by the computing system for display via a graphical interface, data indicative of the intent of the autonomous vehicle for viewing.