Improving passenger pickup and drop-off for autonomous vehicles with weather information

Abstract

This disclosure relates to providing transportation services using autonomous vehicles. For example, a first route to a first destination can be determined. The first route may have a first cost. Weather information for the first destination can be received. Characteristics are determined based on the weather information. A second destination with characteristics can be selected. The second destination may be different from the first destination. A second route to the second destination can be determined. The second route may have a second cost. The first cost can be compared with the second cost, and the vehicle can use the comparison to set either the first destination or the second destination as its current destination, enabling the vehicle to control itself to proceed to the current destination in autonomous driving mode.

Description

Technical Field

[0001] This disclosure relates to providing transportation services to passengers using autonomous vehicles. Specifically, such services can use weather information to improve the user experience during the ride, during disembarkation, and throughout the journey. Background Technology

[0002] Autonomous vehicles (e.g., vehicles that do not require a human driver) can be used to assist in transporting passengers or objects from one location to another. Such vehicles can operate in a fully autonomous mode, where passengers provide initial input (such as the pick-up or destination location), and the vehicle maneuvers itself to that location. Autonomous vehicles are equipped with various types of sensors to detect surrounding objects. For example, autonomous vehicles may include sonar, radar, cameras, LiDAR, and other devices that scan and record data about the vehicle's surroundings. Summary of the Invention

[0003] This disclosure provides a method for providing transportation services using an autonomous vehicle. The method includes: determining a first route to a first destination by one or more processors, the first route having a first cost; receiving weather information for the first destination by one or more processors; determining characteristics by one or more processors based on the weather information; selecting a second destination having characteristics different from the first destination by one or more processors; determining a second route to the second destination by one or more processors, the second route having a second cost; comparing the first cost with the second cost by one or more processors; and setting one of the first destination or the second destination as the vehicle's current destination by one or more processors using the comparison, so that the vehicle controls itself to proceed to the current destination in an autonomous driving mode.

[0004] In one example, the first destination is the passenger's drop-off point. In another example, the first destination is the passenger's pick-up point. In another example, the one or more processors are one or more processors of one or more server computing devices, and setting one of the first or second destinations as the vehicle's current destination using comparison further includes: sending one of the first or second destinations to the vehicle to cause the vehicle to set one of the first or second destinations as its current destination. In another example, the one or more processors are one or more processors of a vehicle, and the method further includes: controlling the vehicle to proceed to the current destination in autonomous driving mode. In another example, the method further includes: comparing weather information with one or more thresholds; and using the comparison of the weather information with one or more thresholds to determine a characteristic. In this example, the weather information includes precipitation rate. Additionally or alternatively, the weather information includes temperature. Additionally or alternatively, the characteristic is associated with one of the one or more thresholds satisfied by the weather information. In another example, the comparison includes: determining the difference between a first cost and a second cost; and comparing the difference with a threshold. In this example, when the difference satisfies the threshold, a notification is provided to the passenger assigned to the vehicle, requesting the passenger to choose between the first and second destinations. In this example, the notification identifies weather conditions based on weather information. Additionally or alternatively, the method further includes: receiving a selection in response to the notification, and wherein the received selection is used to set either a first destination or a second destination as the vehicle's current destination. Additionally or alternatively, the second destination is set as the vehicle's current destination when the difference meets a threshold.

[0005] Another aspect of this disclosure provides a system for providing transportation services using autonomous vehicles. The system includes one or more processors configured to: determine a first route to a first destination, the first route having a first cost; receive weather information for the first destination; determine characteristics based on the weather information; select a second destination having characteristics different from the first destination; determine a second route to the second destination, the second route having a second cost; compare the first cost with the second cost; and use the comparison to set either the first destination or the second destination as the vehicle's current destination, enabling the vehicle to control itself to proceed to the current destination in an autonomous driving mode.

[0006] In one example, one or more processors are further configured to compare weather information with one or more thresholds; and to determine a characteristic using the comparison of the weather information with one or more thresholds. In this example, the characteristic is associated with one of the one or more thresholds that is satisfied by the weather information. In another example, one or more processors are further configured to compare a first cost with a second cost by: determining a difference between the first cost and the second cost; and comparing the difference with a threshold. In another example, one or more processors are further configured to provide a notification to passengers assigned to the vehicle when the difference satisfies the threshold, the notification requesting the passengers to choose between a first destination and a second destination. In another example, the system also includes a vehicle, wherein the processor is a processor of the vehicle. Attached Figure Description

[0007] Figure 1 This is a functional diagram of an example vehicle according to an exemplary embodiment.

[0008] Figures 2A to 2B This is an example of map information based on aspects of this disclosure.

[0009] Figure 3 This is an example external view of a vehicle according to aspects of this disclosure.

[0010] Figure 4 This is a schematic diagram of an example system based on aspects of this disclosure.

[0011] Figure 5 Based on the aspects of this disclosure Figure 4 The system's functional diagram.

[0012] Figure 6 This is an example representation of a first route to a first destination according to aspects of this disclosure.

[0013] Figure 7 This is an example representation of a second route to a second destination according to aspects of this disclosure.

[0014] Figure 8A and Figure 8B This is an example visualization of a notification displayed on a client computing device in accordance with aspects of this disclosure.

[0015] Figure 9 This is an example flowchart based on aspects of this disclosure. Detailed Implementation

[0016] Overview

[0017] This disclosure relates to providing transportation services to passengers using autonomous vehicles. Specifically, such services can use weather information to improve the user experience during boarding, disembarking, and throughout the journey. For example, boarding, disembarking, and routes can be optimized at the autonomous vehicle or at remote computing devices (i.e., scheduling server computing devices) to reduce the impact of weather conditions on passengers, thereby improving the overall passenger experience.

[0018] To do this, vehicle and / or server computing devices can be able to access information about current or predicted weather conditions. In some examples, onboard sensors can be used and this information shared with other vehicle and / or server computing devices to determine current weather conditions. For example, windshield wiper operation and speed, wheel slip detection, and LIDAR, radar, cameras, and other sensors can all be used to detect current weather conditions (e.g., precipitation, solar glare, etc.). Additionally or alternatively, current and predicted weather conditions can be retrieved from a third-party weather source that can provide information such as precipitation rate, solar glare angle, slippery road conditions, temperature, puddle conditions, etc.

[0019] The vehicle's server computing equipment and / or route system can periodically determine the first route to the vehicle's current destination. This destination can be a passenger's pick-up or drop-off point. The first route can be the optimal route determined using a cost function that calculates the cost of traveling from the vehicle's current location to the destination.

[0020] The server computing device and / or route system or other system of the vehicle can determine whether the destination, at the current time or the expected time of arrival when the vehicle is following the determined route, meets any weather condition thresholds. For example, any weather conditions along the route can be compared to one or more thresholds. If the thresholds are met, the server computing device and / or route system or other system of the vehicle can then search for new nearby destinations. The search can be based on the type of weather condition that meets the thresholds.

[0021] The server computing device and / or route system can then determine a second route to the new destination. This second route can be determined in a manner similar to the first route described above. The total cost of the second route can be compared to the total cost of the first route. If the difference is less than a first threshold (e.g., a small difference), the server computing device and / or route system can automatically steer the vehicle along the second route to the new destination. If the difference is greater than a second threshold (e.g., a moderate difference), the server computing device and / or route system can cause a notification to be displayed to the passenger at the vehicle and / or at the passenger's client computing device, offering the passenger the option to choose either the first or second route. The passenger may then be able to provide input at the vehicle or client computing device to select one of the routes and / or destinations. In response to the selection, the server computing device and / or route system can cause the vehicle to specify its own route using the selected route and / or destination.

[0022] The features described in this article can provide an improved user experience for transportation services provided by autonomous vehicles. For example, by utilizing certain weather information, this can be used to select better pick-up or drop-off points, which can greatly please customers and give them more confidence in the advanced capabilities of the transportation service. For instance, the experience of picking up or dropping off passengers or goods can be improved by avoiding or reducing the impact of certain weather conditions, such as precipitation, sun glare, slippery roads, fog, habu sandstorms, temperature, puddle conditions, etc.

[0023] Example System

[0024] like Figure 1 As shown, a vehicle 100 according to one aspect of this disclosure includes various components. While certain aspects of this disclosure are particularly useful for certain types of vehicles, a vehicle can be any type of vehicle, including but not limited to automobiles, trucks, motorcycles, buses, SUVs, etc. The vehicle may have one or more computing devices, such as a computing device 110 containing one or more processors 120, memory 130, and other components typically found in general-purpose computing devices.

[0025] Memory 130 stores information accessible by one or more processors 120, including instructions 134 and data 132 that can be executed or otherwise used by the processors 120. Memory 130 can be any type capable of storing information accessible by a processor, including computing device readable media, or other media that store data readable by means of electronic devices, such as hard disks, memory cards, ROM, RAM, DVDs or other optical discs, and other writable and read-only memories. Systems and methods can include different combinations of the foregoing, thereby storing different portions of instructions and data on different types of media.

[0026] Instruction 134 can be any set of instructions intended to be executed directly by the processor (such as machine code) or indirectly (such as a script). For example, instructions can be stored as computing device code on a computing device-readable medium. In this regard, the terms "instruction" and "program" are used interchangeably herein. Instructions can be stored in object code format for direct processor processing or in any other computing device language, including scripts or sets of independent source code modules that are interpreted on demand or pre-compiled. The function, methods, and routines of instructions are explained in more detail below.

[0027] Data 132 can be retrieved, stored, or modified by processor 120 according to instructions 134. For example, although the claimed subject matter is not limited to any particular data structure, the data can be stored in a computing device register, as a table with multiple different fields and records, an XML document, or a flat file in a relational database. The data can also be formatted in any computing device-readable format.

[0028] One or more processors 120 can be any conventional processor, such as a commercially available CPU or GPU. Alternatively, one or more processors can be special-purpose devices, such as ASICs or other hardware-based processors. Although Figure 1 Functionally, the processor, memory, and other components of computing device 110 are illustrated as being located within the same block; however, those skilled in the art will understand that a processor, computing device, or memory may actually include multiple processors, computing devices, or memories that may or may not be stored in the same physical housing. For example, memory may be a hard disk drive or other storage medium located in a different housing than that of computing device 110. Therefore, references to processors or computing devices will be understood to include references to a class of processors or computing devices or memories that may or may not operate in parallel.

[0029] The computing device 110 may include all components typically used in conjunction with a computing device (such as the processor and memory described above, and user input 150 (e.g., mouse, keyboard, touchscreen, and / or microphone), various electronic displays (e.g., monitors with screens or any other electrical devices operable to display information), and speakers 154 to provide information to passengers of the vehicle 100 as needed. For example, an in-cabin electronic display 152 may be located in the passenger compartment of the vehicle 100 and may be used by the computing device 110 to provide information to passengers within the vehicle 100.

[0030] The computing device 110 may also include one or more wireless network connections 156 to facilitate communication with other computing devices, such as client computing devices and server computing devices described in detail below. Wireless network connections may include: short-range communication protocols such as Bluetooth, Bluetooth Low Energy (LE), and cellular connections; and various configurations and protocols including the Internet, the World Wide Web, intranets, virtual private networks, wide area networks, local area networks, private networks using proprietary communication protocols of one or more companies, Ethernet, WiFi, and HTTP, as well as various combinations thereof.

[0031] The autonomous control system 176 may include various computing devices configured in a similar manner to the computing device 110, which are capable of communicating with various components of the vehicle to control the vehicle in autonomous driving mode. For example, refer back to the previous section. Figure 1 The autonomous control system 176 can communicate with various systems of the vehicle 100 (such as the deceleration system 160, acceleration system 162, steering system 164, route system 170, planning system 168, positioning system 172, and perception system 174) to control the movement and speed of the vehicle 100 according to the instructions 134 of the memory 130 in autonomous driving mode.

[0032] As an example, the computing device of the autonomous control system 176 can interact with the deceleration system 160 and the acceleration system 162 to control the speed of the vehicle. Similarly, the steering system 164 can be used by the autonomous control system 176 to control the direction of the vehicle 100. For example, if the vehicle 100 is configured for use on a road (such as a car or truck), the steering system may include components for controlling the angle of the wheels to steer the vehicle. The autonomous control system 176 may also use a signaling system to signal the vehicle's intention to other drivers or vehicles, for example, by illuminating turn signals or brake lights when needed.

[0033] Route system 170 can be used by autonomous control system 176 to generate routes to destinations. Planning system 168 can be used by computing device 110 to follow routes. In this respect, planning system 168 and / or route system 170 can store detailed map information, such as highly detailed maps identifying road networks, including road shapes and heights, lane lines, intersections, pedestrian crossings, speed limits, traffic signals, buildings, signs, real-time traffic information, parking spots, vegetation, or other such objects and information.

[0034] Figure 2A and Figure 2B This is an example of map information 200 for road segments including intersections 202, 203, 204, 205, and 206. Figure 2AA portion of map information 200 is depicted, which includes information identifying the shape, location, and other characteristics of the following: lane markings or lane lines 210, 212, 214, 216, 218; lanes 220, 221, 222, 223, 224, 225, 226, 228; traffic control equipment including traffic lights 230, 232, 234; and stop sign 236. Figure 2B (Not depicted for clarity) Stop lines 240, 242, 244, and non-drivable area 280. In this example, lane 221 approaching intersection 204 is a dedicated left-turn lane, lane 222 approaching intersection 206 is a dedicated left-turn lane, and lane 226 is a one-way street where traffic direction shifts away from intersection 204. In addition to the features described above, the map information may also include information identifying the traffic direction of each lane and information that allows the computing device 110 to determine whether a vehicle has the right-of-way to perform a specific maneuver (i.e., to turn or cross a traffic lane or intersection).

[0035] Although map information is described herein as image-based maps, it does not necessarily have to be entirely image-based (e.g., raster). For example, map information may include one or more road maps, graph networks, or road networks containing information such as roads, lanes, intersections, and connections between these features that can be represented by road segments. Each feature in the map may also be stored as graph data and may be associated with information such as geographic locations and whether they are linked to other related features; for example, a stop sign may be linked to roads and intersections. In some examples, the associated data may include a grid-based index of the road network to allow for efficient lookup of certain road network features.

[0036] In this regard, in addition to the aforementioned physical characteristics, map information may include multiple graph nodes and edges representing road or lane segments, which together constitute the road network of the map information. Each edge is defined by a starting graph node with a specific geographical location (e.g., latitude, longitude, altitude, etc.), an ending graph node with a specific geographical location (e.g., latitude, longitude, altitude, etc.), and a direction. This direction may refer to the direction that vehicle 100 must move to follow the edge (i.e., the direction of traffic flow). Graph nodes may be located at fixed or variable distances. For example, the spacing between graph nodes may range from a few centimeters to a few meters and may correspond to the speed limit of the road where the graph node is located. In this respect, a greater speed may correspond to a greater distance between graph nodes.

[0037] For example, Figure 2B The map was drawn with multiple edges represented by arrows and graph nodes (depicted as circles) corresponding to the road network of map information 200. Figure 2AMost of the map information is shown. Although many edges and graph nodes are depicted, only a few are referenced for clarity and simplicity. For example, Figure 2B This includes edges 270, 272, and 274 arranged between the start and end graph nodes 260, 262, 264, and 266. It can be seen that graph node 260 represents the start point of edge 270, while graph node 262 represents the end point of edge 270. Similarly, graph node 262 represents the start point of edge 272, while graph node 264 represents the end point of edge 272. Furthermore, graph node 266 represents the start point of edge 274, while graph node 268 represents the end point of edge 274. Likewise, the direction of each of these graph nodes is indicated by the arrow of the edge. Edge 270 can represent a path that a vehicle can follow to change from lane 220 to lane 221, edge 272 can represent a path that a vehicle can follow within lane 220, and edge 274 can represent a path that a vehicle can follow to turn left at intersection 203 to move from lane 221 to lane 226. Although not shown, each of these edges can be associated with an identifier (e.g., a numerical value corresponding to the relative or actual location of the edge, or simply to the location of the start and end graph nodes). In this respect, edges and graph nodes can be used to determine how to define and plan routes and trajectories between locations, change lanes, and perform other maneuvers, but during operation, vehicle 100 does not need to precisely follow the nodes and edges.

[0038] Route system 170 can use a road map to determine a route from the current location (e.g., the location of the current node) to a destination. Routes can be generated using cost-based analysis that attempts to select the route to the destination at the lowest cost. Costs can be evaluated in any number of ways, such as time to reach the destination, distance traveled (each edge can be associated with a cost to traverse that edge), type of maneuver required, convenience for passengers or vehicles, etc. Each route can include a list of multiple nodes and edges that a vehicle can use to reach the destination. Routes can be recalculated periodically as the vehicle travels to the destination.

[0039] Positioning system 172 can be used by autonomous control system 176 to determine the relative or absolute location of the vehicle on a map or on the Earth. For example, positioning system 172 may include a GPS receiver to determine the latitude, longitude, and / or altitude of the device. Other positioning systems (such as laser-based positioning systems, inertial-assisted GPS, or camera-based positioning) may also be used to identify the vehicle's location. The vehicle's location may include: absolute geographic location, such as latitude, longitude, and altitude, the location of a node or edge on a road map; and relative location information, such as the location relative to other vehicles in the immediate vicinity of the vehicle, which can often be determined with less noise than an absolute geographic location.

[0040] The positioning system 172 may also include other devices (such as accelerometers, gyroscopes, or other orientation / velocity detection devices) that communicate with the autonomous control system 176 of the computing device to determine the vehicle's orientation and speed, or changes thereof. By way of example only, an accelerometer may determine its pitch, yaw, or roll (or changes thereof) relative to the direction of gravity or a plane perpendicular to it. The device may also track increases or decreases in speed and the direction of such changes. Location and orientation data as described herein may be automatically provided to the computing device 110, other computing devices, and combinations thereof.

[0041] The perception system 174 also includes one or more components for detecting objects outside the vehicle, such as other vehicles, obstacles in the road, traffic signals, signs, trees, etc. For example, the perception system 174 may include lasers, sonar, radar, cameras, and / or any other detection devices that record data that can be processed by the computing device of the autonomous control system 176. In the case of a passenger vehicle (such as a minivan), the minivan may include lasers or other sensors mounted on the roof or in other convenient locations. For example, Figure 3 This is an example exterior view of vehicle 100. In this example, the roof housing 310 and the dome light housing 312 may include LIDAR sensors as well as various cameras and radar units. Furthermore, housing 320 located at the front of vehicle 100 and housings 330 and 332 located on the driver's and passenger's sides of the vehicle may respectively store LIDAR sensors. For example, housing 330 is located in front of the driver's door 360. Vehicle 100 also includes housings 340 and 342 for radar units and / or cameras, also located on the roof of vehicle 100. Additional radar units and cameras (not shown) may be located at the front and rear of vehicle 100 and / or at other locations along the roof or roof housing 310.

[0042] The autonomous control system 176 may be able to communicate with various components of the vehicle to control the movement of the vehicle 100 according to the main vehicle control code stored in the memory of the autonomous control system 176. For example, return to reference Figure 1 The autonomous control system 176 may include various computing devices that communicate with various systems of the vehicle 100 (such as deceleration system 160, acceleration system 162, steering system 164, planning system 168, route system 170, positioning system 172, sensing system 174, and power system 178 (i.e., the vehicle's engine or motor)) in order to control the movement, speed, etc. of the vehicle 100 according to instructions 134 in the memory 130.

[0043] Various vehicle systems can be operated using autonomous vehicle control software to determine how to control the vehicle. As an example, the perception system software module of perception system 174 can use sensor data generated by one or more sensors of the autonomous vehicle (such as cameras, LiDAR sensors, radar units, sonar units, etc.) to detect and identify objects and their characteristics. These characteristics can include location, type, heading, orientation, speed, acceleration, changes in acceleration, size, shape, etc. In some cases, characteristics can be input into a behavior prediction system software module, which uses various behavior models based on object type to output predicted future behavior of the detected object. In other cases, characteristics can be placed into one or more detection system software modules (such as a traffic light detection system software module configured to detect the state of a known traffic signal, a construction zone detection system software module configured to detect a construction zone based on sensor data generated by one or more sensors of the vehicle, and an emergency vehicle detection system configured to detect an emergency vehicle based on sensor data generated by the vehicle's sensors). Each of these detection system software modules can use various models to output the probability of a construction zone or an object being an emergency vehicle. The detected objects, predicted future behavior, various possibilities from the detection system software module, map information of the vehicle's environment, location and orientation information of the identified vehicle from the positioning system 172, the vehicle's destination location or node, and feedback from various other systems of the vehicle can be input into the planning system software module of the planning system 168. The planning system 168 can use this input to generate a trajectory that the vehicle will follow over a short period of time in the future, based on a route generated by the route module of the route system 170. In this regard, the trajectory can define characteristics such as acceleration, deceleration, and speed to allow the vehicle to follow the route to its destination. The control system software module of the autonomous control system 176 can be configured to control the vehicle's movement, for example, by controlling the vehicle's braking, acceleration, and steering, in order to follow the trajectory.

[0044] The autonomous control system 176 can control the vehicle in autonomous driving mode by controlling various components. For example, as an example, the autonomous control system 176 can autonomously navigate the vehicle to a destination location using detailed map information and data from the planning system 168. The autonomous control system 176 can use the positioning system 172 to determine the vehicle's location and use the perception system 174 to detect objects and respond to them when necessary to safely reach the location. Furthermore, to do this, the computing device 110 and / or the planning system 168 can generate trajectories and guide the vehicle along these trajectories, for example, by accelerating the vehicle (e.g., by supplying fuel or other energy to the engine or power system 178 by the acceleration system 162), decelerating (e.g., by reducing the fuel supplied to the engine or power system 178, changing gears, and / or by applying braking by the deceleration system 160), changing direction (e.g., by steering the front or rear wheels of the vehicle 100 by the steering system 164), and signaling such changes (e.g., by illuminating the turn signals). Therefore, the acceleration system 162 and the deceleration system 160 can be part of a powertrain system that includes various components between the vehicle's engine and the vehicle's wheels. Furthermore, by controlling these systems, the autonomous control system 176 can also control the vehicle's powertrain system to autonomously maneuver the vehicle.

[0045] The computing device 110 of vehicle 100 can also receive information from or transmit information to other computing devices, such as those computing devices that are part of the transportation service and other computing devices. Figure 4 and Figure 5 These are schematic and functional diagrams of an example system 400, which includes multiple computing devices 410, 420, 430, and 440 connected via a network 460, as well as a storage system 450. System 400 also includes vehicle 100 and vehicle 100A, which can be configured in the same or similar manner as vehicle 100. Although only a few vehicles and computing devices are depicted for simplicity, a typical system may include significantly more vehicles and computing devices.

[0046] like Figure 5 As shown, each of computing devices 410, 420, 430, and 440 may include one or more processors, memory, data, and instructions. Such processors, memory, data, and instructions may be configured in a similar manner to one or more processors 120, memory 130, data 132, and instructions 134 of computing device 110.

[0047] Network 460 and intervention map nodes can include a variety of configurations and protocols, including short-range communication protocols (such as Bluetooth, Bluetooth LE), the Internet, the World Wide Web, intranets, virtual private networks, wide area networks, local area networks, private networks using proprietary communication protocols of one or more companies, Ethernet, WiFi, and HTTP, as well as various combinations thereof. This communication can be facilitated by any device capable of transmitting data to and from other computing devices (such as modems and wireless interfaces).

[0048] In one example, one or more computing devices 410 may include one or more server computing devices having multiple computing devices (e.g., a load balancing server cluster) that exchange information with different nodes in the network for receiving, processing, and transmitting data to and from other computing devices. For example, one or more computing devices 410 may include one or more server computing devices capable of communicating via network 460 with computing device 110 of vehicle 100 or similar computing devices of vehicle 100A, as well as computing devices 420, 430, and 440. For example, vehicles 100 and 100A may be part of a fleet of vehicles that can be dispatched to various locations by the server computing devices. In this respect, server computing device 410 may act as a dispatch server computing system that can be used to assign passengers to vehicles (such as vehicle 100 and vehicle 100A) and dispatch these vehicles to different locations for passenger transport. Furthermore, server computing device 410 can use network 460 to transmit and present information to users and / or assigned passengers (such as users 422, 432, 442) on displays (such as displays 424, 434, 444 of computing devices 420, 430, 440 and / or display 152 of vehicles 100, 100A). In this respect, computing devices 420, 430, 440 can be considered as client computing devices.

[0049] like Figure 5As shown, each client computing device 420, 430, 440 may be a personal computing device intended for use by users 422, 432, 442, and has all the components typically used in conjunction with a personal computing device, including one or more processors (e.g., a central processing unit (CPU)), memory for storing data and instructions (e.g., RAM and internal hard disk drives), displays such as displays 424, 434, 444 (e.g., a monitor with a screen, a touchscreen, a projector, a television, or other devices operable to display information), and user input devices 426, 436, 446 (e.g., a mouse, keyboard, touchscreen, or microphone). The client computing device may also include a camera for recording video streams, speakers, network interface devices, and all components for connecting these elements to each other.

[0050] While client computing devices 420, 430, and 440 may each comprise a full-size personal computing device, they may alternatively comprise a mobile computing device capable of wirelessly exchanging data with a server via a network (such as the Internet). By way of example only, client computing device 420 may be a mobile phone or device such as a wireless-enabled PDA, tablet PC, wearable computing device or system, or a netbook capable of accessing information via the Internet or other networks. In another example, client computing device 430 may be as shown in... Figure 4 The watch shown is a wearable computing system. As an example, users can input information using a keypad, keyboard, microphone, visual signals with a camera, or touchscreen.

[0051] In some examples, the client computing device 420 may be a mobile phone used by a passenger of the vehicle. In other words, in some cases, user 422 may represent a passenger assigned to vehicle 100. Furthermore, the client communication device 430 may represent a smartwatch belonging to a passenger of the vehicle. In other words, in other cases, user 432 may represent a passenger assigned to vehicle 100. The client communication device 440 may represent a workstation of an operator (e.g., a remote assistance operator or someone who can provide remote assistance to the vehicle and / or passengers). In other words, user 442 may represent a remote assistance operator. Although in Figure 4 and Figure 5 Only a few passengers and operators are shown in the image, but a typical system could include any number of such passengers and remote assistance operators (and their corresponding client computing devices).

[0052] Like memory 130, storage system 450 can be any type of computerized storage device capable of storing information accessible by server computing device 410, such as hard disk drives, memory cards, ROM, RAM, DVDs, CD-ROMs, writable memory, and read-only memory. Furthermore, storage system 450 can include a distributed storage system in which data is stored on multiple different storage devices, which may be physically located in the same or different geographical locations. Figure 4 and Figure 5 The network 460 shown is connected to a computing device and / or can be directly connected to or incorporated into any of the computing devices 110, 410, 420, 430, 440, etc.

[0053] Example Method

[0054] In addition to the operations described above and illustrated in the figures, various other operations will now be described. It should be understood that the following operations need not be performed in the exact order described below. Instead, various steps can be processed in different orders or simultaneously, and steps can be added or omitted.

[0055] In one aspect, a user can download an application for requesting a vehicle to a client computing device. For example, users 422 and 432 can download the application to client computing devices 420 and 430 via a link in an email, directly from a website, or an app store. For example, the client computing device can transmit a request for the application over a network to, for example, one or more server computing devices 110, and receive the application in response. The application can be installed locally on the client computing device.

[0056] Users can then use their client computing devices to access the application and request vehicles. As an example, a user (such as user 432) can use client computing device 430 to send a request to one or more server computing devices 110 of the vehicle. As part of this, the user can identify the pick-up location, destination location, and drop-off location. In this respect, the drop-off location can be a location physically different from the destination location.

[0057] Users or passengers can specify pick-up, intermediate, and final destination locations in various ways. As an example, the pick-up location can default to the passenger's current location on their client computing device, but it can also be a nearby or saved location near the current location associated with the passenger's account. Passengers can enter addresses or other location information, tap locations on a map, or select locations from a list to identify pick-up and / or destination locations. For example, client computing device 420 can send its current location (such as a GPS location) to one or more server computing devices 110 via network 460 and / or the destination name or address of any intermediate or final destination. In response, server computing device 410 can provide one or more suggested locations, or can identify the current location as the pick-up location and the location corresponding to the destination name or address as an intermediate or final destination for the vehicle. After the user (now the passenger) has selected or confirmed the pick-up and destination locations, the server computing device can assign a vehicle (such as vehicle 100) to the passenger and the passenger's trip, and send dispatch instructions to the vehicle including the pick-up location, intermediate destination, and final destination. This allows the vehicle to control itself in autonomous driving mode, for example, by using various vehicle systems as described above, to complete the trip. Although the examples in this article involve transporting passengers, similar features can be used for transporting goods or cargo.

[0058] Figure 9 An example flowchart 900 for providing transportation services for autonomous vehicles is provided, which can be executed by one or more processors of one or more computing devices (such as processor 120 of computing device 110 and processors of route system 170 or server computing device 410). For example, in block 910, a first route to a first destination is determined. This first route has a first cost. For example, the server computing device 410 and / or route system of the vehicle may periodically determine the first route to the vehicle's current destination. This destination may be a passenger's pick-up or drop-off point, or even an intermediate destination (e.g., at which the passenger may temporarily leave the vehicle, return to the vehicle, and then continue to the destination and / or another intermediate destination).

[0059] As described above, the first route can be the optimal route determined using a cost function that calculates the cost of traveling from the vehicle's current location to its destination. For example, the first route can be selected from multiple possible routes by performing a graph search on map information including multiple nodes connected by edges. Each node can have an associated cost such that the first route is the route with the lowest total cost. This total cost can include, for example, the sum of all costs of the route's nodes and / or edges. The total cost can also be a proxy for the route's total travel time. Furthermore, an estimated arrival time for the vehicle to reach its destination using the first route can be determined.

[0060] Figure 6 An example of a first route 610 leading to a first destination 620 is provided relative to map information 200. For example, vehicle 100 may autonomously follow the first route 610 to reach the first destination 620 using various vehicle systems as described above. In this example, the first destination may be the pick-up or drop-off destination of a passenger (such as user 442 or 443). The first route 610 may be associated with a first cost "X", which, as mentioned above, may be the sum of all nodes and / or edges along the first route.

[0061] Return to reference Figure 9 In box 920, weather information for the first destination is received. For example, the computing device 110 of vehicle 100 and / or the server computing device 410 may be able to access information about current or predicted weather conditions. In some examples, onboard sensors and sharing this information with other vehicles (e.g., from vehicle 100 to vehicle 100A and vice versa) and / or the server computing device 410 may be used to determine current weather conditions. For example, the operation and speed of windshield wipers, the activation of headlights, temperature sensors, anemometer data or data from other sensors, wheel slip detection, and LIDAR, radar, cameras, and other sensors may be used to detect current weather conditions (e.g., precipitation, solar glare, etc.). Additionally or alternatively, current and predicted weather conditions may be retrieved from a third-party weather source that can provide information such as precipitation rate, solar glare angle, slippery road conditions, fog, hab sandstorms, temperature, puddle conditions, etc.

[0062] For example, return to reference Figure 6 Examples, such as Figure 6The ambient temperature at the location of the first destination 620 and / or the area of ​​map information 200 depicted may be quite high, such as 100 degrees or higher or lower, or alternatively. Alternatively, a high precipitation rate may exist at the location of the first destination 620 and / or the area of ​​map information 200. As described above, this weather information (e.g., temperature or precipitation rate) may be received by the vehicle's computing device 110 and / or the server computing device 410 of other vehicles in the fleet (e.g., vehicle 100A) and / or from a third-party source.

[0063] Return to reference Figure 9 In box 930, characteristics are determined based on weather information. Server computing device 410 and / or route system 170 or some other system of vehicle 100 can determine whether the destination currently, or at the expected time of arrival of the vehicle while following the determined route, meets any weather condition thresholds. As further discussed below, each of these one or more thresholds can be associated with a set of one or more characteristics that can be used to perform a search for a second destination. In this regard, a set of one or more characteristics associated with any threshold satisfied by weather information can be identified.

[0064] For example, any weather conditions along the route and / or at the first destination can be compared to one or more thresholds. For instance, if the weather conditions at the destination indicate a specific temperature, that temperature can be compared to one or more temperature thresholds. Similarly, if the weather conditions at the destination indicate a specific precipitation rate, that precipitation rate can be compared to one or more precipitation rate thresholds. As another example, the sun's azimuth and altitude can be used to calculate the sun's position relative to the vehicle. Using this, it can be determined which area of ​​the vehicle will be illuminated by sunlight when the vehicle arrives at its destination, or the angle at which sunlight will actually illuminate the vehicle. For example, if the horizon is zero degrees, the threshold will attempt to capture the area that will produce light at the vehicle door (where passengers can exit), such as approximately 15 to 20 degrees or more or less, depending on the altitude within that range, where the light might be dazzling or annoying to passengers. For example, at an angle of approximately 120 degrees, passengers could actually be in the vehicle's shadow. Even if the vehicle can perceive further, a human-perceived visibility threshold of at least x meters can be used, such as 20 meters or more or less. For wind conditions, a threshold of gusts not exceeding 40 mph is used, such as 20 mph or higher or lower, which can be combined with direction. In this regard, a higher threshold can be used if the vehicle is located between gust sources on the side where passengers are likely to leave the vehicle. For hab sandstorms (wind and dust storms), a threshold combining visibility and wind condition thresholds can be used. Similarly, for wind chill conditions, a threshold combining minimum temperature and maximum wind speed can be used. Other thresholds can be used for slippery road conditions (e.g., whether it is icy, wet, water film thickness, or other conditions that could cause vehicle wheels to slip), puddles (e.g., threshold puddle size), and other weather conditions identified in the received weather information.

[0065] In some cases, different thresholds can be applied to different types of vehicles. For example, for safety reasons, a towing trailer can be associated with a threshold precipitation rate lower than that of a smaller passenger car. This may be because larger towing trailers are generally heavier than smaller passenger cars and may be more prone to losing control in less rain, snow, or other conditions.

[0066] For example, return to reference Figure 6For example, if the received weather information indicates that the ambient temperature at location 620, the first destination, is 100 degrees Celsius, this can be compared to a high-temperature threshold. If the high-temperature threshold is 80 degrees Celsius, then the temperature threshold will be met. Alternatively, if the received weather information indicates a precipitation rate, this can be compared to a precipitation rate threshold, such as 5 millimeters or more or less per hour of rainfall. If the precipitation rate is greater than the precipitation rate threshold, then the threshold will be met. Each of the high-temperature threshold and the precipitation rate threshold can be associated with a corresponding set of characteristics. In this respect, in each example, the comparison can be used to identify the associated set of characteristics.

[0067] Return to reference Figure 9In box 940, a second destination with certain characteristics is selected. This second destination differs from the first destination. If a threshold is met, the server computing device 410 and / or the route system 170 or some other system of the vehicle can search for new nearby destinations that have one or more characteristics from a set of one or more characteristics associated with the met threshold. Furthermore, this new or second destination may differ from the first destination. For example, a high temperature or high precipitation rate threshold may be associated with a set of characteristics including features such as awnings, overhangs, trees or other vegetation, locations where passengers can quickly enter or reach the vehicle from the building, etc. In this regard, if the temperature or precipitation rate is too high (or more precisely, the high temperature or high precipitation rate threshold is met), the search may include finding one or more nearby locations in the map information that have certain characteristics, such as awnings, overhangs, trees or other vegetation, locations where passengers can quickly enter or reach the vehicle from the building, etc. Furthermore, if precipitation is excessively high, the search may include finding nearby locations where vehicles can wait longer to allow passengers to "wait" for several minutes to see if the rain will subside before entering or leaving the vehicle. For wind conditions, wind chill conditions, and hab sandstorm conditions, the search may involve finding one or more nearby locations in map information where vehicles can position themselves to allow passengers to enter and exit the vehicle on the side away from the wind source (i.e., opposite to the wind direction), allowing the vehicle to "protect" passengers from wind and / or dust. If temperatures are excessively low, the search may find locations closer to building entrances. For solar angles, the search may find nearby locations where vehicles will be positioned to avoid solar glare, and / or designated parking spots away from roads (e.g., in parking lots) to avoid other passing vehicles that may not see passengers entering or leaving the vehicle, and vice versa. Similarly, for slippery roads and fog, a search can locate a vehicle in a designated parking spot away from the road (e.g., in a parking lot) to avoid other passing vehicles that might not see passengers entering or leaving the vehicle, and vice versa. As another example, for puddles, if known from weather information, a search can find locations where the puddle is unlikely to be located at or just beyond the puddle's boundary.

[0068] For example, turning Figure 7 A search based on a set of characteristics associated with a high temperature threshold or a precipitation rate threshold can identify a second destination 720, which has characteristics such as awnings, overhangs, trees or other vegetation, locations where passengers can quickly enter or reach vehicles from a building, etc. As mentioned above, each of these features can be incorporated into the map information to enable the search.

[0069] Return to reference Figure 7 An example of a second route 710 to a second destination 720 is provided relative to map information 200. In this regard, server computing device 410 and / or route system 170 can determine the second route 710 from the current location of vehicle 100 to the second destination by selecting the route with the lowest cost as described above. In this example, vehicle 100 can autonomously follow the second route 710 to reach the second destination 720 using various vehicle systems as described above. In this example, like the first destination, the second destination can be the pick-up or drop-off destination of passengers (such as users 442 or 443).

[0070] Return to reference Figure 9 In box 950, a second route to the second destination is determined. This second route has a second cost. For example, server computing device 410 and / or route system 170 can then determine the second route to the new destination. This second route can be determined in a similar manner to the first route as discussed above. (See reference...) Figure 7 For example, the second route 710 can be associated with a second cost "Y", as mentioned above, which can be the sum of all nodes and / or edges along the second route.

[0071] Return to reference Figure 9 In box 960, a first cost is compared with a second cost. In box 970, a comparison is used to set either the first or second destination as the vehicle's current destination, allowing the vehicle to control its own path to the current destination in autonomous driving mode. For example, the total cost of the second route can be compared with the total cost of the first route. For example, the first cost X can be compared with the second cost Y. If the difference (or the value of Y minus X) is less than a first threshold (e.g., a smaller difference), then the server computing device and / or the route system can automatically steer the vehicle along the second route to the new destination. For example, the new destination can be set as the vehicle's current destination. Furthermore, the vehicle can display a notification to the passenger, and / or send a notification to the passenger's client computing device, informing the passenger of the change in destination and the reason for the change (i.e., it's hot, so we think it's better for you to get off in the shade). In this way, the vehicle can seamlessly reroute to the new destination, thereby improving the passenger experience.

[0072] If the difference is greater than a second threshold (e.g., a moderate difference), then the server computing device and / or the route system can cause a notification to be displayed to the passenger at the vehicle and / or at the passenger's client computing device, requesting the passenger to select a first or second destination (e.g., by providing the passenger with the option to select a first or second destination). By doing so, the passenger can also effectively select a first or second route for the vehicle.

[0073] Figure 8A and Figure 8B This example visualization represents the notification 840 of the assigned passengers and destination options displayed to the vehicle 100 on the display 424 of the client computing device 420. Of course, this visualization could, for example, be displayed to the user 422, 432 on the vehicle's display 152 and / or on the displays 424, 434 of the client computing devices 420, 430. Figure 8A and Figure 8B As depicted, some details about each destination can be provided for the destination options, including a map visualization 810 and selection controls such as one or more radio buttons 820, 822 that identify each possible destination option (e.g., each of the first destination 620 and the second destination 720). The map visualization can be interactive, for example, providing zoom capabilities, toggling satellite views, or tapping map pins (such as map pins for the first destination 620 and the second destination 720) to change the selection of radio buttons 820, 822.

[0074] The notification may also include information about why this option is offered (here, due to the ability to provide shade for passengers at the second destination) and an explanation of any difference in the estimated arrival time of the vehicle at the second destination (here, an extra minute). The notification also provides a confirmation option 830 to enable confirmation for the first destination ( Figure 8A ) or second destination ( Figure 8BThe option to select a destination is provided. In this example, since the ambient temperature at the first destination is higher, both a first destination option and a second destination option are displayed. Furthermore, notification 840 provides walking direction 850 (which can be determined by server computing device 410 and / or route system 170) to guide the passenger from the second destination 720 to the first destination 620 and vice versa (depending on whether the first and second destinations are pick-up or drop-off points). In this way, when the difference between X and Y is large, one of the passenger or users 422, 432 can decide which option is most suitable for the passenger. The passenger can then be able to provide input at the vehicle, for example via user input 150, or at the passenger's client computing device (such as at client computing devices 420, 430), to select either the first or second destination. This input can cause a corresponding signal to be sent to and received by server computing device 410 and / or route system 170 or another system of the vehicle (e.g., computing device 110).

[0075] In response to a selection, the vehicle's server computing device 410 and / or route system 170, or another system of the vehicle (e.g., computing device 110), can cause the vehicle to define its own route using the selected route and / or destination. For example, if the above steps are performed at server computing device 410, then server computing device 410 can send signals including instructions to cause the vehicle to set the selected destination as its current destination, thereby enabling the vehicle to control its own path to the selected destination. These instructions may also include a second route (e.g., causing vehicle 100 to follow a second route) or may only allow the vehicle to determine the route to the second destination locally (e.g., using route system 170). Alternatively, if the above steps are performed locally at vehicle 100, then route system 170 can simply set the selected destination as the vehicle's current destination and proceed accordingly.

[0076] The initial value of the second threshold can be manually tuned or set to the "best" guess. The system can gather information that can be used to improve these guesses as the user interacts with it (or even without interaction, which is also a strong signal). For example, if the second threshold for a canopy at 100 degrees or higher is too low, passengers will accept the change 100% of the time. As a counterexample, if the second threshold for rainfall is too high, then in a downpour, passengers might be more willing to brave the rain to run to the front door rather than be trapped under a canopy located further away.

[0077] Notifications can also use weather information to provide passengers with additional information. For example, if the weather information indicates that it is currently raining heavily, then the notification described above, or other notifications or information displayed in the app, could provide additional details such as “It’s raining heavily now, but it should lighten up in 2 minutes,” “Visibility is low, so be careful when you’re temporarily out,” or other messages to let passengers know what will happen when they open the door. If passengers are waiting for a ride, the weather information can also be used to generate notifications or display information in the app, such as telling passengers to stay indoors and then suggesting the best time for passengers to try to reach the vehicle when the weather conditions (e.g., precipitation, fog, wind, etc.) improve or become better.

[0078] While the examples provided pertain to pick-up and drop-off points, the features described herein can also be applied to intermediate destinations where passengers can disembark and re-enter the vehicle after the time periods mentioned above. For example, trips with multiple stops can last for longer periods, meaning that predicted weather along a known set of routes will change over time. In this respect, routes to intermediate and final destinations can change over time due to variations in received weather information. This can be particularly useful for longer journeys, such as those for passengers or long-distance freight delivery.

[0079] In some cases, weather information can be used to add edges / nodes to map information (such as...). Figure 2B The cost of edges / nodes depicted in the map. For example, in areas with less heavy rain or cooler and less hot conditions, a vehicle's planning system will be more inclined to traverse nodes in the map information because these nodes can have lower weights. As another example, prolonged exposure of the vehicle system to environments exceeding 120 degrees Celsius should be avoided, so choosing routes that are generally cooler (such as in the shade of mountains or vegetation) will protect the system. Or, if an area is known to be wetter or has more puddles, the number of nodes and edges in these areas can be increased, so the vehicle can automatically plan its route to avoid such locations.

[0080] The features described in this article can provide an improved user experience for transportation services provided by autonomous vehicles. For example, by utilizing certain weather information, this can be used to select better pick-up or drop-off points, which can greatly please customers and give them more confidence in the advanced capabilities of the transportation service. For instance, the experience of picking up or dropping off passengers or goods can be improved by avoiding or reducing the impact of certain weather conditions, such as precipitation, sun glare, slippery roads, fog, habu sandstorms, temperature, puddle conditions, etc.

[0081] Unless otherwise stated, the foregoing alternative examples are not mutually exclusive, but can be implemented in various combinations to achieve unique advantages. Since these and other variations and combinations of the features discussed above can be utilized without departing from the subject matter defined by the claims, the foregoing description of the embodiments should be understood by way of illustration rather than by way of limitation of the subject matter defined by the claims. Furthermore, the examples described herein and the provision of phrases such as “such as,” “comprising,” etc., should not be construed as limiting the subject matter of the claims to the specific examples; rather, the examples are intended to illustrate only one of many possible embodiments. Further, the same reference numerals in different figures can identify the same or similar elements.

Claims

1. A method for providing transportation services using autonomous vehicles, the method comprising: One or more processors determine a first route to a first destination, the first route having a first cost from the vehicle's current location to the first destination; When the vehicle is traveling from the current location toward the first destination: The weather information for the first destination is received by the one or more processors; The characteristics are determined by the one or more processors based on the weather information, wherein the characteristics are configured to reduce the impact of weather conditions on passengers; The one or more processors select a second destination having the aforementioned characteristics, the second destination being different from the first destination; The one or more processors determine a second route to the second destination, the second route having a second cost from the vehicle's current location to the second destination; The difference between the first cost and the second cost is determined by the one or more processors; and The difference is compared with a threshold. The one or more processors display a notification to the passenger, the notification identifying information about why the second destination is provided; as well as Based on a comparison of the difference and the threshold, one of the first destination or the second destination is set as the vehicle's current destination, so that the vehicle controls itself to proceed to the current destination in autonomous driving mode; The method further includes: As the vehicle travels toward the current destination, the one or more processors select a third destination based on other weather information for the current destination, the third destination being different from the current destination.

2. The method according to claim 1, wherein the first destination is the passenger's drop-off location.

3. The method of claim 1, wherein the first destination is the passenger's boarding location.

4. The method of claim 1, wherein the one or more processors are one or more processors of one or more server computing devices, and setting one of the first destination or the second destination as the current destination of the vehicle further comprises: Send the first destination or the second destination to the vehicle so that the vehicle sets the first destination or the second destination as the vehicle's current destination.

5. The method of claim 1, wherein the one or more processors are one or more processors of the vehicle, and the method further comprises: Control the vehicle to travel to the current destination in autonomous driving mode.

6. The method according to claim 1, wherein the method further comprises: The weather information is compared with one or more thresholds; as well as The characteristic is determined by comparing the weather information with one or more thresholds.

7. The method according to claim 1, wherein, The characteristic is the physical feature of the second destination.

8. The method according to claim 7, wherein, The feature provides the passenger with protection from the weather conditions.

9. The method of claim 6, wherein the characteristic is associated with one of the one or more thresholds that is satisfied by the weather information.

10. The method of claim 1, further comprising: When the difference meets the threshold, the notification further requests the passenger to choose between the first destination and the second destination.

11. The method of claim 10, wherein the notification further identifies the weather conditions based on the weather information.

12. The method of claim 10, further comprising: A selection is received in response to the notification, wherein the received selection is used to set either the first destination or the second destination as the current destination of the vehicle.

13. The method of claim 1, wherein when the difference does not meet the threshold, the second destination is automatically set as the current destination of the vehicle.

14. The method according to claim 1, further comprising: when the difference is less than the threshold, automatically setting the second destination as the current destination.

15. The method according to claim 1, further comprising, before setting, when the difference is greater than the threshold: The difference is compared with a second threshold; and When the difference is greater than the second threshold, the notification further requests the passenger to choose between the first destination and the second destination.

16. The method according to claim 1, wherein: Select the second destination as the current destination, and The method further includes, when the vehicle is traveling toward the second destination: The one or more processors receive additional weather information for the second destination; The one or more processors determine another characteristic based on the other weather information, wherein the other characteristic is configured to reduce the impact of the weather conditions on the passengers; The third destination, which has the other characteristic, is selected by the one or more processors and is different from the second destination.

17. A system for providing transportation services using autonomous vehicles, the system comprising one or more processors configured to: Determine a first route to a first destination, the first route having a first cost from the vehicle's current location to the first destination; When the vehicle is traveling from the current location toward the first destination: Receive weather information for the first destination; The characteristics are determined based on the weather information, and the characteristics are configured to reduce the impact of weather conditions on passengers. Select a second destination that has the aforementioned characteristics, the second destination being different from the first destination; Determine a second route to the second destination, the second route having a second cost; Determine the difference between the first cost and the second cost; and The difference is compared with a threshold. A notification is displayed to the passenger, the notification identifying information about why the second destination is provided; as well as Based on the comparison between the difference and the threshold, one of the first destination or the second destination is set as the current destination of the vehicle, so that the vehicle controls itself to drive to the current destination in autonomous driving mode; The one or more processors are further configured to: As the vehicle travels toward the current destination, a third destination is selected based on other weather information for the current destination, and the third destination is different from the current destination.

18. The system of claim 17, wherein the one or more processors are further configured to: Compare the weather information with one or more thresholds; and The characteristic is determined by comparing the weather information with one or more thresholds.

19. The system of claim 18, wherein the characteristic is associated with one of the one or more thresholds that is satisfied by the weather information.

20. The system of claim 17, wherein when the difference satisfies the threshold, the notification further requests the passenger to choose between the first destination and the second destination.

21. The system of claim 17, further comprising the vehicle, wherein the processor is a processor of the vehicle.

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