Patent Publication Number: US-2021190518-A1

Title: Determining vehicle actions based upon astronomical data

Description:
Embodiments relate to determining actions for a vehicle based upon local astronomical data. 
     BACKGROUND 
     The operation design domain (“ODD”) of an autonomous or partially autonomous vehicle includes the operating conditions under which a given automated driving system (“ADS”) or feature thereof is designed to function. An ODD may include environmental, geographical, and time-of-day restrictions. Typically, an ADS is limited to operating in the ODD. Driving outside of the ODD is not safe and may, therefore, not be allowed or only be allowed for a limited amount of time before the autonomous vehicle must stop operating. 
     One aspect of an ODD is the current lighting conditions of the driving environment of the vehicle. If lighting conditions are poor, such as at night, during overcast or stormy weather, or other poor visibility conditions, vehicle sensors, such as cameras, may not be able to perceive the driving environment sufficiently enough to properly control the vehicle. 
     SUMMARY 
     Therefore, among other objects, one object of some embodiments is to predict when lighting conditions will change based upon local astronomical data. In one example, predicting when lighting conditions will change is based on or accomplished by predicting when the sun will set along a planned route of the vehicle. If the planned route cannot be completed before lighting conditions are outside of the ODD, other actions are taken in order to ensure safe operation of the vehicle. 
     One embodiment provides a system for determining an action for a vehicle. The system includes an electronic controller configured to determine a planned route of the vehicle, determine local astronomical data based upon the planned route, compare the local astronomical data to the planned route of the vehicle to determine a probability of completion of the planned route, and if the probability of completion is below a threshold, generate a command indicating an action for the vehicle. 
     Another embodiment provides a method for determining an action for a vehicle. The method includes determining, with an electronic controller, a planned route of the vehicle; and determining, with the electronic controller, local astronomical data based upon the planned route. The method also include comparing, with the electronic controller, the local astronomical data to the planned route of the vehicle to determine a probability of completion of the planned route; and if the probability of completion is below a threshold, generating, with the electronic controller, a command indicating an action for the vehicle. 
     These and other features, aspects, and advantages will be apparent from a reading of the following detailed description and a review of the associated drawings. It is to be understood that both the foregoing general description and the following detailed description are explanatory and do not restrict aspects as claimed. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  illustrates a vehicle equipped with an ADS according to one embodiment. 
         FIG. 2  illustrates an electronic controller according to one embodiment. 
         FIG. 3  illustrates a method for determining an action for a vehicle according to one embodiment. 
         FIG. 4  illustrates a planned route of a vehicle according to one embodiment. 
     
    
    
     DETAILED DESCRIPTION 
     One or more embodiments are described and illustrated in the following description and accompanying drawings. These embodiments are not limited to the specific details provided herein and may be modified in various ways. Furthermore, other embodiments may exist that are not described herein. Also, the functionality described herein as being performed by one component may be performed by multiple components in a distributed manner. Likewise, functionality performed by multiple components may be consolidated and performed by a single component. Similarly, a component described as performing particular functionality may also perform additional functionality not described herein. For example, a device or structure that is “configured” in a certain way is configured in at least that way, but may also be configured in ways that are not listed. Furthermore, some embodiments described herein may include one or more electronic processors configured to perform the described functionality by executing instructions stored in non-transitory, computer-readable medium. Similarly, embodiments described herein may be implemented as non-transitory, computer-readable medium storing instructions executable by one or more electronic processors to perform the described functionality. As used in the present application, “non-transitory computer-readable medium” comprises all computer-readable media but does not consist of a transitory, propagating signal. Accordingly, non-transitory computer-readable medium may include, for example, a hard disk, a CD-ROM, an optical storage device, a magnetic storage device, a ROM (Read Only Memory), a RAM (Random Access Memory), register memory, a processor cache, or any combination thereof. 
     In addition, the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting. For example, the use of “including,” “containing,” “comprising,” “having,” and variations thereof herein is meant to encompass the items listed thereafter and equivalents thereof as well as additional items. The terms “connected” and “coupled” are used broadly and encompass both direct and indirect connecting and coupling. Further, “connected” and “coupled” are not restricted to physical or mechanical connections or couplings and can include electrical connections or couplings, whether direct or indirect. In addition, electronic communications and notifications may be performed using wired connections, wireless connections, or a combination thereof and may be transmitted directly or through one or more intermediary devices over various types of networks, communication channels, and connections. Moreover, relational terms such as first and second, top and bottom, and the like may be used herein solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. 
       FIG. 1  illustrates a vehicle  100  equipped with an ADS  105  according to one embodiment. In the example, illustrated, the vehicle  100  is illustrated as an automobile having 4 wheels  110 - 113 . In other embodiments, the vehicle  100  may be a motorcycle, a tractor-trailer, a truck, or some other form of vehicle having different number of wheels. 
     The ADS  105  includes an electronic controller  115  communicatively coupled to other vehicle systems  120  and a plurality of sensors  125 . An example of the electronic controller  115  is illustrated in  FIG. 2 . The electronic controller  115  includes a communication interface  205 , an electronic processor  210 , and a memory  215 . The communication interface  205  allows the electronic processor  210  to communicate with external hardware, such as the vehicle systems  120  and the plurality of sensors  125 . The electronic processor  210  is communicatively coupled to the communication interface  205  and the memory  215 . The electronic processor  210  is configured to access the memory  215  and, among other things, execute instructions for the ADS  105 . The electronic processor  210  may be a microprocessor, an application-specific integrated circuit, or a similar processing circuit. The memory  215  is a non-transitory, computer-readable medium and contains instructions that, amongst other things, perform the methods and functions described herein when executed by the electronic processor  210 . 
     In one embodiment, the memory  215  includes vehicle navigation software  220 . Because the ADS  105  is automatically driving the vehicle  100 , the navigation software  220  allows the ADS  105  to select a route for the vehicle  100  for driving from a route origin to a route destination. The navigation software  220  may also include a digital map of the driving area of the vehicle  100  and may be in communication with a remote server to constantly update the digital map based upon the location of the vehicle  100 . The digital map may include road features, traffic information, construction information and other road closures, and other environmental features. By using the digital map, the navigation software  220  is able to determine potential routes from the route origin to the route destination and select a planned route based upon driving time for each potential route, traffic information, road closure information, and other factors, such as the safety of each route. 
     The navigation software  220 , through the remote server, may also access local astronomical data and weather data based upon the location of the vehicle  100 . For example, the navigation software  220  may access a sunrise time, a sunset time, a moonrise time, a moonset time, a sun angle, a phase of the moon, and other astronomical data. The navigation software  220  may also access weather data, such as possibility of precipitation, amount of current precipitation, an upcoming weather forecast, 
     Returning to  FIG. 1 , the vehicle systems  120  include, for example, steering systems, braking systems, propulsion systems, navigation systems, communication systems, lighting systems, and other systems that must be controlled by the ADS  105 . 
     The plurality of sensors  125  includes one or more sensors configured to gather data about the driving environment of the vehicle  100 . The plurality of sensors  125  may include one or more cameras, one or more radar sensors, one or more LIDAR sensors, one or more electro-optical sensors, one or more luminosity sensors, and other types of sensors for use in autonomous operation of the vehicle  100  by the ADS  105 . Each of the plurality of sensors  125  can be located on any portion of the vehicle  100 . 
     Some of the plurality of sensors  125  may be limited by environmental conditions. For example, during night operation of the vehicle  100  or during operation of the vehicle  100  during overcast periods of time (or other environments where lighting conditions are poor), cameras will not be able to gather accurate image data of the driving environment of the vehicle  100 . In another example, cameras, radar sensors, and LIDAR sensors may not gather accurate data during periods of time where precipitation, such as rain or snow, impairs data collection. Because these conditions make operation of the vehicle  100  by the ADS  105  unsafe, other actions must be taken in order to ensure the safety of passengers and the vehicle  100 . 
       FIG. 3  illustrates a method  300  for determining an action for the vehicle  100  according to one embodiment. The method  300  includes determining, with the electronic controller  115 , a planned route for the vehicle  100  (at block  305 ) and determining, with the electronic controller  115 , local astronomical data based upon the planned route (block  310 ). 
     For example,  FIG. 4  illustrates a planned route  405  for the vehicle  100 . The planned route  405  includes route portions  410  and  415  and ends at route destination  420 . The vehicle  100  may be at a route origin or may be in transit along the planned route  405  to the route destination  420 . Route portions  410  and  415  are meant for purely illustrative purposes. It is to be understood that the planned route  405  may include more or less route portions than the two illustrated route portions  410  and  415 . 
     When accessing local astronomical data, the electronic controller  115  may access the local astronomical data from a remote server for any portion of the planned route  405 , such as a current position of the vehicle  100 , route portions  410  or  415 , and the route destination  420 . For example, the electronic controller  115  may access a sunset time for the current position of the vehicle  100  or the route destination  420 , as at the sunset time particular sensors of the plurality of sensors  125  may no longer operate at full capacity, leading to more dangerous driving situations. 
     The electronic controller  115  may also access weather data from the remote server. In one example, the electronic controller  115  accesses weather data and determines the current weather status, for example, clear, overcast, precipitation, and others. Certain weather conditions, for example, overcast and precipitation, may hinder the ability of the plurality of sensors  125  to gather data. The accessed weather data includes, for example, a forecast, a weather radar map, and other data. 
     In one embodiment, the electronic controller  115  is also configured to determine a sun shadow  425  based upon local astronomical data, the weather data, or both. The sun shadow  425  indicates which areas are now past sunset or otherwise do not have sufficient lighting conditions or other environmental factors for the plurality of sensors  125  to accurately gather data, endangering the vehicle  100 . In  FIG. 4 , the sun shadow  425  is a sun shadow of a sunset, moving from east to west. In other embodiments, such as a sun shadow caused by incoming weather, the sun shadow  425  may move in other directions. The electronic controller  115  is configured to use the local astronomical data, the weather data, or both to determine how quickly the sun shadow  425  moves and when different areas are covered by the sun shadow  425 . In some embodiments, the electronic controller  115  is configured to determine astronomical data for multiple locations along the planned route  405 . 
     Returning to  FIG. 3 , the method  300  includes comparing, with the electronic controller  115 , the local astronomical data to the planned route to determine a probability of completion of the planned route (block  315 ). For example, the electronic controller  115  determines an estimated completion, or the time it takes to reach the route destination from the current location of the vehicle  100 , and compares that amount of time to a time when a sun shadow reaches a portion of the planned route, the current location of the vehicle  100 , or the route destination. The electronic controller  115  then determines the probability or likelihood that the planned route is completed before the sun shadow makes operation of the vehicle  100  unsafe. The probability may be determined as a binary value (“will complete” or “will not complete”) or may be some other value indicative of the probability that the planned route will be completed, such as a percentage indicating the chance of completion of the planned route. 
     In some embodiments, the probability of completion is determined using additional information, for example, traffic data. In one example, the electronic controller  115  is configured to determine current traffic data for the planned route and modify an expected completion time of the planned route based upon the amount of traffic along the planned route. The traffic data may include construction data, traffic congestion data, road closures, and other events that impact traffic along the planned route. In addition, the electronic controller  115  may utilize a model stored on the remote server to predict traffic data if current traffic data is not available. Based upon current and predicted traffic data, the electronic controller  115  modifies the expected completion time of the route. 
     Another possible data could include current lighting conditions gathered by the plurality of sensors  125 . For example, light sensors could detect a current illumination level surrounding the vehicle  100  and use this data in addition to sun shadow and traffic data in order to determine if the planned route will be completed. 
     The method  300  also includes comparing the probability of completion to a threshold (at block  320 ). The threshold may be manually set by a user, automatically determined by the electronic controller  115 , set on the remote server and accessed by the electronic controller  115 , or otherwise determined. For example, based on the local astronomical data, weather data, other data from the plurality of sensors  125 , the navigation software  220 , traffic data, and others, the electronic controller  115  may automatically determine the threshold using a suitable algorithm. 
     If the probability of completion is above the threshold, the ADS  105  controls the vehicle  100  to complete the planned route (at block  325 ). However, if the probability of completion is below the threshold, the ADS  105  generates a command to take an action for the vehicle  100  (at block  330 ). 
     In one example, the action for the vehicle  100  is not departing on the planned route. For example, if the current location of the vehicle  100  is a route origin of the planned route, the ADS  105  may generate a command instructing the vehicle  100  to not depart along the planned route and instead stay parked at the route origin until lighting conditions or other environmental conditions are deemed to fall within parameters of the ODD of the vehicle  100 . So, for example, the vehicle might remain at its current position until sunrise the next day or after overcast weather has passed. 
     The action for the vehicle  100  may include generating a command to navigate the vehicle  100  to a known safe harbor location instead of navigating the vehicle  100  to the route destination. The safe harbor location may be along the planned route or in a location different than the planned route that is closer to the current location of the vehicle  100  than the route destination. Known safe harbors may be identified in the navigation software  220  or may be determined by the electronic controller  115  by accessing the remote server. Once the vehicle  100  reaches the safe harbor, the ADS  105  generates a command to park the vehicle  100  at the safe harbor until conditions are again within parameters of the ODD. 
     Another possible action for the vehicle  100  is stopping the vehicle at its current location. If the route destination and a safe harbor location are not reachable before the lighting conditions or other environmental conditions, the ADS  105  is configured to end driving along the planned route and instead stop the vehicle  100  at the current location. 
     In some embodiments, data from the plurality of sensors  125  may be used by the electronic controller  115  to determine a safe spot or area for the vehicle  100  to park at the current location. For example, after generating the command to stop the vehicle  100  at the current location, the electronic controller  115  receives video from the plurality of sensors  125  and identifies a safe spot for parking, such as a parking space, a parking lot, a driveway, or other place away from driving lanes, traffic, and pedestrians. 
     If the action for the vehicle  100  is stopping at the current location, the electronic controller  115  may be further configured to send a message to a remote location indicating that the vehicle  100  needs to be retrieved by a human operator, such as a driver or a tow truck. For example, if the vehicle  100  stops at a parking space, the vehicle  100  may need to be retrieved in order to avoid parking citations, parking on private property for an extended period of time, or other potential issues with stopping the vehicle  100  at the current location. 
     The action for the vehicle  100  may also include re-planning the planned route to allow for completion of the planned route before the sun shadow reaches the route destination. In one example, to re-plan the planned route, the electronic controller  115 , using the navigation software  220 , analyzes various alternative routes to reach the route destination before the sun shadow arrives at the route destination. The alternative routes may be shorter than the planned route, have less traffic than the planned route, travel on roads with higher speed limits, and otherwise reduce travel time in order to reach the route destination before the sun shadow reaches the route destination. In some embodiments, alternative routes include routes with better lighting conditions, such as including more streetlights. This may be determined based upon accessing a digital map indicating where streetlights are placed or by using light sensors from the plurality of sensors  125 . 
     In one embodiment, the route is re-planned by prioritizing selecting alternative routes or portions of alternative routes that travel east and west along a latitude instead of driving along alternative routes or portions of alternative routes that travel north and south. By prioritizing east-west travel routes, the ADS  105  can take routes that travel in parallel with the moving sun shadow instead of routes perpendicular to the moving sun shadow, maximizing the amount of time spent moving in the same direction as the movement of the sun shadow (e.g., “staying in front of the sun shadow”). 
     The prioritization of east-west routes over north-south routes is accomplished using a cost function. For example, the cost function maximizes the amount of time spent on an east-west highway, where the vehicle  100  can travel at a higher speed and avoid surface street traffic. The cost function may also be used to prioritize selection of east-west routes and north-south routes based upon various traffic delays, known road features such as traffic lights, one-way streets, multi-lane roads, roundabouts, number of left turns necessary to reach the route destination, and other features of the driving environment. 
     A probability density function may be used to evaluate a probability of the vehicle  100  encountering the sun shadow for individual portions of the planned route. An overall cost function can then be calculated as the sum of the probability density function outputs for each segment of the planned route. Based upon the overall cost function and a calculation of an overall cost function for alternative routes, the route may be re-planned or another action may be taken as described above. 
     The following examples illustrate example systems and methods described herein. 
     Example 1: a system for determining an action for a vehicle, the system comprising an electronic controller configured to determine a planned route of the vehicle, determine local astronomical data based upon the planned route, compare the local astronomical data to the planned route of the vehicle to determine a probability of completion of the planned route, and if the probability of completion is below a threshold, generate a command indicating an action for the vehicle. 
     Example 2: the system of example 1, wherein the probability of completion of the planned route is further determined based on traffic data along the planned route. 
     Example 3: the system of any of examples 1-2, wherein the action is an action selected from the group consisting of not departing on the planned route, navigating the vehicle to a safe location to stop, stopping the vehicle at a current location of the vehicle, and re-planning the planned route to allow completion. 
     Example 4: the system of example 3, wherein the navigating the vehicle to the safe location to stop includes navigating the vehicle to a known safe harbor location. 
     Example 5: the system of example 3, wherein stopping the vehicle at the current location further includes sending a message to a remote location indicating that the vehicle needs to be retrieved. 
     Example 6: the system of example 3, wherein re-planning the route includes modifying at least one portion of the route to reduce driving time. 
     Example 7: the system of example 3, wherein re-planning the route includes modifying at least one portion of the route to prioritize travelling along a latitude instead of a longitude. 
     Example 8: the system of example 7, wherein the modification of the at least one portion of the route is determined based upon a cost function associated with a sun shadow determined from the local astronomical data. 
     Example 9: the system of any of examples 1-8, wherein the local astronomical data is determined from a remote server. 
     Example 10: the system of any of examples 1-9, wherein the local astronomical data includes astronomical data for a current position of the vehicle, astronomical data for a destination of the planned route, and astronomical data for at least one portion of the planned route. 
     Example 11: a method for determining an action for a vehicle, the method comprising determining, with an electronic controller, a planned route of the vehicle; determining, with the electronic controller, local astronomical data based upon the planned route; comparing, with the electronic controller, the local astronomical data to the planned route of the vehicle to determine a probability of completion of the planned route; and if the probability of completion is below a threshold, generating, with the electronic controller, a command indicating an action for the vehicle. 
     Example 12: the method of example 11, wherein the probability of completion of the planned route is further determined based on traffic data along the planned route. 
     Example 13: the method of any of examples 11-12, wherein the action is an action selected from the group consisting of not departing on the planned route, navigating the vehicle to a safe location to stop, stopping the vehicle at a current location of the vehicle, and re-planning the planned route to allow completion. 
     Example 14: the method of example 13, wherein the navigating the vehicle to the safe location to stop includes navigating the vehicle to a known safe harbor location. 
     Example 15: the method of example 13, wherein stopping the vehicle at the current location further includes sending a message to a remote location indicating that the vehicle needs to be retrieved. 
     Example 16: the method of example 13, wherein re-planning the route includes modifying at least one portion of the route to reduce driving time. 
     Example 17: the method of example 13, wherein re-planning the route includes modifying at least one portion of the route to prioritize travelling along a latitude instead of a longitude. 
     Example 18: the method of example 17, wherein the modification of the at least one portion of the route is determined based upon a cost function associated with a sun shadow determined from the local astronomical data. 
     Example 19: the method of any of examples 11-18, wherein the local astronomical data is determined from a remote server. 
     Example 20: the method of any of examples 11-19, wherein the local astronomical data includes astronomical data for a current position of the vehicle, astronomical data for a destination of the planned route, and astronomical data for at least one portion of the planned route. 
     Thus, embodiments described herein provide, among other things, systems and methods for determining an action for a vehicle. Various features, advantages, and embodiments are set forth in the following claims.