System and method for managing environmental conditions for an autonomous vehicle

Abstract

Systems and methods for managing environmental conditions for an autonomous vehicle are disclosed. In one aspect, an autonomous vehicle includes a perception sensor configured to generate perception data indicative of a condition of the environment, a network communication transceiver configured to communicate with an oversight system and an external weather condition source, a non-transitory computer readable medium, and a processor. The processor is configured to: receive the perception data from the at least one perception sensor, receive an indication of current weather conditions from the external weather condition source, determine a current environmental condition severity level from a plurality of severity levels based on the perception data and the indication of current weather conditions, modify one or more driving parameters that that govern a range of actions that can be autonomously executed by the autonomous vehicle, and navigate the autonomous vehicle based on the modified driving parameters.

What is claimed is: 
     
         1 . An autonomous vehicle comprising:
 at least one perception sensor configured to generate perception data indicative of a condition of the environment;   a network communication transceiver configured to communicate with an oversight system and receive information from an external weather condition source;   a non-transitory computer readable medium; and   a processor configured to:
 receive the perception data from the at least one perception sensor, 
 receive an indication of current weather conditions from the external weather condition source, 
 determine a current environmental condition severity level from a plurality of severity levels based on the perception data and the indication of current weather conditions, 
 modify one or more driving parameters that govern a range of actions that can be autonomously executed by the autonomous vehicle, and 
 navigate the autonomous vehicle based on the modified one or more driving parameters. 
   
     
     
         2 . The autonomous vehicle of  claim 1 , wherein the processor is further configured to:
 determine a current environmental condition severity level for each of a plurality of different environmental conditions.   
     
     
         3 . The autonomous vehicle of  claim 2 , wherein the plurality of different environmental conditions includes two or more of: road traction, stability, or visibility. 
     
     
         4 . The autonomous vehicle of  claim 3 , wherein the processor is further configured to:
 determine that at least two of the plurality of different environmental conditions has a severity level other than normal,   wherein modifying the one or more driving parameters is further based on the determination that at least two of the plurality of different environmental conditions have a severity level other than normal.   
     
     
         5 . The autonomous vehicle of  claim 1 , wherein the plurality of severity levels comprises at least two of: normal, degraded, cautionary, and critical. 
     
     
         6 . The autonomous vehicle of  claim 1 , wherein the processor is further configured to:
 determine that the current environmental condition is critical,   in response to determining that the current environmental condition is critical, cause the autonomous vehicle to execute a minimal risk condition (MRC) maneuver.   
     
     
         7 . The autonomous vehicle of  claim 6 , wherein the MRC maneuver comprises pulling the autonomous vehicle over to a safe zone of a roadway. 
     
     
         8 . The autonomous vehicle of  claim 1 , wherein the processor is further configured to:
 determine that the autonomous vehicle is operating out of an operational design domain (ODD) of the autonomous vehicle,   in response to determining that the autonomous vehicle is operating out of the ODD, determining that the current environmental condition severity level is critical, and   in response to determining that the current environmental condition is critical, cause the autonomous vehicle to execute a first minimum risk condition (MRC) maneuver.   
     
     
         9 . The autonomous vehicle of  claim 8 , wherein the processor is further configured to:
 determine that the autonomous vehicle has been attempting the first MRC for longer than a predetermined period of time without success, and   in response to determining that the autonomous vehicle has been attempting the first MRC for longer than a predetermined period of time without success, cause the autonomous vehicle to execute a second MRC maneuver.   
     
     
         10 . The autonomous vehicle of  claim 1 , wherein the processor is further configured to:
 determine that the current environmental condition severity level is degraded, and   in response to determining that the current environmental condition severity level is degraded, modify the one or more driving parameters to instruct the autonomous vehicle to change lanes to the right-most lane based on determining that it is safe to perform lane changes.   
     
     
         11 . The autonomous vehicle of  claim 1 , wherein the processor is further configured to:
 determine that the current environmental condition severity level is cautionary, and   in response to determining that the current environmental condition severity level is cautionary, modify the one or more driving parameters to instruct the autonomous vehicle to avoid all lane changes, except for lane changes that are required for safety or lane changes required to continue the current mission.   
     
     
         12 . A non-transitory computer-readable medium having stored thereon instructions which, when executed by a processor, cause the processor to:
 receive perception data from at least one perception sensor of an autonomous vehicle;   receive an indication of current weather conditions from an external weather condition source;   determine a current environmental condition severity level from a plurality of severity levels based on the perception data and the indication of current weather conditions;   modify one or more driving parameters that govern a range of actions that can be autonomously executed by the autonomous vehicle; and   navigate the autonomous vehicle based on the modified one or more driving parameters.   
     
     
         13 . The non-transitory computer-readable medium of  claim 12 , wherein the instructions further cause the processor to:
 determine a road traction coefficient based on the perception data; and   determine that the current environmental condition severity level is degraded in response to the road traction coefficient being less than a threshold value.   
     
     
         14 . The non-transitory computer-readable medium of  claim 13 , wherein the instructions further cause the processor to:
 in response to determining that the current environmental condition severity level is degraded: reduce a speed of the autonomous vehicle, perform lane changes with critical intent, apply a maximum available deceleration rate or less to decelerate, if safe to do so, lane change to a right-most lane, and/or maintain a preference for the right-most lane.   
     
     
         15 . The non-transitory computer-readable medium of  claim 12 , wherein the instructions further cause the processor to:
 determine that the autonomous vehicle has slowed down to a level below a normal speed but still greater than a threshold speed; and   determine that the current environmental condition severity level is degraded in response to determining that the autonomous vehicle has slowed down to the level below the normal speed but still greater than the threshold speed.   
     
     
         16 . The non-transitory computer-readable medium of  claim 12 , wherein the instructions further cause the processor to:
 determine a road traction coefficient based on the perception data;   determine that the autonomous vehicle has modified its behavior when the road traction coefficient is less than a threshold value; and   determine that the current environmental condition severity level is degraded in response to determining that the autonomous vehicle has modified its behavior when the road traction coefficient is less than the threshold value.   
     
     
         17 . A method comprising:
 receiving perception data from at least one perception sensor of an autonomous vehicle;   receiving an indication of current weather conditions from an external weather condition source;   selecting a current environmental condition severity level from a plurality of severity levels based on the perception data and the indication of current weather conditions;   modifying one or more driving parameters that govern a range of actions that can be autonomously executed by the autonomous vehicle; and   navigating the autonomous vehicle based on the modified one or more driving parameters.   
     
     
         18 . The method of  claim 17 , further comprising:
 estimating a visibility range based on the perception data;   determining that the current environmental condition is degraded in response to the visibility range being less than a threshold value.   
     
     
         19 . The method of  claim 17 , further comprising:
 determining that the autonomous vehicle will enter a fog area based on the perception data and the indication of current weather conditions; and   activating low beams of the autonomous vehicle in response to determining that the autonomous vehicle will enter the fog area.   
     
     
         20 . The method of  claim 17 , further comprising:
 estimating a level of water based on road crown visibility from the perception data; and   slowing down a speed of the autonomous vehicle in response to the level of water being greater than a threshold level.