System and method for maps for an autonomous vehicle

Abstract

A high precision digital map is pre-developed and stored in a memory of an in-vehicle control computer on an autonomous vehicle. The digital map is updated by the in-vehicle control computer with detected roadway data that is a fusion of roadway perception data from at least one perception sensor on the autonomous vehicle and real time GPS signal from at least one GPS receiving devices on the autonomous vehicle. The updated digital map is transferred to a remote oversight system via a network communication subsystem, and the oversight system distributes the updated digital map to other autonomous vehicles connected over the network communication subsystem.

What is claimed is: 
     
         1 . An autonomous vehicle configured to drive on a roadway, comprising:
 at least one perception sensor configured to generate perception data indicative of roadway conditions;   at least one global positioning system (GPS) receiving device configured to receive a GPS signal;   a network communication subsystem configured to communicate with a remote oversight system;   a processor; and   a non-transitory computer readable medium configured to store mapped data and having stored thereon instructions that, when executed by the processor, cause the processor to:
 receive the perception data from the at least one perception sensor, 
 generate roadway condition data based on the perception data, 
 receive the GPS signal from the at least one GPS receiving device, 
 retrieve the mapped data from the non-transitory computer readable medium, 
 determine that the GPS signal meets a minimum localization accuracy requirement, 
 combine the generated roadway condition data with the GPS signal to form detected road data, 
 determine that there is a discrepancy between the detected road data and the retrieved mapped data, 
 in response to the determining that there is a discrepancy between the detected road data and the retrieved mapped data, update the mapped data with the detected road data, and 
 transmit the updated mapped data to the remote oversight system through the network communication subsystem. 
   
     
     
         2 . The autonomous vehicle of  claim 1 , wherein the at least one GPS receiving device is a plurality of GPS receiving devices located on different parts of the autonomous vehicle to improve a strength of the received GPS signal and a positioning accuracy of the GPS signal. 
     
     
         3 . The autonomous vehicle of  claim 1 , wherein in response to determining that the received GPS data does not meet the minimum localization accuracy requirement, the processor is further configured to cause the autonomous vehicle to perform a minimal risk condition (MRC) maneuver to stop the autonomous vehicle. 
     
     
         4 . The autonomous vehicle of  claim 3 , wherein the processor is further configured to cause the autonomous vehicle to stop at a shoulder of the roadway. 
     
     
         5 . The autonomous vehicle of  claim 3 , wherein the processor is further configured to communicate to the remote oversight system and request for assistance. 
     
     
         6 . The autonomous vehicle of  claim 1 , further comprising:
 a visual inertia odometry (VIO) configured to generate location data; and   wherein when the received GPS signal does not meet the minimum localization accuracy requirement, the processor is further configured to:
 derive road positioning data from the VIO location data and the perception data received from the at least one perception sensor, and 
 cause the autonomous vehicle to operate according to the derived road positioning data. 
   
     
     
         7 . The autonomous vehicle of  claim 6 , wherein the derived road positioning data comprises a road longitudinal data and a road lateral data, and wherein the road longitudinal data is derived from the VIO location data, and the road lateral data is derived from the perception data received from the at least one perception sensor. 
     
     
         8 . The autonomous vehicle of  claim 7 , wherein the road lateral data is derived at least in part from perception of a lane marking by the at least one perception sensor. 
     
     
         9 . The autonomous vehicle of  claim 6 , wherein the processor is further configured to cause the autonomous vehicle to operate in a tunnel where the GPS signal is unavailable or is inaccurate. 
     
     
         10 . The autonomous vehicle of  claim 6 , wherein the processor is further configured to cause the autonomous vehicle to operate in a parking building where the GPS signal does not meet the minimum localization accuracy requirement. 
     
     
         11 . A method comprising:
 receiving perception data from at least one perception sensor of an autonomous vehicle;   generating roadway condition data based on the perception data;   receiving global positioning system (GPS) signal from at least one GPS receiving device of the autonomous vehicle;   retrieving mapped data from a non-transitory computer readable medium of the autonomous vehicle;   determining that the GPS signal meets a minimum localization accuracy requirement;   combining the generated roadway condition data with the GPS signal to form detected road data;   determining that there is a discrepancy between the detected road data and the retrieved mapped data;   in response to the determining that there is a discrepancy between the detected road data and the retrieved mapped data, updating the mapped data with the detected road data; and   transmitting the updated mapped data to the remote oversight system through a network communication subsystem.   
     
     
         12 . The method of  claim 11 , wherein for each off-ramp exit on a limited access highway in the digital map a plurality of safety areas is marked within 5 miles from the off-ramp exit. 
     
     
         13 . The method of  claim 12 , wherein each of the plurality of safety areas is at least 96 meters long and 3.4 meters wide. 
     
     
         14 . The method of  claim 11 , wherein when the autonomous vehicle is a truck and a roadway is identified as restrictive to truck traffic, further comprising:
 finding a route excluding the roadway identified as restricted to truck traffic.   
     
     
         15 . The method of  claim 14 , wherein the roadway identified restrictive to truck traffic is a roadway having a weight limit that is lower than a weight of the autonomous vehicle. 
     
     
         16 . The method of  claim 14 , wherein the roadway and/or a lane of the roadway identified as restrictive to truck traffic is a roadway and/or a lane of the roadway having a no-truck-traffic sign. 
     
     
         17 . The method of  claim 11 , wherein when a construction zone traffic sign and traffic control devices on a roadway are detected by the at least one perception sensor of the autonomous vehicle, further comprising:
 establishing a virtual wall separating the construction zone and the roadway; and   causing the autonomous vehicle to stay at least a predetermined safe distance away from the virtual wall.   
     
     
         18 . The method of  claim 17 , wherein the predetermined safe distance is 8% of a lane width of the roadway. 
     
     
         19 . The method of  claim 17 , wherein the traffic control devices include at least a traffic control barricade, a traffic control cone, a traffic control barrel, and a construction zone flagger. 
     
     
         20 . A non-transitory computer-readable medium having stored thereon mapped data and instructions which, when executed by a processor, cause the processor to:
 receive perception data from at least one perception sensor of an autonomous vehicle;   generate roadway condition data based on the perception data;   retrieve mapped data from the non-transitory computer readable medium of the autonomous vehicle;   determine that a global positioning system (GPS) signal from at least one GPS receiving device of the autonomous vehicle meets a minimum localization accuracy requirement;   combine the generated roadway condition data with the GPS signal to form a detected road data;   determine that there is a discrepancy between the detected road data and the retrieved mapped data;   in response to the determining that there is a discrepancy between the detected road data and the retrieved mapped data, update the mapped data with the detected road data; and   transmit the updated mapped data to a remote oversight system through a network communication subsystem.