Method and apparatus for providing road surface friction data for a response action
First Claim
1. A method for effectuating a mode of operation in an autonomous vehicle, comprising:
- processing sensor data associated with the autonomous vehicle to determine at least one sensed road-vehicle friction change associated with at least one travel segment, wherein the autonomous vehicle is operating in an autonomous mode;
calculating at least one expected friction change from friction data of at least one guideline friction map for the at least one travel segment, wherein the friction data of the at least one guideline friction map is aggregated from a plurality of vehicles that previously traveled on the at least one travel segment;
comparing the at least one sensed road-vehicle friction change to the at least one expected friction change; and
determining at least one response action to change the mode of operation of the autonomous vehicle from the autonomous mode to a manual mode based on the comparison.
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Abstract
An approach is provided for determining road surface friction data for at least one travel segment via sensor data and/or guideline friction map to cause at least one response action. The approach involves processing and/or facilitating a processing of sensor data to determine at least one road-vehicle friction change associated with at least one travel segment. The approach also involves causing, at least in part, a comparison of the at least one road-vehicle friction change to at least one guideline friction map. The approach further involves determining at least one response action to the at least one road-vehicle friction change based, at least in part, on the comparison.
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Citations
22 Claims
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1. A method for effectuating a mode of operation in an autonomous vehicle, comprising:
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processing sensor data associated with the autonomous vehicle to determine at least one sensed road-vehicle friction change associated with at least one travel segment, wherein the autonomous vehicle is operating in an autonomous mode; calculating at least one expected friction change from friction data of at least one guideline friction map for the at least one travel segment, wherein the friction data of the at least one guideline friction map is aggregated from a plurality of vehicles that previously traveled on the at least one travel segment; comparing the at least one sensed road-vehicle friction change to the at least one expected friction change; and determining at least one response action to change the mode of operation of the autonomous vehicle from the autonomous mode to a manual mode based on the comparison. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14)
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15. An apparatus comprising:
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at least one processor; and at least one memory including computer program code for one or more programs, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following, process sensor data associated with an autonomous vehicle to determine at least one sensed road-vehicle friction change associated with at least one travel segment, wherein the autonomous vehicle is operating in an autonomous mode; calculate at least one expected friction change from friction data of at least one guideline friction map for the at least one travel segment, wherein the friction data of the at least one guideline friction map is aggregated from a plurality of vehicles that previously traveled on the at least one travel segment; compare the at least one sensed road-vehicle friction change to the at least one expected friction change; and determine at least one response action to change a mode of operation of the autonomous vehicle from the autonomous mode to a manual mode based on the comparison. - View Dependent Claims (16, 17, 18, 19, 20)
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21. A non-transitory computer-readable storage medium carrying one or more sequences of one or more instructions which, when executed by one or more processors, cause an apparatus to perform:
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process sensor data associated with the autonomous vehicle to determine at least one sensed road-vehicle friction change associated with at least one travel segment, wherein the autonomous vehicle is operating in an autonomous mode; calculate at least one expected friction change from friction data of at least one guideline friction map for the at least one travel segment, wherein the friction data of the at least one guideline friction map is aggregated from a plurality of vehicles that previously traveled on the at least one travel segment compare the at least one sensed road-vehicle friction change to the at least one expected friction change guideline friction map; and determine at least one response action to change a mode of operation of the autonomous vehicle from the autonomous mode to a manual mode based on the comparison. - View Dependent Claims (22)
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Specification