Abstract: A system for impact-based operation of an autonomous agent (equivalently referred to herein as an ego agent and autonomous vehicle) includes and/or interfaces with a computing subsystem (equivalently referred to herein as a computer and/or set of computers). A method for impact-based operation of an autonomous agent includes: receiving a set of inputs; predicting a set of future scenarios; and determining a set of metrics based on the set of future scenarios. Additionally or alternatively, the method can include operating the autonomous agent based on the set of metrics and/or any other processes.

Abstract: A system for impact-based operation of an autonomous agent (equivalently referred to herein as an ego agent and autonomous vehicle) includes and/or interfaces with a computing subsystem (equivalently referred to herein as a computer and/or set of computers). A method for impact-based operation of an autonomous agent includes: receiving a set of inputs; predicting a set of future scenarios; and determining a set of metrics based on the set of future scenarios. Additionally or alternatively, the method can include operating the autonomous agent based on the set of metrics and/or any other processes.

Abstract: A system for impact-based operation of an autonomous agent (equivalently referred to herein as an ego agent and autonomous vehicle) includes and/or interfaces with a computing subsystem (equivalently referred to herein as a computer and/or set of computers). A method for impact-based operation of an autonomous agent includes: receiving a set of inputs; predicting a set of future scenarios; and determining a set of metrics based on the set of future scenarios. Additionally or alternatively, the method can include operating the autonomous agent based on the set of metrics and/or any other processes.

Abstract: A method of decoding a plurality of diverse signals for low-density parity-check (LDPC) decoders that takes advantage of signal diversity. The method allows for the combining of soft-decision LDPC encoded non-coherently modulated signals, which is in contrast to existing approaches where hard decision combining is used for non-coherently modulated signals. The method includes the steps of inputting each diversity signal into a unique demodulator, and calculating the LLR of each demodulated signal. When the diverse demodulated signals are combined into a single combined signal, each bit of the combined signal is selected according to the value of either the highest LLR value of each bit across the demodulated signals or according to the sum of the LLR of each bit across the demodulated signals.

Abstract: A method of decoding a plurality of diverse signals for low-density parity-check (LDPC) decoders that takes advantage of signal diversity. The method allows for the combining of soft-decision LDPC encoded non-coherently modulated signals, which is in contrast to existing approaches where hard decision combining is used for non-coherently modulated signals. The method includes the steps of inputting each diversity signal into a unique demodulator, and calculating the LLR of each demodulated signal. When the diverse demodulated signals are combined into a single combined signal, each bit of the combined signal is selected according to the value of either the highest LLR value of each bit across the demodulated signals or according to the sum of the LLR of each bit across the demodulated signals.