Abstract: A vehicle platoon following deciding system based on cloud computing is configured to decide a plurality of vehicle platoon accelerations of a leading vehicle and at least one following vehicle. A cloud processing unit receives a leading vehicle parameter group and at least one following vehicle parameter group. The cloud processing unit is configured to implement a cloud deciding step. The cloud deciding step includes judging whether the leading vehicle is manually driven according to the leading vehicle parameter group to generate a driving mode judging result, calculating a driving acceleration range according to a leading vehicle acceleration range and at least one following vehicle acceleration range, estimating a compensated acceleration according to the leading vehicle parameter group, and calculating the vehicle platoon accelerations according to the driving mode judging result and at least one of the driving acceleration range and the compensated acceleration.

Abstract: A vehicle platoon following deciding system based on cloud computing is configured to decide a plurality of vehicle platoon accelerations of a leading vehicle and at least one following vehicle. A cloud processing unit receives a leading vehicle parameter group and at least one following vehicle parameter group. The cloud processing unit is configured to implement a cloud deciding step. The cloud deciding step includes judging whether the leading vehicle is manually driven according to the leading vehicle parameter group to generate a driving mode judging result, calculating a driving acceleration range according to a leading vehicle acceleration range and at least one following vehicle acceleration range, estimating a compensated acceleration according to the leading vehicle parameter group, and calculating the vehicle platoon accelerations according to the driving mode judging result and at least one of the driving acceleration range and the compensated acceleration.

Abstract: A driving risk assessment and control decision-making method for an autonomous vehicle includes: detecting the surrounding state of the vehicle multiple times to generate multiple sensing signals; quantifying the sensing signals to generate multiple sensing values and calculating a sensing average value of the sensing values; calculating a sensing error value between each sensing value and the sensing average value, a sensing error average value of sensing error values and a sensing error variation value; integrating the sensing error average value, the sensing error variation value and a sensor systematic error average value and a sensor systematic error variation value to generate a sensing signal correction value; combining the sensing values and the sensing signal correction value to generate multiple sensing signal reference values; judging whether a stability of the sensing signal reference values falls within a preset range; generating a control mechanism based on the judgement.

Abstract: A driving risk assessment and control decision-making method for an autonomous vehicle includes: detecting the surrounding state of the vehicle multiple times to generate multiple sensing signals; quantifying the sensing signals to generate multiple sensing values and calculating a sensing average value of the sensing values; calculating a sensing error value between each sensing value and the sensing average value, a sensing error average value of sensing error values and a sensing error variation value; integrating the sensing error average value, the sensing error variation value and a sensor systematic error average value and a sensor systematic error variation value to generate a sensing signal correction value; combining the sensing values and the sensing signal correction value to generate multiple sensing signal reference values; judging whether a stability of the sensing signal reference values falls within a preset range; generating a control mechanism based on the judgement.