FIG. 8B illustrates an example of a fuzzy rule-based system 850 illustrating different membership values producing different actions based on an initial set of rules for three different scenarios. Feature A and Feature B may be any set of inputs or data as described herein such as driving and driver context information. In the first instance illustrated, a first membership function 852 is used to determine a membership value for Feature A, resulting in membership in A, or a low value. Feature B is likewise in a membership category of A, a low value using a second membership function 854. The combination of low Feature A and low Feature B results in Action #1, according to the initial set of rules. Similarly, in the second instance, a low value for Feature A and a high value, shown as membership in C, results in Action #2. Similarly, a mid-range membership in B and a high value or membership in C results in Action #3. These examples are intended to be illustrative only, and not limiting with respect to how the adaptive fuzzy-based rule system operates. Further, as indicated in FIG. 8B, many combinations of features may have many resulting actions not depicted, and additional features can expand the number of possible combinations.
