Adaptive Cruise Control (ACC) systems represent an active research area in the automobile industry. The design of such systems
typically involves several, possibly conflicting criteria such as driving safety, comfort and fuel consumption. When the different
design objectives cannot be met simultaneously, a number of non-dominated solutions exists, where no single solution is better
than another in every aspect. The knowledge of this set is important for any design decision as it contains valuable information
about the design problem at hand.
In this paper we approximate the non-dominated set of a given ACC-controller design problem for trucks using multi-objective
evolutionary algorithms (MOEAs). Two different search strategies based on a continuous relaxation and on a direct representation
of the integer design variables are applied and compared to a grid search method.