Evolutionary Multi-objective Integer Programming for the Design of Adaptive Cruise Control Systems

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 ACCcontroller 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.