The urgency of extending functionalities of current advanced driver assistance systems (ADAS), and eventually progressing to highly automated highway driving necessitates the design of automatic lane change system. This paper presents an automatic lane change system targeting on discretional lane change scenario in highway driving. Assuming motion signals of all participants to be available, the MOBIL model is employed as the decision module. The functionality of the adaptive cruise controller is extended to realize dual-target tracking, so as to prevent abrupt acceleration change provoked by the sudden switch of the leading vehicle during the lane change. For the lateral part, a hierarchical trajectory planning algorithm, which combines parametric function and learning-based technique, is proposed to account for uncertainties of driver characteristics in different traffic situations. The trajectory is then tracked by a low-level controller based on model predictive control (MPC) theory, which employs a force input model to predict the motion of the vehicle, and formulates environment envelope and handling limits as constraints. The proposed algorithm is validated through simulations of typical scenarios. Overall, this paper lays a solid foundation for the prototype of ADAS regarding lane change.
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