“…Motion planning approaches can be classified based on different criteria. In the following sections we present two dif- Rule-based approaches [17], [24], [25], [26] Logical-constrains for lane changes; Finite State Machines for overtaking maneuvers; predictive lane and reference speed selection state machine in highway traffic; state machine for merging on highway, intersection crossing and give free passage to emergency vehicles [17], [24], [25], [26] [17], [26] [17], [24], [25], [26] Utility-based approaches [21], [15], [16] Cost function for lane change decision making; receding-horizon multi-objective optimization for automatic parallel parking; fused decision making and trajectory planning with cost function deciding on maneuver-based tactical patterns; Utility function for mandatory, discretionary and anticipatory lane change decisions [15], [16], [17] [17] [17] [15], [16], [17] Probabilisticbased approaches [18], [27], [28], [19], [20] POMDP for uncertain environments; POMDP based on Monte-Carlo tree search for decision-making in highways; probabilistic model for lane change maneuver in highways; POMDP with discrete Bayesian network for decision making in dynamic and uncertain unsignalized urban environments; online POMDP considering uncertainty on intersections.…”