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This paper presents a spatial-based trajectory planning method for automatedvehicles under actuator, obstacle avoidance, and vehicle dimension constraints.Starting from a nonlinear kinematic bicycle model, vehicle dynamics aretransformed to a road-aligned coordinate frame with path along the roadcenterline replacing time as the dependent variable. Space-varying vehicledimension constraints are linearized around a reference path to pose convexoptimization problems. Such constraints do not require to inflate obstacles bysafety-margins and therefore maximize performance in very constrainedenvironments. A sequential linear programming (SLP) algorithm is motivated. Alinear program (LP) is solved at each SLP-iteration. The relation between LPformulation and maximum admissible traveling speeds within vehicle tirefriction limits is discussed. The proposed method is evaluated in a roomy andin a tight maneuvering driving scenario, whereby a comparison to asemi-analytical clothoid-based path planner is given. Effectiveness isdemonstrated particularly for very constrained environments, requiring toaccount for constraints and planning over the entire obstacle constellationspace.

Trajectory Planning Under Vehicle Dimension Constraints Using Sequential Linear Programming