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.
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