Motion planning for autonomous heavy duty vehicles has been intensively studied during the last years due to its promising benefits for industry in terms of money savings and security. The system treated in this thesis is a 1-trailer truck and the focus was to develop and evaluate different methodologies in order to optimize the reverse parking manoeuvre for this specific system, while considering its kinematic constraints and collision avoidance. Until now, most of the methodologies developed for the system at hand focused on finding a feasible path connecting a start configuration to a goal configuration, but very little attention has been paid to the optimality of the solution given. Along the report the author assumes that a feasible solution is available and four different methodologies are developed and evaluated in order to optimize the initial given path. The algorithms were tested in different environments in order to assess their advantages and weaknesses. Results show that a good description of the obstacles in the map is required to obtain a good solution in all class of environments, and if that description is scarce the optimization for narrow and spatially constrained environments does not provide the desired results. Furthermore, it was discovered that using a good feasible solution as a starting point reduces the convergence time of the algorithms presented.
