Optimization-Based Maneuver Planning for a Tractor-Trailer Vehicle in a Curvy Tunnel: A Weak Reliance on Sampling and Search

Abstract

This study is focused on the maneuver planning problem for a tractor-trailer vehicle in a curvy and tiny tunnel. Due to the curse of dimensionality, the prevalent sampling-andsearch-based planners used to handle a rigid-body vehicle well become less efficient when the trailer number grows or when the tunnel narrows. This fact also has impacts on an optimizationbased planner if it counts on a sampling-and-search-based initial guess to warm-start. We propose an optimization-based maneuver planner that weakly relies on the sampling and search, hoping to get rid of the curse of dimensionality and thus find optima rapidly. The proposed planner comprises three stages: stage 1 identifies the homotopy class via A* search in a 2D grid map; stage 2 recovers the kinematic feasibility with softened intermediate problems iteratively solved; stage 3 finds an optimum that strictly satisfies the nominal collision-avoidance constraints. Optimization-based planners are commonly known to run slowly, but this work shows that they have obvious advantages over the prevalent sampling-and-search-based planners when the solution space dimension is high and/or the constraints are harsh.

Online Competition of Trajectory Planning for Automated Parking: Benchmarks, Achievements, Learned Lessons, and Future Perspectives

“…If a sampling-/searchbased planner is adopted, then the sampling/search resolution needs to be high to find zig-zag path primitives precisely. However, setting a high resolution inevitably suffers from the curse of dimensionality, which increases the runtime of a sampling-/search-based planner and even harms algorithm completeness [23]. If a numerical-optimizationbased planner is used to deal with problem 7, then the collocation point density needs to be set high, which renders a large-scale mathematical programming problem [21], [24], [25].…”

Time-optimal trajectory planning for autonomous parking of tractor-semitrailer vehicle based on piecewise Gauss pseudospectral method

“…The traditional Gauss pseudospectral method for solving the parking trajectory may not converge or converge slowly. Li et al, 36,37 divided the automatic parking process of a single vehicle into two stages for extremely small parking space conditions, and used the interior point method to solve the optimal trajectory in each stage. The simulation results show that the method can effectively improve the success rate and efficiency of the solution.…”

“…The simulation results show that the method can effectively improve the success rate and efficiency of the solution. Referring to the division of single car parking area in different stages in the literature, 36,37 this paper divides the autonomous parking process of a tractor-semitrailer into two stages according to the parking area. At each stage, the pseudo spectral method is used to solve the optimal collision-free trajectory with the goal of minimizing the parking time.…”

“…An iterative computation framework is proposed to accumulatively handle the collision avoidance constraint and nonconvex kinematics constraint in curve trajectory planning task in literature. 35 In literature, 36 an optimization-based trajectory planning method is proposed to solve the motion planning problem of tractor-trailer vehicle in a curvy and tiny tunnel. This method has significant advantages over popular sampling and search-based algorithms in solving high spatial dimensions or harsh constraint conditions.…”

A trajectory planning method based on triggered planning framework for autonomous driving on unstructured roads in mining areas

“…Artificial intelligence methods mainly address decision-making and planning problems in complex traffic flow scenarios [11]. Numerical optimization methods often rely on other methods to provide initial solutions for them [12].…”