Analysis of the Hybrid Global Path Planning Algorithm for Different Environments

Abstract

To achieve the overall goal of realising an efficient and advantageous participation of autonomous ground vehicles in the transport system as fast as possible, a lot of work is being done in different and specific research fields. One of the most important research fields, which has a large impact on safe autonomous ground vehicle realisation, is the development of path planning algorithms. Therefore, this work describes in detail the development and application of a hybrid path planning algorithm. The described algorithm is based on classical and heuristic path planning approaches and can be applied in unstructured and structured environments. The efficiency of the algorithm was investigated by applying the algorithm and executing theoretical and experimental tests. The theoretical and experimental tests were executed while optimising different complexity paths. Results analysis demonstrated that the described algorithm can generate a smooth, dynamically feasible and collision-free path.

Trajectory Planning of Autonomous Vehicle in Freeway Driving

“…Shojaei introduced a trajectory planning with 5th degree polynomial and applied boundary conditions to define coefficient of 5th degree equation [6], Ghariblu introduced a trajectory planning with 4th degree polynomials. Skačkauskas et al (2019) proposed a hybrid global path planning algorithm combined from both, classical and heuristic genetic algorithm approaches. To calculate value of the 4th coefficients, boundary conditions must be satisfied.…”