Evaluation of Path Planning Algorithms of Autonomous Surface Vehicles Based on Safety and Collision Risk Assessment

Improved safety while navigating on waters and reduction of collision risk is a vital part of the guidance, navigation and control system of an autonomous surface vehicle. Another problem is, how to compare the performance of existing path planning and collision avoidance algorithms in a unified way. To tackle these problems, a novel evaluation simulator platform is proposed in this paper for simulation-based testing of algorithms. The platform is designed for generating different scenarios based on the system's inputs, such as static and dynamic obstacles, environmental disturbances, vessel's dynamic model, and environment, and to evaluate algorithm performance based on path fitness, risk assessment and, in the future, good seamanship practice. Formation of safety maps is used for assessment of each performance measure. Additionally, a root sum square method combines these measures into a total algorithm performance rating. Finally, multi-objective optimisation is applied to evaluate the algorithms based on their performance ratings.