A Multiobjective Optimization Approach for COLREGs-Compliant Path Planning of Autonomous Surface Vehicles Verified on Networked Bridge Simulators

Abstract

This paper presents a multiobjective optimisation approach for path planning of autonomous surface vehicles (ASVs). A unique feature of the technique is the unification of the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs) with good seamanship's practice alongwith hierarchical (rather than simultaneous) inclusion of objectives. The requirements of collision avoidance are formulated as mathematical inequalities and constraints in the optimisation framework and thus collision-free manoeuvres and COLREGs-compliant behaviours are provided in a seafarerlike way. Specific expert knowledge is also taken into account when designing the multiobjective optimisation algorithm. For example, good seamanship reveals that if allowed, an evasive manoeuvre with course changes is always preferred over one with speed changes in practical maritime navigation. As a result, a hierarchical sorting rule is designed to prioritize the objective of course/speed change preference over other objectives such as path length and path smoothness, and then incorporated into a specific evolutionary algorithm called hierarchical multiobjective particle swarm optimisation (H-MOPSO) algorithm. The H-MOPSO algorithm solves the real-time path planning problem through finding solutions of the formulated optimisation problem. The effectiveness of the proposed H-MOPSO algorithm is demonstrated through both desktop and high-fidelity networked bridge simulations.

Path planning and collision avoidance for autonomous surface vehicles II: a comparative study of algorithms

“…These rules have been implemented as components of the cost function or as penalty functions. Some papers emphasise that, according to good seamanship practice, course change is preferred over speed change in collision avoidance scenarios [38,49].…”

Adaptive Potential Field-Based Path Planning for Complex Autonomous Driving Scenarios

“…Based on the Frenet-Serret formulas [22], a moving road coordinate is transformed with the Cartesian coordinates of a given road. Fig.1 indicates that the descriptions of the relative position between the ego vehicle and obstacle in two coordinate systems are different as (1) and (2).…”

“…A. MOTIVATION P ATH planning as an important component of autonomous driving techniques has been widely researched in recent years [1]. Various algorithms have been developed for path planning according to the application scenarios [2], e.g.…”

Local Path Planning for Unmanned Surface Vehicle Collision Avoidance Based on Modified Quantum Particle Swarm Optimization

“…Based on the motion velocity model and COLREGs, a reverse eccentric expansion method was designed to deal with dynamic obstacles [17]. A multiobjective optimization approach for path planning of an autonomous surface vehicle combined COLREGs with good seaman's practice and stratified the objectives [18].…”