Optimized selection of vessel air emission controls—moving beyond cost-efficiency

Shipping currently has an unexploited potential for improved energy efficiency and reduced emissions to air. Many existing air emission controls have been proved to be cost-efficient but are still not commonly installed on board vessels. This paper discusses the so-called ‘energy paradox’ in maritime transportation, presenting barriers to overcome and criteria to consider when selecting cost-efficient air emission controls. Current approaches typically select available controls based on their cost-effectiveness. While this is an important aid in the decision-making process, and, in relative terms, easy to quantify, it is not a sufficient criterion to capture the true preferences of the decision-maker. We present in this paper a multi-criteria optimization model for the selection of air emission controls. This decision framework can also incorporate subjective and qualitative factors, and is applied to the shipping company Grieg Shipping. A survey among internal Grieg Shipping stakeholders identifies the important criteria to consider, their relative importance, and the scoring of the controls. This empirical data is used as parameters in the model and the model is then applied on a vessel of the Grieg Shipping fleet. The results show that nonfinancial factors play an important role in the selection of air emission controls in shipping.     

A study on model fidelity for model predictive control-based obstacle avoidance in high-speed autonomous ground vehicles

This paper investigates the level of model fidelity needed in order for a model predictive control (MPC)-based obstacle avoidance algorithm to be able to safely and quickly avoid obstacles even when the vehicle is close to its dynamic limits. The context of this work is large autonomous ground vehicles that manoeuvre at high speed within unknown, unstructured, flat environments and have significant vehicle dynamics-related constraints. Five different representations of vehicle dynamics models are considered: four variations of the two degrees-of-freedom (DoF) representation as lower fidelity models and a fourteen DoF representation with combined-slip Magic Formula tyre model as a higher fidelity model. It is concluded that the two DoF representation that accounts for tyre nonlinearities and longitudinal load transfer is necessary for the MPC-based obstacle avoidance algorithm in order to operate the vehicle at its limits within an environment that includes large obstacles. For less challenging environments, however, the two DoF representation with linear tyre model and constant axle loads is sufficient.