Weather Route Research Articles

Investigating the influence of e-navigation and S-100 over the computation of the weather route

The weather route presents significant potential in identifying the most efficient route for vessels, enabling the optimisation of distance, time, or fuel consumption. Although there have been notable advancements in most technologies in recent years, weather routing has failed to keep pace with these developments. The purpose of this document is to determine whether a specific IMO’s concept called e-navigation may have an impact on vessel’s route optimisation. Today, mariners are required to integrate heterogeneous data types (hydrographic, weather, oceanographic, etc.) that are transmitted on board via various devices and in diverse formats in order to execute weather routing. When e-navigation becomes operational, relevant marine-related data will be accessible in a standardised format on a unified device. The objective of this work is to examine the potential of S-100 in the context of weather routing and route optimisation for the benefit of navigation. There are two methodologies discussed: manual and automated. A range of S-100-based products will be evaluated in relation to a variety of optimisation algorithms in order to predict whether e-navigation could be advantageous in addressing the weather routing problem. Constraints regarding the implementation of electronic navigation and the mariners’ duties are outlined in the final part of the paper.

Weather Route Optimization Method of Unmanned Ship Based on Continuous Dynamic Optimal Control

Intelligent weather route optimization method was an essential guarantee for safe and efficient navigation of ships. In traditional methods, the multi-stage decision-making method was generally used to solve route dynamic optimization problems, in which it was impossible to achieve dynamic optimal routes, due to the temporal and spatial complexity of route design. In this paper, an unmanned ship weather route optimization model was established based on a method of continuous dynamic optimal control. Marine meteorological information was analyzed. Navigation safety, energy consumption, and sailing time were integrated considered. Dual-target route evaluation function of energy consumption and sailing time was established. The problem about the multi-stage decision was transformed into that of one-step optimal control, and an improved ant colony algorithm was adopted. Simulation results showed that compared with some traditional methods, the proposed method was better performed, which can be applied to dynamic route optimization of the unmanned ship in a large marine area under complex meteorological conditions.

Research on Ship Meteorological Route Based on A-Star Algorithm

Ship meteorological navigation is based on hydrometeorological data of a certain time scale, considering the ship’s motion characteristics and its own characteristics. First, we provide the best route for the ship and then use real-time local weather information to correct the route during the ship’s navigation. It can also be expressed as follows: it is based on the hydrological and meteorological conditions of the ship during its voyage and the seakeeping characteristics of the ship itself, and the route planning method is used to select the best route for the ship. The best route is a balance between economy and safety, that is, based on ensuring the safety of ship navigation, the route that meets the shortest navigation time, the least fuel consumption, or the least navigation risk is obtained. Weather navigation includes the optimization of the initial route before sailing and the correction of the route after sailing. As there may be errors in hydrometeorological forecasts, especially in the accuracy and real-time performance of medium and long-term forecasts, the optimal initial route may not achieve the best results. Therefore, after the ship sails, it is necessary to adjust and correct the preferred initial route based on the meteorological information detected by the sensors or the continuously updated hydrometeorological forecast data to ensure the best effect of meteorological navigation. This paper proposes a weather route planning method based on the improved A-star algorithm. The convex shape of the concave obstacle and the expansion of the obstacle are carried out; according to the position of the target point relative to the starting point, the search direction of the A-star algorithm at each node is restricted, and an improved A-star algorithm is proposed. The simulation of global weather route planning shows that the improved A-star algorithm can not only find the optimal path but also effectively reduce the number of nodes that the algorithm needs to search during operation. Compared with the classic algorithm, the improved algorithm reduces the number of node searches by 29.25%.

Dynamic Optimization Method for Unmanned Ship Weather Route Based on Multi-stage Inverse Reasoning

Route is an important factor for safe and efficient navigation of ships. In this paper, unmanned ship navigation environment under complex marine meteorological conditions was analyzed. Wind, wave conditions were integrated considered. Dynamic optimization model of unmanned ship weather route was established, in which meteorological and hydrological information was considered, unfavorable influences of which on ship navigation were reduced, energy and sailing time were saved, and route was found. Simulation results showed that initial fixed weather route could be optimized, and the model could be applied to dynamic optimization of weather routes of unmanned ships in large areas under complex meteorological conditions.

An Research on the design and optimization of shipping routes in the Arctic

In the design and research of the Arctic route, the route design can be interfered by other factors. This paper studies the route design and optimization after considering the interference of external factors. According to the external environment factors to design the arctic route weather route, the first arctic route design model was established, using the method of dynamic programming. Therefore, it is necessary to continuously determine the shortest sailing time of the ship, namely the actual sailing speed of the ship. According to the sailing conditions of the ship in different environments, so that the highest degree of navigation safety can be achieved, and the route optimization problem is transformed into a multi-stage decision-making problem. The global optimal solution is obtained by looking for the local optimal solution of each stage. Combined with the original Arctic route model, the meteorological route is optimized. By separating the present period from the future period, the present and future benefits are considered together. By determining the stage index function and the optimal index function, the basic equation of dynamic programming is established. The Pareto front curve corresponding to the requirements of the shortest voyage time and the voyage safety is given, that is, the optimal solution function curve of the two objectives. The influence between the shortest voyage time and the voyage safety is weighed comprehensively, and the optimal solution is obtained by combining the actual situation of the ship during the voyage, that is, the route optimization is completed. Finally, the optimized Arctic route is simulated and evaluated in an electronic computer simulation system with similar environment.

Onboard weather routing model and algorithm based on ant colony optimization

Due to many limitations and deficiencies in the onshore weather routing, the onboard weather routing based on ant colony optimization (ACO) is proposed in this paper. Firstly, this work analyses the similarities and differences between weather route optimization and TSP, proposes a more appropriate heuristic function which makes ants tend to search for grids nearer to the destination. Secondly, an onboard weather routing algorithm based on ant-cycle model is established, including constraint criteria, path search strategy and smoothing strategy. At last, the history meteorological data was used to simulate the forecast information, and the feasibility and rationality of the model and algorithm is verified based on an experimental ship. As the simulation shown, the final optimal route solved in this paper can be in line with the actual situation of navigation and having practical significance.

Dynamic Weather Routes: Two Years of Operational Testing at American Airlines

The Dynamic Weather Routes (DWR) tool continuously and automatically analyzes active flights in en route airspace and finds simple route corrections to achieve more time- and fuel-efficient routes around convective weather. A strong partnership between the National Aeronautics and Space Administration (NASA), American Airlines (AA), and the Federal Aviation Administration (FAA) has enabled testing of DWR in real-world air traffic operations. NASA and AA have been conducting a trial of DWR at AA’s Integrated Operations Control Center in Fort Worth, Texas since July 2012. This paper describes test results based on AA’s use of DWR for their flights in and around Fort Worth Center (ZFW). Results indicate an actual savings of 3,949 flying minutes for 624 AA revenue flights from January 2013 through December 2014. Of these, 101 flights each indicate a savings of 15 min or more. Potential savings for all flights in ZFW airspace, corrected for savings flights achieve today through normal pilot requests and controller clearances without DWR, is about 100,000 flying minutes for 15,000 flights in 2013. Results indicate that AA flights with DWR in use realize about 15% more savings than non-AA flights. A weather forecast analysis examines the extent to which DWR routes rated acceptable by AA users remain clear of downstream weather. A sector congestion analysis indicates congestion could be reduced by about 20% if all flights fly DWR routes rather than nominal weather-avoidance routes.

Multi-objective Weather Routing with Customised Criteria and Constraints

The paper presents a weather routing algorithm utilising a multi-objective optimisation with constraints, namely the Multi-objective Evolutionary Weather Routing Algorithm (MEWRA). In the proposed approach weather route recommendations can be made simultaneously e.g. for passage time, fuel consumption and safety of passage by means of Pareto optimisation. The sets of criteria and constraints in the optimisation process are fully customisable. The algorithm handles static (time-independent) and dynamic (time-dependent) constraints e.g. forecasted high wind speed regions or customisable areas to be excluded from routing (e.g. due to piracy). The paper includes a description of MEWRA as well as examples of its usage for finding Pareto-optimal transoceanic ship routes.

Part 1: Pavement Management: Analysis of Long-Term Effectiveness of Thin Hot-Mix Asphaltic Concrete Overlay Treatments

Thin hot-mix asphalt (HMA) concrete overlays are preventive maintenance treatments used to address minor distresses, increase ride quality, and extend pavement life. This paper determines the long-term effectiveness of such treatments by using three measures of effectiveness: treatment service life, increase in average pavement condition, and area bounded by the performance curve. For each measure of effectiveness, the pavement performance indicators used are the international roughness index (IRI), rutting, and pavement condition rating (PCR). For each measure of effectiveness and performance indicator, treatment benefits were found to lie within a wide range because of the effect of varying levels of weather severity, traffic, and route type. The service life of the treatment ranges from 3 to 13 years (IRI performance indicator), 3 to 14 years (rutting), and 3 to 24 years (PCR). When the increase in average pavement condition is used as the measure of effectiveness, the results show that such treatments...