Optimizing route choice for lowest fuel consumption – Potential effects of a new driver support tool

Abstract. A method is presented for the evaluation of the exhaust emissions of marine traffic, based on the messages provided by the Automatic Identification System (AIS), which enable the identification and location determination of ships. The use of the AIS data enables the positioning of ship emissions with a high spatial resolution, which is limited only by the inaccuracies of the Global Positioning System (typically a few metres) that is used in vessel navigation. The emissions are computed based on the relationship of the instantaneous speed to the design speed, and these computations also take into account the detailed technical information of the ships' engines. The modelling of emissions is also based on a few basic equations of ship design, including the modelling of the propelling power of each vessel in terms of its speed. We have also investigated the effect of waves on the consumption of fuel, and on the emissions to the atmosphere. The predictions of fuel consumption were compared with the actual values obtained from the shipowners. For a RoPax vessel, the predicted and reported values of fuel consumption agreed within an accuracy of 6%. According to the data analysis and model computations, the emissions of NOx, SOx and CO2 originating from ships in the Baltic Sea in 2007 were in total 400 kt, 138 kt and 19 Mt, respectively. A breakdown of emissions by flag state, ship's type and year of construction is also presented. The modelling system can be used as a decision support tool in the case of issues concerning, e.g., health effects caused by shipping emissions, the construction of emission-based fairway dues systems or emissions trading. The computation of emissions can also be automated, which will save resources in constructing emission inventories. Both the methodologies and the emission computation program can be applied in any sea region in the world, provided that the AIS data from that specific region are available.

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Drivers’ adaptive travel behaviors towards green transportation development: a critical review

Archives of Transport ◽

10.5604/08669546.1218793 ◽

2016 ◽

Vol 38 (2) ◽

pp. 49-70 ◽

Cited By ~ 6

Author(s):

Arezou Shafaghat ◽

Ali Keyvanfar ◽

Nurul Hidayah Muslim

Keyword(s):

Fuel Consumption ◽

Decision Support Tool ◽

Assessment Model ◽

Second Phase ◽

Lifestyle Behaviors ◽

Driver Behaviour ◽

Support Tool ◽

Traffic Calming ◽

Green Transportation ◽

Travel Behaviors

The transportation professionals integrated the concept Green in various dimensions of transportation, such as, green vehicle, green highway. The current study has established a new dimension to green transportation, which is called Green Driver as whom substantially contributes to less emission and fuel consumption, and higher-safety. The research established the driver’s Green Adaptive Travel Behaviors (GATB), in particular, that is referred to voluntary personal and lifestyle behaviors on less energy consumption and emission. The methodology was designed into two phases. Phase one was to investigate driver’s GATBs through systematic literature review process and content analysis method. The second phase was to verify greenery value impact (GVI) of the finalized list of drivers’ GATBs through an expert input study and Grounded Group Decision Making (GGDM) method. Total twenty six (26) GATB factors have been determined. Amongst, the factor ‘F27- Dangerous overtaking’ has received the highest value (97%) followed with ‘F3- Slow once realizing bike lanes for cyclist crossing’ (91%). In contrast, ‘F4- Realize visual Obstacles to manage the speed’ and ‘F21- Brake with smooth deceleration’ has received the lowest value (77%) among other factors. Two of the initial factors;‘F5-Use traffic calming devices’ (55%), and ‘F24- Change highest possible gear’ (69%) could not reach the 70% saturation; hence, they have been dropped from the list of GATB factors. Indeed, the GATB efforts are not limited to technology and practice; but also can include education and enforcement to driving regulations in order to interconnect driver, technology, environment, and vehicle. The research concluded with an innovative technique used as the decision support tool to evaluate the greenery grade of any individual driver on committing to less emission, less fuel consumption, and higher safety in traveling. As future study, the Green driver behaviour index assessment model will be developed based on this study outputs.

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A combined algorithm approach to fuel consumption rate analysis and prediction of sea-worthy diesel engine-powered marine vessels

Proceedings of the Institution of Mechanical Engineers Part M Journal of Engineering for the Maritime Environment ◽

10.1177/1475090216663946 ◽

2016 ◽

Vol 231 (2) ◽

pp. 542-554 ◽

Cited By ~ 1

Author(s):

Thaddeus C Nwaoha ◽

Garrick Ombor ◽

Modestus O Okwu

Keyword(s):

Fuel Consumption ◽

Consumption Rate ◽

Fuzzy Rule ◽

Decision Support Tool ◽

Rule Base ◽

Support Tool ◽

Rate Level ◽

Fuel Consumption Rate ◽

Marine Vessels ◽

Combined Algorithm

Prediction of fuel consumption rate level of a vessel per voyage posed to be a challenge under uncertainties. In such uncertain conditions, revealing of fuel consumption rate levels of the fleet of vessels is deemed imperative to ensure effective and efficient operations of the vessels per voyage. Therefore, development of uncertainty treatment model is necessary in this research. A combined algorithm that is made up of fuzzy rule base and utility theory methods is incorporated in the investigation of the fuel consumption rate levels of marine vessels. The mechanism of the algorithm is used to capture and combine all the important parameters that determine the fuel consumption rate level of each marine vessel. The workability of the model is demonstrated. The produced results revealed that the combined algorithm can support estimation of the fuel consumption rate levels of marine vessels and show which vessel is better than the other. Based on the results of this article, the management and crew of a marine vessel are equipped with the necessary decision support tool to optimize, implement and manage improvements on the performance characteristics and fuel consumption rate of their marine vessels during voyages.

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Fuel consumption analysis of driven trips with respect to route choice

2020 IEEE 36th International Conference on Data Engineering Workshops (ICDEW) ◽

10.1109/icdew49219.2020.000-9 ◽

2020 ◽

Author(s):

Ekaterina Gilman ◽

Satu Tamminen ◽

Anja Keskinarkaus ◽

Theodoros Anagnostopoulos ◽

Xiang Su ◽

...

Keyword(s):

Fuel Consumption ◽

Route Choice

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A Voyage Planning Tool for Arctic Transit of Cargo Ships

Volume 8: Polar and Arctic Sciences and Technology; Petroleum Technology ◽

10.1115/omae2019-95128 ◽

2019 ◽

Author(s):

Zhiyuan Li ◽

Jonas W. Ringsberg ◽

Francisco Afonso Rita

Keyword(s):

Fuel Consumption ◽

Fuel Efficiency ◽

Open Water ◽

Decision Support Tool ◽

Planning Tool ◽

Arctic Seas ◽

Support Tool ◽

Maritime Operations ◽

Cost Efficient ◽

Extra Resistance

Abstract The paper presents a decision-support tool for maritime operations in Arctic seas. This tool targets at improving the safety and fuel efficiency of existing and future cargo vessels that are designed to operate in Arctic and in open water conditions. It is achieved by smart voyage planning using meteorological, oceanographic and ice forecasting. A single-objective optimization for minimizing the fuel consumption in various scenarios of Arctic transits is established, with the transit time and the safety as the two major constraints. The tool is implemented in an in-house Matlab code, which is based on Dijkstra’s algorithm, a grid-based approach that aims at finding the most cost-efficient path connecting any chosen nodes in a given grid. Results from case studies along the Northern Sea Route indicate that the tool generates appropriate routes in ice-infested Arctic waters. The fuel consumption accounting for ice-induced extra resistance is optimized and the risk of collision with icebergs has been considered.

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A modelling system for the exhaust emissions of marine traffic and its application in the Baltic Sea area

Atmospheric Chemistry and Physics ◽

10.5194/acp-9-9209-2009 ◽

2009 ◽

Vol 9 (23) ◽

pp. 9209-9223 ◽

Cited By ~ 163

Author(s):

J.-P. Jalkanen ◽

A. Brink ◽

J. Kalli ◽

H. Pettersson ◽

J. Kukkonen ◽

...

Keyword(s):

Baltic Sea ◽

Fuel Consumption ◽

Exhaust Emissions ◽

Automatic Identification ◽

Identification System ◽

The Baltic Sea ◽

Support Tool ◽

Marine Traffic ◽

The Baltic ◽

Modelling System

Abstract. A method is presented for the evaluation of the exhaust emissions of marine traffic, based on the messages provided by the Automatic Identification System (AIS), which enable the identification and location determination of ships. The use of the AIS data facilitates the positioning of ship emissions with a high spatial resolution, which is limited only by the inaccuracies of the Global Positioning System (typically a few metres) that is used in vessel navigation. The emissions are computed based on the relationship of the instantaneous speed to the design speed, and the detailed technical information of the engines of the ships. The modelling of emissions is also based on a few basic principles of ship design, including the modelling of the propelling power of each vessel in terms of its speed. We have investigated the effect of waves on the consumption of fuel, and on the emissions to the atmosphere. The predictions of fuel consumption were compared with the actual values obtained from the shipowners. For a Roll on – Roll off cargo/passenger ship (RoPax), the predicted and reported values of annual fuel consumption agreed within an accuracy of 6%. According to the data analysis and model computations, the emissions of NOx, SOx and CO2 originating from ships in the Baltic Sea during the full calendar year of 2007 were in total 400 kt, 138 kt and 19 Mt, respectively. A breakdown of emissions by flag state, the type of ship and the year of construction is also presented. The modelling system can be used as a decision support tool in the case of issues concerning, e.g., the health effects caused by shipping emissions or the construction of emission-based fairway dues systems or emissions trading. The computation of emissions can be automated, which will save resources in constructing emission inventories. Both the methodologies and the emission computation program can be applied in any sea region in the world, provided that the AIS data from that specific region are available.

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Ship Speed Optimization Considering Ocean Currents to Enhance Environmental Sustainability in Maritime Shipping

Sustainability ◽

10.3390/su12093649 ◽

2020 ◽

Vol 12 (9) ◽

pp. 3649 ◽

Cited By ~ 2

Author(s):

Liqian Yang ◽

Gang Chen ◽

Jinlou Zhao ◽

Niels Gorm Malý Rytter

Keyword(s):

Fuel Consumption ◽

Environmental Sustainability ◽

Ghg Emissions ◽

Oil Products ◽

Ocean Currents ◽

Support Tool ◽

Maritime Shipping ◽

Proposed Model ◽

Speed Optimization ◽

Ship Speed

Enhancing environmental sustainability in maritime shipping has emerged as an important topic for both firms in shipping-related industries and policy makers. Speed optimization has been proven to be one of the most effective operational measures to achieve this goal, as fuel consumption and greenhouse gas (GHG) emissions of a ship are very sensitive to its sailing speed. Existing research on ship speed optimization does not differentiate speed through water (STW) from speed over ground (SOG) when formulating the fuel consumption function and the sailing time function. Aiming to fill this research gap, we propose a speed optimization model for a fixed ship route to minimize the total fuel consumption over the whole voyage, in which the influence of ocean currents is taken into account. As the difference between STW and SOG is mainly due to ocean currents, the proposed model is capable of distinguishing STW from SOG. Thus, in the proposed model, the ship’s fuel consumption and sailing time can be determined with the correct speed. A case study on a real voyage for an oil products tanker shows that: (a) the average relative error between the estimated SOG and the measured SOG can be reduced from 4.75% to 1.36% across sailing segments, if the influence of ocean currents is taken into account, and (b) the proposed model can enable the selected oil products tanker to save 2.20% of bunker fuel and reduce 26.12 MT of CO2 emissions for a 280-h voyage. The proposed model can be used as a practical and robust decision support tool for voyage planners/managers to reduce the fuel consumption and GHG emissions of a ship.

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