Autor(es): Schröder, Marc Frederic
Data: 2018
Identificador Persistente: http://hdl.handle.net/10362/33651
Origem: Repositório Institucional da UNL
Assunto(s): 3D-Road-Network; ArcGIS; CO2-Emissions; Digital Elevation Model; GIS Applications; Green Logistics; Green Routing; Heavy-Duty-Vehicles; Route Optimization
Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial Technologies
Road Freight Transportation accounts for a significant share of the worldwide CO2-Emissions, indicating that respective operations are not sustainable. Regarding the forecasted increase in CO2-Emissions from Road Freight Transportation, this sector needs to undertake responsibilities for its environmental impact. Although technical and strategic solutions to reduce emissions have been introduced or are in development, such solutions rarely yield instant emission reduction potentials. A strategic approach to reduce them instantly, based on the given infrastructure and existing vehicle fleet, is represented through route optimization. Route optimization is a well-researched topic in the transportation domain. However, it is mainly used to reduce transportation times and expenses. Rising expectation towards sustainability through stakeholders such as authorities and consumers, let to an increased interest in route optimization where environmental externalities as fuel consumption and CO2-Emissions are minimized. This paper introduces a Geographic Information System (GIS) based 3D-Routing-Model, which incorporates models to estimate vehicle fuel consumption while taking effects as road inclination and varying velocities into account. The proposed model utilizes a Digital Elevation Model to enrich a Road Network with elevation data – An approach which is applicable to any area where respective data is available. To evaluate the effects of road inclination on a vehicles fuel consumption and its proportional CO2-Emissions, the 3D-Routing-Model is applied in different distribution scenarios within the framework of an artificial company in the Lisbon Metropolitan Area. The obtained results indicate that eco-friendly routes can yield significant fuel and emission saving potentials of up to 20 % in the tested scenarios. However, the results also indicate that eco-friendly routes are characterized through longer distances as well as operation times, which eventually leads to increased expenses. It remains the question if companies within the transportation sector are more interested in maximizing their profits, or to invest in a sustainable future.
