Eco-friendly 3D-Routing: A GIS based 3D-Routing-Model to estimate and reduce CO2-emissions of distribution transports

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Abstract

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 this sector, undertaking responsibilities for its environmental impact are needed. Although technical and strategic solutions to reduce emissions have been introduced, or are in development, these rarely yield instant emission reduction potentials. A strategic approach to reducing them instantly, based on the given infrastructure and existing vehicle fleet, may be achieved 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 expectations towards sustainability by authorities and consumers led to an increased interest in route optimization in which environmental externalities, such 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, such as road inclination and varying velocities into account. The proposed model utilizes a Digital Elevation Model (DEM) to enrich a road network with elevation data. The 3D-Routing-Model is applied in different distribution scenarios within the framework of an artificial company in the Lisbon Metropolitan Area, Portugal to evaluate the effects of road inclination on vehicles fuel consumption and its proportional CO2-Emissions. Results indicate that eco-friendly routes can yield significant fuel and emission saving potentials of up to 20% in the tested scenarios. However, eco-friendly routes are characterized by longer distances as well as operation times, which leads to increased expenses. The question remains if companies within the transportation sector are more interested in maximizing their profits, or investing in a sustainable future.

Original languageEnglish
Pages (from-to)40-55
Number of pages15
JournalComputers, Environment and Urban Systems
Volume73
Early online date16 Aug 2018
DOIs
Publication statusPublished - 2019

Keywords

  • CO-Emissions
  • GIS Applications
  • Green Logistics
  • Route Optimization
  • Vehicle Routing

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