Automobile transportation consumes a significant amount of non-reusable energy and emits emissions as by-products of fuel consumption. There has been much progress in the development of vehicle engine technology and alternative fuels to reduce the adverse impact of highway transportation on the environment. However, the research regarding the reduction of the adverse impact through highway design is still in its infancy. Furthermore, highway design manuals/guidebooks do not provide any information on environmentally-friendly designs. The primary objective of this research was to provide the tools and guidelines for a quantitative environmental evaluation in highway design. This research provided the results regarding the quantitative environmental impacts, by means of fuel consumption and emissions, of various highway geometric design conditions on the vertical grades as well as for horizontal and vertical crest curves that could be included in the highway design process. The researcher generated second-by-second speed profiles using the speed prediction models and non-uniform acceleration/deceleration models, and extracted the fuel consumption and emissions rates based on vehicle specific powers and speeds using recently developed motor vehicle emission simulator (MOVES). The generated speed profiles were matched with the extracted rates and aggregated during a trip on the grades and curves. In addition, the researcher conducted the environmental evaluation including a benefit-cost analysis with actual highway geometric data based on the proposed method and processes. The results demonstrated that fuel consumption and emissions could be significantly changed according to highway design conditions on grades and curves. Throughout the analyses, this research provides the guidelines and tools for environmental evaluations related to selected design features as a part of the highway development process. The provided guidelines and tools can reduce the uncertainty associated with the engineering judgment for environmentally-conscious highway design. Finally, this research shows the efficacy of environmentally-friendly design for sustainable (i.e., social, economical, and environmental) transportation.

The issues of global warming and climate change are a worldwide concern and the UK government has committed itself to major reductions in CO2 emissions, the most significant of the six greenhouse gases. Road transport currently accounts for about 22% of total UK emissions of CO2, and has been steadily rising. Therefore, initiatives are required to try and reduce the gas emissions in this sector. The aim of this research has been to develop a computer based vehicle routing model that calculates the overall amount of CO2 emitted from road journeys, as well as time and distance. The model has been used to examine a number of delivery strategies to assess how CO2 emissions vary. The aim has not been to produce new mathematical theories, but to produce an innovative basis for routing which will provide new information and knowledge about how CO2 emissions vary for different minimisation and congestion criteria. The approach used in this research brings together elements from transportation planning and environmental modelling combined with logistics based vehicle routing techniques. The model uses a digitised road network containing predicted traffic volumes, to which speed flow formulae are applied so that a good representation of speed can be generated on each of the roads. This means that the model is uniquely able to address the issue of congestion in the context of freight vehicle routing. It uses driving cycle data to apply variability to the generated speeds to reflect acceleration and deceleration so that fuel consumption, and therefore CO2, can be estimated. Integrated within the model are vehicle routing heuristics to enable routes to be produced which minimise the specified criterion of time, distance or CO2. The results produced by the model show that there is a potential to reduce CO2 emissions by about 5%. However, when other transport externalities are considered overall benefits are dependent on road traffic volumes.

The issues of global warming and climate change are a worldwide concern and the UK government has committed itself to major reductions in CO2 emissions, the most significant of the six greenhouse gases. Road transport currently accounts for about 22% of total UK emissions of CO2, and has been steadily rising. Therefore, initiatives are required to try and reduce the gas emissions in this sector. The aim of this research has been to develop a computer based vehicle routing model that calculates the overall amount of CO2 emitted from road journeys, as well as time and distance. The model has been used to examine a number of delivery strategies to assess how CO2 emissions vary. The aim has not been to produce new mathematical theories, but to produce an innovative basis for routing which will provide new information and knowledge about how CO2 emissions vary for different minimisation and congestion criteria. The approach used in this research brings together elements from transportation planning and environmental modelling combined with logistics based vehicle routing techniques. The model uses a digitised road network containing predicted traffic volumes, to which speed flow formulae are applied so that a good representation of speed can be generated on each of the roads. This means that the model is uniquely able to address the issue of congestion in the context of freight vehicle routing. It uses driving cycle data to apply variability to the generated speeds to reflect acceleration and deceleration so that fuel consumption, and therefore CO2, can be estimated. Integrated within the model are vehicle routing heuristics to enable routes to be produced which minimise the specified criterion of time, distance or CO2. The results produced by the model show that there is a potential to reduce CO2 emissions by about 5%. However, when other transport externalities are considered overall benefits are dependent on road traffic volumes.

O transporte rodoviário é uma das atividades econômicas do homem que mais contribuem para a emissão de Gases de Efeito Estufa (GEE) na atmosfera. Sabe-se que a emissão de CO2 está diretamente vinculada ao consumo de combustível. Por isso, é possível encontrar uma série de trabalhos que objetivam diminuir as emissões por meio da redução do consumo de combustível dos veículos. A otimização de rotas é uma importante ferramenta para essa redução e, consequentemente, possibilita minimizar as emissões dos veículos. Esta pesquisa tem como objetivo aplicar em uma empresa líder na distribuição de revistas no país o PRP, que é um modelo de minimização do consumo de combustível/emissão de GEE por meio de ajustes das variáveis como velocidade média, quantidade de carga transportada, distância percorrida e inclinações das vias. Como a maioria das metodologias de estimativa de combustível existentes na literatura não considera a inclinação das vias nos seus cálculos, neste trabalho foi necessário desenvolver uma metodologia para incluí-la no modelo. Testes foram efetuados com variações nas janelas de tempo, e o modelo mostrou-se sensível a cada uma das variáveis analisadas, gerando economias em 100% das rotas estudadas. / Road transport is one of the biggest contributors of Greenhouse Gases emissions of all humans economic activities. It is known that CO2 emissions are directly related to fuel consumption, so that is why it is possible to find a series of studies that aims to reduce emissions by reducing vehicles fuel consumption. Route optimization is an important tool for reducing fuel consumption and hence emissions. This research aims to implement the PRP model in a leading company in the country, which is a model that minimizes fuel consumption/GHG emissions through adjustments of variables such as average speed, pay load, distance traveled and slopes of the road. Most existing fuel estimation methodologies found in the literature does not consider the slope of the roads in their calculations. So in this research it was necessary to develop a methodology to include it in the model. Tests were performed with variations in the time windows and the model was sensitive to each of the variables analyzed, generating savings on 100% of the studied routes.

O transporte rodoviário é uma das atividades econômicas do homem que mais contribuem para a emissão de Gases de Efeito Estufa (GEE) na atmosfera. Sabe-se que a emissão de CO2 está diretamente vinculada ao consumo de combustível. Por isso, é possível encontrar uma série de trabalhos que objetivam diminuir as emissões por meio da redução do consumo de combustível dos veículos. A otimização de rotas é uma importante ferramenta para essa redução e, consequentemente, possibilita minimizar as emissões dos veículos. Esta pesquisa tem como objetivo aplicar em uma empresa líder na distribuição de revistas no país o PRP, que é um modelo de minimização do consumo de combustível/emissão de GEE por meio de ajustes das variáveis como velocidade média, quantidade de carga transportada, distância percorrida e inclinações das vias. Como a maioria das metodologias de estimativa de combustível existentes na literatura não considera a inclinação das vias nos seus cálculos, neste trabalho foi necessário desenvolver uma metodologia para incluí-la no modelo. Testes foram efetuados com variações nas janelas de tempo, e o modelo mostrou-se sensível a cada uma das variáveis analisadas, gerando economias em 100% das rotas estudadas. / Road transport is one of the biggest contributors of Greenhouse Gases emissions of all humans economic activities. It is known that CO2 emissions are directly related to fuel consumption, so that is why it is possible to find a series of studies that aims to reduce emissions by reducing vehicles fuel consumption. Route optimization is an important tool for reducing fuel consumption and hence emissions. This research aims to implement the PRP model in a leading company in the country, which is a model that minimizes fuel consumption/GHG emissions through adjustments of variables such as average speed, pay load, distance traveled and slopes of the road. Most existing fuel estimation methodologies found in the literature does not consider the slope of the roads in their calculations. So in this research it was necessary to develop a methodology to include it in the model. Tests were performed with variations in the time windows and the model was sensitive to each of the variables analyzed, generating savings on 100% of the studied routes.