Multi-Year Program under Budget Constraints Using Multi-Criteria Analysis

Road investment appraisal requires joint consideration of multiple criteria which are related to engineering, economic, social and environmental impacts. The investment consideration could be based on the economic analysis but however for some factors, such as environmental, social, and political, are difficult to quantify in monetary term. The multi-criteria analysis is the alternative tool which caters the requirements of the issues above. The research, which is based on 102 class D and class E paved road sections in Kenya, is about to optimize road network investment under budget constraints by applying a multi-criteria analysis (MCA) method and compare it with the conventional economic analysis. The MCA is developed from hierarchy structure which is considered as the analytical framework. The framework is based on selected criteria and weights which are assigned from Kenya road policy. The HDM-4 software is applied as decision-making tool to obtain the best investment alternatives and road work programs from both MCA and economic analysis. The road work programs will be the results from the analysis using both MCA and economic analysis within HDM-4 software to see the difference and compare the results between both programs. The results from MCA show 51 road sections need periodic work, which is overlay or resealing. Meanwhile, 51 others need rehabilitation or reconstruction. The five years road work program which based on economic analysis result shows that it costs almost Kenyan Shilling (KES) 130 billion to maintain the class D and E paved road in Kenya. Meanwhile, the MCA only requires KES 59.5 billion for 5 years program. These results show huge margin between two analyses and somehow MCA result provides more efficient work program compared to economic analysis

Rolling resistance contribution to a road pavement life cycle carbon footprint analysis

Purpose Although the impact of road pavement surface condition on rolling resistance has been included in the life cycle assessment (LCA) framework of several studies in the last years, there is still a high level of uncertainty concerning the methodological assumptions and the parameters that can affect the results. In order to adopt pavement carbon footprint/LCA as a decision-making tool, it is necessary to explore the impact of the chosen methods and assumptions on the LCA results. Methods This paper provides a review of the main models describing the impact of the pavement surface properties on vehicle fuel consumption and analyses the influence of the methodological assumptions related to the rolling resistance on the LCA results. It compares the CO2 emissions, calculated with two different rolling resistance models existing in literature, and performs a sensitivity test on some specific input variables (pavement deterioration rate, traffic growth, and emission factors/fuel efficiency improvement). Results and discussion The model used to calculate the impact of the pavement surface condition on fuel consumption significantly affects the LCA results. The pavement deterioration rate influences the calculation in both models, while traffic growth and fuel efficiency improvement have a limited impact on the vehicle CO2 emissions resulting from the pavement condition contribution to rolling resistance. Conclusions and recommendations Existing models linking pavement condition to rolling resistance and hence vehicle emissions are not broadly applicable to the use phase of road pavement LCA and further research is necessary before a widely-used methodology can be defined. The methods of modelling and the methodological assumptions need to be transparent in the analysis of the impact of the pavement surface condition on fuel consumption, in order to be interpreted by decision makers and implemented in an LCA framework. This will be necessary before product category rules (PCR) for pavement LCA can be extended to include the use phase

Rural road management in Botswana

This paper discusses the management of rural roads in Chobe in Botswana, which are mainly tertiary and access roads. These roads are low-volume roads and mostly gravelled. It was observed that the maintenance management of these roads was based on engineering judgement through visual inspection all over the country, without having any economic or technical analysis. Therefore, a comprehensive pavement management system for rural roads' maintenance is needed in Chobe and also in all the council areas of Botswana, which would consist of data collection, database, use of the Highway Development and Management Model to undertake efficient decision making project preparation, funding, implementation and feedback. A partial implementation of pavement management system in Chobe has been highlighted in this paper. The present analysis reveals that total demand for the road network in Chobe was 41·29 million pula, the backlog was 34·86 million pula and the first-year backlog demand was 20·63 million pula. Furthermore, the analysis found the long-term periodic maintenance strategy for the network at 6·43 million pula when there is no backlog. This huge backlog indicates that roads are not being maintained appropriately. The paper also estimates current road asset value in Chobe at 55·48 million pula. Finally, the paper recommends several solutions for the efficient preservation of road assets in Botswana

Integrated policy analysis of sustainable urban and transportation development

Sustainable urban and transportation development needs to balance economic sustainability, environmental sustainability, and social equity. This study conducts integrated policy analyses by explicitly incorporating these sustainability goals and optimizing the performance of transportation networks. This is done based on a bi-level programming approach, in which the upper level addresses sustainability goals and the lower level describes the optimization of a transportation network. On the upper level, car ownership, number of trips according to travel mode and accessibility-based social equity are optimized under the constraint of environmental capacity, which is calculated based on stochastic frontier analysis. On the lower level, a four-step travel demand modeling framework is adopted. In case studies, the maximal mobility level under the environmental capacity constraint is calculated, and various package policies for sustainable development are simulated