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Slope Optimization (or “Sloop”): Customized Optimization for Road Longitudinal Profile Eco-Design

Authors
  • vandanjon, pierre-olivier
  • vinot, emmanuel
Publication Date
Dec 14, 2020
Identifiers
DOI: 10.3390/en13246575
OAI: oai:mdpi.com:/1996-1073/13/24/6575/
Source
MDPI
Keywords
Language
English
License
Green
External links

Abstract

Current transportation systems contributed to one quarter to the Greenhouse Gases (GhG) emissions and the mobility demand increases continuously. The transportation infrastructure design has to be optimized to mitigate these emissions. The methodology &ldquo / Sloop&rdquo / (acronym for Slope Optimization) has recently been set up to optimize the longitudinal road profile with respect to a Global Warming Potential (GWP) criterion calculated for both the construction and operational phases while incorporating accurate vehicle models. This paper proposes a customized optimization strategy that significantly improves the Sloop methodology. From an initial longitudinal profile generated by road designers, our algorithm identifies the optimized profile in terms of GWP. This optimization step is complex due to the large number of degrees of freedom, along with various constraints to obtaining a feasible solution and the computational cost of the operational phase assessment. The most stringent constraint entails connecting the profile with the existing road (i.e., a constraint on the final profile altitude). We have developed a specific algorithm based on the Sequential Quadratic Programming (SQP) method / this algorithm takes into account the quasi-quadratic nature of the constraint on the final altitude. In a real case study, our algorithm outputs a profile whose GWP assessment saves 4% compared to the GWP assessment of the initial profile. The benefit of our specific protocol for treating the final altitude constraint is demonstrated in this example. By means of this new efficient and open-box algorithm, profile evolution at each iteration is analyzed to determine the most sensitive degrees of freedom, and the sensitivity of the optimization with respect to the main construction parameters and traffic assumptions are conducted. The results are consistent and stable.

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