Various studies have emphasized the interesting advantages related to the use of new transition curves for improving the geometric design of highway horizontal alignments. In a previous paper, one of the writers proposed a polynomial curve, called a polynomial parametric curve (PPC), proving its efficiency in solving several design problems characterized by a very complex geometry (egg-shaped transition, transition between reversing circular curves, semidirect and inner-loop connections, and so on). The PPC also showed considerable advantages from a dynamic perspective, as evidenced by the analysis of the main dynamic variables related to motion (as well as rate of change of radial acceleration, steering speed, roll speed, and so on). In this paper, an optimization procedure using genetic algorithms (GAs) for selecting the different parameters of the PPC has been proposed. In particular, a specific algorithm defines the parameter values in order to minimize an appropriate fitness function. Besides, the final PPC can be examined from a dynamic point of view for evaluating the compliance with the comfort and safety conditions. Moreover, to simplify the geometric representation and the calculation of the dynamic variables of the PPC, using computer software, a specific and innovative routine has been specifically developed by the writers.

Using Genetic Algorithms for Optimizing the PPC in the Highway Horizontal Alignment Design.

BOSURGI, Gaetano
Primo
;
PELLEGRINO, Orazio
Secondo
;
Sollazzo G.
Ultimo
2016

Abstract

Various studies have emphasized the interesting advantages related to the use of new transition curves for improving the geometric design of highway horizontal alignments. In a previous paper, one of the writers proposed a polynomial curve, called a polynomial parametric curve (PPC), proving its efficiency in solving several design problems characterized by a very complex geometry (egg-shaped transition, transition between reversing circular curves, semidirect and inner-loop connections, and so on). The PPC also showed considerable advantages from a dynamic perspective, as evidenced by the analysis of the main dynamic variables related to motion (as well as rate of change of radial acceleration, steering speed, roll speed, and so on). In this paper, an optimization procedure using genetic algorithms (GAs) for selecting the different parameters of the PPC has been proposed. In particular, a specific algorithm defines the parameter values in order to minimize an appropriate fitness function. Besides, the final PPC can be examined from a dynamic point of view for evaluating the compliance with the comfort and safety conditions. Moreover, to simplify the geometric representation and the calculation of the dynamic variables of the PPC, using computer software, a specific and innovative routine has been specifically developed by the writers.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11570/2944168
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