Optimization of Horizontal Highway Alignment Using a Path Planner Method

Abstract

This paper proposes Path Planner Method (PPM) that operates on the principal of Rapidly-exploringRandom Tree (RRT) algorithm to obtain an optimal horizontal alignment. It has the ability to efficiently search in non-convex high dimension space. It primary goal is to explore the entire study area by generating random point of intersections (PIs). In this, a tree like path is developed iteratively by expanding from start to end point. These paths would meet the requirements of highway geometric guidelines and minimizes cost. It's an interactive two-stage process. Firstly, it finds an optimum set of PI's connected by tangent sections. Secondly, appropriate curves are fitted at each PI to obtain horizontal alignment. The alignment is checked for encroachment to the restricted area and any violation leads to further refinement of the PI locations. The method's efficiency is verified through a case study using a geographical map of a place in Odisha, India.

A sequential exploration algorithm for the design optimization of horizontal road alignment

“…Predefined assumption of PI Predefined or upper bound on the number of PIs EM (Jong & Schonfeld, 2003), PSO (Shafahi & Bagherian, 2013), SQP (Casal et al, 2017), (Vázquez-Mendez et al, 2021) PIs located on orthogonal sections or sampling points GA (Kang et al, 2012), MMPA (Maji, 2017), DP (Li et al, 2013), PSO (Shafahi & Bagherian, 2013;Ghoreishi et al, 2019), WLS (Y. , ACO PIs located on grid center or grid vertex DA (Pushak et al, 2016), DT (Li et al, 2017; No need to think about or use PIs SEA (this study) original works. Finally, the conclusions are presented in Section 5, and a list of abbreviations and symbols of this work is given in Appendix A.…”