Abstract: This paper investigates the optimization of the RouteSegmentation algorithm by integrating the Douglas-Peucker line simplification method in the context of intercity travel. The primary goal of the research is to enhance the algorithm's performance by effectively reducing the number of route pathway points while preserving the quality of perimeter area identification. The study focuses on a single pair of source and destination coordinates within East Java Province, analyzing up to 2,000 route pathway points. These points were divided into 20 subsets, each containing between 100 and 2,000 points with an increment of 100 points per subset. To optimize the RouteSegmentation process, a fixed threshold distance of 50 meters was applied using the Douglas-Peucker algorithm, which resulted in an average reduction of 96.84% in the number of points across all subsets. Importantly, this reduction was achieved without sacrificing the visual quality of the algorithm's output, as the perimeter area identification remained consistent and accurate. The experimental results, conducted within an Android application environment, demonstrate that the optimized RouteSegmentation algorithm significantly reduces processing time and memory usage compared to the non-simplified version. This substantial improvement underscores the effectiveness and efficiency of the Douglas-Peucker simplification in enhancing the RouteSegmentation algorithm's performance, offering a robust solution for efficient and scalable navigation systems, particularly in mobile applications.

Abstract: Prior study has developed the RouteSegmentation algorithm to identify the perimeter area surrounding a route. In this study, a comparative experiment was carried out to investigate the performance of the RouteSegmentation algorithm implementation in contrast to the RouteBoxer algorithm. Both algorithms play a crucial role in geographical information systems (GIS), particularly in enhancing navigational tools by identifying points of interest along specified routes. Through systematic experimentation using various perimeter distance values and types of route, the trade-offs between processing efficiency and the granularity of the area identified by these algorithms were evaluated. The results demonstrate that RouteSegmentation maintained relatively consistent performance across different perimeter distance values and statistically significantly faster processing time than RouteBoxer. Furthermore, while the RouteBoxer algorithm benefits from larger perimeter distance values by reducing processing time, it compromises the coverage results of the algorithm and potentially undermines its usefulness in practical scenarios. This study not only provides insights into the optimal use of perimeter distance values for each algorithm but also guides users in selecting the appropriate algorithm based on their specific application needs, balancing detailed geographical analysis and runtime efficiency.

Abstract: This paper introduces RouteSegmentation, an algorithm to identify the perimeter area that surrounds a travel route. RouteSegmentation, which is suggested in this study, consists of two main processes: generating the segment polygons and merging all the segment polygons into a single polygon depicting the perimeter area surrounding the route. A comprehensive performance analysis of RouteSegmentation, including a comparison of three different polygon union methods for the second process of the algorithm, is presented. The results demonstrate that for the first process, which is generating segment polygons, RouteSegmentation maintains consistent performance across a range of numbers of points. The second process, with the comparison of three different polygon union methods, results in a tie between the Unary Union and Cascaded Union, and both outperform the Overlay Union in terms of performance. Therefore, the Unary Union or Cascaded Union method is a fine choice for the second process to apply in RouteSegmentation.