Taxi Hotspots Identification through Origin and Destination Analysis of Taxi Trips using K-means Clustering and H-indexing

Author:

Magsino Elmer R.,Abello Ara Jyllian,Lalusin Joaquin Miguel

Abstract

Abstract It is apparent that the taxi industry has grown and developed over the years. In addition to that, it will presumably continue to grow as time goes on due to the increasing popularity of taxi-hailing applications. However, taxi origin and destination (O-D) locations are not clearly established since taxis are very flexible in terms of where they can pick up and drop off passengers. In this study, the taxi origin and destination hotspots are determined by first clustering the available O-D pairs from empirical mobility traces. The validity of these formed clusters is determined by utilizing the silhouette analysis. Finally, hotspots are located by measuring the cluster’s h-index. Simulation results reveal that more clusters tend to provide unreliable silhouette values due to the fact that origin/destination GPS points are very close to each other. For a given number of clusters, the h-index tend to locate clusters that can be considered as hotspots.

Publisher

IOP Publishing

Subject

General Physics and Astronomy

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Game Theory-based Pricing Technique for Ridesharing Pairings;2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC);2023-01-23

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3. Evaluating Stable Matching Methods and Ridesharing Techniques in Optimizing Passenger Transportation Cost and Companionship;ISPRS International Journal of Geo-Information;2022-11-09

4. Demand-Based Deployment of Electric Vehicle Charging Stations Employing Empirical Mobility Dataset;Pervasive Computing and Social Networking;2022-09-02

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