Analyzing Public Transport Wait Times and Identifying the Most Affected Users in the Metropolitan Area of Valparaíso, Chile
Public transportation wait times are a crucial factor influencing users’ perception of the system’s efficiency, their satisfaction, and their willingness to continue using these services. This study analyzes long wait times in public transportation and identifies the most affected users in the Metro...
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| Format: | Article |
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MDPI AG
2025-05-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/11/5969 |
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| author | Felipe González Vicente Aprigliano Sebastian Seriani Alvaro Peña |
| author_facet | Felipe González Vicente Aprigliano Sebastian Seriani Alvaro Peña |
| author_sort | Felipe González |
| collection | DOAJ |
| description | Public transportation wait times are a crucial factor influencing users’ perception of the system’s efficiency, their satisfaction, and their willingness to continue using these services. This study analyzes long wait times in public transportation and identifies the most affected users in the Metropolitan Area of Valparaíso, Chile. Using data from the Gran Valparaíso Mobility and Transportation Survey conducted by the Transportation Planning Secretariat (SECTRA) in 2014, only public transportation trips were selected, resulting in a dataset of 17,951 records. Exploratory data analysis techniques and Artificial Intelligence algorithms, such as DBSCAN clustering, were applied, as well as Moran’s Index for spatial autocorrelation, in order to identify patterns and groups of users experiencing prolonged wait times. The results show that certain demographic groups and specific geographic areas face longer wait times, negatively impacting equity and accessibility within the public transportation system. This study provides insights for improving transportation planning by identifying patterns and user groups that experience extended wait times, which can guide decisions to enhance user satisfaction and promote the use of public transportation. |
| format | Article |
| id | doaj-art-4ef151b9313e428199e3c48dab815247 |
| institution | OA Journals |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-4ef151b9313e428199e3c48dab8152472025-08-20T02:23:00ZengMDPI AGApplied Sciences2076-34172025-05-011511596910.3390/app15115969Analyzing Public Transport Wait Times and Identifying the Most Affected Users in the Metropolitan Area of Valparaíso, ChileFelipe González0Vicente Aprigliano1Sebastian Seriani2Alvaro Peña3Escuela de Ingeniería de Construcción y Transporte, Pontificia Universidad Católica de Valparaíso, Avda. Brasil, Valparaíso 2147, ChileEscuela de Ingeniería de Construcción y Transporte, Pontificia Universidad Católica de Valparaíso, Avda. Brasil, Valparaíso 2147, ChileEscuela de Ingeniería de Construcción y Transporte, Pontificia Universidad Católica de Valparaíso, Avda. Brasil, Valparaíso 2147, ChileEscuela de Ingeniería de Construcción y Transporte, Pontificia Universidad Católica de Valparaíso, Avda. Brasil, Valparaíso 2147, ChilePublic transportation wait times are a crucial factor influencing users’ perception of the system’s efficiency, their satisfaction, and their willingness to continue using these services. This study analyzes long wait times in public transportation and identifies the most affected users in the Metropolitan Area of Valparaíso, Chile. Using data from the Gran Valparaíso Mobility and Transportation Survey conducted by the Transportation Planning Secretariat (SECTRA) in 2014, only public transportation trips were selected, resulting in a dataset of 17,951 records. Exploratory data analysis techniques and Artificial Intelligence algorithms, such as DBSCAN clustering, were applied, as well as Moran’s Index for spatial autocorrelation, in order to identify patterns and groups of users experiencing prolonged wait times. The results show that certain demographic groups and specific geographic areas face longer wait times, negatively impacting equity and accessibility within the public transportation system. This study provides insights for improving transportation planning by identifying patterns and user groups that experience extended wait times, which can guide decisions to enhance user satisfaction and promote the use of public transportation.https://www.mdpi.com/2076-3417/15/11/5969waiting times in public transportationartificial intelligencecluster analysismetropolitan area of Valparaísospatial analysisDBSCAN |
| spellingShingle | Felipe González Vicente Aprigliano Sebastian Seriani Alvaro Peña Analyzing Public Transport Wait Times and Identifying the Most Affected Users in the Metropolitan Area of Valparaíso, Chile Applied Sciences waiting times in public transportation artificial intelligence cluster analysis metropolitan area of Valparaíso spatial analysis DBSCAN |
| title | Analyzing Public Transport Wait Times and Identifying the Most Affected Users in the Metropolitan Area of Valparaíso, Chile |
| title_full | Analyzing Public Transport Wait Times and Identifying the Most Affected Users in the Metropolitan Area of Valparaíso, Chile |
| title_fullStr | Analyzing Public Transport Wait Times and Identifying the Most Affected Users in the Metropolitan Area of Valparaíso, Chile |
| title_full_unstemmed | Analyzing Public Transport Wait Times and Identifying the Most Affected Users in the Metropolitan Area of Valparaíso, Chile |
| title_short | Analyzing Public Transport Wait Times and Identifying the Most Affected Users in the Metropolitan Area of Valparaíso, Chile |
| title_sort | analyzing public transport wait times and identifying the most affected users in the metropolitan area of valparaiso chile |
| topic | waiting times in public transportation artificial intelligence cluster analysis metropolitan area of Valparaíso spatial analysis DBSCAN |
| url | https://www.mdpi.com/2076-3417/15/11/5969 |
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