An Activity-Based Travel Personalization Tool Driven by the Genetic Algorithm
The necessity for an external control mechanism that optimizes daily urban trips becomes evident when considering numerous factors at play within a complex environment. This research introduces an activity-based travel personalization tool that incorporates 10 travel decision-making factors driven b...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi-Wiley
2023-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2023/6678628 |
| _version_ | 1797660115811172352 |
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| author | Ali Enes Dingil Domokos Esztergár-Kiss |
| author_facet | Ali Enes Dingil Domokos Esztergár-Kiss |
| author_sort | Ali Enes Dingil |
| collection | DOAJ |
| description | The necessity for an external control mechanism that optimizes daily urban trips becomes evident when considering numerous factors at play within a complex environment. This research introduces an activity-based travel personalization tool that incorporates 10 travel decision-making factors driven by the genetic algorithm. To evaluate the framework, a complex artificial scenario is created comprising six activities in a daily plan. Afterwards, the scenario is simulated for predefined user profiles, and the results of the simulation are compared based on the users’ characteristics. The simulations of the scenario successfully demonstrate the appropriate utilization of activity constraints and the efficient implementation of users’ spatiotemporal priorities. In comparison to the base case, significant time savings ranging from 31.2% to 70.2% are observed in the daily activity chains of the simulations. These results indicate that the magnitude of time savings in daily activity simulations depends on how users assign values to the travel decision-making parameters, reflecting the attitudinal differences among the predefined users in this study. This tool holds promise for advancing longitudinal travel behavior research, particularly in gaining a more profound understanding of travel patterns. |
| first_indexed | 2024-03-11T18:25:46Z |
| format | Article |
| id | doaj.art-7a2f4be2c52446afa289ffbc2ae460ee |
| institution | Directory Open Access Journal |
| issn | 2042-3195 |
| language | English |
| last_indexed | 2024-03-11T18:25:46Z |
| publishDate | 2023-01-01 |
| publisher | Hindawi-Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj.art-7a2f4be2c52446afa289ffbc2ae460ee2023-10-14T00:00:04ZengHindawi-WileyJournal of Advanced Transportation2042-31952023-01-01202310.1155/2023/6678628An Activity-Based Travel Personalization Tool Driven by the Genetic AlgorithmAli Enes Dingil0Domokos Esztergár-Kiss1LAMbDA Lab (λ)Faculty of Transportation and Vehicle EngineeringThe necessity for an external control mechanism that optimizes daily urban trips becomes evident when considering numerous factors at play within a complex environment. This research introduces an activity-based travel personalization tool that incorporates 10 travel decision-making factors driven by the genetic algorithm. To evaluate the framework, a complex artificial scenario is created comprising six activities in a daily plan. Afterwards, the scenario is simulated for predefined user profiles, and the results of the simulation are compared based on the users’ characteristics. The simulations of the scenario successfully demonstrate the appropriate utilization of activity constraints and the efficient implementation of users’ spatiotemporal priorities. In comparison to the base case, significant time savings ranging from 31.2% to 70.2% are observed in the daily activity chains of the simulations. These results indicate that the magnitude of time savings in daily activity simulations depends on how users assign values to the travel decision-making parameters, reflecting the attitudinal differences among the predefined users in this study. This tool holds promise for advancing longitudinal travel behavior research, particularly in gaining a more profound understanding of travel patterns.http://dx.doi.org/10.1155/2023/6678628 |
| spellingShingle | Ali Enes Dingil Domokos Esztergár-Kiss An Activity-Based Travel Personalization Tool Driven by the Genetic Algorithm Journal of Advanced Transportation |
| title | An Activity-Based Travel Personalization Tool Driven by the Genetic Algorithm |
| title_full | An Activity-Based Travel Personalization Tool Driven by the Genetic Algorithm |
| title_fullStr | An Activity-Based Travel Personalization Tool Driven by the Genetic Algorithm |
| title_full_unstemmed | An Activity-Based Travel Personalization Tool Driven by the Genetic Algorithm |
| title_short | An Activity-Based Travel Personalization Tool Driven by the Genetic Algorithm |
| title_sort | activity based travel personalization tool driven by the genetic algorithm |
| url | http://dx.doi.org/10.1155/2023/6678628 |
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