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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2403.16580 |
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| _version_ | 1866910882324283392 |
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| author | Ardizzoni, Stefano Laurini, Mattia Praxedes, Rafael Consolini, Luca Locatelli, Marco |
| author_facet | Ardizzoni, Stefano Laurini, Mattia Praxedes, Rafael Consolini, Luca Locatelli, Marco |
| contents | The behavior of cyclists when choosing the path to follow along a road network is not uniform. Some of them are mostly interested in minimizing the travelled distance, but some others may also take into account other features such as safety of the roads or pollution. Individuating the different groups of users, estimating the numerical consistency of each of these groups, and reporting the weights assigned by each group to different characteristics of the road network, is quite relevant. Indeed, when decision makers need to assign some budget for infrastructural interventions, they need to know the impact of their decisions, and this is strictly related to the way users perceive different features of the road network. In this paper, we propose an optimization approach to detect the weights assigned to different road features by various user groups, leveraging knowledge of the true paths followed by them, accessible, for example, through data collected by bike-sharing services. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_16580 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Identification of Cyclists' Route Choice Criteria Ardizzoni, Stefano Laurini, Mattia Praxedes, Rafael Consolini, Luca Locatelli, Marco Optimization and Control The behavior of cyclists when choosing the path to follow along a road network is not uniform. Some of them are mostly interested in minimizing the travelled distance, but some others may also take into account other features such as safety of the roads or pollution. Individuating the different groups of users, estimating the numerical consistency of each of these groups, and reporting the weights assigned by each group to different characteristics of the road network, is quite relevant. Indeed, when decision makers need to assign some budget for infrastructural interventions, they need to know the impact of their decisions, and this is strictly related to the way users perceive different features of the road network. In this paper, we propose an optimization approach to detect the weights assigned to different road features by various user groups, leveraging knowledge of the true paths followed by them, accessible, for example, through data collected by bike-sharing services. |
| title | Identification of Cyclists' Route Choice Criteria |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2403.16580 |