Abstract
New rideshare and shared mobility services have transformed urban mobility in recent years. Such services have the potential to improve efficiency and reduce costs by allowing users to share rides in high-capacity vehicles and vans. Most transit agencies already operate various ridepooling services, including microtransit and paratransit. However, the objectives and constraints for implementing these services vary greatly between agencies and can be challenging. First, off-the-shelf ridepooling formulations must be adapted for real-world conditions and constraints. Second, the lack of modular and reusable software makes it hard to implement and evaluate new ridepooling algorithms and approaches in real-world settings. We demonstrate a modular on-demand public transportation scheduling software for microtransit and paratransit services. The software is aimed at transit agencies looking to incorporate state-of-the-art rideshare and ridepooling algorithms in their everyday operations. We provide management software for dispatchers and mobile applications for drivers and users and conclude with results from the demonstration in Chattanooga, TN.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024 |
| Editors | Kate Larson |
| Publisher | International Joint Conferences on Artificial Intelligence |
| Pages | 8767-8770 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781956792041 |
| State | Published - 2024 |
| Event | 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024 - Jeju, Korea, Republic of Duration: Aug 3 2024 → Aug 9 2024 |
Publication series
| Name | IJCAI International Joint Conference on Artificial Intelligence |
|---|---|
| ISSN (Print) | 1045-0823 |
Conference
| Conference | 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024 |
|---|---|
| Country/Territory | Korea, Republic of |
| City | Jeju |
| Period | 8/3/24 → 8/9/24 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
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