Abstract
While on-demand ride-sharing services have become popular in recent years, traditional on-demand transit services cannot be used by everyone, e.g., people who use wheelchairs. Paratransit services, operated by public transit agencies, are a critical infrastructure that offers door-to-door transportation assistance for individuals who face challenges in using standard transit routes. However, with declining ridership and mounting financial pressure, public transit agencies in the USA struggle to operate existing services. We collaborate with a public transit agency from the southern USA, highlight the specific nuances of paratransit optimization, and present a vehicle routing problem formulation for optimizing paratransit. We validate our approach using real-world data from the transit agency, present results from an actual pilot deployment of the proposed approach in the city, and show how the proposed approach comprehensively outperforms existing approaches used by the transit agency. To the best of our knowledge, this work presents one of the first examples of using open-source algorithmic approaches for paratransit optimization.
| 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 | 7430-7437 |
| Number of pages | 8 |
| 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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