SmartTransit.AI: A Dynamic Paratransit and Microtransit Application

Conference · Sat Aug 03 04:00:00 EDT 2024

DOI:https://doi.org/10.24963/ijcai.2024/1028· OSTI ID:2583692

Pavia, Sophie; Rogers, David; Sivagnanam, Amutheezan; Wilbur, Michael; Edirimanna, Danushka; Kim, Youngseo; Mukhopadhyay, Ayan; Pugliese, Philip; Samaranayake, Samitha; Laszka, Aron; Dubey, Abhishek

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.

• Research Organization: National Energy Technology Laboratory; Vanderbilt University; Pennsylvania State University; Cornell University; Chattanooga Area Regional Transportation Authority
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office; National Science Foundation under grant
• DOE Contract Number: EE0009212
• OSTI ID: 2583692
• Country of Publication: United States
• Language: English