@inproceedings{wilbur2023mobility,
author = {Wilbur, Michael and Coursey, Maxime and Koirala, Pravesh and Al-Quran, Zakariyya and Pugliese, Philip and Dubey, Abhishek},
booktitle = {Proceedings of the ACM/IEEE 14th International Conference on Cyber-Physical Systems (with CPS-IoT Week 2023)},
title = {Mobility-On-Demand Transportation: A System for Microtransit and Paratransit Operations},
year = {2023},
address = {New York, NY, USA},
note = {demonstration},
pages = {260--261},
publisher = {Association for Computing Machinery},
series = {ICCPS '23},
contribution = {lead},
doi = {10.1145/3576841.3589625},
isbn = {9798400700361},
keywords = {ridepooling, software, mobility-on-demand, transit operations},
location = {San Antonio, TX, USA},
numpages = {2},
url = {https://doi.org/10.1145/3576841.3589625}
}
New rideshare and shared-mobility services have transformed urban mobility in recent years. Therefore, transit agencies are looking for ways to adapt to this rapidly changing environment. In this space, ridepooling has 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. This brings multiple challenges. 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. Therefore, we propose an on-demand transportation scheduling software for microtransit and paratransit services. This 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. Lastly, we discuss the challenges in adapting state-of-the-art methods to real-world operations.