Deploying Mobility-On-Demand for All by Optimizing Paratransit Services

Deploying Mobility-On-Demand for All by Optimizing Paratransit Services

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

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence
AI for Good. Pages 7430-7437. https://doi.org/10.24963/ijcai.2024/822

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.
Keywords:
Multidisciplinary Topics and Applications: General
Planning and Scheduling: General