Why This Matters

Paratransit services are critical for accessibility but face significant operational challenges due to complex constraints not present in traditional ridesharing. Existing commercial systems are often inflexible and fail to adapt to real-world conditions, while research algorithms are difficult to deploy in practice. This work is innovative because it bridges this gap by creating a modular software system that can accommodate different algorithmic approaches and constraints specific to transit agencies, while also providing human operators the ability to override and validate system recommendations.

What We Did

This work develops a software framework and routing application for paratransit and microtransit services operating in urban environments. The SmartTransit.AI system integrates multiple ridesharing algorithms including both day-ahead optimization for planned trips and real-time dynamic vehicle routing problem solvers. The framework provides operational interfaces for dispatchers, a vehicle operator mobile application, and a user-facing booking interface. The system incorporates state-of-the-art algorithms while addressing practical constraints like time windows, vehicle capacity limitations, and service accessibility requirements.

Key Results

The deployed system demonstrates substantial operational improvements when tested with real paratransit data, showing significantly higher shared ride rates and reduced vehicle miles compared to baseline approaches. Pilot testing in Chattanooga, Tennessee with the Chattanooga Area Regional Transportation Authority validates the system's ability to improve both efficiency and service quality in a real operational environment. The results show clear benefits in reducing operational costs while maintaining service accessibility.

Full Abstract

Cite This Paper

@inproceedings{paviaIJCAI24AISG,
  author = {Pavia, Sophie and Rogers, David and Sivagnanam, Amutheezan and Wilbur, Michael and Edirimanna, Danushka and Kim, Youngseok and Pugliese, Philip and Samaranayake, Samitha and Laszka, Aron and Mukhopadhyay, Ayano and Dubey, Abhishek},
  booktitle = {Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence},
  title = {Deploying mobility-on-demand for all by optimizing paratransit services},
  year = {2024},
  series = {IJCAI '24},
  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.},
  articleno = {822},
  contribution = {lead},
  acceptance = {15},
  doi = {10.24963/ijcai.2024/822},
  isbn = {978-1-956792-04-1},
  location = {Jeju, Korea},
  numpages = {8},
  url = {https://doi.org/10.24963/ijcai.2024/822},
  keywords = {paratransit optimization, microtransit, vehicle routing, shared mobility, transportation dispatch, accessibility, real-time optimization, mobility-on-demand}
}
Quick Info
Year 2024
Series IJCAI '24
Keywords
paratransit optimization microtransit vehicle routing shared mobility transportation dispatch accessibility real-time optimization mobility-on-demand
Research Areas
transit energy planning scalable AI middleware
Search Tags

Deploying, mobility, demand, optimizing, paratransit, services, paratransit optimization, microtransit, vehicle routing, shared mobility, transportation dispatch, accessibility, real-time optimization, mobility-on-demand, transit, energy, planning, scalable AI, middleware, 2024, Pavia, Rogers, Sivagnanam, Wilbur, Edirimanna, Kim, Pugliese, Samaranayake, Laszka, Mukhopadhyay, Dubey, IJCAI24