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

被引：0

作者：

Pavia, Sophie ^{[1
]}

Rogers, David ^{[1
]}

Sivagnanam, Amutheezan ^{[2
]}

Wilbur, Michael ^{[1
]}

Edirimanna, Danushka ^{[3
]}

Kim, Youngseo ^{[3
]}

Pugliese, Philip ^{[4
]}

Samaranayake, Samitha ^{[3
]}

Laszka, Aron ^{[2
]}

Mukhopadhyay, Ayan ^{[1
]}

Dubey, Abhishek ^{[1
]}

机构：

[1] Vanderbilt Univ, Nashville, TN 37235 USA

[2] Penn State Univ, University Pk, PA USA

[3] Cornell Univ, Ithaca, NY USA

[4] Chattanooga Area Reg Transportat Author, Chattanooga, TN USA

来源：

PROCEEDINGS OF THE THIRTY-THIRD INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, IJCAI 2024 | 2024年

基金：

美国国家科学基金会;

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

While on-demand ride-sharing services have become popular in recent years, traditional ondemand 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 opensource algorithmic approaches for paratransit optimization.

引用

页码：7430 / 7437

页数：8