Vanderbilt University developing AI software system to improve transit services for individuals with special needs

June 21, 2024
The research is based on work between the university and CARTA to improve the operation of the authority’s paratransit service.

Researchers at Vanderbilt University have developed an software system incorporating artificial intelligence (AI) that aims to improve the efficiency of public transportation for individuals with special needs.  

The research, led by Abhishek Dubey, associate professor of computer science and electrical and computer engineering at Vanderbilt University, will be presented in a paper at the International Joint Conference on Artificial Intelligence (IJCAI) in August.

The university says that in the paper, Dubey and his team discuss their work with the Chattanooga Area Regional Transportation Authority (CARTA) that started in 2020 to improve the operation of its paratransit service, a critical component of traditional transit services that offers door-to-door assistance for people who face challenges using standard transit routes. Pick-up and drop-off times for those individuals must also be adhered to under federal regulations.

According to the university, CARTA has struggled operationally because of decreasing ridership and increasing operational costs. To improve efficiency, the team developed a set of data-driven optimization modules that incorporates AI to handle online booking, day-ahead scheduling and real-time requests received by CARTA’s paratransit fleet for routes in the Chattanooga, Tenn., region. Recently, the team has also started running tests with a microtransit version of the system that will be open to the general public.

The university says that results from a test of the SmartTransit system that Dubey and his team developed showed significantly fewer detour miles and a higher percentage of trips with more than one passenger, thus reducing the total number of miles the vehicles must drive. Another area of improvement was in the generation of manifests, a sequence of pick-ups and drop-offs assigned to each vehicle.

“The CARTA operators revealed that the algorithm closely resembled the manifests generated by hand and even more crucial, the algorithm took a minute to generate the manifests, whereas CARTA operators took two weeks to generate the manifests by hand,” Dubey said. “To the best of our knowledge, this work presents one of the first examples of using open-source algorithmic approaches for paratransit optimization.”

David Rogers, a research engineer with the Institute for Software Integrated Systems and co-author of the research, said the system prioritizes the needs of dispatchers, drivers and riders.

“We maintain continuous communication with CARTA personnel to ensure our solutions are both practical and beneficial for all stakeholders,” Rogers said.

The system is continuing to be tested but Philip Pugliese, CARTA’s general manager of planning and grants, said its results are promising.

“The project has identified some key opportunities to improve service,” Pugliese said. “We look forward to continued development and implementation.”

Other Vanderbilt authors on the SmartTransit paper are Ayan Mukhopadhyay, Sophie Pavia, Jacob Buckelew and Samir Gupta. Vanderbilt University also collaborated with Professor Aron Laszka from Pennsylvania State University and Professor Samitha Samaranayake from Cornell University. CARTA’s Pugliese is also part of the team. The project was funded through a grant from the National Science Foundation. 

Recently, Dubey and another team won “Best Paper” at the 15th ACM/IEEE International Conference on Cyber-Physical Systems for work in the development of an AI system to help improve operations of the transit network in Nashville, Tenn.