Multi-Modal Tripchain Planner for Disadvantaged Travelers to Incentivize Transit Usage

This research project aims to enhance accessibility and mobility for disadvantaged travelers by developing an artificial intelligence (AI)-powered multimodal tripchain planner. Current navigation solutions overlook the needs of people with mobility limitations, leading to challenges in accessing essential services. The proposed planner optimizes for multiple trips in a day, considering various modes and group-based travel preferences. Collaborating with partners like CoA, and Replica, the project tests the planner's reliability and effectiveness on real-world instances. Outputs include an open-source tripchain planner, behavioral models for Arlington users, survey data demonstrating data collection capabilities, and revenue management strategy evaluation. This initiative promotes equity and reduces congestion by facilitating transit ridership, mobility for all users, and car use reduction. Ultimately, the project advances equitable mobility, supported by stakeholder collaboration and AI-driven analytics, in alignment with U.S. Department of Transportation (USDOT) goals.


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Subject/Index Terms

Filing Info

  • Accession Number: 01897931
  • Record Type: Research project
  • Source Agency: Connected Communities for Smart Mobility Towards Accessible and Resilient Transportation for Equitably Reducing Congestion (C2SMARTER)
  • Contract Numbers: 69A3551747124
  • Files: UTC, RIP
  • Created Date: Oct 30 2023 10:56PM