bike-share

Implementing and Evaluating Machine Learning Algorithms for Bikeshare System Demand Prediction

  • Principal Investigator Mehdi Azimi, Ph.D.
  • Texas Southern University
This research project will develop models for Houston bikeshare system demand prediction at the station level by leveraging data on station activities. Accurate prediction of bikeshare demand has the potential to transform the way these systems are managed and integrated into urban transportation networks, leading to improved efficiency, customer satisfaction, and sustainability.
Project Status
In Progress

Integrating Micromobility with Public Transit: A Case Study of the California Bay Area

Research Product Type
Research Report
This research covered environmental audits at 18 BART stations, an online survey of BART and micromobility users, and interviews with government, industry, and community stakeholders. Recommendations were made for: station design, including greater availability of shared micromobility vehicles, more affordable secure parking for personal micromobility, better signage and wayfinding, protected bike lanes and consistent design standards for bike facilities.