Evaluation of Technology-enabled Opportunities for Transportation

Our research focuses on the design and optimization of service models in on-demand transportation systems, leveraging both steady-state analytical models and state-dependent dynamic programming techniques. We aim to capture and address the unique characteristics of these systems, including the stochastic nature of demand, the dynamic interactions between passengers and service providers, and the operational constraints faced by fleet operators. By considering the complex interplay among multiple stakeholders—such as passengers, drivers, platform operators, and regulators—we develop comprehensive frameworks to assess and improve system performance. Our work emphasizes balancing demand and supply to enhance service efficiency, minimize waiting times, and optimize resource allocation. Additionally, we provide decision-makers with robust analytical tools to evaluate system performance under various service designs, operational policies, and regulatory constraints, ultimately contributing to the development of more efficient, equitable, and sustainable on-demand transportation solutions.

Key capabilities:

• On-demand meal delivery services
• Ride-sourcing services
• Market equilibrium
• Dynamic pricing
• Autonomous vehicles