CPS: Breakthrough: Improving Metropolitan-Scale Transportation Systems with Data-Driven Cyber-Control

Principal Investigator(s):

Tian He, Former Professor, Computer Science and Engineering

Project summary:

The theory and practice of transportation sharing systems have typically focused on isolated, individual transportation modes. This project is collecting massive, multi-modal online feeds from metropolitan information infrastructure to model dynamic behaviors of transportation systems. The project is then utilizing massive, micro-level trip information to apply fine-grained, real-time control to handle rapid changes in dynamic metropolitan environments. General principles and design methodologies are being designed to build multi-modal, integrated urban transportation systems. These research discoveries will be applied toward commercial applications. The long-term deployment problem of bike stations is being addressed, especially in the low-income districts, to provide suggestions regarding the station deployment and assessment of specific deployment plans. The project also solves the short-term bike maintenance issue of balancing the usage of shared bikes to prevent quick deterioration of rental bikes and improving availability of bike rental services in real time. This project is also studying fleet-oriented ride sharing systems that decide fares based on real-time supply/demand ratio to handle dynamic metropolitan scenarios.

Project details:

  • Project number: 2017071
  • Start date: 07/2015
  • Project status: Completed
  • Research area: Planning and Economy