CAIT project no.: CAIT-UTC-REG26
Fiscal Year: 2018/2019
Status: Final
Principal investigator(s): Xiang Liu, Ph.D., Rutgers
Performing organization(s): Rutgers CAIT
Managing organization: Rutgers CAIT
In cooperation with: NJ Transit Corporation
Partner project manager: Brad Mason, Director, Capital Resiliency and Continuity
Supported by: USDOT-OST-R
UTC, grant, or agreement no.: 69A3551847102
Passenger flow is a very important parameter for understanding how passengers interact with built infrastructure. The primary goal of this proposal is to model and simulate passenger flows in transit stations using computer vision and agent-based simulation technologies.
The information generated during the performance of this project can potentially be used by NJ Transit to understand the benefit of infrastructure design or upgrade in terms of changing passenger flow and reducing congestion.