This project investigates the development and evaluation of an Arterial-Friendly Ramp (AF-Ramp) metering system to optimize freeway and arterial traffic flow near freeway on-ramps. The AF-Ramp system integrates realtime data to coordinate ramp metering and intersection signal plans within the ramp impact area. Its primary goal is to mitigate common traffic issues such as on-ramp queue spillbacks and freeway congestion by optimizing ramp metering rates and local traffic signals in unison. This report, focusing on Phase I of the project, documents the system’s enhancements for real-time operation and presents preliminary findings from simulations comparing the AF-Ramp system with conventional ramp metering models like ALINEA/Q. Results demonstrate the AF-Ramp system’s superior performance in maintaining throughput and minimizing congestion in various traffic scenarios. Key contributions include introducing a lane-group-based macroscopic traffic prediction model and a comprehensive control mechanism integrating freeway ramp and arterial signal coordination.
Universities Involved
University of Maryland, College Park
Principal Investigators
Dr. Gang-Len Chang
Yao Cheng
Funding Sources and Amounts
USDOT: $100,000
Start Date
September 1, 2023
Completion Date
September 1, 2024
Expected Research Outcomes & Impacts
The project intends to observe the system’s performance from its field operations with respect to its three key control objectives: (1) maximizing the freeway’s throughput under the optimized ramp metering rate; (2) preventing ramp queues from spilling over to its neighboring arterial; and (3) mitigating the potential mutual impedance between the arterial’s through traffic and its turning-flows to the ramp with the coordinated signal timings, variable phase sequences, and progression offsets.
Prior to use in practice, new control technology or systems must go through extensive tests, using field data feedback from target deployment locations for any necessary enhancements or refinements. With the results from this study, the AF-Ramp can certainly evolve its status from the academic work to a well-calibrated system ready for deployment on Maryland’s highway networks.
Subject Areas
Connected and Automated Vehicles, Intelligent Transportation Systems