CLR Analytics


Development of an ALINEA based coordinated ramp metering plugin

San Diego experiences significant traffic congestion during peak travel periods, has limited HOV and HOT lanes, and has limited transit capacity. Potential solution is to increase multi-jurisdictional and multi-agency collaboration on corridor management. The San Diego I-15 corridor was chosen as a site for Analysis, Modeling and Simulation (AMS) of Integrated Corridor Management (ICM) strategies. One strategy proposed by the study team is coordinated ramp metering control.

Caltrans District 11 proposed a coordinated ramp metering algorithm based on ALINEA control logic, which is a feedback ramp metering control logic originally proposed by Prof. Markos Papageorgiou in 1990s. A specific requirement for the algorithm is that it needs to work with the existing SDRMS ramp metering system, the ramp metering system deployed in San Diego, Sacramento, Riverside-San Bernardino areas.

Based on our extensive knowledge on ramp metering control and multiple literatures about the ALINEA algorithm, CLR Analytics further refined the proposed algorithm. As the consultant that reverse-engineered the SDRMS ramp metering algorithm and developed its plugin under TransModeler in Year 2009, we further implemented the algorithm as an additional module in the existing SDRMS plugin under TransModeler.

The developed plugin provides users with a user-friendly UI to set up various parameters of the metering control. The plugin will be used by the modelers in Cambridge Systematics to test how the improved algorithm can help decrease the traffic congestion for the I-15 corridor.

This study is a collaboration project with Cambridge Systematics, Caltrans District 11 and SANDAG.

Prime Contractor: Cambridge Systematics

Client: USDOT

Sponsor: California Department of Transportation

Time Period: Oct 2011-Nov 2011