Connected and Automated Vehicle Data-Enhanced Ramp Metering Simulated on Corridor I-210 Reduced Travel Time by 12 Percent, Speed Variations by Five Percent, and Number of Stops on Mainline by 25 Percent.
The Ramp-Metering Simulation Case Study on I-210 Corridor in Los Angeles, California, Found Improvements in Mobility, Safety, Productivity and Efficiency.
Los Angeles, California, United States
Using Cooperative Automated Transportation Data for Freeway Operational Strategies
Summary Information
Cooperative Automated Transportation (CAT) involves the collaboration of all transportation system stakeholders to enhance safety, mobility, and efficiency through interconnected vehicle, infrastructure, and systems automation, enabled by data exchange. CAT data, generated and shared among connected and automated vehicles (CAVs), mobile devices, and connected infrastructure, is utilized by transportation management systems (TMS) to improve traffic flow and safety. This study aimed to improve freeway operational strategies by transmitting data between a TMS and the broader CAT system, either directly or via a third party. It developed use cases for 10 key strategies with high potential for improvement using CAT data: 1) Queue warning, 2) Ramp metering, 3) Dynamic route guidance, 4) Speed harmonization and lane control for a single lane, 5) Traffic incident management, 6) Integrated decision support and demand management, 7) Speed harmonization for an entire roadway, 8) Performance monitoring, 9) Variable pricing for a single lane, and 10) Variable pricing for an entire roadway. Using the I-210 corridor in Los Angeles, California, as a case study, the study developed, tested, and evaluated the effectiveness of incorporating CAT data to enhance ramp-metering strategies with data from 2019 in a traffic simulation model.
METHODOLOGY
The case study developed queue-informed and incident-aware enhanced ramp-metering algorithms with CAV data. The former enhanced algorithm employed more accurate on-ramp queue estimations derived from CAV data to regulate metering rates, the later addressed distant bottlenecks and offered more precise traffic information, including traffic flow, travel time, and density, surrounding incidents using CAV data. These control strategies were assessed at both local and systemwide levels using the simulation model of a 9.1 mile long I-210 corridor, developed in an open-source traffic simulation model with generated basic safety messages (BSMs) from simulated vehicle trajectories. The evaluation was conducted using four baseline scenarios and twelve alternatives consider CAV penetration rates, infrastructure deployment, communication and equipment errors, and GPS accuracy. The study assessed the impact of enhanced algorithms on freeway performance.
FINDINGS
The main findings of this simulation study included:
- Up to 12.4 percent corridor travel time savings and up to 13.5 percent travel time savings per vehicle.
- Up to 4.9 percent reduction in speed variation and up to 10.3 percent speed improvement.
- Up to 25.4 percent reduction in the number of stops per vehicle on the mainline.
- Slightly reduced saturation rate variations and reduced/maintained maximum saturation rate on the ramps.
- Marginal increase in throughput and slightly improved travel time reliability.
