| Abstract: |
| Connected and automated vehicles (CAV) allow for the generation and sharing of enriched data. When these data are collected and utilized, it presents opportunities to enhance operational strategies aimed at better managing and improving traffic flow and safety. This study aims to develop and evaluate advanced queue-informed and incident-aware ramp metering algorithms. The queue-informed algorithm uses more accurate on-ramp queue estimation from CAV data to smooth metering rates, while the incident-aware algorithm integrates feedforward control into feedback ramp metering for distant bottlenecks. These control strategies are evaluated at both local and system-wide levels using a simulation-based approach to assess their impact on highway mobility, safety, efficiency, and reliability. |
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