Mixed-Traffic impacts of CAVs: A reproducible benchmark and Multi-Aspect evaluation framework for freeway corridors

As connected and automated vehicles (CAVs) become more prevalent, quantifying their system-level impacts in realistic mixed traffic is critical. This paper releases a reproducible benchmark and evaluation framework for longitudinal CAV control in mixed traffic simulation. We evaluate four representative longitudinal controllers across two freeway scenarios: an on-ramp corridor and a calibrated Interstate-24 corridor. Outcomes are assessed consistently from four metrics: safety, throughput and stability, fuel consumption, and interactions with other drivers. The simulation analysis proceeds in three layers: comparison of controllers, market penetration analysis, and explanation of unmodeled effects. Results show that various controllers have distinct traffic impact based on their modeling principles. Generally speaking, higher CAV penetration consistently improves throughput and stability across all controllers, but safety and fuel consumption metrics may have subtle variations across controllers and scenarios. This subtlety can be captured by our comprehensive evaluation framework where the interplay across all four metrics can be quantified. Overall, the framework provides a reproducible and extensible simulation platform for assessing any custom CAV control in various traffic scenarios.