Evaluating the Potential of Connected and Autonomous Vehicles on Freeway Work Zone Capacity

Connected and autonomous vehicles (CAVs) can have a profound impact on work zone capacity by optimizing traffic flow, reducing congestion, and increasing overall capacity. However, there is a lack of studies specifically examining the effect of CAVs on work zone capacity. To address this gap, our study focuses on quantifying the influence of CAVs on work zone capacity using different market penetration rates.

Due to limited real-world CAV data, we conducted simulations to study the interaction between CAVs and traditional vehicles. Using VISSIM simulation software, we created a model of a work zone with a right lane closure on a 1-mile segment of California's I-10 EB corridor. The simulation model was calibrated and validated using flow and speed data collected from the Freeway Performance Measurement System (PeMS).

Through the gradual introduction of CAVs into the simulation with increasing penetration rates, ranging from 20% to 100%, we observed the impact on work zone capacity. The results were highly encouraging. With a 60% CAV penetration rate, we observed a significant 18.6% improvement compared to the base case without any CAVs. The maximum benefit of 36.4% was achieved when CAV penetration reached 100%.

These findings emphasize the potential of CAVs to alleviate congestion and minimize traveler delays in work zones. By leveraging their communication capabilities and seamless coordination with the work zone management system, CAVs can optimize traffic flow and maximize work zone capacity. This study significantly contributes to our understanding of the transformative role that CAVs can play in enhancing work zone operations and overall transportation efficiency.