Evaluating The Platooning Parameters and Future Impacts of CAVs at Freeway Merging Segments

Abstract: Highway merging requires vehicles to adjust speed to safely join the main flow. Efficient merging is crucial as bottlenecks can reduce capacity, safety, and increase fuel consumption. Connected and Automated Vehicle (CAV) technologies are among the most heavily researched automotive technologies that offer solutions, using technologies like Adaptive Cruise Control (ACC) and Cooperative Adaptive Cruise Control (CACC) to improve safety and efficiency. CACC allows vehicles to maintain closer, safer gaps using V2V and V2I communication. Research has shown that CACC can increase lane capacity, with higher Market Penetration Rates (MPRs) leading to greater benefits. Studies predict significant CAV market penetration by 2034 and 2048, necessitating a clear understanding of CAV impacts for planning and decision-making. The vehicle technologies currently available are only a fraction of what is being developed for the future. Thus, it is important to evaluate the future impact of CAVs on freeway merging and assess their impact on our transportation system. By simulating mixed traffic scenarios, including conventional and automated vehicles, the study assessed the effects of CAVs at merge points. This research performed a sensitivity analysis on SAE International Level Four CAV platooning on freeway flow at merge bottleneck locations at the microscopic level. The proposed methodology explains how recently incorporated CAV platooning-parameters impact specific traffic engineering measures of effectiveness. The analysis assessed parameters include the intra-platoon headway, maximum platoon size, and desired platoon velocity. The sensitivity analysis was performed on various scenarios generated from varying the built-in driver behaviors (conservative, normal, and aggressive) and the Market Penetration Rates (MPRs). A four-lane freeway segment with a single-lane merge bottleneck, located on I-70 in Kansas City, MO, was coded and calibrated based on the available macroscopic data. Three hundred scenarios combined with the selected factors were run on the coded network. The results indicated that the MPR and intra-platoon headway were highly correlated with roadway travel time, delay, and throughput (capacity), where lower intra-platoon headways resulted in lower travel time and higher network throughput. Introducing CAVs in merging bottlenecks decreased the travel time and increased the throughput with safe merging from the on-ramp due to increasing V2V communication. This positive impact gradually increased with the increase of CAV MPR. In addition to the visual comparison, the Analysis of Variance (ANOVA) and Tukey’s test were used to investigate the differences in values for various performance measures. The research findings suggest that fully reaching 100% MPR of CAVs may be challenging in the near future. As a result, some assumptions about CAV driving behavior may need to be re-evaluated due to ongoing technological advancements. At a 100% CAV MPR, irregularities were observed, such as excessive queues forming on the on-ramp, preventing flow merging onto the freeway because of platooned vehicles on the shoulder lane. The study suggests that using lower intra-platoon headways than the pre-defined values in car-following models could encourage platooning and improve performance measures. This adjustment could enhance the benefits of platooning features rather than hinder them by slowing down freeway movement.