Meta-Analysis of Adaptive Cruise Control Applications: Operational and Environmental Benefits

With the increasing adoption of adaptive cruise control (ACC) and development of cooperative adaptive cruise control (CACC), their effect on traffic, energy, and emissions is an ever more urgent question. Using the rapidly growing body of research on these impacts, this report presents a systematic review and meta-analysis of 67 recent studies. The majority were simulation studies with a few field tests. While the assumptions and methodology between studies in our review differ widely, a meta-analysis of maximum reported capacity improvements and fuel savings confirmed that CACC applications tend to increase capacity and fuel savings over manual driving due to shortened following time gaps and greater string stability from connectivity. In contrast, ACC applications do not always show capacity improvements, and if so, these improvements are more modest on average than for CACC systems. We found that ACC systems do, however, appear to smooth driving through less braking and reduced hard acceleration events such that fuel consumption is reduced, but not on average as much as CACC systems. With the increasing adoption of adaptive cruise control (ACC) and development of cooperative adaptive cruise control (CACC), their effect on traffic, energy, and emissions is an ever more urgent question. Using the rapidly growing body of research on these impacts, this report presents a systematic review and meta-analysis of 67 recent studies. The majority were simulation studies, with a few field tests also included. Our systematic review showed that research has shifted from ACC to CACC technologies over the past five years and many recent studies are focused on CACC. The following U.S. Department of Transportation report provides meta-analyses of ACC and CACC vehicle-following time gaps, roadway capacity improvements, and fuel savings under a broader automated vehicle benefits research program. The time gap from the lead vehicle to the following vehicle often factors into whether an automation system will achieve operational and environmental benefits compared to a human driver. In a meta-analysis of following time gaps across studies, CACC applications produced consistent time gap reductions, but the average of ACC time gaps was greater than the average gaps for naturalistic, manual driving. This potential increase in time gaps from CACC to ACC applications is most likely linked to drivers being more confident in the predictability of following a connected vehicle than a human-driven vehicle when they are not in control of their own acceleration or deceleration. While the assumptions and methodology between studies in our review differ widely, our meta-analyses of maximum reported roadway capacity improvements and fuel savings confirmed that CACC applications tend to increase capacity and fuel savings over manual driving. This is likely due to shortened time gaps and greater string stability resulting from connectivity. The CACC studies showed an increase in capacity (or observed throughput) ranging from 3 - 100%, with an average of 59%. In contrast, ACC studies did not always show capacity improvements, and if they did, these improvements were more modest on average than for CACC systems. Capacity changes ranged from -26 - 66% for ACC driving, with an average of 7%. On the other hand, ACC systems do, however, appear to smooth driving through less braking and reduced hard acceleration. The studies of ACC or CACC applications showed fuel savings in the range of nearly 30% 15 how CACC-equipped flow lane dedicated Their simulations predicted that at high penetration rates, the dedicated lane improve performance for all vehicles—not just those equipped Some studies compared ACC and CACC systems in stochastic microscopic traffic simulations or agent-based models ( 17 , 18 ). Shladover, Su, and Lu utilized AIMSUN to show that one lane with 100% penetration of CACC-equipped vehicles could double in throughput from approximately 2,000 to 4,000 vehicles per hour ( 17 ). The most recent simulations model CAVs in complex, real-world networks with observed speeds and traffic volumes by vehicle class. Shelton et al. modeled CACC vehicles on a 12-mile stretch of a congested urban interstate in Texas with multiple lanes and many entry and exit ramps . Their results suggest that the connected vehicles may form platoons that block other traffic from maneuvering, subsequently reducing throughput ( 19 ). Mattas et al. implemented a CACC model on the road ring network around Antwerp, Belgium to investigate the potential impacts at various penetration levels and several potential demand scenarios. The authors found that increasing levels of CACC penetration in all demand scenarios improved speed and delay metrics during rush hour and resulted in a faster return to free-flow after rush hour. However, congestion reduction did not necessarily correspond with decreased fuel consumption and emissions ( 20 ). This report presents a systematic review of 67 studies implementing ACC and CACC systems to evaluate operational and environmental benefits. We find the pace of publications has risen tremendously over the last three years, particularly for CACC studies. ACC publications seem to be lagging in spite of many manufacturers now shipping production vehicles with ACC functionality. This review is dominated by simulation studies. Field tests have been limited in scope, often occurring in controlled environments or on public roads with light congestion. More field testing in real traffic conditions is warranted, especially for CACC systems, to validate model results from the simulation studies. Network performance and environmental benefits are highly sensitive to the time gap between vehicles. On average, we find drivers accept the shortest time gap for CACC applications, most frequently at 0.6 seconds, likely from confidence in the predictable driving of the lead CACC vehicle. Manual driving usually leads to a slightly longer time gaps ranging from 0.8 - 1.6 s based on the studies reviewed, whereas ACC applications seem to be bimodal, which have either a gap setting 1.1 s to eliminate cut-in vehicles or a 1.5 s gap likely due to a lack in trust of the ACC system being able to stop in time. For these reasons, ACC driving appears to have a higher average time gap than manual driving in our meta-analysis. Additional evaluations of time gap acceptance between ACC and CACC driving would be useful. Our meta-analyses of maximum capacity improvements and fuel savings against manual driving suggest that CACC systems will perform better on average than ACC systems due to shorter time gaps and more stable strings. We observe that the longer time gaps and lack of connectivity for ACC translate to more modest capacity improvements than CACC. Though only four studies were considered, our findings also indicate some fuel savings for ACC applications from smoother driving with a reduction in braking and rapid accelerations. Real-world fuel consumption and emissions testing could confirm these environmental benefits.