Researchers at the University of Michigan's Transportation Research Institute have recently completed a study of adaptive cruise control (ACC) in traffic streams. To augment performance of ACC, the study focused on developing an understanding of driver-control of range- clearance and time-gap. The first phase of research involved the development of data acquisition and data analysis measures. These measures related to the observed behavior of vehicles outfitted with ACC in response to changes in speed and location of preceding vehicles. The second phase looked at nonlinear driving modeling, a key component of programs aimed at exploring the influence of ACC systems on traffic flow that has both ACC-equipped vehicles and vehicles without ACC. Results of the study indicated that capacity and flow sustainability are heavily dependent on the characteristics of individual drivers. However, the study also indicated that in general drivers operate with limited accuracy in perceiving range, range-rate, and velocity. Fluctuations in drivers' stress levels also causes variation in performance. Research showed that ACC systems can significantly influence traffic flow. Driver-modeling work enhances researchers' ability to predict and evaluate results for mixed traffic pertaining both to ACC and manually controlled vehicles.
Abstract