Abstract
Data gathered during a 1996 Intelligent Cruise Control (ICC) Field Operational Test conducted in Michigan and sponsored by NHTSA were analyzed. The purpose was to evaluate driver deceleration and acceleration behavior at stop sign–controlled intersections on rural highways when the driver is unimpeded by a leading vehicle. A novel trip analysis technique was developed to scan the ICC data and identify 299 deceleration and 214 acceleration events at appropriate intersections, and a new mathematical model was used to evaluate those events. This model was used to compute the average rates of deceleration and acceleration for each of these events, and these average rates were compared for different subgroups (e.g., subgroups based on initial speed, final speed, driver gender, and type of street). The results indicate a strong and statistically significant dependence of the deceleration rate on the initial speed but little dependence of these rates on any of the other factors studied. The data indicate that there is a large, random component in the rate of deceleration or acceleration initiated by a driver. This result demonstrates the stochastic nature of driver deceleration and acceleration behavior, which may indicate a need to revisit how deceleration and acceleration rates are treated in common traffic calculations.
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