|dc.description.abstract||This dissertation investigates two innovative applications of the Second Strategic Highway Research Program Naturalistic Driving Study (SHRP 2 NDS) data: (1) freeway interchange deceleration lane design and (2) work zone mobility analysis.
For freeway interchange deceleration lane design, the objective is to determine the minimum lengths of freeway deceleration lanes based on naturalistic driving speeds and deceleration rates from the SHRP 2 NDS database. SHRP 2 NDS has the distinct advantage of providing insight into driver behavior based on a wide-ranging collection of data regarding the driver, the vehicle, and the environment, whereas previous studies of this subject relied primarily on crash data, radar data, computer simulations, and driving simulators. Ten study locations that are located on I-75 in Florida with varying deceleration lane lengths and off-ramp lengths were used. The analysis included (1) speed distribution on different lengths of freeway deceleration lanes and off-ramps based on polynomial regression models; (2) drivers’ behavior, including brake pedal usage, critical speed change point detection, and the distribution of deceleration rates compared with the American Association of State Highway and Transportation Officials (AASHTO) Green Book assumptions; and (3) a new method to determine the minimum deceleration lane lengths based on naturalistic driving speeds and deceleration rates. The results revealed that (1) typically, vehicle speeds reduced by 10% to 25% on deceleration lanes while 75% to 90% on off-ramps; (2) deceleration rates on deceleration lanes and off-ramps before critical speed change points are lower than assumptions from the Green Book; and (3) deceleration lanes can be shorter when off-ramps are long at diamond interchanges (e.g., greater than 1,550 ft). The research results provided guidance to improve freeway deceleration lane design.
For freeway work zone mobility analysis, the objective is to study work zone mobility by utilizing the SHRP 2 NDS data. The NDS data provides a unique opportunity to study car-following behaviors for different driver types in various work zone configurations, which cannot be achieved through traditional field data collection. The complete NDS work zone trip data of 200 traversals by 103 individuals, including time-series data, forward-view videos, radar data, and driver characteristics, was collected at four work zone configurations (two-to-one and three-to-two lane closure, and two-to-two and three-to-three shoulder closure), which encompasses nearly 1,100 vehicle miles traveled (VMT), 19 vehicle hours traveled (VHT), and over 675,000 data points at 0.1-s intervals. First, the gap and headway were analyzed for different drivers (gender, age group, and risk perceptions) to develop the gap and headway selection tables. Then, the speed profiles for different work zone configurations were established to explore the speed change through the entire work zones. The generalized additive model (GAM) was used to develop the best-fitted curves of time headway and speed distributions. The change point detection method was used to identify where significant changes in mean and variance of speeds occur. The research results provided additional information on the potential impact of human factors on car-following models at work zones that have been implemented in current work zone planning and simulation tools. Additionally, it can also be helpful to improve the Adaptive Cruise Control (ACC) gap spacing setting at the work zone for the automotive industry.||en_US