No abstract

Acceleration characteristics of passenger cars starting from rest are often used in traffic simulation, modeling of vehicle fuel consumption and emissions, and design of intersections, acceleration lanes for entrance terminals, turning bays, and passing lanes. Most of the previous studies developed four different acceleration models: the constant acceleration model, the two-phase model, the linear-decreasing acceleration model, and the polynomial acceleration model. However, most of the studies were based on outdated and limited data, so their conclusions may not be applicable for the current vehicle fleet and drivers. The normal acceleration behavior of current passenger vehicles starting from rest at all-way stop-controlled intersections is evaluated, and the previous acceleration models are verified with recent observations. A comparison is included between the acceleration behaviors of straight and turning maneuvers and the influence of speed limits on acceleration rates, and two new polynomial models are developed for driver acceleration behavior for turning maneuvers versus straight maneuver acceleration from a stopped condition.

The results suggest that institutions should provide more alternative models of success and increase flexible work options. Future studies of women in academic medicine should explore the role of value conflict in career development in academic medicine and probe the idea that the priorities articulated by the women in these focus groups may reflect the values of a generation as much as they do gender.

The Georgia Institute of Technology is evaluating the feasibility and effectiveness of mileage-based pricing programs as transportation control measures. Incentives were provided to study participants who change driving behavior in response to cent per mile pricing (fixed pricing and pricing as a function of congestion level). In-vehicle Global Positioning System (GPS) devices were used to estimate distance traveled and driver behavior (e.g., speed and acceleration profiles). The accuracy of estimated mileage accrual speeds by road classification, and acceleration rates used in pricing algorithms, is paramount. Various data-smoothing techniques were applied to the instrumented vehicle GPS speed data, and performance of the algorithms was evaluated in minimizing the impact of GPS random error on speed, acceleration, and distance estimates. The conventional discrete Kalman filter algorithm was modified to enhance its ability to control GPS random errors. Each smoothing method produces different second-by-second speed and acceleration profiles ( t-test and χ2 tests) except for the Kalman filters. The techniques provided different travel distance estimates, but the modified Kalman filter was the most accurate compared with distance estimates from the onboard vehicle speed sensor monitor. The modified Kalman filter is the recommended technique for smoothing GPS data for use in pricing studies. Additional smoothing methods will be evaluated as they are identified.