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The time gap is defined as the time difference between the rear of a vehicle and the front of its follower, which affects both safety and the saturation flow rate of a roadway segment. In this study, naturalistic driving data were examined to measure time gaps from seven different drivers in a car-following scenario within steady-state conditions. The measurements were taken from a 13-km section of a Dulles Airport access road in Washington, DC. In total, 168,053 time gap samples were obtained covering seven speed intervals. Analysis of the data revealed a large variation in time gaps within individual drivers' driving data, with coefficients of variation as high as 63.8% observed for some drivers. Results also showed that the variability within drivers was more significant at speeds higher than 54 km/h. In addition, there was a large variability between drivers. At speeds above 108 km/h, minimum time gaps left by some drivers could be 1.6 times longer than those left by others. Several statistical distributions were used to fit the data of the seven drivers as well as the data for all drivers combined for each speed interval. The selected distributions passed the goodness-of-fit (Kolmogorov-Smirnov, Chi-square, and Anderson-Darling) criteria only when the number of samples was reduced. Data reduction was not performed randomly, but rather in a manner intended to maintain the same observed distribution when all the samples were used. It is therefore recommended that empirical measures of distributions be used in traffic microsimulation software rather than theoretically fit distributions obtained based on statistical tests. This will lead to better naturalistic traffic behavior simulations, resulting in more precise predicted measures of performance (travel time, fuel consumption, and gas emissions). [ABSTRACT FROM AUTHOR]

The paper develops an analytical formulation that quantifies the effect of vertical grade on vehicle fuel consumption and then illustrates the use of the developed procedure in the identification of the fuel efficient freeway layouts. Specifically, the Virginia Tech Comprehensive Power-based Fuel consumption Model (VT-CPFM) was used to develop the formulation and then applied using 2015's 10 most-sold vehicles in the U.S. and Europe to quantify the vertical grade effect on vehicle fuel consumption rates. An increase in fuel consumption of approximately 140% was found when the roadway grade increased from 0.5% to 6%. The proposed selection procedure uses Geographical Information System (GIS) applications in the design phase to evaluate possible freeway layouts. A multi-criteria analysis is performed to rank the feasible alternatives. The yearly fuel consumed by cars traveling on each feasible layout is then predicted and the alternatives are sorted in ascendingly. If the alternative selected by the multi-criteria analysis gives the least yearly fuel consumption, then that alternative should be constructed. If not, then the alternative that results in the least yearly fuel consumption should be re-evaluated with respect to the one selected by the multi-criteria analysis tool. The proposed procedure is validated using a real case study involving the construction of a new freeway in Cameroon. As much as a 12% difference in fuel consumption was found between the alternative with the least estimated yearly fuel consumption and that selected based on a multiple-criteria decision analysis. [ABSTRACT FROM AUTHOR]

One of the 12 instrumented sections of the Virginia Smart Road was used to compare measured vertical compressive stress and measured transverse horizontal strain under the hot-mix asphalt (HMA) layer induced by a 25.8 kN (5.8 kip) single tire and a 39.5 kN (8.9 kip) set of dual tires to those calculated using layered linear elastic theory. The pavement section is composed of 38 mm (1.5 in.) HMA wearing surface, 150 mm (6 in.) of HMA base mix, 75 mm (3 in.) of asphalt stabilized open graded drainage layer, 150 mm (6 in.) of cement stabilized aggregate layer, and 175 mm (7 in.) of unbound aggregate base. The subgrade is a fill material composed mainly of rocks. Measured stresses were obtained using pressure cells embedded in the pavement during construction. Horizontal transverse strain was measured using H-type strain gauges that were also embedded during construction. Temperature in the pavement layers was measured using embedded T-type thermocouples. Theoretically calculated stresses and strains were obtained using software based on the layered-elastic theory (Kenpave, Bisar 3.0, Elsym5, and Everstress 5.0). In addition, two finite-element approaches were used. Results indicated that the layered elastic theory overestimates pavement responses at low and intermediate temperatures, but significantly underestimates the pavement responses to vehicular loading at high temperatures. [ABSTRACT FROM AUTHOR]