The geometric elements of the road, such as tangents and curves, play a vital role in road safety because significant crashes are reported on the horizontal curves and tangent-to-curve transitions. Literature reveals that inconsistent geometric design of roads violates driver's expectation of operating speed leading to crashes. For safe manoeuver, it is necessary to achieve consistent operating speed with road geometry based on the driver's expectations rather than the designer's perception. Estimation of reliable operating speeds in the design phase will help to design safer road alignments. Several past studies developed operating speed models on the curves and tangent-to-curve transitions. However, these models used spot speed data with the assumption that the constant speed persists on the horizontal curves and entire deceleration/acceleration occurs on the approach/departure tangents. In this study, an instrumented vehicle with a high-end GPS (global positioning system) device was used to obtain the continuous speed profiles for passenger cars which resulted in reliable and robust speed prediction models for a tangent, curve, and tangent-to-curve. The study also establishes a relationship between the differential of the 85th percentile speed ðΔV 85 Þ and 85th percentile speed differential ðΔ 85 VÞ. The analysis results revealed that ΔV 85 underestimates Δ 85 V by 5.32 km=h, and Δ 85 V predicted the actual speed reduction from tangent-to-curve transitions. Statistical analysis results showed low errors, variations, and strong correlation of the proposed models with the field data. The models developed in the present study were validated and compared with various other models available in the literature. The comparative study highlights the importance of using continuous speed profile data to calibrate the operating speed models.

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Several past studies developed acceleration/deceleration rate models as a function of a single explanatory variable. Most of them were spot speed studies with speeds measured at specific locations on curves (usually midpoint of the curve) and tangents to determine acceleration and deceleration rates. Fewer studies adopted an estimated value of 0.85 m/s2 for both deceleration and acceleration rates while approaching and departing curves, respectively. In this study, instrumented vehicles with a high-end GPS (global positioning system) device were used to collect the continuous speed profile data for two-lane rural highways. The speed profiles were used to locate the speeds at the beginning and end of deceleration/acceleration on the successive road geometric elements to calculate the deceleration/acceleration rate. The influence of different geometric design variables on the acceleration/deceleration rate was analysed to develop regression models. This study also inspeced the assumption of constant operating speed on the horizontal curve. The study results indicated that mean operating speeds measured at the point of curvature (PC) or point of tangency (PT), the midpoint of curve (MC), and the end of deceleration in curve were statistically different. Acceleration/deceleration rates as a function of different geometric variables improved the accuracy of models. This was evident from model validation and comparison with existing models in the literature. The results of this study highlight the significance of using continuous speed profile data to locate the beginning and end of deceleration/acceleration and considering different geometric variables to calibrate acceleration/deceleration rate models.