This paper investigates the potential changes in the geometric design elements in response to a fully autonomous vehicle fleet. When autonomous vehicles completely replace conventional vehicles, the human driver will no longer be a concern. Currently, and for safety reasons, the human driver plays an inherent role in designing highway elements, which depend on the driver’s perception-reaction time, driver’s eye height, and other driver related parameters. This study focuses on the geometric design elements that will directly be affected by the replacement of the human driver with fully autonomous vehicles. Stopping sight distance, decision sight distance, and length of sag and crest vertical curves are geometric design elements directly affected by the projected change. Revised values for these design elements are presented and their effects are quantified using a real-life scenario. An existing roadway designed using current AASHTO standards has been redesigned with the revised values. Compared with the existing design, the proposed design shows significant economic and environmental improvements, given the elimination of the human driver.

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Passing sight distance (PSD) is provided to ensure the safety of passing maneuvers on two lane two way roads. Many random variables determine the minimum length required for a safe passing maneuver. Current PSD design practices replace these random variables by single-value means in the calculation process, disregarding their inherent variations, which results in a single-value PSD design criteria. The main objective of the article is to derive a PSD distribution that accounts for the variations in the contributing random variables. Two models are devised, a Monte-Carlo simulation model used to obtain the PSD distribution and a closed form analytical estimation model used for verification purposes. The Monte-Carlo simulation model uses random sampling to select the values of the contributing parameters from their corresponding distributions in each run. The analytical model accounts for each parameter variation by using their means and standard deviations in a closed form estimation method. The means and standard deviations of the PSD using both models are compared for verification purposes. Both models use the same PSD formulation. The analysis is conducted for a design speed of 80 Km/h (50 mph). A PSD distribution is developed accordingly. The results of both models differ only by less than 2%. The obtained distribution is used to estimate the reliability index

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