An Initial Investigation of the Effects of a Fully Automated Vehicle Fleet on Geometric Design

Abstract

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.

Optimizing Road Networks for Automated Vehicles with Dedicated Links, Dedicated Lanes, and Mixed-Traffic Subnetworks

“…e first set of constraints for the upper level problem is the lower level problem defined by (1)- (12), which means the upper level should be evaluated when the lower level is at equilibrium. (15) shows how TTC is calculated based on equilibrium flows and costs obtained from the lower level problem. TAC in (16) is the summation of link adjustment costs for all subnetworks.…”

“…Rondinone et al [14] have discussed vehicle to infrastructure (V2I) communications to support cooperative automated driving. Khoury et al [15] have investigated the effects of a fully automated vehicle fleet on geometric design of roads. Lu et al [16] have provided lists of infrastructure requirements for AVs under four future scenarios based on expert opinion.…”

Visibility-Based Technologies and Methodologies for Autonomous Driving

“…For human-driven vehicles, the required sight distance is based on driver's perception-reaction time (PRT), vehicle speed, and other factors. A value of 2.5 s is used for human-driven vehicles and a value of 0.5 s has been assumed for AV in the literature [11]. This smaller reaction time will result in shorter required sight distances for AV.…”

“…Since the AV response time is less than the driver's PRT, the required SD for autonomous vehicles would be shorter than that for human-driven vehicles. The impact of AV on highway geometric design has been explored in a preliminary manner by making simple assumptions regarding system reaction time and Lidar field of view [11]. The study focused on SSD, DSD, and vertical curves.…”

The automated driver as a new road user

“…This occurs because camera-based detection of signage typically uses algorithms to manage exposure, and LED flicker causes oscillations in overall image brightness, leading to automated drivers incorrectly identifying LED traffic signs (IEEE P2020 Working Group, 2018. Automated driving has also been suggested to be a factor that lowers road construction costs (Khoury, Amine, & Saad, 2019). The reasoning behind this claim is the idea that an automated driver is assumed to have different characteristics than humans, including longer sight distances, which might allow for a more flexible road design that better suits the terrain, leading to less earthwork during road construction.…”