Feasibility study of highway alignment design controls for autonomous vehicles

In recent years, the development and testing of autonomous driving technology have become widespread around the world. However, due to differences in perception abilities between autonomous vehicles and human drivers, the current geometric design controls for highway alignments, designed for the human driver, may not be applicable to the autonomous vehicle (AV). Few studies, however, have systematically investigated the design controls for autonomous vehicles, though we face full driving automation in the next few decades. Because the range of modern AV sensors reaches 250 m, with expected further improvements in the near future, there is a need to determine how the sensors' perception field and perception-reaction time may affect the current road design standards developed for human drivers. This study therefore tested the feasibility of the current design controls for fully-autonomous vehicles by separately computing controls for vertical alignments and combined horizontal and vertical alignments, considering the AV's perception abilities of perception-reaction time (PRT), sensor height, and upward angle from the horizontal. The required stopping sight distance (SSD) and minimum length of sag and crest vertical curves were derived and compared with those for human drivers. Computations for combined alignments were based on Green Book coordination guidelines: as the minimum length of horizontal curve can be used for alignments adhering to guidelines, preview sight distance (PVSD) was computed for alignments that do not. Results showed that 1) AV-based design controls on vertical curves were more tolerant than those based on human drivers; and 2) the dominating criterion of sag vertical curve design control was comfort for autonomous vehicles, versus required SSD for human drivers.