Feasibility study of highway alignment design controls for autonomous vehicles

Area of Science:

• Transportation Engineering
• Autonomous Systems
• Road Safety

Background:

• Current highway geometric design standards are based on human driver capabilities.
• Autonomous vehicle (AV) sensor technology, with ranges up to 250m, surpasses human perception.
• Existing road design controls may not be suitable for AVs due to differing perception-reaction times and sensor abilities.

Purpose of the Study:

• To investigate the feasibility of current highway geometric design controls for fully autonomous vehicles.
• To determine how AV sensor perception fields and perception-reaction times impact existing road design standards.
• To compare AV-specific design controls with those for human drivers.

Main Methods:

• Calculated design controls for vertical alignments and combined horizontal-vertical alignments for AVs.
• Incorporated AV perception-reaction time (PRT), sensor height, and upward angle into calculations.
• Derived required stopping sight distance (SSD) and minimum lengths for sag and crest vertical curves.
• Computed preview sight distance (PVSD) for combined alignments not adhering to Green Book guidelines.

Main Results:

• AV-based design controls for vertical curves are more tolerant than human-driver-based controls.
• Comfort emerged as the primary design criterion for sag vertical curves for AVs, unlike the SSD requirement for human drivers.
• Preview sight distance (PVSD) was a key consideration for combined alignments.

Conclusions:

• Existing geometric design standards need revision to accommodate autonomous vehicle capabilities.
• Autonomous vehicles offer potential for more efficient and potentially safer road designs.
• Future research should focus on optimizing road design for AVs based on their unique operational characteristics.