Work

Evaluation of the Intersection Sight Distance at Stop-Controlled Intersections in a Mixed Vehicle Environment

Year: 2025

Type: article

Abstract: The introduction of autonomous vehicles (AVs) on roadways will result in a mixed vehicle environment consisting of these vehicles and manual vehicles (MVs). This vehicular environment will impact intersection sight distances (ISDs) due to differences in the driving behaviors of AVs and MVs. Currently, ISD design values for stop-controlled intersections are based on AASHTO’s guidelines, which account only for human driver behaviors. However, with AVs in the traffic stream, it is important to assess whether the existing MV-based ISDs are compliant when an AV is present at an intersecting roadway. Hence, this study utilizes the Monte Carlo Simulation method to compute the PNC of various object locations on the major and minor roadways for possible vehicle interaction types in a mixed vehicle environment at a stop-controlled intersection. Scenarios generated considered these variables and the major roadway speed limits and sight distance triangles (SDTs). ISD non-compliance was determined by examining the PNC metric, which occurred when the demand exceeded the supply. The results indicated that when AV–MV interaction was present at the intersection, the MV-based ISD design was non-compliant. However, it is possible to correct this non-compliance issue by reducing the AV speed limit.

Source: World Electric Vehicle Journal

DOI: 10.3390/wevj16050245

Authors: Jana Sarran, Sean Sarran

Institution: University of Guyana

Language: English

Topic: Traffic control and management

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $1,689