# Optimizing Autonomous Taxi Deployment for Safety at Skewed Intersections: A Simulation Study

## TL;DR

This study uses simulations to find the best way to deploy autonomous taxis at skewed intersections to improve safety.

## Contribution

The study identifies an optimal penetration rate and control strategies for autonomous taxis at skewed intersections.

## Key findings

- An optimal autonomous taxi penetration rate of 0.5–0.7 maximizes safety metrics like TTC and PET.
- Connectivity among autonomous taxis does not linearly improve safety.
- The 'Normal' control strategy shows a direct link between taxi penetration and TTC.

## Abstract

This study optimizes the deployment of autonomous taxis for safety at skewed intersections through a simulation-based approach, identifying an optimal penetration rate and control strategies. Here, we investigate the safety impacts of autonomous taxis (ATs) at such intersections using a simulation-based approach, leveraging the VISSIM traffic simulation tool and the Surrogate Safety Assessment Model (SSAM). Our study identifies an optimal AT penetration rate of approximately 0.5–0.7, as exceeding this range may lead to a decline in safety metrics such as TTC and PET. We find that connectivity among ATs does not linearly correlate with safety improvements, suggesting a nuanced approach to AT deployment is necessary. The “Normal” control strategy, which mimics human driving, shows a direct proportionality between AT penetration and TTC, indicating that not all levels of automation enhance safety. Our conflict analysis reveals distinct patterns for crossing, lane-change, and rear-end conflicts under various control strategies, underscoring the need for tailored approaches at skewed intersections. This research contributes to the discourse on AT safety and informs the development of traffic management strategies and policy frameworks that prioritize safety and efficiency in the context of skewed intersections.