Simulating the Impact of Autonomous Vehicles on Transportation Safety

In recent years, efforts have been made to use computer technologies in driving, including adaptive cruise control systems, parking assistance systems, and the construction of autonomous vehicles. Autonomous vehicles have enabled people without a driver's license, the disabled, and the elderly to travel safely. In this study, a decision-making control algorithm for autonomous vehicles has been developed and implemented in the Application Programming Interface (API) of the external driver model of the PTV VISSIM software. This algorithm is assigned to a specific class of vehicles in the simulation software and its performance has been tested on the Shahid Kasai Highway in Tabriz and a number of intersections in this city. Finally, the safety impact of CAVs at the corridor level has been evaluated using the Surrogate Safety Assessment Model (SSAM) to provide a more accurate understanding of the safety implications of this technology. The results showed that the reduction in collisions at 100% penetration rate ranged from 90 to 94%, which is close to the predicted safety benefits of CAVs, but these results should not be interpreted as equivalent to a similar reduction in crashes. The limited improvement from 75% to 100% penetration rate could be due to the formation of long CAV queues and reduced human-vehicle interactions. Overall, the percentage of collisions associated with autonomous vehicles is significantly lower than their market penetration rate.