Network-level analysis of the effects of drivers’ preferences toward driving behavior of Automated Vehicles: a microsimulation study on a highway segment

With the increasing prevalence of Level 2 and Level 3 Automated Vehicles (AVs) equipped with advanced technological features like Adaptive Cruise Control (ACC), the need to investigate their impact on traffic efficiency when sharing roads with Human-Driven Vehicles (HDVs) becomes crucial. The performance of these AVs (Level 2 and Level 3) primarily depends on the behaviour of users, as they prefer a similar or more defensive driving style when riding in AVs compared to their normal driving behaviour. Neglecting this diversity in the driving styles of AVs undermines the accuracy of the results of studies investigating their impact on traffic efficiency. Therefore, this study aimed to assess the impact of AVs on travel time, delay, and flow rate, considering the typical driving styles of drivers. We investigated a gradual increase in the penetration rate of AVs from 0% to 100% in 25% increments within a simulated mixed traffic environment of AVs and HDVs on a highway segment in the Veneto region, Italy, using the VISSIM microsimulation software. The results show that an increase in the penetration rates of AVs with different driving styles increases travel time (1.08% - 4.09%) and delay (13.22% - 99.28%) while exhibiting a negligible improvement in flow rate (0.09% - 0.26%).