• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.4
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• pp.13-27
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• 2021

In this study, the impact of traffic flow on the market penetration rate of autonomous vehicles(AV) was analyzed using the data for the year 2020 of the Yongin IC~Yangji IC section of Yeongdong Expressway. For this analysis, a microscopic traffic simulation model VISSIM was utilized. To construct the longitudinal control of the AV, the Intelligent Driver Model(IDM) was built and applied, and the driving behavior was verified by comparison with a normal vehicle. An examination of the study results of mobility and safety according to the market penetration rate of the AV, showed that the network's mobility improves as the market penetration rate increases. However, from the point of view of safety, the network becomes unstable when normal vehicles and AVs are mixed, so there should be a focus on traffic management for ensuring safety in mixed traffic situations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.42-60
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• 2024

This study analyzed the characteristics of mixed traffic flows with autonomous vehicles on highway weaving sections and assessed the safety of vehicle-following pairs based on surrogate safety indicators. The intelligent driver model (IDM) was utilized to emulate the driving behavior of autonomous vehicles, and the weaving sections were divided into lengths of 300 and 600 meters for analysis within a micro-traffic simulation (VISSIM). Although significant differences were found in the average speed, density, and headway between the two sections through t-test results, no significant differences were observed when comparing the number of conflicts per indicator and the vehicle-following pair. Four safety indicators were selected for the mixed traffic evaluation based on their ability to represent risk levels similar to those perceived by drivers. The safety analysis, based on the selected four indicators, determined that autonomous vehicles following other autonomous vehicles were the safest pairing. Future research should focus on integrating these indicators into a single comprehensive index for analysis.