Driver Behavior at a Freeway Merge to Mixed Traffic of Conventional and Connected Autonomous Vehicles

Abstract

Freeway merge ramps serve as one of the most challenging areas in traffic operations. This paper primarily focuses on creating a mixed traffic of conventional and connected/autonomous vehicles (CAVs) on freeways, and capturing driver behaviors both for the merging vehicle on the ramp and the freeway vehicles. The mixed distribution of vehicle headways of the freeway vehicles, developed based on various market penetration rates of the CAVs, was used to randomly generate vehicles through Monte Carlo simulation, and assigned as headways in a driving simulator. Based on perception, young drivers on the merge ramp were observed to choose critical headway gaps of 2.9 s, 1.8 s, and 1.7 s for freeway traffic of 0%, 50%, 75% penetration rates, respectively. For similar CAV penetration rates, the critical gaps observed for elderly drivers were 3.5 s, 2.0 s, and 1.9 s, respectively. When actually driving in the simulator, for the scenarios of 0% CAVs and 50% CAVs on the freeway, the values of average headway gaps accepted by young drivers were estimated as 2.36 s and 1.53 s, respectively. For the elderly drivers driving the simulator, the average headway gap values accepted were estimated as 2.72 s and 1.55 s, respectively, in the 0% and 50% penetration rates on the freeway traffic. Analyses of the speed profiles of the vehicles showed the effects of the acceleration/deceleration of merging vehicles, for both young and older drivers, on the freeway vehicles, including a few cases of collision. Overall, it was observed that the subject drivers accepted shorter headway gaps for increased CAV penetration levels.