TRAFFIC INSTABILITY THRESHOLDS AT FREEWAY OFF-RAMPS UNDER MIXED AUTONOMOUS-HUMAN VEHICLE FLOWS: ROLE OF AV BEHAVIORAL PROFILES
Abstract
Autonomous vehicles hold significant promise for improving urban traffic efficiency and reducing emissions; however, their impact on traffic stability at freeway off-ramps under mixed traffic conditions remains insufficiently understood. While existing studies have examined autonomous vehicle penetration rates in isolation, the interacting influence of autonomous vehicle behavioral profiles and traffic demand levels on instability at diverge zones has received limited attention. This study investigates traffic instability thresholds at the Eskisehir Road Golbasi Peripheral Road freeway off-ramp in Ankara, Turkiye, using Eclipse Simulation of Urban Mobility enhanced with the Traffic Control Interface application programming interface, which enables real-time per-vehicle behavioral parameter assignment, dynamic instability event detection, and high resolution data collection at 0.5-second intervals. A full factorial experiment comprising 195 simulation scenarios examined five autonomous vehicle penetration rates (0% to 100%), three behavioral profiles (conservative, moderate, and aggressive), and three demand levels (600, 1000, and 1400 veh/h). One-way analysis of variance confirmed that autonomous vehicle behavioral profile (F=35.84, p<0.001) and demand level (F=53.93, p<0.001) are the dominant determinants of traffic instability, while penetration rate alone produced no statistically significant effect (F=0.15, p=0.93). Aggressive autonomous vehicle profiles reduced instability by up to 62.7% and carbon monoxide emissions by up to 35.4% at high demand, whereas conservative profiles paradoxically increased instability by up to 110.7% and carbon monoxide emissions by up to 14.0% under the same conditions. These findings demonstrate that autonomous vehicle behavioral calibration represents a more decisive policy lever than fleet penetration rate alone, with direct implications for autonomous vehicle deployment strategies at freeway diverge zones.