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  • Summary & Details

Verification of Effectiveness of Traffic Management by CACC on Highway Merging Using Networked Driving Simulator with Ten Human Drivers

Detailed Information

Category(E)Research paper
Author(E)1) Tohru Yoshioka, 2) Keisuke Suzuki, 3) Hironori Suzuki, 4) Jun Tajima
Affiliation(E)1) Mazda Motor Corporation / Kagawa University, 2) Kagawa University, 3) Toyo University, 4) Misaki Design, LLC
Abstract(E)Personal mobility supports social participation and well-being, yet highway merging remains stressful and risky. Driving behavior is influenced by prediction errors between actual traffic and drivers' predictions. We hypothesized that designing traffic environments to improve driver prediction accuracy can effectively assist drivers. We previously proposed position-triggered speed management using Cooperative Adaptive Cruise Control (CACC) vehicles near highway merging sections to smooth merging by reducing speed differentials between merging and mainline vehicles. However, empirical validation of speed differentials' impact on drivers' merging experience was lacking due to no methods for evaluating human interactions in mixed traffic involving human-driven vehicles (HDVs) and CACC vehicles. To address this, we developed a networked multi-driver driving simulator (NMDDS) allowing ten participants to interact in a virtual merging environment, essential for studying complex driver dynamics in real traffic. Experimental results showed CACC speed management effectively moderated mainline HDV speeds near merging sections, with effectiveness depending on CACC penetration rate. We clarified how personality traits relate to subjective evaluations like perceived danger and merging difficulty. Structural Equation Modeling (SEM) also indicated relative speed between merging and mainline vehicles significantly influences these factors. These findings empirically support that reducing speed differentials improves merging comfort and safety. Future research will implement methods to further minimize speed differentials, including managing merging vehicle speeds and refining adaptive speed control strategies, aiming to enhance safety and driver intuitiveness during highway merging.

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