Modeling the Lane-Change Reactions to Merging Vehicles for Highway On-Ramp Simulations
<|reference_start|>Modeling the Lane-Change Reactions to Merging Vehicles for Highway On-Ramp Simulations: Enhancing simulation environments to replicate real-world driver behavior is essential for developing Autonomous Vehicle technology. While some previous works have studied the yielding reaction of lag vehicles in response to a merging car at highway on-ramps, the possible lane-change reaction of the lag car has not been widely studied. In this work we aim to improve the simulation of the highway merge scenario by including the lane-change reaction in addition to yielding behavior of main-lane lag vehicles, and we evaluate two different models for their ability to capture this reactive lane-change behavior. To tune the payoff functions of these models, a novel naturalistic dataset was collected on U.S. highways that provided several hours of merge-specific data to learn the lane change behavior of U.S. drivers. To make sure that we are collecting a representative set of different U.S. highway geometries in our data, we surveyed 50,000 U.S. highway on-ramps and then selected eight representative sites. The data were collected using roadside-mounted lidar sensors to capture various merge driver interactions. The models were demonstrated to be configurable for both keep-straight and lane-change behavior. The models were finally integrated into a high-fidelity simulation environment and confirmed to have adequate computation time efficiency for use in large-scale simulations to support autonomous vehicle development.<|reference_end|>
@article{holley2024modeling,
    title={Modeling the Lane-Change Reactions to Merging Vehicles for Highway
  On-Ramp Simulations},
    author={Dustin Holley, Jovin Dsa, Hossein Nourkhiz Mahjoub, Gibran Ali, Tyler
  Naes, Ehsan Moradi-Pari, Pawan Sai Kallepalli},
    journal={2024 IEEE Intelligent Vehicles Symposium (IV)},
    year={2024},
    doi={10.1109/IV55156.2024.10588857},
    archivePrefix={arXiv},
    eprint={2404.09851},
    primaryClass={cs.RO cs.SY eess.SY}
}