Modeling the Lane-Change Reactions to Merging Vehicles for Highway On-Ramp Simulations
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arXiv
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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866910542912815104 |
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| author | Holley, Dustin Dsa, Jovin Mahjoub, Hossein Nourkhiz Ali, Gibran Naes, Tyler Moradi-Pari, Ehsan Kallepalli, Pawan Sai |
| author_facet | Holley, Dustin Dsa, Jovin Mahjoub, Hossein Nourkhiz Ali, Gibran Naes, Tyler Moradi-Pari, Ehsan Kallepalli, Pawan Sai |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_09851 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Modeling the Lane-Change Reactions to Merging Vehicles for Highway On-Ramp Simulations Holley, Dustin Dsa, Jovin Mahjoub, Hossein Nourkhiz Ali, Gibran Naes, Tyler Moradi-Pari, Ehsan Kallepalli, Pawan Sai Robotics Systems and Control 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. |
| title | Modeling the Lane-Change Reactions to Merging Vehicles for Highway On-Ramp Simulations |
| topic | Robotics Systems and Control |
| url | https://arxiv.org/abs/2404.09851 |