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December 11, 2025Journal of Autonomous Vehicles and Systems

Autonomous Vehicle Lane-Changing Decision-Making via Social Value Orientation and Cumulative Prospect Theory: Development, Parameter Identification, and Validation

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Authors

YYYanwen YangNNNatnael M. NegashJYJames Yang

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Overview

This model enhances decision-making in autonomous vehicles, improving F1 score and safety through dynamic parameter identification and validation.

Key Points

  • The study aims to develop a decision-making model for autonomous vehicle lane-changing that mimics human behavior and balances efficiency and safety.
  • Developed a lane-changing decision-making model integrating cumulative prospect theory and social value orientation.
  • Used the highD dataset for parameter identification and validation with two separate subsets.
  • Conducted comparative experimental analysis against traditional utility-based methods.
  • Model achieved an accuracy of 81.87% during testing.
  • F1 score was 79.05% for lane-changing and 74.56% for lane-keeping tasks.
  • G-mean of the model reached 76.41%, indicating improved performance in lane-changing scenarios.

Cite This Study

Yang et al. (2025) studied this question.

synapsesocial.com/papers/694019342d562116f28f6ee3https://doi.org/10.1115/1.4070633
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