Potential Game-Based Decision-Making for Autonomous Driving

no code implementations • 16 Jan 2022 • Mushuang Liu, Ilya Kolmanovsky, H. Eric Tseng, Suzhou Huang, Dimitar Filev, Anouck Girard

Statistical comparative studies, including 1) finite potential game vs. continuous potential game, and 2) best response dynamics vs. potential function optimization, are conducted to compare the performances of different solution algorithms.

Autonomous Driving Decision Making

Calibration of Human Driving Behavior and Preference Using Naturalistic Traffic Data

no code implementations • 5 May 2021 • Qi Dai, Di Shen, Jinhong Wang, Suzhou Huang, Dimitar Filev

Towards this end it is necessary that we have a comprehensive modeling framework for decision-making within which human driving preferences can be inferred statistically from observed driving behaviors in realistic and naturalistic traffic settings.

Autonomous Vehicles Decision Making

Towards a Systematic Computational Framework for Modeling Multi-Agent Decision-Making at Micro Level for Smart Vehicles in a Smart World

no code implementations • 25 Sep 2020 • Qi Dai, Xunnong Xu, Wen Guo, Suzhou Huang, Dimitar Filev

To demonstrate how our approach can be applied to realistic traffic settings, we conduct a simulation experiment: to derive merging and yielding behaviors on a double-lane highway with an unexpected barrier.

Autonomous Vehicles Computational Efficiency +1