A human-like game theory-based controller for automatic lane changing

By Hongtao Yu, H. Tseng, Reza Langari. 2018

301 citations recorded by the source corpus.

Subfields: Automotive Engineering, Computer Vision and Pattern Recognition, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/f8b3528822f1090da788cc1ce120b2977c90aa81

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

1. Ardalan Vahidi
2. Antonio Sciarretta

In Computer Vision and Pattern Recognition

1. Chen Lv
2. Yang Xing

In Control and Systems Engineering

1. Ardalan Vahidi
2. Antonio Sciarretta

Citations in the corpus

• Energy saving potentials of connected and automated vehicles (2018, background): “In (Yu et al., 2018) a game theoretic approach to automatic lane changing is proposed and is shown to outperform rule-based controllers.”
• Human-Like Decision Making for Autonomous Driving: A Noncooperative Game Theoretic Approach (2020, background): “A game theory-based lane-changing model is built in [25], which can make AV change lanes in a human-like manner.”