Mandatory lane-changing decision and control method based on game theory
Zhe Wang, Xinyi Zhang, Haoze Ren, Liu Yang · 2026
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Description
Zhe Wang and co-authors propose a decision and control method for required lane changes by self-driving cars in a 2026 journal article. A mandatory lane change is forced by a lane ending, an obstacle, or a needed turn. Their framework uses game theory, which models how each driver reacts to others, with payoff scores for the self-driving car and vehicles behind it in the target lane.
The plan updates as nearby traffic responds, and a sliding mode controller, a robust steering method, tracks the planned path. Tracking error combines sideways drift and heading angle, held within preset limits. The team built a joint simulation platform with human drivers in the loop. Tests with three drivers of different styles gave early evidence on how the method behaves.
Catalog record
| CREATOR | Zhe Wang, Xinyi Zhang, Haoze Ren, Liu Yang |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 47605 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |