# A Mixed-Logical-Dynamical model for Automated Driving on highways

arXiv: https://arxiv.org/abs/1803.10678 · HTML: https://mlsanity.com/paper/1803.10678/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Mar 2018.

## Built on by (most cited first, 1 of 1)

- [Human-aligned Safe Reinforcement Learning for Highway On-Ramp Merging in Dense Traffic](https://mlsanity.com/paper/2503.02624/) (2025)

## Abstract (arXiv)

We propose a hybrid decision-making framework for safe and efficient autonomous driving of selfish vehicles on highways. Specifically, we model the dynamics of each vehicle as a Mixed-Logical-Dynamical system and propose simple driving rules to prevent potential sources of conflict among neighboring vehicles. We formalize the coordination problem as a generalized mixed-integer potential game, where an equilibrium solution generates a sequence of mixed-integer decisions for the vehicles that trade off individual optimality and overall safety.