# Robust Vehicle Lane Keeping Control with Networked Proactive Adaptation

arXiv: https://arxiv.org/abs/2009.12349 · HTML: https://mlsanity.com/paper/2009.12349/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Sep 2020.

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

- [Empirical Performance Evaluation of Lane Keeping Assist on Modern Production Vehicles](https://mlsanity.com/paper/2505.11534/) (2025)

## Abstract (arXiv)

Road condition is an important environmental factor for autonomous vehicle control. A dramatic change in the road condition from the nominal status is a source of uncertainty that can lead to a system failure. Once the vehicle encounters an uncertain environment, such as hitting an ice patch, it is too late to reduce the speed, and the vehicle can lose control. To cope with future uncertainties in advance, we study a proactive robust adaptive control architecture for autonomous vehicles' lane-keeping control problems. The data center generates a prior environmental uncertainty estimate by combining weather forecasts and measurements from anonymous vehicles through a spatio-temporal filter. The prior estimate contributes to designing a robust heading controller and nominal longitudinal velocity for proactive adaptation to each new abnormal condition. Then the control parameters are updated based on posterior information fusion with on-board measurements.