A New Lane Keeping Method Based on Human-Simulated Intelligent Control

In this paper, a novel lane keeping control method for automated vehicles based on human-simulated intelligent control (HSIC) is proposed, which is inspired by human expert drivers' steering characteristics including good foresight, precise execution and notable intermittency. The novelty of the paper is to introduce the HSIC concept into lateral control of vehicles, which is a multi-mode control scheme implemented by the combination of the feedforward control for curve tracking and actand-wait control for intermittent error correction. Theoretically, the stabilization problem of the HSIC method is investigated based on the switched system related method. Experiments on the joint simulation platform of PreScan and CarSim show that the newly presented HSIC scheme has better matching performance to the expert driver and good robustness. For automated lane keeping systems, the HSIC method could provide human-like qualities, which may be one of the essential points to determine whether the driver is comfortable or not when the driver hands over the steering authority, improve the transition smoothness in the scenario of human vehicle co-piloting, and eliminate the potential conflicts between manual driving and automated driving vehicles in the future mixed traffic flow.

Automated summary

This paper introduces a novel lane keeping control method for automated vehicles based on human-simulated intelligent control (HSIC), which shows good matching performance with expert drivers and good robustness in experiments. The method could provide human-like qualities for automated lane keeping systems, which is essential for driver comfort, transition smoothness, and potential conflicts in mixed traffic flow scenarios.