In view of the fact that a driver's smoking behavior seriously affects driving safety, feature pyramid network (FPN)-based identification method has been studied in order to reduce occurrence driver smoking. Most existing research focused on detection and recognition based movements while or smog characteristics. Therefore, probability misjudgment such methods is high, thus address this issue, ...

Human drivers have limited and time-varying cognitive resources when making decisions in real-world traffic scenarios, which often leads to unique stochastic behaviors that can not be explained by perfect rationality assumption, a widely accepted premise modeling driving presume rationally make maximize their own rewards under all circumstances. To explicitly address this disadvantage, study pr...

Drivers have unique and rich driving behaviors when operating vehicles in traffic. This paper presents a novel driver behavior learning approach that captures the uniqueness richness of human realistic scenarios. A stochastic inverse reinforcement (SIRL) is proposed to learn distribution cost function, which represents with given set driver-specific demonstrations. Evaluations are conducted on ...

overtaking a slow lead vehicle is a complex maneuver because of the variety of overtaking conditions and driver behavior. in this study, two novel prediction models for overtaking behavior are proposed. these models are derived based on multi-input multi-output adaptive neuro-fuzzy inference system (manfis). they are validated at microscopic level and are able to simulate and predict the future...

Experiments with the Fuzzy ACC under various traffic conditions have shown that the fuzzy approach is very robust especially with regard to the inevitable sensor noise. The modular architecture facilitates fine-tuning of the fuzzy controller for the different situation-specific components and minimizes interference of those components during operation. The approach to adaptation has two main go...