Refine Your Search

Search Results

Viewing 1 to 2 of 2
Technical Paper

A Trajectory Planning Method for Different Drivers in the Curve Condition

Lane Centering Control System (LCCS) is a lateral Advanced Driving Assistance System (ADAS) with low acceptance. One of the main reasons is that the centering trajectory can’t satisfy different drivers, which is more obvious in the curve condition. So LCCS adaptive to different drivers needs to be designed. The trajectory planning module is an important part for LCCS. It generates trajectory according to the road information for the vehicle control module to track. This paper uses road information obtained from the scenario established in Prescan, and the trajectory planning method proposed can generate trajectories for different drivers in the curve condition. To achieve the goal, this paper proposes a trajectory planning method which contains lateral path planning and longitudinal speed planning. Firstly, the overall strategy of “road equidistant segments division” is used to describe the road information.
Technical Paper

Driver Lane Keeping Characteristic Indices for Personalized Lane Keeping Assistance System

In the recent years, the interaction between human driver and Advanced Driver Assistance System (ADAS) has gradually aroused people’s concern. As a result, the concept of personalized ADAS is being put forward. As an important system of ADAS, Lane Keeping Assistance System (LKAS) also attracts great attention. To achieve personalized LKAS, driver lane keeping characteristic (DLKC) indices which could distinguish different driver lane keeping behavior should be researched. However, there are few researches on DLKC indices for personalized LKAS. Although there are many researches on modeling driver steering behavior, these researches are not sufficient to obtain DLKC indices. One reason is that most of researches are for double lane change behavior which is different from driver lane keeping behavior. The other reason is that the researches on driver lane keeping behavior only provide model structure and rarely discuss identification procedure such as how to select suitable data.