This study quantifies the main characteristics of a terrain-following, G-coordinate through mathematical analyses of its covariant and contravariant basis vectors as well as the vertical coordinate of σ. A 3-D schema...This study quantifies the main characteristics of a terrain-following, G-coordinate through mathematical analyses of its covariant and contravariant basis vectors as well as the vertical coordinate of σ. A 3-D schematic of the σ-coordinate in a curvilinear coordinate system is provided in this study. The characteristics of the basis vectors were broken down into their ＂local vector charac- teristics＂ and ＂spatial distribution characteristics＂, and the exact expressions of the covariant; in addition, the con- travariant basis vectors of the G-coordinate used to eluci- date their detailed characteristics were properly solved. Through rewriting the expression of the vertical coordi- nate of G, a mathematical expression of all the cr-coor- dinate surfaces was found, thereby quantifying the so- called terrain-following characteristics and lack of flexi- bility to adjust the slope variation of G-coordinate sur- faces for the classic definition of G. Finally, an analysis on the range value of the vertical coordinate demonstrated that the general value range of G could be obtained by eliminating the G-coordinate surfaces below the Earth＇s surface. All these quantitative descriptions of the charac- teristics of G-coordinate were the foundation for improv- ing the G-coordinate or creating a new one.展开更多
It is difficult to model human behavior because of the variability in driving styles and driving skills. However, for some driver assistance systems, it is necessary to have knowledge of that behavior to discriminate ...It is difficult to model human behavior because of the variability in driving styles and driving skills. However, for some driver assistance systems, it is necessary to have knowledge of that behavior to discriminate potentially hazardous situations, such as distraction, fatigue or drowsiness. Many of the systems that look for driver distraction or drowsiness are based on intrusive means （analysis of the electroencephalogram--EEG） or highly sensitive to operating conditions and expensive equipment （eye movements analysis through artificial vision）. A solution that seeks to avoid the above drawbacks is the use of driving parameters This article presents the conclusions obtained after a set of driving simulator tests with professional drivers with two main objectives using driving variables such as speed profile, steering wheel angle, transversal position on the lane, safety distance, etc., that are available in a non-intrusive way： （1） To analyze the differences between the driving patterns of individual drivers; and （2） To analyze the effect of distraction and drowsiness on these parameters. Different scenarios have been designed, including sequences with distractions and situations that cause fatigue. The analysis of the results is carried out in time and frequency domains in order to identify situations of loss of attention and to study whether the evolution of the analyzed variables along the time could be considered independent of the driver.展开更多
基金supported by the National Natural Science Foundation of China under Grant Nos. 40821092,40633016,and 40875022
文摘This study quantifies the main characteristics of a terrain-following, G-coordinate through mathematical analyses of its covariant and contravariant basis vectors as well as the vertical coordinate of σ. A 3-D schematic of the σ-coordinate in a curvilinear coordinate system is provided in this study. The characteristics of the basis vectors were broken down into their ＂local vector charac- teristics＂ and ＂spatial distribution characteristics＂, and the exact expressions of the covariant; in addition, the con- travariant basis vectors of the G-coordinate used to eluci- date their detailed characteristics were properly solved. Through rewriting the expression of the vertical coordi- nate of G, a mathematical expression of all the cr-coor- dinate surfaces was found, thereby quantifying the so- called terrain-following characteristics and lack of flexi- bility to adjust the slope variation of G-coordinate sur- faces for the classic definition of G. Finally, an analysis on the range value of the vertical coordinate demonstrated that the general value range of G could be obtained by eliminating the G-coordinate surfaces below the Earth＇s surface. All these quantitative descriptions of the charac- teristics of G-coordinate were the foundation for improv- ing the G-coordinate or creating a new one.
文摘It is difficult to model human behavior because of the variability in driving styles and driving skills. However, for some driver assistance systems, it is necessary to have knowledge of that behavior to discriminate potentially hazardous situations, such as distraction, fatigue or drowsiness. Many of the systems that look for driver distraction or drowsiness are based on intrusive means （analysis of the electroencephalogram--EEG） or highly sensitive to operating conditions and expensive equipment （eye movements analysis through artificial vision）. A solution that seeks to avoid the above drawbacks is the use of driving parameters This article presents the conclusions obtained after a set of driving simulator tests with professional drivers with two main objectives using driving variables such as speed profile, steering wheel angle, transversal position on the lane, safety distance, etc., that are available in a non-intrusive way： （1） To analyze the differences between the driving patterns of individual drivers; and （2） To analyze the effect of distraction and drowsiness on these parameters. Different scenarios have been designed, including sequences with distractions and situations that cause fatigue. The analysis of the results is carried out in time and frequency domains in order to identify situations of loss of attention and to study whether the evolution of the analyzed variables along the time could be considered independent of the driver.
