Bifurcation analysis of visual angle model with anticipated time and stabilizing driving behavior

In the light of the visual angle model(VAM),an improved car-following model considering driver's visual angle,anticipated time and stabilizing driving behavior is proposed so as to investigate how the driver's behavior factors affect the stability of the traffic flow.Based on the model,linear stability analysis is performed together with bifurcation analysis,whose corresponding stability condition is highly fit to the results of the linear analysis.Furthermore,the time-dependent Ginzburg–Landau(TDGL)equation and the modified Korteweg–de Vries(m Kd V)equation are derived by nonlinear analysis,and we obtain the relationship of the two equations through the comparison.Finally,parameter calibration and numerical simulation are conducted to verify the validity of the theoretical analysis,whose results are highly consistent with the theoretical analysis.

Visual acuity evaluated by pattern-reversal visual-evoked potential is affected by check size/visual angle

Objective To systemically explore the range of visual angles that affect visual acuity, and to establish the relationship between the P 1 component （peak latency -100 ms） of the pattern-reversal visual-evoked potential （PRVEP） and the visual acuity at particular visual angles. Methods Two hundred and ten volunteers were divided into seven groups, according to visual acuity as assessed by the standard logarithmic visual acuity chart （SLD-II）. For each group, the PRVEP components were elicited in response to visual angle presentations at 8°, 4°, 2°, 1°/60＇, 30＇, 15＇, and 7.5＇, in the whiteblack chess-board reversal mode with a contrast level of 100% at a frequency of 2 Hz. Visual stimuli were presented monocularly, and 200 presentations were averaged for each block of trials. The early and stable component P1 was recorded at the mid-line of the occipital region （Oz） and analyzed with SPSS 13.00. Results （1） Oz had the maximum Pl amplitude; there was no significant difference between genders or for interocular comparison in normal controls and subjects with optic myopia. （2） The P1 latency decreased slowly below 30＇, then increased rapidly. The P1 amplitude initially increased with check size, and was maximal at -1° and -30＇. （3） The P1 latency in the group with visual acuity 〈0.2 was signifi- cantly different at 8°, 15＇ and 7.5＇, while the amplitude differed at all visual angles, compared with the group with normal vision. Differences in P1 for the groups with 0.5 and 0.6 acuity were only present at visual angles 〈1°. （4） Regression analysis showed that the P1 latency and amplitude were associated with visual acuity over the full range of visual angles. There was a moderate correlation at visual angles 〈30＇. Regression equations were calculated for the P1 components and visual acuity, based on visual angle. Conclusion （1） Visual angle should be taken into consideration when exploring the function of the visual pathway, especially visual acuity. A visual angle -60＇ might be appropriate when using PRVEP com- ponents to evaluate poor vision and to identify malingerers. （2） Increased P1 amplitude and decreased P1 latency were as- sociated with increasing visual acuity, and the P1 components displayed a linear correlation with visual acuity, especially in the range of optimal visual angles. Visual acuity can be deduced from P 1 based on visual angle.

The Exact Estimation of Visual Acuity by VEP Technology:A Report of 726 Cases of Eye Injury

This study explored the accuracy of using visual evoked potentials(VEP)technology for visual acuity estimation.The enrolled 726 patients with post-traumatic unilateral decrease in visual acuity included the injured eyes served as the experimental group,and the healthy eyes as the control group.The least signal visual angle(LSVA),and amplitude and latency of P100 were chosen as test indexes.The results under different experimental conditions were recorded by PRVEP technology.All data collected were processed...

Modeling and analysis of car-following behavior considering backward-looking effect

The car-following behavior can be influenced by its driver’s backward-looking effect.Especially in traffic congestion,if vehicles adjust the headway by considering backward-looking effect,the stability of traffic flow can be enhanced.A model of car-following behavior considering backward-looking effect was built using visual information as a stimulus.The critical stability conditions were derived by linear and nonlinear stability analyses.The results of parameter sensitivity analysis indicate that the stability of traffic flow was enhanced by considering the backward-looking effect.The spatiotemporal evolution of traffic flow of different truck ratios and varying degrees of backward-looking effect was determined by numerical simulation.This study lays a foundation for exploring the complex feature of car-following behavior and making the intelligent network vehicles control rules more consistent with human driver habits.

嵌入与脱域:技术美学视角下的李安电影

从2012年的《少年派的奇幻漂流》,到2016年的《比利·林恩的中场战事》,再到2019年的《双子杀手》,李安导演推陈出新,力图在影片题材和技术特效上不断突破自我,展现了自身对于技术电影的不懈追求。此般电影创作探索呈现出李安电影艺术与技术融合又脱离的特征。本文将以李安电影技术层面、艺术层面多维度的关系为出发点,立足于电影技术美学视角,剖析李安以上三部电影作品中艺术形态融合又脱离的具体表现方式,归纳其影像文本技术美学的独特表征等问题。

Car-following theory of steady-state traffic flow using time-to-collision

The conventional car-following theory is based on the assumption that vehicles will travel along the center line of lanes. However, according to the field survey data, in complex traffic conditions, a lateral separation between the leader and the follower frequently occurs. Accordingly, by taking lateral separation into account, we redefined the equation of time-to-collision (TTC) using visual angle information. Based on the stimulus-response framework, TTC was introduced into the basic General Motors (GM) model as a stimulus, and a non-lane-based car-following model of steady-state traffic flow was developed. The property of flow-density relationship was further investigated after integrating the proposed car-following model with different parameters. The results imply that the property of steady-state traffic flow and the capacity of each lane are highly relevant to the microscopic staggered car-following behavior, and the proposed model significantly enhances the practicality of the human driving behavior model.