Estimating time to contact during pursuit eye movements: Comparison between geometric model prediction and human performance

While an object is approaching a particular location, we can make an estimate of the time when the object will arrive at that location. A geometric model predicts that the estimate of time-to-contact (TTC) is greatly improved by using the rate of change of visual direction of the object when the object is moving with a slow velocity toward a point of nearest approach at a distance far from the observer. It has been shown that pursuit eye movements provide the rate of change of visual direction of an approaching object. We conducted psychophysical experiments, and compared TTC estimates during pursuit eye movements to those during fixation. We found that the differences in TTC estimates between fixation and pursuit show a qualitatively similar pattern to the geometric model prediction. However, the results also show that the magnitudes of the TTC estimation errors are greater than the theoretical values from the geometric model, indicating that the human visual system has a perceptual bias in estimating TTC. These results suggest that the human visual system estimates TTC during pursuit eye movements in a different way from the geometric model, although the effect of these eye movements on TTC estimates in human performance is qualitatively consistent with the model prediction.     

Simon-Gutowitz bidirectional traffic model revisited

The Simon-Gutowitz bidirectional traffic model [P.M. Simon, H.A. Gutowitz, Phys. Rev. E 57 (1998) 2441] is revisited in this Letter. We found that passing cars get stuck with oncoming cars before returning to their home lanes. This provokes the occurrence of wide jams on both lanes. We have rectified the rules for lane changing. Then, the wide jams disappear and the revisited model can describe well the realistic bidirectional traffic.     

Second-order phase transition in two-dimensional cellular automaton model of traffic flow containing road sections

Two-dimensional cellular automaton model has been broadly researched for traffic flow, as it reveals the main characteristics of the traffic networks in cities. Based on the BML models, a first-order phase transition occurs between the low-density moving phase in which all cars move at maximal speed and the high-density jammed phase in which all cars are stopped. However, it is not a physical result of a realistic system. We propose a new traffic rule in a two-dimensional traffic flow model containing road sections, which reflects that a car cannot enter into a road crossing if the road section in front of the crossing is occupied by another car. The simulation results reveal a second-order phase transition that separates the free flow phase from the jammed phase. In this way the system will not be entirely jammed (“don’t block the box” as in New York City).     

A stochastic multi-cluster model of freeway traffic

A stochastic approach based on the Master equation is proposed to describe the process of formation and growth of car clusters in traffic flow in analogy to usual aggregation phenomena such as the formation of liquid droplets in supersaturated vapour. By this method a coexistence of many clusters on a one-lane circular road has been investigated. Analytical equations have been derived for calculation of the stationary cluster distribution and related physical quantities of an infinitely large system of interacting cars. If the probability per time (or p) to decelerate a car without an obvious reason tends to zero in an infinitely large system, our multi-cluster model behaves essentially in the same way as a one-cluster model studied before. In particular, there are three different regimes of traffic flow (free jet of cars, coexisting phase of jams and isolated cars, highly viscous heavy traffic) and two phase transitions between them. At finite values of p the behaviour is qualitatively different, i.e., there is no sharp phase transition between the free jet of cars and the coexisting phase. Nevertheless, a jump-like phase transition between the coexisting phase and the highly viscous heavy traffic takes place both at and at a finite p. Monte-Carlo simulations have been performed for finite roads showing a time evolution of the system into the stationary state. In distinction to the one-cluster model, a remarkable increasing of the average flux has been detected at certain densities of cars due to finite-size effects. Received 17 September 1999     

On pattern formation in a class of traffic models

We consider a simple microscopic follow-the-leader model of N identical cars on a circular road. In the classical setting, a car is not allowed to reach its leader. If it happens at a particular time t_E, we propose to extend the model beyond this time t_E: The idea is to define a physically reasonable leader for each car. Mathematically, the resulting model is a kind of Filippov system. The objective is to study a long time behavior of the model. In case N=3, we observed several invariant patterns which apparently exhibit spatial-temporal symmetries. We managed to classify and identify two kinds of rotating waves. The classification exploits symbolic dynamical notions.     

Efficiency promotion for an on-ramp system based on intelligent transportation system information

<正>The effect of cars with intelligent transportation systems(ITSs) on traffic flow near an on-ramp is investigated by car-following simulations.By numerical simulations,the dependences of flux on the inflow rate are investigated for various proportions of cars with ITSs.The phase diagrams as well as the spatiotemporal diagrams are presented to show different traffic flow states on the main road and the on-ramp.The results show that the saturated flux on the main road increases and the free flow region is enlarged with the increase of the proportion of cars with ITS.Interestingly,the congested regions of the main road disappear completely when the proportion is larger than a critical value.Further investigation shows that the capacity of the on-ramp system can be promoted by 13%by using the ITS information, and the saturated flux on the on-ramp can be kept at an appropriate value by adjusting the proportion of cars with ITS.     

An optimized in vivo multiple-baseline stereo imaging system for skin wrinkles

Recent developments in computer vision have attempted to mimic human visual physiology. One application of this technology is the evaluation of skin wrinkles. We have developed a non-convergence stereo system that can be calibrated in vivo and can be controlled to the level of microns for baseline. We are able to obtain more accurate 3D information by calibrating nonlinear interrelations between the disparity of object and depth information.     

A Cellular Automaton Model for Two-Lane Traffic

We present some long time limit properties of a cellular automaton that models traffic of cars on a (infinite) two-lane road. This model, called TL184, is a natural generalization of the cellular automaton classified as 184 by Wolfram (to be abbreviated by CA184) and studied before as a model for one-lane traffic. TL184 models cars' motions on each lane by particles that interact via the CA184 rules, and cars' lane changes by a possibility for particles to flip from one CA184 to another. We calculate the infinite-time limit of the particle current in TL184, starting from a translation invariant measure, and use this result to show how the possibility of lane changes may enhance the current of cars in TL184 compared to that in a corresponding model of two non-interacting one-lane roads. We provide examples which demonstrate that even though the rules that regulate lane changes are completely symmetric, the system does not evolve to an equipartition of cars among both lanes from a given initially asymmetric distribution; moreover, the asymptotic car velocities and currents may be different on different lanes. We also show that, for a particular class of initial distributions, the asymptotic car density on a lane may be a non-monotonic function of the initial car density on this lane. Finally, we derive the current-density relation for an extended continuous-time version of TL184 with asymmetric lane-changing rules.     

圆柱型层析计算全息技术研究

研究了三维物体圆柱型层析计算全息技术:分别将不同深度三维物体的圆柱截面与对应的点扩展函数进行卷积后叠加获得位于全息面的物光场分布,并与参考光干涉获得计算全息图,再现该全息图可对原物体实现360°观测。首先建立三维物体圆柱型层析计算全息模型,推导系统点扩展函数与不同方向采样间隔所需满足的条件;然后通过理论与实验分析了物体不同圆柱截面半径、波长对空间频率和系统传递函数的影响,采用峰值信噪比和均方误差来评价再现图质量;最后对三维地球模型采用圆柱型层析计算全息编码,再现了不同观察角度与深度的信息。仿真结果表明,该方法对于一般三维物体360°全视场显示具有较高的应用价值。     

基于大功率LED的闪光成像速度测量系统

设计出一种非接触式高速运动物体速度测量系统,在CCD单帧曝光时间内利用闪光灯对飞行中的物体进行两次闪光照明,CCD对两个不同位置的飞行物体成像,设定两个光脉冲之间的时间间隔以及测量出两个物体像之间的距离即可算出其飞行速度.该系统能够进行实时测量,突破了空间单点测量技术的局限,可在同一幅图像上记录下不同时刻多个空间点目标的图像信息,以及同一时刻不同空间点目标的图像信息,从而可以获得目标运动的瞬时速度.     

基于大功率LED的闪光成像速度测量系统(英文)

设计出一种非接触式高速运动物体速度测量系统,在CCD单帧曝光时间内利用闪光灯对飞行中的物体进行两次闪光照明,CCD对两个不同位置的飞行物体成像,设定两个光脉冲之间的时间间隔以及测量出两个物体像之间的距离即可算出其飞行速度.该系统能够进行实时测量,突破了空间单点测量技术的局限,可在同一幅图像上记录下不同时刻多个空间点目标的图像信息,以及同一时刻不同空间点目标的图像信息,从而可以获得目标运动的瞬时速度.     

Effect of real-time information upon traffic flows on crossing roads

The effect of real-time information on the traffic flows of the crossing roads is studied by simulations based on a cellular automaton model. At the intersection, drivers have to enter a road of a shorter trip-time, by making a turn if necessary, as indicated on the information board. Dynamics of the traffic are expressed as a return map in the density-flow space. The traffic flow is classified into six phases, as a function of the car density. It is found that such a behavior of drivers induces too much concentration of cars on one road and, as a result, causes oscillation of the flow and the density of cars on both roads. The oscillation usually results in a reduced total flow, except for the cases of high car density.     

Effects of time delay on stochastic resonance of the stock prices in financial system

The effect of time delay on stochastic resonance of the stock prices in finance system was investigated. The time delay is introduced into the Heston model driven by the extrinsic and intrinsic periodic information for stock price. The signal power amplification (SPA) was calculated by numerical simulation. The results indicate that an optimal critical value of delay time maximally enhances the reverse-resonance in the behaviors of SPA as a function of long-run variance of volatility or cross correlation coefficient between noises for both cases of intrinsic and extrinsic periodic information. Moreover, in both cases, being a critical value in the delay time, when the delay time takes value below the critical value, reverse-resonance increases with the delay time increasing, however, when the delay time takes value above the critical value, the reverse-resonance decrease with the delay time increasing.     

Cortical dynamics and awareness state: an interpretation of observed interstimulus interval dependence in apparent motion

In a recent paper on Cortical Dynamics, Francis and Grossberg raise the question how visual forms and motion information are integrated to generate a coherent percept of moving forms? In their investigation of illusory contours (which are, like Kanizsa squares, mental constructs rather than stimuli on the retina) they quantify the subjective impression of apparent motion between illusory contours that are formed by two subsequent stimuli with delay times of about 0.2 s (called the interstimulus interval ISI). The impression of apparent motion is due to a back referral of a later experience to an earlier time in the conscious representation. A model is developed which describes the state of awareness in the observer in terms of a time dependent Schroedinger equation to which a second order time derivative is added. This addition requires as boundary conditions the values of the solution both at the beginning and after the process. Satisfactory quantitative agreement is found between the results of the model and the experimental results.We recall that in the von Neumann interpretation of the collapse of the quantum mechanical wave-function, the collapse was associated with an observer’s awareness. Some questions of causality and determinism that arise from later-time boundary conditions are touched upon.     

Automated Traffic and the Finite Size Resonance

We investigate in detail what one might call the canonical (automated) traffic problem: A long string of N+1 cars (numbered from 0 to N) moves along a one-lane road “in formation” at a constant velocity and with a unit distance between successive cars. Each car monitors the relative velocity and position of only its neighboring cars. This information is then fed back to its own engine which decelerates (brakes) or accelerates according to the information it receives. The question is: What happens when due to an external influence—a traffic light turning green—the ‘zero’th’ car (the “leader”) accelerates?As a first approximation, we analyze linear(ized) equations and show that in this scenario the traffic flow has a tendency to be stop-and-go. We give approximate solutions for the global traffic as function of all the relevant parameters (the feed back parameters as well as cruise velocity and so on). We discuss general design principles for these algorithms, that is: how does the choice of parameters influence the performance.     

Contour level object detection with top-down information

This paper presents a contour level object detection approach. In contrast to conventional bounding box results, we give out the salient closed contour of the object, which provides a possibility of semantic analysis for the object. We get the salient closed contour with Ratio Contour algorithm. The top-down information needed by salient closed contour extraction is based on the well-known Bag-of-Features methodology. Our top-down information based contour extraction and completion is much more efficient and robust than many related approaches lack of the top-down information. We also propose a novel post-processing framework for object detection. With low threshold and a refined binary classifier, we can get stable high performance. We evaluate our approaches on UIUC cars dataset. We show that our approaches apparently improve the performance of object detections under clutter.     

发光二极管路灯光强空间分布的非线性优化设计

道路照明的首要目的是满足使用者的视觉需求,在此前提下还应尽可能降低能耗实现节能环保,这两点均与道路灯具的光强空间分布密切相关。而很难用一种通用的光强分布适用不同的道路和灯具安装条件。针对主干路、次干路、支路3种典型道路类型,提出了根据具体道路、安装条件以及驾驶员视觉光环境需求逆向设计灯具最节能光强空间分布的思路,并建立了以驾驶员视觉光环境需求为约束、以灯具总光通量最小为目标的非线性优化模型,将路面照度分布表述为余弦多项式并利用分级优化方法进行了求解。得到了3种典型道路条件下发光二极管(LED)路灯的最佳光强空间分布,相比现基于照度均匀分布设计的LED路灯光强分布,驾驶员视觉光环境质量显著改善,且灯具节能30%左右。     

基于生物视觉特征和视觉心理学的视频显著性检测算法

提出了一种空域和时域相结合的视频显著性检测算法.对单帧图像,受视觉皮层层次化感知特性和Gestalt视觉心理学的启发,提出了一种层次化的静态显著图检测方法.在底层,通过符合生物视觉特性的特征图像（双对立颜色特征及亮度特征图像）的非线性简化模型来合成特征图像,形成多个候选显著区域;在中层,根据矩阵的最小Frobenius-范数（F-范数）性质选取竞争力最强的候选显著区域作为局部显著区域;在高层,利用Gestalt视觉心理学的核心理论,对在中层得到的局部显著区域进行整合,得到具有整体感知的空域显著图.对序列帧图像,基于运动目标在位置、运动幅度和运动方向一致性的假设,对Lucas-Kanade算法检测出的光流点进行二分类,排除噪声点的干扰,并利用光流点的运动幅度来衡量运动目标运动显著性.最后,基于人类视觉对动态信息与静态信息敏感度的差异提出了一种空域和时域显著图融合的通用模型.实验结果表明,该方法能够抑制视频背景中的噪声并且解决了运动目标稀疏等问题,能够较好地从复杂场景中检测出视频中的显著区域.     

Neutrinos in gravitational collapse: Analysis of the flux profile

The flux profile of the neutrinos emitted from a collapsing spherical object, as seen by a remote observer is studied. The model of the collapsing star consists of the Friedmann dust interior matched onto the Schwarzschild exterior. It is assumed that the neutrino emission occurs from an interior shell in a very short time interval. It is found that the nature of the flux profile falls into four distinct categories depending on the progress of collapse. Interesting features such as bursts, discontinuities, decay, etc are observed when the collapse has sufficiently progressed.