一种提高光学目标识别速度的多通道方案

本文以形态学击中击不中变换作为理论依据，以非相干光相关器作为光学实现硬件，推导了在非共轴相关条件下相关点位置的计算公式。基于系统的平移不变性，在无需增加任何分束器的情况下实现了多通道并行处理方案，不仅充分利用了空间光调制器的工作幅面，而且大大提高了识别速度，体现了光学方法的并行性和快速性。文中给出了用四通道结构，以正面人脸图像作为测试对象的实验结果。     

A New Macro Model for Traffic Flow on a Highway with Ramps and Numerical Tests

In this paper, we present a new macro model for traffic flow on a highway with ramps based on the existing models. We use the new model to study the effects of on-off-ramp on the main road traffic during the morning rush period and the evening rush period. Numerical tests show that, during the two rush periods, these effects are often different and related to the status of the main road traffic. If the main road traffic flow is uniform, then ramps always produce stop-and-go traffic when the main road density is between two critical values, and ramps have little effect on the main road traffic when the main road density is less than the smaller critical value or greater than the larger critical value. If a small perturbation appears on the main road, ramp may lead to stop-and-go traffic, or relieve or even eliminate the stop-and-go traffic, under different circumstances. These results are consistent with real traffic, which shows that the new model is reasonable.     

基于STAMP的航空管制空中危险目标识别方法研究

为了保证航空管制中航空器的完整性,提高航空器的使用寿命,并且可以最大限度的保障航空乘客和其他航空人员的人身安全,需要对航空管制空中危险目标进行识别。但采用当前目标识别方法对空中危险目标识别时,识别系统对空中危险目标无法稳定识别,存在空中危险目标识别精度低的问题。为此,提出一种基于STAMP的航空管制空中危险目标识别方法。该方法先利用STAMP模型对航空管制空中危险目标识别系统各组成部分进行任务分配,然后采用Harris法对空中危险目标进行特征选择和提取,依据Mean-Shift法的Bhattacharyya系数,描述候选空中危险目标和空中目标的危险概率分布相似度,随着Bhattacharyya系数的不断增加,候选空中危险目标和空中危险目标的相似度越大,使危险目标跟踪系统朝着空中目标危险密度增大的位置移动,在最优位置收敛,从而实现空中危险目标跟踪,最后利用D-S理论对跟踪结果进行识别,通过引入空中目标危险性基本概率赋值函数获得空中目标危险基本概率,采用Dempster组合规则对空中目标危险证据进行合成,依据空中危险目标证据融合结果完成对航空管制空中危险目标的识别。实验仿真证明,所提方法增强了航空管制空中危险目标识别的效果,提高了航空管制空中危险目标识别的精度。     

A quantum mechanics-based approach to model incident-induced dynamic driver behavior

A better understanding of the psychological factors influencing drivers, and the resulting driving behavior responding to incident-induced lane traffic phenomena while passing by an incident site is vital to the improvement of road safety. This paper presents a microscopic driver behavior model to explain the dynamics of the instantaneous driver decision process under lane-blocking incidents on adjacent lanes. The proposed conceptual framework decomposes the corresponding driver decision process into three sequential phases: (1) initial stimulus, (2) glancing-around car-following, and (3) incident-induced driving behavior. The theorem of quantum mechanics in optical flows is applied in the first phase to explain the motion-related perceptual phenomena while vehicles approach the incident site in adjacent lanes, followed by the incorporation of the effect of quantum optical flows in modeling the induced glancing-around car-following behavior in the second phase. Then, an incident-induced driving behavior model is formulated to reproduce the dynamics of driver behavior conducted in the process of passing by an incident site in the adjacent lanes. Numerical results of model tests using video-based incident data indicate the validity of the proposed traffic behavior model in analyzing the incident-induced lane traffic phenomena. It is also expected that such a proposed quantum-mechanics based methodology can throw more light if applied to driver psychology and response in anomalous traffic environments in order to improve road safety.     

Noise, sign problems, and statistics

We show how sign problems in simulations of many-body systems can manifest themselves in the form of heavy-tailed correlator distributions, similar to what is seen in electron propagation through disordered media. We propose an alternative statistical approach for extracting ground state energies in such systems, illustrating the method with a toy model and with lattice data for unitary fermions.     

提高道路交通系统的驾驶安全

道路交通系统是一个复杂的系统，其中包含了人的直接参与。在该系统中，人的因素起了重要的作用。本文中，在道路系统路面的某一点设计了一种类型控制信号，该点被称为信号点。在控制信号的作用下，当车辆经过信号点的时候，车辆需要降低速度。其目的在于能够通过控制信号控制交通流的状态，使其由无序变为有序，从而提高道路系统的交通安全。应用双车道的确定性NaSch模型进行仿真模拟，结果表明不仅交通流的状态能够由无序变为有序，而且交通流的状态是安全的。     

光学多目标识别的新方案

介绍一种数学形态学的击中与否（Ｈｉｔ－ｏｒ－Ｍｉｓｓ）算法，能快速准确实现光学多目标识别的新方案，避免了普通光学相关目标识别方法中经常出现的错误信号，因此，其目标识别结果更为有效可靠。     

Volume holographic optical correlator based on fractal-space/shift multiplexing

In this paper, we demonstrate theoretically and experimentally a new multiplexing method for volume holographic optical correlator using fractal-space/shift multiplexing. We multiplex the hologram recording by repetition of fractal-space multiplexing with partial area-overlap. This method makes a way for high recognition rate and full use of the dynamic range for volume holographic optical correlator.     

A Novel Lightweight Real-Time Traffic Sign Detection Integration Framework Based on YOLOv4

As a popular research direction in the field of intelligent transportation, various scholars have widely concerned themselves with traffic sign detection However, there are still some key issues that need to be further solved in order to thoroughly apply related technologies to real scenarios, such as the feature extraction scheme of traffic sign images, the optimal selection of detection methods, and the objective limitations of detection tasks. For the purpose of overcoming these difficulties, this paper proposes a lightweight real-time traffic sign detection integration framework based on YOLO by combining deep learning methods. The framework optimizes the latency concern by reducing the computational overhead of the network, and facilitates information transfer and sharing at diverse levels. While improving the detection efficiency, it ensures a certain degree of generalization and robustness, and enhances the detection performance of traffic signs in objective environments, such as scale and illumination changes. The proposed model is tested and evaluated on real road scene datasets and compared with the current mainstream advanced detection models to verify its effectiveness. In addition, this paper successfully finds a reasonable balance between detection performance and deployment difficulty by effectively reducing the computational cost, which provides a possibility for realistic deployment on edge devices with limited hardware conditions, such as mobile devices and embedded devices. More importantly, the related theories have certain application potential in technology industries such as artificial intelligence or autonomous driving.     

分数相关畸变不变模式识别特性研究

本文从理论上分析了分数相关器的分数级次对相关输出面能量分布的影响,利用数值模拟方法,对基于匹配滤波结构的分数相关器畸变不变模式识别特性进行了深入的讨论,并与传统相关器进行了比较.结果表明在畸变不变模式识别中,分数相关器比传统相关器有着更强的畸变不变相关识别能力.     

Color pattern recognition based on the joint fractional Fourier transform correlator

A new system of multi-channel single-output joint fractional Fourier transform correlator (JFRTC) for color pattern recognition is proposed based on the conventional system of multi-channel single-output joint transform correlator (JTC). The theoretical analysis and optical experiments are performed. With this method, one can obtain three correlation peaks at the output plane which show a pair of desired cross-correlation peaks and one auto-correlation peak. In comparison, the conventional system leads to more correlation peaks playing a noise role in color pattern recognition.     

Optical Fractional Derivative Matched Correlator

We suggest a new optical matched correlator which combines the fractional derivative with the conventional correlation for application to space shift-invariant pattern recognition. This new correlator possesses the favorable feature of being able to enhance the discrimination capability and anti-interference to noise ability over that of the conventional matched spatial filter. Varying the fractional order enables one to trade off between the light efficiency and the discrimination ability of the correlator.     

基于主元证据理论在车辆识别中的应用

车辆识别技术作为智能交通管理系统中的研究热点和难点;在车辆识别技术中,应用Dempster- Shafer证据组合规则融合冲突信息时会产生不合理的结果;基于修正证据源的思想,提出了一种新的权重系数确定方法,该方法从证据主元角度分析,确定各组证据主元,利用该主元求出证据相容度、可信度,进而确定证据权重系数;通过新的证据冲突衡量方法,确定冲突值,归一化权重,修正证据源,按ER规则融合各组证据对目标进行识别;仿真部分以实际路面车辆车型识别为算例,将该方法与其他方法对比,结果表明:该方法能更有效地融合高度冲突的证据,减小计算复杂度,目标识别的准确性提高20%。     

The effects of accelerating lane in the on-ramp system

Usually there is an accelerating lane as an on-ramp merges with the main road. How the length of this section and the traffic regulations influence the traffic behaviors has seldom been investigated. In this paper, we study this issue using the cellular automata traffic flow model. We find that (i) the permission of lane changing from main road to the accelerating lane will deteriorate the capacity of the road, hence it should be forbidden; (ii) when lane changing from main road to accelerating lane is forbidden, the introduction of an accelerating lane can improve the capacity of the on-ramp system.     

Decision optimization for face recognition based on an alternate correlation plane quantification metric

We consider a new approach for enhancing the discrimination performance of the VanderLugt correlator. Instead of trying to optimize the correlation filter, or propose a new decision correlation peak detection criterion, we propose herein to denoise the correlation plane before applying the peak-to-correlation energy (PCE) criterion. For that purpose, we use a linear functional model to express a given correlation plane as a linear combination of the correlation peak, noise, and residual components. The correlation peak is modeled using an orthonormalized function and the singular value decomposition method. A set of training correlation planes is then selected to create the correlation noise components. Finally, an optimized correlation plane is reconstructed while discarding the noise components. Independently of the filter correlation used, this technique denoises the correlation plane by lowering the correlation noise magnitude in case of true correlation and decreases the false alarm rate when the target image does not belong to the desired class. Test results are presented, using a composite filter and a face recognition application, to verify the effectiveness of the proposed technique.     

基于道路限速策略的规划路网噪声控制*

为缓解交通噪声污染,研究限速方案对噪声的影响,考虑道路限速策略下的阻抗函数,建立基于道路限速的随机用户均衡模型并实现路网交通分配,对规划路网在不同限速策略下的噪声控制规律进行研究。案例结果表明：道路限速控制对象应选取噪声影响道路;道路限速策略控制噪声的主要因素在于降低影响道路上出行车辆的出行速度,控制区域噪声值与路网总出行时间呈线性关系,道路限速80%的情况下,控制区域噪声和路网总出行时间分别降低2.94dB和增加0.66%;路网总噪声排放存在两种不同变化趋势,且与道路等级,绕行系数相关。研究可为从道路规划角度实现交通噪声控制提供有效参考。     

A prediction method for road traffic noise generated from arbitrary non-poisson type traffic flow based on an approach equivalent to that for a standard poisson type traffic flow

In order to establish a prediction method for road traffic noise generated from actual traffic flow of an arbitrary non-Poisson type, a new approach equivalent to that for an idealized Poisson type traffic flow is proposed for practical use. This prediction method is able to treat any kind of road traffic noise fluctuation generated from actual non-Poisson type traffic flow, once information has been obtained on the wave form of the level time pattern observed when one vehicle passes directly in front of an observation point. The validity of the proposed prediction method has been experimentally confirmed by applying it to actually observed road traffic noise data.     

信号灯控制下的主道双车道入匝道系统交通流特性研究

采用元胞自动机模型研究了具有信号灯控制的主道为双车道的入匝道系统交通流特性.将信号灯设置在入匝道口处,通过信号灯来引导主道和匝道上的车辆通行.分析了信号灯控制对主道与匝道的车流量、系统通行能力以及入匝道口处的车流平均速度的影响.通过相图比较,说明信号灯控制的双车道入匝道系统能模拟出比信号灯控制的单车道入匝道系统更加符合实际的交通流特性.与姜锐提出的模型［Jiang R 2003 J. Phys. A 36 11713］结果相比,信号灯控制下的匝道系统的交通流状态得到改善并且道路通行能力有所提 关键词： 交通流 元胞自动机 入匝道系统 信号灯     

Fingerprint identification by an optical joint transform correlation system

An optical correlator has been used in fingerprint identification, and in order to test its properties in a practical application a compact joint transform correlation system was constructed. The system’s identification performance was qualitatively and statistically evaluated, based on fingerprint data gathered from 500 fellow workers. The power of parallelism and fast processing of optical processing enabled the system to verify an individual’s identity in less than 0.1 s on each try. The system performed a verification with a 4.1% false rejection rate and no false acceptance in “three-try.”