复杂交通环境下多层交叉融合多目标检测

针对目前复杂交通环境下还存在多目标检测精度和速度不高等问题,以特征金字塔网络(Feature Pyramid Network, FPN)为基础,提出了一种多层融合多目标检测与识别算法,以提高目标检测精度和网络泛化能力。首先,采用ResNet101的五层架构将空间分辨率上采样2倍构建自上而下的特征图,按照元素相加的方式将上采样图和自下而上的特征图合并,并构建一个融合高层语义信息与低层几何信息的特征层;然后,根据BBox回归存在训练样本不平衡问题,选择Efficient IOU Loss损失函数并结合Focal Loss提出一种改进Focal EIOU Loss;最后,充分考虑复杂交通环境下的实际情况,进行人工标注混合数据集进行训练。该模型在KITTI测试集上的平均检测精度和速度比FPN分别提升了2.4%和5 frame/s,在Cityscale测试集上平均检测精度和速度比FPN提升了1.9%和4 frame/s。     

多波束相控阵天线角度测量方法

在雷达、通信、测控等领域中,基于相控阵天线的幅度和差单脉冲测角技术是基本方法,但该方法通过旋转法向方向图去近似表示子波束方向图,并用一阶泰勒公式近似表示子波束接收信号幅度,从而带来非噪声因素误差,最终导致目标角度估计精度不高。为此,通过相控阵天线同时产生两个形状相同但相互独立的子波束,旋转波束指向中心轴方向的方向图函数来确定两个子波束的方向图函数,并用高阶泰勒公式对子波束接收信号幅度进行近似,从而减少误差。仿真和硬件测试结果表明所提方法能够有效提高测角精度。     

Robust integrated sequential covariance intersection fusion Kalman filters and their convergence and stability for networked sensor systems with five uncertainties

For networked sensor systems (NSSs) with hard and soft sensors including five uncertainties, two universal approaches of solving the robust fusion estimation problems are presented. It includes an integrated sequential covariance intersection (SCI) fusion minimax robust Kalman filtering approach with cross-covariance information and a generalized Lyapunov equation approach with four pairs of Lyapunov equations. Applying them, the robust local and SCI fused time-varying and steady-state Kalman filters are presented in the sense that their actual estimation error variances are guaranteed to have the corresponding minimal upper bounds. The equivalent batch SCI fusers are also presented. Their robustness and accuracy relations are proved, and the sensitivity of the SCI fuser with respect to the fused orders of sensors is analyzed. Applying the dynamic error system analysis method and the dynamic variance error system analysis method, a new convergence and absolute asymptotic stability theory of robust fusion Kalman filtering is presented. The classical Kalman filtering convergence and stability theory is developed. Compared with the original covariance intersection fuser, they significantly reduced the computational complexity and burden. Compared with the optimal and conservative SCI fusers, they significantly improved the robust accuracies. They are suitable to deal with asynchronous or random delayed data and are suitable for real-time applications. A simulation applied to the two-mass spring damper mechanical system shows their effectiveness.     

交叉口混合交通流微观控制模型

为构建智能网联汽车(CAV)和有人驾驶汽车(HDV)混合通行情况下的交叉口通行机制与控制方法, 本文提出CAV专用道条件下交叉口协同通行模型. 首先, 设计CAV专用道条件下的交叉口布置, 对交叉口进行网格化处理,将CAV通行时隙和HDV绿灯相位对交叉口某部分网格某时段的占用统一到交叉口时空资源描述框架下; 其次, 建立兼顾CAV与HDV的交叉口时空网格资源分配模型, 构建自适应信号灯控制算法和CAV轨迹规划算法; 再次, 以车辆最小延误为目标进行自适应信号灯配时优化和CAV轨迹优化; 最后, 选取广州某典型交叉口建立仿真实验对所提方法的有效性进行了验证.     

基于弹性秘密共享的多方门限隐私集合交集协议

$ (t, n) $门限隐私集合交集协议, 指$ N $个参与者各自拥有大小为$ n $的隐私集合, 在不泄露自身隐私信息的前提下, 如果各参与者交集数量大于门限值$ t $, 则参与各方能够获得交集信息, 其有广泛的应用, 如指纹识别、在线拼车、相亲网站等. 然而现有门限隐私集合交集协议大多针对两方参与者进行研究, 对多方门限隐私集合交集协议的研究仍存在许多挑战, 现有的多方门限隐私集合交集协议使用全同态加密等开销较大的公钥算法, 尚没有有效实现. 针对上述问题, 结合弹性秘密共享、布隆过滤器提出两种有效的多方门限隐私集合交集协议, 并首次仿真实现了协议. 首先, 设计一种新的布隆过滤器构造方法, 将弹性秘密共享生成的份额与参与方的集合元素相对应, 通过查询布隆过滤器获取的秘密子份额能否重构出正确秘密来判断各方交集是否达到门限值, 有效防止交集基数的泄露. 设计的第1个协议避免使用开销较大的公钥算法, 当设置安全参数$ \lambda $为128, 集合大小为$ {2^{14}} $, 门限值为$ 0.8n $时, 在三方场景下协议在线阶段的时间成本为191 s. 此外, 为了能在半诚实模型下抵抗至多$ N - 1 $个敌手合谋, 在第1个协议基础上结合不经意传输设计一种该协议的变体, 相同条件下, 在线阶段时间成本为194 s. 最后通过安全证明, 证明上述协议在半诚实模型下是安全的.     

IXT: Improved searchable encryption for multi-word queries based on PSI

Oblivious Cross-Tags (OXT) [1] is the first efficient searchable encryption (SE) protocol for conjunctive queries in a single-writer single-reader framework. However, it also has a trade-off between security and efficiency by leaking partial database information to the server. Recent attacks on these SE schemes show that the leakages from these SE schemes can be used to recover the content of queried keywords. To solve this problem, Lai et al. [2] propose Hidden Cross-Tags (HXT), which reduces the access pattern leakage from Keyword Pair Result Pattern (KPRP) to Whole Result Pattern (WRP). However, the WRP leakage can also be used to recover some additional contents of queried keywords. This paper proposes Improved Cross-Tags (IXT), an efficient searchable encryption protocol that achieves access and searches pattern hiding based on the labeled private set intersection. We also prove the proposed labeled private set intersection (PSI) protocol is secure against semi-honest adversaries, and IXT is L^{\prime }-semi-honest secure (L^{\prime } is leakage function). Finally, we do experiments to compare IXT with HXT. The experimental results show that the storage overhead and computation overhead of the search phase at the client-side in IXT is much lower than those in HXT. Meanwhile, the experimental results also show that IXT is scalable and can be applied to various sizes of datasets.     

基于卡口上下文和深度置信网络的车辆轨迹预测模型研究

针对车辆轨迹预测中节点序列的时序特性和实际路网中的空间关联性,该文提出一种基于深度置信网络和SoftMax (DBN-SoftMax)轨迹预测方法.首先,考虑到轨迹在节点集合中的强稀疏性和一般特征学习方法对新特征的泛化能力不足,该文利用深度置信网络(DBN)较强的无监督特征学习能力,达到提取轨迹局部空间特性的目的;然后,针对轨迹的时序特性,该文采用逻辑回归的预测思路,用当前轨迹集在路网特征空间中的线性组合来预测轨迹;最后,结合自然语言处理领域中的词嵌入的思想,基于实际轨迹中节点存在的上下文关系,运用节点的向量集表征了节点间的交通时空关系.实验结果表明该模型不仅能够有效地提取轨迹特征,并且在拓扑结构复杂的路网中也能得到较好的预测结果.     

基于5G、物联网的新一代智能交通路口研究与设计

与4G通信传输技术相比,5G传输技术在终端密度、峰值速率、传输延时以及传输容量等多个方面取得突破性进展。这种优势有利于实现信息的高速传递,有助于构建出“人-车-路”智能化的通信系统,进而降低交通事故的风险率,构建出靓丽的城市交通风景线。对此,文章从新一代智能交通道路的发展以及5G的新一代智能交通道路的构成、功用、开发以及瓶颈五方面对此做了介绍。     

Analysis of vehicle-bicycle interactions at unsignalized crossings: A probabilistic approach and application

In the last decades, bicycle usage has been increasing in many countries due to the potential environmental and health benefits. Therefore, there is a need to better understand cyclists’ interactions with vehicles, and to build models and tools for evaluating multimodal transportation infrastructure with respect to cycling safety, accessibility, and other planning aspects. This paper presents a modeling framework to describe driver-cyclist interactions when they are approaching a conflicting zone. In particular, the car driver yielding behavior is modeled as a function of a number of explanatory variables. A two-level hierarchical, probabilistic framework (based on discrete choice theory) is proposed to capture the driver’s yielding decision process when interacting with a cyclist. The first level models the probability of the car driver perceiving a situation with a bicycle as a potential conflict whereas the second models the probability of yielding given that a conflict has been perceived by the driver. The framework also incorporates the randomness of the location of the drivers’ decision point. The methodology is applied in a case study using observations at a typical Swedish roundabout. The results show that the conflict probability is affected differently depending on the user (cyclist or driver) who arrives at the interaction zone first. The yielding probability depends on the speed of the vehicle and the proximity of the cyclist.     

An adaptive method based on the improved LPA-ICI algorithm for MRI enhancement

Various diseases are diagnosed using medical imaging used for analysing internal anatomical structures. However, medical images are susceptible to noise introduced in both acquisition and transmission processes. We propose an adaptive data-driven image denoising algorithm based on an improvement of the intersection of confidence intervals (ICI), called relative ICI (RICI) algorithm. The 2D mask of the adaptive size and shape is calculated for each image pixel independently, and utilized in the design of the 2D local polynomial approximation (LPA) filters. Denoising performances, in terms of the PSNR, are compared to the original ICI-based method, as well as to the fixed sized filtering. The proposed adaptive RICI-based denoising outperformed the original ICI-based method by up to 1.32 dB, and the fixed size filtering by up to 6.48 dB. Furthermore, since the denoising of each image pixel is done locally and independently, the method is easy to parallelize.