基于多入侵线的视频车速检测方法

为提高视频中车速检测的精度，提出一种基于多入侵线的视频车速检测方法。首先在视频中布设已知相对距离的多条入侵线，其次检测车辆经过每条入侵线时的帧数，最后结合帧数、 摄像机的采样时间、入侵线间的距离生成关于车速的概率密度函数模型以计算车速。通过构建仿真环境验证模型性能，仿真结果表明：减小摄像机的采样时间、增加入侵线数量、增大入侵线之间的距离可以提高模型性能，并且在不同检测条件下使用多入侵法进行车速检测的误差率都更低。采用Deepsort+YOLOv5目标跟踪算法实现视频中车速的检测，同时，在视频车速检测综合数据集BrnoCompSpeed上与主流车速检测方法进行实验对比，实验结果表明，该方法测量结果的平均误差率为1.40%，与主流视频车速检测方法相比精度更高。     

基于多红外传感器的闸机通行逻辑设计及实现研究

对铁路自助实名制核验设备的技术要求和实际应用场景的需要,研究并设计一种基于多红外传感器的人体识别闸机。采用多对对射式红外光管和光幕,在对闸机系统分析的基础上,设计红外传感器的布局、并对旅客单人正常通行、旅客无票闯闸、旅客反向闯闸、无票旅客尾随和携带行李的旅客5种闸机常见通行事件进行分析和实验研究,结果表明,实验系统能够有效识别闸机通行事件,实时性好,可以满足行业实际应用需求。     

基于日照阴影识别的桁式拱肋三维温度场模拟方法

为精确高效地识别桁式拱肋的阴影分布范围并准确计算日照温度场，在传统三维温度场计算方法的基础上，引入三角形重心坐标及栅格加速结构，形成一套高效三维温度场模拟方法。首先，将光线追踪技术的阴影识别算法嵌入ABAQUS软件的自定义热源(DFLUX)子程序，实现了三维日照温度场的数值模拟，给出了详细的计算流程并验证了该方法的准确性；其次，选取高效的相交算法与合理的栅格划分方式解决了复杂结构桥梁阴影识别计算量庞大、计算效率低下的问题；最后，利用该方法计算了桁式拱肋的日照温度场并量化了温度效应。结果表明：提出的模拟方法可以实现阴影的精确识别与结构三维温度场的准确计算，通过引入基于栅格加速结构的三角形重心坐标法可以有效减少阴影识别的计算量，显著提升计算效率;日照阴影对桁式拱肋温度场及温度效应的影响不容忽视，考虑日照阴影后：下弦杆温度纵向波动十分显著，且波动幅度随着太阳辐射强度的增强逐渐增加，相邻的光照、阴影区域最大温差达13.0 ℃,拱肋竖向位移减小19%，上弦管上缘应力最大增加12.9 MPa，下弦管上缘由受压状态转变为受拉状态，应力差值达39.1 MPa;桁式拱肋的日照温度效应十分突出,日照温度作用下拱顶位移变化幅度达76 mm，较钢管混凝土拱肋拱圈施工允许误差大26 mm,最大温度应力达58.7 MPa，为恒载效应的3倍，叠加温度效应后钢管最大初应力为110 MPa，为空管稳定承载应力的32%;提出的模拟方法在桁式拱肋日照温度效应分析中得到了成功应用，亦可应用于大跨复杂结构的施工线形精细化控制、健康监测数据的温度响应分离及结构损伤识别中的温度模态频率剔除等多个场景。     

基于分类车头时距的城市道路大型车影响分析

为量化大型车对城市道路交通运行的影响，提出基于大量车牌识别(License Plate Recognition, LPR)数据研究路段、交叉口左转、交叉口直行这3类车头时距，分析大型车影响的方 法。首先，将LPR数据按采集位置划分，提出差异化数据预处理流程，得到用于考察不同车道条 件下4类过车组合的车头时距集合；然后，以高斯混合模型(Gaussian Mixed Model, GMM)、对数正 态混合模型及高斯/对数正态混合模型这3类共13个子模型分别对上述所有集合建模，以最大期 望算法求解参数；之后，以Kolmogorov-Smirnov检验排除不满足要求的模型，综合赤池信息准则 与最小描述长度准则对剩余模型择优；最后，基于最优模型参数定量评价大型车对不同类型车道 的影响。以某城市区域多个卡口与电子警察设备采集的大量LPR数据验证方法有效性。结果表 明：路段与交叉口、交叉口各功能车道的车头时距不符合同一分布，宜区分建模；3个密度分支的 GMM拟合各类车头时距集合均有最佳表现，其他模型在不同阶段体现出不适应性；各种车道条 件下，大型车对相关过车组合的车头时距均值及标准差均有不同程度的影响，且该影响按照路 段、交叉口左转、交叉口直行的顺序依次递减。拟合结果可供大型车影响评价借鉴。     

Energy recovery based on pedal situation for regenerative braking system of electric vehicle

ABSTRACT

Energy recovery is a key technology to improve energy efficiency and extend driving range of electric vehicle. It is still a challenging issue to maximise energy recovery. We present an energy recovery mode (mode A) which recovers braking energy under all situations that accelerator pedal (AP) is lifted, brake pedal (BP) is depressed, as well as AP and BP are released completely; and propose a control strategy of regenerative braking based on driver's intention identified by a fuzzy recognition method. Other two modes: (1) recovery braking energy only the BP is depressed (mode B), (2) no energy recovery, have been studied to compare with mode A. Simulations are carried out on different adhesion conditions. Recovered energy and driving range are also obtained under FTP75 driving cycle. Road test is implemented to validate simulation results. Results show that mode A can improve energy recovery by almost 15.8% compared with mode B, and extend driving range by almost 8.81% compared with mode B and 20.39% with the mode of no energy recovery; the control strategy of regenerative braking can balance energy recovery and braking stability. The proposed energy recovery mode provides a possibility to achieve a single-pedal design of the electric vehicle.     

主动降低光照强度对暗适应及交通安全的影响

为探索减轻驾驶员暗适应水平的方法,以不同速率主动降低光照强度,并测试光照强度突变为零后驾驶员辨识前方物体时间。建立室内实验环境;测量以不同速率提前降低光照强度的情况下,外界光照强度突变为零后驾驶员辨识前方物体的时间。根据数理统计原理,解析辨识时间与光照强度变化率之间的关系,分析提前改变光照强度对辨识时间的影响,寻找最短辨识时间及其相应的光照强度变化率。实验数据显示,提前降低光照强度7.0s以上与不降低相比,对驾驶员暗适应的作用显著且趋于稳定,驾驶员辨识前方物体时间最多可以减少61.91%。实验结果表明,提前改变光照强度对于短时间内缓解驾驶员暗适应现象有所帮助。     

一种改进的三角形识别算法

星图匹配识别是确定载体平台姿态的关键步骤,匹配识别的速度和准确率决定了其姿态识别的效率,星图匹配识别算法也决定了导航方式的选取和导航星库的存储和读取方式。对当前应用最为广泛的三角形算法进行改进,提出了一种新的表征星三角形的方法。     

Lane-based real-time queue length estimation using license plate recognition data

License plate recognition (LPR) data are emerging data sources that provide rich information in estimating the traffic conditions of urban arterials. While large-scale LPR system is not common in US, last few years have seen rapid developments and implementations in many other parts of world (e.g. China, Thailand and Middle East). Due to privacy issues, LPR data are seldom available to research communities. However, when available, this data source can be valuable in estimating real-time operational metrics in transportation systems. This paper proposes a lane-based real-time queue length estimation model using the license plate recognition (LPR) data. In the model, an interpolation method based on Gaussian process is developed to reconstruct the equivalent cumulative arrival–departure curve for each lane. The missing information for unrecognized or unmatched vehicles is obtained from the reconstructed arrival curve. With the complete arrival and departure information, a car-following based simulation scheme is applied to estimate the real-time queue length for each lane. The proposed model is validated using ground truth information of the maximum queue lengths from the city of Langfang in China. The results show that the model can capture the variations in queue lengths in the ground truth data, and the maximum queue length for each signal cycle can be estimated with a reasonable accuracy. The estimated queue length information using the proposed model can serve as a useful performance metric for various real-time traffic control applications.     

Speed profile estimation using license plate recognition data

Vehicle speed profile is a fundamental data support for calculating vehicular emission using the micro-emission model. However, achieving accuracy and breadth for the speed profile estimation is difficult. This study proposes a new vehicle speed profile estimation model using license plate recognition (LPR) data. This model allows speed profile estimation of every individual vehicle between two consecutive intersections. A systematic LPR data-mending method is developed to infer the information of unmatched vehicles. Using the complete arrival and departure information as boundary conditions, a customized car-following model combined with dummy-overtaking hypothesis and boundary constraints is then applied to estimate the speed profile of vehicles. The proposed model is validated using ground truth speed information from a field experiment conducted in Langfang City in China. Results show that the model can fully capture the pattern of ground truth speed profile. A complementary model validation using the Next Generation Simulation dataset and a model application for calculating emissions are also conducted. The numerical results indicate the effectiveness of the proposed model in estimating vehicle speed profile and emissions.     

汽车可靠性工程数据分布规律的模糊模式识别法

根据汽车可靠性工程数据,对其进行可靠性定量分析时,应该首先判别可靠性数据的分布规律。汽车可靠性工程数据的分布规律具有模糊集合的性质。本文探索了用模糊模式识别法识别汽车可靠性工程数据的分布规律,简单易行,实用。