基于Multigen Creator和Vega的"数字校园"演示系统开发

为了展示武汉大学美丽的校园风貌 ,充分利用我校新近引进的虚拟现实系统 ,开发了一个“数字校园”演示系统 ,实现了虚拟现实表现的基本功能。介绍了该演示系统的有关技术细节 ,包括系统构成、数据处理流程和应用软件的二次开发技术等     

构架式轨距——轨向检测系统信号合成算法及系统验证

通过对图像传感器输出的轨距左右偏移信号和左右高低偏移信号、加速度计输出信号和车体惯性平台输出的轨道倾角信号进行合成处理,得到准确的轨距和轨向测量结果。从理论上推导轨向的合成算法,对安装于轨距测量梁中心的轨向加速度计的响应进行重力和旋转运动修正后,与三角窗函数卷积运算,得到轨距测量梁中心横向位移的二阶差分,然后再通过二次积分和滤波得到左右轨向值。通过设计模拟低通滤波和相应的数字滤波器,实现了加速度滤波器的幅频响应与检测车速度无关,保证了系统的检测精度。对轨向加速度计测得的位移和摄像式轨距系统测得的位移进行比较,验证了系统测量原理和合成算法的正确性。经静态验证和现场试验,结果证明构架式轨距—轨向检测系统具有检测精度高、性能稳定和故障率低的优点。     

GSM-R无线网络覆盖预测方法探讨

从工程设计实际应用出发,对采用网络规划软件进行网络规划前期各设计阶段的无线网络覆盖预测方法进行了探讨。     

自律分布数字化列车控制系统及在线扩展技术

现行ATC系统控制模式存在自动闭塞区间长度以性能最差的列车确定,多级制动时加减速度急剧变化,降低乘坐舒适度等缺点,需要构建车载设备智能化程度高的自律数字化列车控制系统(D ATC),以提高我国CTCS等级。有综合车载系统与独立车载系统两种方法实现系统在线构建。用测试方法进行确信性评估,证明综合车载系统便于进行高效率的在线测试和安全运行。     

软件无线电技术在铁路通信中的应用

首先介绍目前先进的软件无线电技术,然后通过实际的研发项目,详细地描述此技术在铁路高速移动接入通信系统中的应用.     

Mobile ICTs and physical mobility: Review and research agenda

The question of the relationship between the spread of communication tools and the physical mobility of individuals is not new and arose with the arrival of the fixed telephone and, more recently, the development of the Internet and especially e-commerce. The extraordinary spread of individual, especially portable, communication tools like the mobile phone, has recently generated new interest in this topic in the fields of transportation economics, geography and sociology. This article discusses the main topics that have been explored, from the debate between complementarity and substitution to analyses in terms of interactions with the spatiotemporal organization of daily activities, the size and maintenance of social networks, and, finally, perception of travel and spaces. We then identify several issues that we think merit further exploration.     

城市轨道交通中个人导向方法研究

文章运用层次分析的方法来阐述个人导向功能的实现原理,提出了利用现阶段飞速发展的移动通信体技术,设计一种应用在城市轨道交通中具有个人导向功能的移动通信体,以改善城市轨道交通中个人导向功能薄弱的现状。     

基于数码摄影技术的隧道围岩变形非接触量测方法研究

基于数码摄影技术的隧道围岩变形非接触量测法是一种与传统测量完全不同的新方法,具有设备简单、不干扰施工、自动化程度高等特点,能更好地满足现在长大隧道各种技术要求。文章对数码摄影测量技术原理及其实现过程进行了比较全面的研究,并对现场试验获取的测量数据加以分析,得到了较好的结论。该方法为地下工程量测技术开辟了一条新的途径。     

Real time queue length estimation for signalized intersections using travel times from mobile sensors

We study how to estimate real time queue lengths at signalized intersections using intersection travel times collected from mobile traffic sensors. The estimation is based on the observation that critical pattern changes of intersection travel times or delays, such as the discontinuities (i.e., sudden and dramatic increases in travel times) and non-smoothness (i.e., changes of slopes of travel times), indicate signal timing or queue length changes. By detecting these critical points in intersection travel times or delays, the real time queue length can be re-constructed. We first introduce the concept of Queue Rear No-delay Arrival Time which is related to the non-smoothness of queuing delay patterns and queue length changes. We then show how measured intersection travel times from mobile sensors can be processed to generate sample vehicle queuing delays. Under the uniform arrival assumption, the queuing delays reduce linearly within a cycle. The delay pattern can be estimated by a linear fitting method using sample queuing delays. Queue Rear No-delay Arrival Time can then be obtained from the delay pattern, and be used to estimate the maximum and minimum queue lengths of a cycle, based on which the real-time queue length curve can also be constructed. The model and algorithm are tested in a field experiment and in simulation.     

Estimating traffic volumes for signalized intersections using connected vehicle data

Recently connected vehicle (CV) technology has received significant attention thanks to active pilot deployments supported by the US Department of Transportation (USDOT). At signalized intersections, CVs may serve as mobile sensors, providing opportunities of reducing dependencies on conventional vehicle detectors for signal operation. However, most of the existing studies mainly focus on scenarios that penetration rates of CVs reach certain level, e.g., 25%, which may not be feasible in the near future. How to utilize data from a small number of CVs to improve traffic signal operation remains an open question. In this work, we develop an approach to estimate traffic volume, a key input to many signal optimization algorithms, using GPS trajectory data from CV or navigation devices under low market penetration rates. To estimate traffic volumes, we model vehicle arrivals at signalized intersections as a time-dependent Poisson process, which can account for signal coordination. The estimation problem is formulated as a maximum likelihood problem given multiple observed trajectories from CVs approaching to the intersection. An expectation maximization (EM) procedure is derived to solve the estimation problem. Two case studies were conducted to validate our estimation algorithm. One uses the CV data from the Safety Pilot Model Deployment (SPMD) project, in which around 2800 CVs were deployed in the City of Ann Arbor, MI. The other uses vehicle trajectory data from users of a commercial navigation service in China. Mean absolute percentage error (MAPE) of the estimation is found to be 9–12%, based on benchmark data manually collected and data from loop detectors. Considering the existing scale of CV deployments, the proposed approach could be of significant help to traffic management agencies for evaluating and operating traffic signals, paving the way of using CVs for detector-free signal operation in the future.